International Journal of Recent Technology and Engineering

ISSN : 2277 - 3878 Website: www.ijrte.org Volume-8 Issue-2S10, SEPTEMBER 2019 Published by: Blue Eyes Intelligence Engineering and Sciences Publication

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www.ijrte.org Exploring Innovation Editor-In-Chief Chair Dr. Shiv Kumar Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT), Senior Member of IEEE Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India.

Associated Editor-In-Chief Chair Prof. MPS Chawla Member of IEEE, Professor-Incharge (head)-Library, Associate Professor in Electrical Engineering, G.S. Institute of Technology & Science Indore, Madhya Pradesh, India, Chairman, IEEE MP Sub-Section, India

Dr. Vinod Kumar Singh Associate Professor and Head, Department of Electrical Engineering, S.R.Group of Institutions, Jhansi (U.P.), India

Dr. Rachana Dubey Ph.D.(CSE), MTech(CSE), B.E(CSE) Professor & Head, Department of Computer Science & Engineering, Lakshmi Narain College of Technology Excellence (LNCTE), Bhopal (M.P.), India

Associated Editor-In-Chief Members Dr. Hai Shanker Hota Ph.D. (CSE), MCA, MSc (Mathematics) Professor & Head, Department of CS, Bilaspur University, Bilaspur (C.G.), India

Dr. Gamal Abd El-Nasser Ahmed Mohamed Said Ph.D(CSE), MS(CSE), BSc(EE) Department of Computer and Information Technology , Port Training Institute, Arab Academy for Science ,Technology and Maritime Transport, Egypt

Dr. Mayank Singh PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu- Natal, Durban, South Africa.

Scientific Editors Prof. (Dr.) Hamid Saremi Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran

Dr. Moinuddin Sarker Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor) Stamford, USA.

Prof. (Dr.) Nishakant Ojha Principal Advisor (Information &Technology) His Excellency Ambassador Republic of Sudan& Head of Mission in New Delhi, India

Dr. Shanmugha Priya. Pon Principal, Department of Commerce and Management, St. Joseph College of Management and Finance, Makambako, Tanzania, East Africa, Tanzania

Dr. Veronica Mc Gowan Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman, China.

Dr. Fadiya Samson Oluwaseun Assistant Professor, Girne American University, as a Lecturer & International Admission Officer (African Region) Girne, Northern Cyprus, Turkey.

Dr. Robert Brian Smith International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie Centre, North Ryde, New South Wales, Australia

Dr. Durgesh Mishra Professor & Dean (R&D), Acropolis Institute of Technology, Indore (M.P.), India

Special Issue Section Editor Mr. Siddth Kumar Founder and Managing Director, IFERP, Technoarete Groups, India

Mr. Rudra Bhanu Satpathy Founder and Managing Director, IFERP, Technoarete Groups, India

Dr. Mahdi Esmaeilzadeh Founder & Chairman, of Scientific Research Publishing House (SRPH), Mashhad, Iran

Executive Editor Chair Dr. Deepak Garg Professor & Head, Department Of Computer Science And Engineering, Bennett University, Times Group, Greater Noida (UP), India

Executive Editor Members Dr. Vahid Nourani Professor, Faculty of Civil Engineering, University of Tabriz, Iran.

Dr. Saber Mohamed Abd-Allah Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Shanghai, China.

Dr. Xiaoguang Yue Associate Professor, Department of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China.

Dr. Labib Francis Gergis Rofaiel Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology, Mansoura, Egypt.

Dr. Hugo A.F.A. Santos ICES, Institute for Computational Engineering and Sciences, The University of Texas, Austin, USA.

Dr. Sunandan Bhunia Associate Professor & Head, Department of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia (Bengal), India.

Dr. Awatif Mohammed Ali Elsiddieg Assistant Professor, Department of Mathematics, Faculty of Science and Humatarian Studies, Elnielain University, Khartoum Sudan, Saudi Arabia.

Technical Program Committee Chair Dr. Mohd. Nazri Ismail Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia.

Technical Program Committee Members Dr. Haw Su Cheng Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia (Cyberjaya), Malaysia.

Dr. Hasan. A. M Al Dabbas Chairperson, Vice Dean Faculty of Engineering, Department of Mechanical Engineering, Philadelphia University, Amman, Jordan.

Dr. Gabil Adilov Professor, Department of Mathematics, Akdeniz University, Konyaaltı/Antalya, Turkey.

Dr.Ch.V. Raghavendran Professor, Department of Computer Science & Engineering, Ideal College of Arts and Sciences Kakinada (Andhra Pradesh), India.

Dr. Thanhtrung Dang Associate Professor & Vice-Dean, Department of Vehicle and Energy Engineering, HCMC University of Technology and Education, Hochiminh, Vietnam.

Dr. Wilson Udo Udofia Associate Professor, Department of Technical Education, State College of Education, Afaha Nsit, Akwa Ibom, Nigeria.

Manager Chair Mr. Jitendra Kumar Sen Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Editorial Chair Dr. Arun Murlidhar Ingle Director, Padmashree Dr. Vithalrao Vikhe Patil Foundation’s Institute of Business Management and Rural Development, Ahmednagar (Maharashtra) India.

Editorial Members Dr. Wameedh Riyadh Abdul-Adheem Academic Lecturer, Almamoon University College/Engineering of Electrical Power Techniques, Baghdad, Iraq

Dr. T. Sheela Associate Professor, Department of Electronics and Communication Engineering, Vinayaka Mission’s Kirupananda Variyar Engineering College, Periyaseeragapadi (Tamil Nadu), India

Dr. Manavalan Ilakkuvan Veteran in Engineering Industry & Academics, Influence & Educator, Tamil University, Thanjavur, India

Dr. Shivanna S. Associate Professor, Department of Civil Engineering, Sir M.Visvesvaraya Institute of Technology, Bengaluru (Karnataka), India

Dr. H. Ravi Kumar Associate Professor, Department of Civil Engineering, Sir M.Visvesvaraya Institute of Technology, Bengaluru (Karnataka), India

Dr. Pratik Gite Assistant Professor, Department of Computer Science and Engineering, Institute of Engineering and Science (IES-IPS), Indore (M.P), India

Dr. S. Murugan Professor, Department of Computer Science and Engineering, Alagappa University, Karaikudi (Tamil Nadu), India

Dr. S. Brilly Sangeetha Associate Professor & Principal, Department of Computer Science and Engineering, IES College of Engineering, Thrissur (Kerala), India

Dr. P. Malyadri Professor, ICSSR Senior Fellow Centre for Economic and Social Studies (CESS) Begumpet, Hyderabad (Telangana), India

Dr. K. Prabha Assistant Professor, Department of English, Kongu Arts and Science College, Coimbatore (Tamil Nadu), India

Dr. Liladhar R. Rewatkar Assistant Professor, Department of Computer Science, Prerna College of Commerce, Nagpur (Maharashtra), India

Dr. Raja Praveen.N Assistant Professor, Department of Computer Science and Engineering, Jain University, Bengaluru (Karnataka), India

Dr. Issa Atoum Assistant Professor, Chairman of Software Engineering, Faculty of Information Technology, The World Islamic Sciences & Education University, Amman- Jordan

Dr. Balachander K Assistant Professor, Department of Electrical and Electronics Engineering, Karpagam Academy of Higher Education, Pollachi (Coimbatore), India

Dr. Sudhan M.B Associate Professor & HOD, Department of Electronics and Communication Engineering, Vins Christian College of Engineering, Anna University, (Tamilnadu), India

Dr. T. Velumani Assistant Professor, Department of Computer Science, Kongu Arts and Science College, Erode (Tamilnadu), India

Dr. Subramanya.G.Bhagwath Professor and Coordinator, Department of Computer Science & Engineering, Anjuman Institute of Technology & Management Bhatkal (Karnataka), India

Dr. Mohan P. Thakre Assistant Professor, Department of Electrical Engineering, K. K. Wagh Institute of Engineering Education & Research Hirabai Haridas Vidyanagari, Amrutdham, Panchavati, Nashik (Maharashtra), India

Dr. Umar Lawal Aliyu Lecturer, Department of Management, Texila American University Guyana USA.

Dr. K. Kannan Professor & Head, Department of IT, Adhiparasakthi College of Engineering, Kalavai, Vellore, (Tamilnadu), India Volume-8 Issue-2S10, September 2019, ISSN: 2278-3075 (Online) S. No Published By: Blue Eyes Intelligence Engineering & Sciences Publication Page No.

Authors: Ezarina Zakaria, Fauziah Ibrahim, Norulhuda Sarnon, Nazirah Hassan Needle and Syringe Exchange Program for HIV/AIDS Prevention : Areas to be Considered by Law Paper Title: Enforcement Agency for Implementation Abstract: Needle and Syringe Exchange Programme (NSEP) is a HIV/AIDS prevention programme targeting hardcore drug addicts. NSEP encourages addicts to exchange used needles with new syringe for free. The NSEP in Malaysia involves the cooperation of multi-sector agencies such as the Ministry of Health (MOH), the Royal Malaysian Police (RMP) and the Malaysian AIDS Council (MAC). The implementation of the NSEP creates controversy when it being seen to encourage continuous drug addicts activities and solely focus on HIV/AIDS prevention. An exploratory study being conducted to examine the involvement of multisectoral in the NSEP. This article would only discuss RMP's findings with regards to its discretionary dilemma as a drug law enforcement agency. Five police officers of the Narcotics Crime Investigation Department were selected as informants. Data collection being carried out by using an in-depth interview method. The analyses form theme from data that being carried out inductively. This article would discuss only two of the overall studies: i) the form of discretion given by the RMP to NSEP clients and ii) the challenges encountered by RMP in defending its discretion. The findings highlighted dilemma encountered by police on their discretion not to arrest or impose any detention procedures towards NSEP clients. The RMP found it difficult to exercise discretion towards client because: i) the discretion not to arrest the addict was against the law, ii) the RMP was concerned about the misuse of discretion by the client and iii) the discretionary giving could affect public perception of RMP responsibility and integrity. The study proposes a module in implementing the NSEP on a multisectoral network especially involving the police.

Keyword: police discretion, NSEP, HIV/AIDS, law enforcement References: 1. D. Mogg, and M. Levy, “Moving beyond non-engagement on regulated needle-syringe exchange programs in Australian prisons,” Harm Reduction Journal, 6, 7, 2009. 2. M. M. Philbin, R.Lozada, M.L. Zuniga, A. Mantsios, P.Case, C. Magis-Rodriguez, C.A. Latkin, and S.A Strathdee, “A Qualitative assessment of stakeholder perceptions and socio-cultural influences on the acceptability of harm reduction programs in Tijuana, Mexico,” Harm Reduction Journal, 5, 36, 2008. 3. UNAIDS, “GLOBAL REPORT : UNAIDS report on the global AIDS epidemic 2013,” Joint United Nations Programme on HIV/AIDS (UNAIDS), 2013. 4. I. Baba, “HIV/AIDS: Cabaran dan kesan kepada masyarakat Malaysia,” Dalam Omar, Roziah & Pandain, Sivamurugan (ed). Malaysia: Isu-Isu Sosial Semasa. Kuala Lumpur: Unit Penerbitan ISM, 2005. 1. 5. Memoona Hasnain. “Cultural approach to HIV/AIDS harm reduction in muslim countries,” Harm Reduction Journal, 2(23), 2005 doi:10.1186/1477-7517-2-23. 6. S. J. Rogers, and T.Ruefli, “Does harm reduction programming make a difference in the lives of highly marginalized, at-risk drug 1-9 users?” Harm Reduction Journal, 7(1), 2004. doi:10.1186/1477-7517-1-7 7. C. J. Strike, T. Myers, and M. Millson, “Finding a place for needle exchange programs,” Critical Public Health, 14(3), 261-275. 2004. 8. T.Tammi, and T. Hurme, “How the harm reduction movement contrasts itself againts punitive prohibition,” International Journal of Drug Policy, 18, 84 – 87, 2007. 9. G. Reid, K. Adeeba, and S. Kaur Sran, Rapid Situation Assessment of Malaysia 2004. University of Malaya Kuala Lumpur : Infectious Disease Unit Publishers. 2005. 10. N. Stafford, “Using Words : The harm reduction conception of drug use and drug users,” International Journal of Drug Policy, 18, 88 – 91, 2007. 11. G. Reid, K. Adeeba, and S. Kaur Sran, “Malaysia and harm reduction : The challenges and responses;” International Journal of Drug Policy, 18, 136 – 140, 2007. 12. P. O’Hare, R. Newcombe, A. Matthews, E. Bunning, and E. Drucker, The reduction of drug related harm. London : Routledge. 1992. 13. E. Drucker, and A. Clear, “Harm reduction in the home of war on drugs : Methadone and needle exchange in the USA,” Drugs and Alcohol Review, 18, (1) 103 – 112, 1999. 14. H.G. Levine, “The secret of worldwide drug prohibition. The varieties and uses of drug prohibition,” In T. Tammi, & T. Hurme, (2007). How the harm reduction movement contrasts itself againts punitive prohibition. International Journal of Drug Policy, 18, 84 – 87, 2002. 15. M.T. Aoyagi, “Beyond punitive prohibition: liberalizing the dialogue on international drug policy,” International Law And Politics. Vol. 37 :555 – 610, 2006. 16. P. Chatterjee, “AIDS in India: Police powers and public health,” The Lancet, 367, 9513, 2006. 17. C.S. Davis, S. Burris, J. Kraut-Becher, K.G. Lynch, and D. Metzger, “Effects of an intensive street-level police intervention on syringe exchange,” American Journal of Public Health, 95, (2). 2005. 18. L. Beletsky, G. Macalino, and S. Burris, “Attitudes of police officers towards syringe access, occupational needle –sticks and drug use : A qualitative study of One City Police Department in the United States,” International Journal of Drug Policy, 16, 267, 2009. 19. R. Midford, J. Acres, S. Lenton, W. Loxley, and K. Boots, “Cops, drugs and the community : Establishing consultative harm reduction structures in two Western Australian locations,” International Journal of Drug Policy, 13, 185 – 192, 2002. 20. G. Lough, “Law enforcement and harm reduction : Mutually exclusive or mutually compatible,” International Journal of Drug Policy, 9, 169 – 173, 1997. 21. Z. Ezarina, I. Baba, A. Azman, N. Sarnon, I. Fauziah, and H. A. Wahab, “Police Involvement in the Needle and Syringe Exchange Programme (NSEP): The Malaysian Experience,” Pertanika Journals Social Sciences & Humanities, 22(S):49-62, 2013. 22. Z. Ezarina, I. Baba, A. Azman, “Indikator Keberkesanan Pendekatan Pengurangan Kemudaratan dan Cabaran Implementasi di Peringkat Agensi Berkepentingan,” The Malaysian Journal of Social Administration, vol 7-8 : 1-30, 2011. 23. L. Beletsky, J. Cochrane, Sawyer, L. Anne, C. Serio-Chapman, M. Smelyanskaya, J. Han, N. Robinowitz, S. G. Sherman, “Police encounters among Needle Exchange Clients in Baltimore : Drug law enforcement as a structural determinant of health,” American Journal of Public Health, Vol. 105 Issue 9 : 1872-1879, 2015. 24. A. N. Martinez, R. N. Bluthenthal, J. Lorvick and R.Anderson et. al. “The impact of legalizing syringe exchange programs on arrests among injection drug users in California,” Journal of Urban Health, 84: 3, 2007. 25. S. Bronitt, and P. Stenning, “Understanding discretion in modern policing,” Crim LJ. 35 : 319 – 334, 2011. 26. S.Walker, and C. M. Katz, The police in America: An introduction (5th ed). New York, NY: McGraw-Hill Companies, 2005. 27. R. K. Wortley, “Measuring police attitudes towards discretion,” Criminal Justice & Behavior, Vol. 30, (5), pp. 538-558, 2003. 28. G. L. Halliday (2009). Police discretion. Western Journal of Criminal Justice. 29. S.T. Reid, Crime and criminology (11th ed). McGraw-Hill Companies, New York: NY, 2006. 30. L. K. Gaines, and V. E. Kappeler, Policing in America (4th ed). Cincinnati, OH : Anderson Publishing, 2003. 31. T. O’Connor, Police discretion, Retrieved March 20, 2008, from http://www.apsu.edu/oconnort/4000/4000lect07.html 2004. 32. Centre for Harm Reduction, The manual for reducing drug-related harm in Asia. Macfarlane Burnet Institute for Medical Research and Public Health. Author, 2003. 33. L. Beletsky, L.E. Grau, E. White, S. Bowman and R. Heimer, “The roles of law, client race, and program visibility in shaping police interference with the operation of US syringe exchange programs,” Addiction, 106(2) : 357-365, 2011. 34. J. Bargen, “The next step: Developing restorative communities,” Criminal Law Journal, (2), pp. 1-5, 2005. 35. S. Burris, “Drug policing, harm reduction and health : Directions for advocacy,” International Journal of Drug Policy, 20, 293 – 295, 2009. 36. K. Dolan, P. Dillon, and E.Sillins, Needle and syringe programs : Your questions answered. Canberra, Australian Government Department of Health and Aging. 2005. 37. B. Silverman, C.S. Davis, J. Graff, U. Bhatti, M. Santos, and L. Beletsky, “Harmonizing disease prevention and police practice in the implementation of HIV prevention programs : Up-stream strategies from Wilmington, Delaware,” Harm Reduction Journal. 9:17, 2012.doi:10.1186/1477-7517-9-17 38. N. Blaikie. “Approaches to Social Enquiry: Advancing Knowledge”. 2nd edition. Polity Press,Cambridge. 2007 39. A. E. Fortune, W. J. Reid, R. L. Miller. “Qualitative Research in Social Work”. Columbia University Press, New York. 2014 40. V. Braun and V. Clarke. “Successful Qualitative Research: A Practical Guide for Beginners”. Sage Publication. Thousands Oaks, California. 2013. Authors: Abdul Rahman Ahmad Badayai, Wan Shahrazad Wan Sulaiman, Rozainee Khairudin Inhibitory and Emotional Control Deficits as Mediators between Protective Factors and Symptoms Paper Title: of Problem Behaviors in Delinquency Abstract: Much research has examined the role of inhibitory and emotional controls in the educational setting with an emphasis on learning and coaching. However, they underestimate the effect and role of inhibitory and emotional controls in delinquent behaviors. Therefore, the current study examined the impact of inhibitory and emotional controls as mediators between protective factors and symptoms of problem behaviors. Respondents of the survey consisted of 404 delinquents convicted of several crimes such as armed robbery, drug trafficking, and drug use, gang fights, rape, homicide, and out of control behaviors. Three psychological instruments; Developmental Assets Questionnaire-Malaysian Version (DAQ-MV), Behavior Rating Inventory of Executive Function- Self Report (BRIEF-SR) and Achenbach System of Empirical Behavior Assessment- Youth Self-Report (ASEBA-YSR) were used to collect data. The result showed that there was no evidence that planning/decision making influenced rule-breaking behavior independent of its effect on inhibitory and emotional controls (c’ = -.113, p = .062). On the contrary, there was evidence that resistance skill/resilience influenced rule-breaking behavior independently of its effect on inhibitory and emotional controls (c’ = -.204, p = .000). Morality and religiosity also have been found to influence rule-breaking behavior independently of its effect on inhibitory and emotional controls (c’ = -.231, p = .000). The results contributed to an enhancement of early prevention strategy based on executive function, especially in institutions like prison and rehabilitation school.

Keyword: executive function, developmental assets, rule-breaking behavior, at-risk youth. 2. References: 1. Hall, G.S. (1904). Adolescence: In psychology and its relation to physiology, anthropology, sociology, sex, crime, religion, and education. (vol I & II). New Jersey: Prentice-Hall. 10-15 2. Mohamed, M. Z., Marican, S., Elias, N., & Don, Y. (2008). Pattern of substance and drug misuse among youth in Malaysia. Jurnal Antidadah Malaysia, 3,1–56. 3. Hammond, D., Kin, F., Prohmmo, A., Kungskulniti, N., Lian, T. Y., Sharma, S. K., Buppha, S., Borland, R., & Fong, G. T. (2008). Patterns of smoking among adolescents in Malaysia and Thailand: Findings from the International Tobacco Control Southeast Asia Survey. Asia-Pacific Journal of Public Health /Asia-Pacific Academic Consortium for Public Health, 20(3), 193– 203. Doi.org/10.1177/1010539508317572 4. Lim, K.H., Sumarni, M.G., Kee, C.C., Christopher, V.M., Noruiza Hana, M., Lim, K.K., & Amal, N.M. (2010). Prevalence and Factors Associated With Smoking Among Form Four students In Petaling District, Selangor, Malaysia. Tropical Biomedicine, 27(3), 394-403. 5. Lee, W.E., Wadsworth, M.E., & Hotopf, M. (2006). The protective role of trait anxiety: A longitudinal cohort study. Psychological Medicine, 36, 345–351. 6. Omar, Hatim A., Ventegodt, S., & Merrick, J. (2010). Quality of Life and Adolescents in Rural Kentucky. Pediatrics Faculty Publications. Paper 115. Retrieved from http://uknowledge.uky.edu/pediatrics_facpub/115 7. Wicks-Nelson, R., & Israel, A.C. (2009). Abnormal child and adolescent psychology. (7th Ed.).Pearson Education: New Jersey. 8. Wicks-Nelson, R., & Israel, A.C. (2013). Abnormal child and adolescent psychology. (8th Ed.).Pearson Education: New Jersey. 9. Kendall, P.C. (2006). The Present and Future of Clinical Psychology. Clinical Psychology: Science and Practice, 13(3), 203–204. doi: 10.1111/j.1468-2850.2006.00024.x 10. Steinberg, L. (2007). Adolescence (8th ed.). New York: McGraw-Hill. 11. Steinberg, L. (2010). Risk taking in adolescence: New perspectives from brain and behavioral science. 2004. Edited by Dodge, K. A. In Currents directions in child psychopathology. Boston: Pearson. 12. Reyna, V.F., & Farley, F. (2006). Risk and Rationality in Adolescent Decision Making Implications for Theory, Practice, and Public Policy. Psychological Science in the Public Interest, 7(1), 1-44. 13. Millstein, S.G. & Halpern–Felsher, B.L. (2002). Judgments about Risk and Perceived Invulnerability in Adolescents and Young Adults. Journal of Research on Adolescence, 12(4), 399–422. doi: 10.1111/1532-7795.00039. 14. Iselin, A.M. & Decoster, J. (2009). Reactive and proactive control in incarcerated and community adolescents and young adults. Cognitive Development, 24(2), 192-206. 15. Bronfenbrenner, U. (1979). The ecology of human development Experiments in nature and design. Cambridge, MA: Harvard University Press. 16. Tudge, J.R.H., Mokrova, I., Hatfield, B.E., & Karnik, R.B. (2009). Uses and Misuse of Bronfenbrenner’s Bioecological Theory of Human Development. Journal of Family Theory & Review, 1, 198–210. 17. Guy, S.C., Isquith, P.K., & Gioia, G.A. (2004). Behavior rating inventory of executive function-self report version: professional manual. Florida: PAR. 18. Achenbach, T.M., & Rescorla, L.A. (2001). Manual for the ASEBA School-Age Forms & Profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth & Families. 19. Nor Ba’yah, A.K., Samsudin, A.R., Mustapha, Z., Mutalib, A., Hanida, M., & Kee, C.P. (2012). External assets as predictors of positive emotions among at‐risk youth in Malaysia. Asian Social Work and Policy Review, 6 (3), 203-217. 20. Guerra, N.G., Boxer, P., & Kim, T. (2005). A cognitive-ecological approach to serving students with emotional and behavioral disorders: Application to aggressive behavior. Behavioral Disorders, 30, 277–288. 21. Crick, N.R., & Dodge, K.A. (1994). A review and reformulation of social information-processing mechanisms in children's social adjustment. Psychological Bulletin, 115, 74-101. 22. Dodge, K.A., & Pettit, G.S. (2003). A biopsychosocial model of the development of chronic conduct problems in adolescence. Developmental Psychology, 39, 349 – 371. 23. Dodge, R.N. (2010). Childhood emotional maltreatment and later Intimate relationships: Themes from the empirical literature. Journal of Aggression, Maltreatment and Trauma, 19(2), 224–242. Authors: Abdul Rahman Ahmad Badayai, Rozainee Khairudin, Wan Shahrazad Wan Sulaiman Inhibitory and Emotional Control Deficits as Predictors of Symptoms of Problem Behaviors among Paper Title: Juvenile Delinquents Abstract: Executive dysfunction of inhibitory and emotional control deficits has not gained attention as a predictor in previous research on problem behaviors. Thus, this study examined inhibitory and emotional control deficits as predictors of symptoms of problem behaviors. There were 404 young offenders with various crimes such as stealing, substance use, rape, homicide, gang fights, and early sexual relation/pregnancy and out of control behavior participated in the study. Behavior Rating Instrument of Executive Function-Self Report (BRIEF-SR) and Achenbach System of Empirical Behavior Assessment (ASEBA-YSR) were employed, respectively. The results showed there was a significant relationships between inhibitory and emotional control deficits with both symptoms of problem behaviours; rule-breaking behavior and aggressive behavior. Moreover, based on regression weights, inhibitory control deficit was the best predictor of attention problems and aggressive behavior. On the contrary, an emotional control deficit was the best predictor of both symptoms of problem behaviors. In conclusion, the executive function plays a significant role in problem behaviors among juvenile delinquents. Thus early prevention based on both inhibitory and emotional controls component must be considered in three different settings such as family, school, and community. Thorough consideration in developing and inserting these two executive function components also are much needed in an educational setting as it is where adolescents spend much of the time.

Keyword: inhibition, emotion, problem behavior, delinquency. References: 1. Séguin, J. R., & Zelazo, P. D. (2005). Executive function in early physical aggression. In R. E. Tremblay, W. W. Hartup, & J. Archer (Eds.), Developmental origins of aggression (pp. 307–329). New York: Guilford. 2. Senn, T. E., Espy, K. A., & Kaufmann, P. M. (2004). Using path analysis to understand executive function organization in preschool children. Developmental Neuropsychology, 26(1), 445-464. http://dx.doi.org/10.1207/s15326942dn2601_5 3. 3. Mattison, R. E., & Mayes, S. D. (2012). Relationships between learning disability, executive function, and psychopathology in children with ADHD. Journal of Attention Disorders, 16(2), 138-146. http://dx.doi.org/10.1177/1087054710380188 4. Wicks-Nelson, R., & Israel, A.C. (2009). Abnormal child and adolescent psychology. (7th Ed.).Pearson Education: New Jersey. 5. Willcutt, E. G., Doyle,T A.T E.,T Nigg,T J.T T.,T Faraone,T S.T V.,T &T Pennington,T B.T F.T (2005).T AT meta-analyticT 16-20 reviewT ofT theT executiveT functionT theoryT ofT ADHD.T BiologicalT Psychiatry,T 57,T 1336–1346.T 6. Mullane,T J.T C.,T Corkum,T P.T V.,T Klein,T R.T M.,T McLaughlin,T E.T N.,T &T Lawrence,T M.T A.T (2011).T Alerting, 7. orienting,T andT executiveT attentionT inT childrenT withT ADHD.T JournalT ofT AttentionT Disorders,T 15(4),T 310- 320.http://dx.doi.org/10.1177/1087054710366384T 8. Schoemaker,T K.,T Bunte,T T.,T Wiebe,T S.T A.,T Espy,T K.T A.,T Deković,T M.,T &T Matthys,T W.T (2012).T ExecutiveT functionT deficitsT inT preschoolT childrenT withT ADHDT andT DBD.T JournalT ofT ChildT PsychologyT andT Psychiatry,T 53(2),T 111-119.T http://dx.doi.org/10.1111/j.1469-7610.2011.02468.x AmericanT PsychiatricT Association.T (2013).T DiagnosticT andT statisticalT manualT ofT mentalT disorders:T DSMT 5T (5thT ed.).T Washington,T DC:T iGroupT Press.T 9. VanT Goozen,T S.T H.T M.,T Cohen-Kettenis,T P.T T.,T Snoek,T H.,T Matthys,T W.,T Swaab-Barneveld,T H.,T &T VanT Engeland,T H.T (2004).T ExecutiveT functioningT inT children:T AT comparisonT ofT hospitalizedT ODDT andT ODD/T ADHDT childrenT andT normalT controls.T JournalT ofT ChildT PsychologyT andT Psychiatry,T 45(2),T 284-292.T http://dx.doi.org/10.1111/j.1469-7610.2004.00220. 10. Raaijmakers,T M.A.J.,T Smidts,T D.P.,T Sergeant,T J.A.,T Maassen,T G.H.,T Posthumus,T J.A.,T Engeland,T H.,T &T Matthys,T W.T (2008).T ExecutiveT functionsT inT preschoolT childrenT withT aggressiveT behavior:T ImpairmentsT inT inhibitoryT control.T JournalT ofT AbnormalT ChildT Psychology,T 36(7),T 1097-1107.T http://dx.doi.org/10.1007/s10802- 008-9235-7T 11. Qian,T Y.,T Shuai,T L.,T Cao,T Q.,T Chan,T R.T C.T K.,T &T Wang,T Y.T (2010).T DoT executiveT functionT deficits differentiate between children with Attention Deficit Hyperactivity Disorder (ADHD) and ADHD – comorbid with Oppositional Defiant Disorder? A cross-cultural study using performance-based tests and the Behavior Rating Inventory of Executive Function. The Clinical Neuropsychologist, 24(5), 793-810. http://dx.doi.org/10.1080/13854041003749342 12. Blair, C., & Razza, R.A. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78, 647-663. 13. Araujo, E.A., Jané-Ballabriga, M., Bonillo, A., & Capdevilla, C. (2014). Executive function deficits and symptoms of disruptive behaviour disorders in preschool children. Universitas Psychologica, 13(4), xxx-xxx. https:// dx.doi.org/10.11144/Javeriana.UPSY13-4.efds 14. Saunders, M., Lewis, P., & Thornhill, A. (2012). Research methods for business students. (6th ed). Pearson Education Limited. 15. Guy, S.C., Isquith, P.K., & Gioia, G.A. (2004). Behavior Rating Inventory of Executive Function-Self Report Version Professional Manual. Florida: PAR. 16. Achenbach, T.M., & Rescorla, L.A. (2001). Manual for the ASEBA School-Age Forms & Profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families. Authors: Aizan Sofia Amin, Siti Zuliana Md Zuki, Noremy Md Akhir

Paper Title: Accessibility to Facilities for Persons with Disabilities at Public Institutes of Higher Learning Abstract: Issues related to Persons with Disabilities (PWD) rights are increasingly being considered in Malaysia. This includes their rights in education, employment, healthcare as well as access to the facilities and services provided. Accessibility in education especially at universities are among the major issues faced by PWD. Therefore, this study was conducted to identify the accessibility of facilities for persons with disabilities in public institutes of higher education. This study focuses on structured observations of PWD facilities at four faculties and four resource centres in Universiti Kebangsaan Malaysia. Five basic facilities for PWD such as parking space, stairs, lifts, toilets and pathways/ramps were thoroughly observed. A detailed comparison was carried out to identify the accessibility of those facilities and the extent of compliance to specifications outlined in universal design criteria. The study findings show that although PWD facilities were available, those facilities were still inadequate and did not follow the specifications set. Facility providers namely the university should devise a specific action plan and establish an inclusive policy for PWD to ensure their rights and needs are entirely fulfilled.

Keyword: Accessibility, Facilities, Persons With Disabilities, Universal Design References: 1. Bodaghi, N.B. and Zainab, N.A.. Examining the accessibility and facility for the disabled in public and university library buildings in Iran. Information Development, 2013, 29(1): 1-10. 2. Hill, J.L., Accessibility: Students with disabilities in universities in Canada. Canadian Journal of Higher Education Vol. XXII-1, 1992, 48-82. 4. 3. Hazlin Falina Rosli & Safura Ahmad Sabri, Halangan Fasiliti Pelajar Orang Kurang Upaya (OKU) Di Institusi Pengajian Tinggi Di Lembah Klang, International Journal for Studies on Children, Women, Elderly And Disabled, 2017, Vol. 2. 4. Fatimah Abdullah. 2009. Keperluan Kemudahan untuk Orang Kurang Upaya Kes di Universiti Kebangsaan Malaysia, 21-37 Persidangan Psikologi Malaysia, 2009. 5. Aizan Sofia Amin & Jamiah Manap. Geografi, Kemiskinan dan Wanita Kurang Upaya Di Malaysia. Journal of of Society and Space. 2015. 11(7): 82-91. 6. Rahim, A.A. & Abdullah, F., Access audit on universal design: The case of Kota Kinabalu Water Front. The International Journal of Interdisciplinary Social Sciences, 2009, Volume 4. 7. Nur Amirah Abd Samad, Ismail Said, Asiah Abdul Rahim, Planning Accessibility Strategies And Connectivity For Malaysian Urban Built Environment Studies In Health Technology And Informatics, 2018, 256:367-377. 8. Ostroff, Elaine. "Universal Design: The New Paradigm." In Universal Design Handbook, edited by Wolfgang F.E. Preiser and Elaine Ostroff: McGraw-Hill Education, 2001. 9. Saito, Yoko. "Awareness of Universal Design among Facility Managers in Japan and the United States." Automation in Construction 15, no. 4 (7/ 2006): 462-78. 10. Syazwani Abdul Kadir & Mariam Jamaludin (2012)Applicability of Malaysian Standards and Universal Design in Public Buildings in Putrajaya Asian Journal of Environment-Studies (ajE-Bs), 2012, Vol 3(9). 11. Tinklin, T. & Hall, J. Getting round obstacle: disabled students’ experiences in higher education in Scotland. Studies in Higher Education, 1999. 24(2), 183-194. 12. Mohd Faizul Ismail & Norizan Abdul Ghani, Sokongan yang Diperlukan Pelajar OKU Cacat Penglihatan di Universiti Awam Malaysia, Proceeding of International Conference of Empowering Islamic Civilization, 2017, ISBN 978-967-0899-70-1. 13. Mohd Reduan Bin Buyung, Haryati Binti Shafii. Kolej Kediaman Lestari: Penelitian Kemudahan Golongan Orang Kurang Upaya (OKU). 2015. Seminar Kebangsaan Majlis Dekan-Dekan Pendidikan Universiti Awam 2015. 14. Kamarul Azmi Jasmi. Penyelidikan Kualitatif Dalam Sains Sosial. 2012. 15. Yuhainis Abdul Talib, Nurul Izzati Abdul Ghani , Kharizam Ismail & Nor’Aini Salleh, The Provision of the Disabled Facilities in Public Hospitals. 2016. MATEC Web of Conferences 66, 00081. 16. Asiah Abdul Rahim, Ismawi Zen, Nur Amirah Abd. Samad & Che Raiskandar Che Rahim, Universal Design and Accessibility: Towards Sustainable Built Environment in Malaysia: Three Days of Creativity and Diversity. 2014. Volume 35, 299 – 306. 17. Hazreena Hussein, Naziaty Mohd Yaacob. Development of Accessible Design in Malaysia. Procedia - Social and Behavioral Sciences, 2012. Volume 68, pages 121-133. Authors: Mohd Suhaimi Mohamad, Rozita Ibrahim, Daniella M. Mokhtar, Nasrudin Subhi

Paper Title: Youth-to-Youth Engagement Abstract: Youth-to-youth engagement develops as well as enhances sense of belonging, autonomy and power control, competence, motivation and decision-making skills. Millennial youth are self-learned generation; thus, peer influence is vital. Based on these premises, GENIUS Remaja programmes are created ‘with youths’ rather than ‘for youth’. GENIUS Remaja programmes have proven to be effective and produced positive results for the participants. Empowerment of youth through personal development trainings as well as participation in addressing community needs help them to become empathic and reflective individuals. Besides that, the programmes instilled good work ethics to ensure success in their future careers. Aspects of rethinking behaviour 5. modification and intervention among reckless bikers (Mat Rempit) via youth-to-youth engagement in positive activities will be explored and shared in this article. 38-42

Keyword: GENIUS Remaja, youth empowerment, youth-to-youth empowerment. References: 1. Alicea,S., Pardo,G.,Conover,K.,Gopalan, G., & McKay, M. “Step-up: Promoting youth mental health and development in inner- city high schools”. Clinical Social Work Journal, vol. 40 no. 2,2012, pp. 175– 186. 2. Blanchet-Cohen, N., & Salazar, J, “Empowering practices for working with marginalized youth”, Relational Child & Youth Care Practice, vol. 22, no. 4, 2009, pp. 5–15. 3. Hazita, A., Bahiyah, A. H., & Zarina, O, “Malaysian Youth in the Global World: Issues and Challenges”, Bangi: Penerbit Universiti Kebangsaan Malaysia, 2011. 4. Jennings, L.B., Parra-Medina, D.M., Messias, D.K.H., & McLoughlin, K, “Toward a critical social theory of youth empowerment”, Journal of Community Practice, vol.14 no.1-2, 2006, pp. 31–55. 5. Malaysian Youth Index, “Malaysian Institute for Research in Youth Development. Ministry of Youth and Sports, Putrajaya”, 2015. 6. Ministry of Education, “Malaysia Education Blueprint Annual Reports 2013. Putrajaya”, 2014 7. Muhamad Fuad Abdul Karim, Rokiah Ismail, and Mohamad Fauzi Sukimi, “Sub-budaya Mat Rempit dan Perubahan Sosiobudaya, Malaysian Journal of Society and Space”, Vol.3, 2009, 26-43(In Malay) Injury Severity Analysis of Accidents Involving Young Motorcycle Riders in Malaysia. 8. Mohamed, I. A., & Wheeler, W, “Broadening the bounds of youth development, youth as engaged citizens”. The Innovation Center for Community and Youth Development and The Ford Foundation, 2001, pp. 1-15. 9. Pearrow, M.M, “A critical examination of an urban-based youth empowerment strategy: The teen empowerment program.”, Journal of Community Practice, vol. 16, no.4, 2008, pp. 509–525. 10. Rahim, S. A, “Regenerating Youth Development: The Challenges for Development Communication” The Journal of Development Communication, 2014, 17-27. 11. Rogers, E, Diffusion of Innovation. New York. Free Press, 2003. 12. Rokiah Ismail, “Kumpulan ‘Mat Motor’ dan perlumbaan motor haram: Suatu penelitian dari aspek sosiologi”, Prosiding Seminar Kebangsaan Ke-3 Psikologi dan Masyarakat 2004. Pusat Teknologi Pendidikan, Universiti Kebangsaan Malaysia. 4-5 Oktober, 2004. 13. Rozmi Ismail, “Gejala perlumbaan motosikal haram di kalangan remaja: Peranan keluarga dan masyarakat dalam mengenai gejala ini”, Prosiding Seminar Kebangsaan Ke-3 Psikologi dan Masyarakat 2004. Pusat Teknologi Pendidikan, Universiti Kebangsaan Malaysia. 4-5 Oktober 2004. 14. Rozmi Ismail. “Personaliti dan Salah laku di Kalangan Mat Rempit.” A report submitted to the Malaysian Institute for Research in Youth Development, 2007. 15. Schaefer RT, “Sociology”. Mc Graw Hill, New York, NY, 2003. 16. Singhal, A. “Turning Diffusion of Innovation Paradigm on its Head: The Positive Deviance Approach to Social Change”. In Arun Vishwanath & George Barnett (in press). Advances in the Study of the Diffusion of Innovation; Theory, Methods, and Application, 2010. 17. World Youth Report, Young People Today, and in 2015. United Nations, 2015. 18. Yohalem, N., & Martin, S, “Building the evidence base for youth engagement: Reflections on youth and democracy”, Journal of Community Psychology, vol. 35, no. 6, 2007, pp. 807–810. Authors: Fauziah Ibrahim, Ezarina Zakaria, Norulhuda Sarnon, Salina Nen, Nazirah Hassan Relationship between Emotional Disturbance, Family Conflict, Social Pressure and Drug Craving Paper Title: Among Former Drug Addicts Abstract: Research on drug cravings among former drug addicts is an important issue to be addressed in order to provide input to the government in an effort to prevent relapse among former drug addicts. This article aims to identify the relationship between emotional disturbance, family conflict, social pressure and drug cravings among former drug addicts. A survey study was conducted by using a cross sectional design. A total of 380 former addicts, who completed the rehabilitation program at the Cure and Care Rehabilitation Center (CCRC) and were undergoing a period of supervision by the National Anti-Drug Agency (AADK), were selected to participate in the survey study. The data were analyzed using an inferential statistic, the Pearson Correlation test. The results showed a moderate and positive significant relationship between drug cravings and emotional disturbance (r = .703, p <0.01), family conflict (r = .540, p <0.01) and social pressure (r = .606, p <0.01) among former addicts. These findings indicated that emotional disturbance, family conflict and social pressure that experienced by former addicts should be tackled by the stakeholders as it has a significant relationship with cravings, which may lead to relapse among former addicts.

Keyword: emotional disturbance, family conflict, social pressure, drug craving, drug addicts References: 1. Ekhtiari H. (2008). Cognitive and neural infrastructure of craving, assessment and intervention methods. J Addict. 3: 90-96. 2. Witkiewitz, K., Lustyk, M. B., & Bowen, S. (2013). Retraining the addicted brain: A review of hypothesized neurobiological 6. mechanisms of mindfulness-based relapse prevention. Psychology of Addictive Behaviors. 27(2):351-365. 3. Koob GF, Le Moal M. (2001). Drug addiction, dysregulation of reward and allostasis. Neuropsychopharmacology. 24(2):97–129 4. Fauziah Ibrahim, Ezarina Zakaria, Salina Nen, Norulhuda Sarnon & Nazirah Hassan. (2018). Pengaruh Gangguan Emosi Dalam 43-47 Kalangan Orang Kena Pengawasan. Jurnal Psikologi Malaysia, 32(4):159-171 5. Norazleen Mohamad Noor. (2015). Kerinduan dan ketagihan terhadap dadah: Punca belia kecundang dan kembali menagih. International Drug Prevention and Rehabilitation Conference (Prevent 2015). Selangor. 6. Fauziah Ibrahim, Bahaman Abu Samah, Mansor Abu Talib & Mohamad Shatar Sabran. (2012). Penagih dadah dan keadaan berisiko tinggi kembali relaps. eBangi Jurnal Sains Sosial dan Kemanusiaan. 7(1):1-13. 7. Melemis S.M. (2015). Relapse prevention and the five rules of recovery. YALE Journal of Biology and Medicine, 88: 325-332. 8. Agensi Anti Dadah Kebangsaan (2019). Statistik Maklumat Dadah 2019. Kementerian Dalam Negeri, Selangor. 9. Zainudin Sharif & Norazmah Mohamad Roslan. (2011). Faktor-faktor yang mempengaruhi remaja terlibat dalam masalah sosial di sekolah Tunas Bakti, Sungai Lereh, Melaka. Journal of Education Psychology & Counseling 1(1):115-140. 10. Stevens, Alex and Trace, Mike and Bewley-Taylor, D. (2005) The Reduction of Drug-Related Crime: an overview of the global evidence. Project report. The Beckley Foundation, Oxford. 11. Fauziah Ibrahim, Ezarina Zakaria, Norulhuda Sarnon, Salina Nen, Suzana Mohd Hoesni, Khadijah Alavi, Nasrudin Subhi dan Mohd Suhaimi Mohamad. (2016). Meneroka Pendekatan Fenomenologikal Sosial Jenayah Jalanan dan Mekanisme Pencegahan Berasaskan Komuniti. Laporan Penyelidikan ERGS. UKM: Bangi. 12. Kassel, J. D. (Ed.). (2010). Substance abuse and emotion. Washington, DC, US: American Psychological Association. 13. Zywiak W.H, Stout R.L, Trefry W.B, Glasser I, Connors G.J, Maisto S.A, Westerberg V.S. (2006). J Subst Abuse Treat. 30(4):349-53. 14. Cornelius J.R, Maisto SA, Martin, CS, Bukstein OG, Salloum IM, Daley, DC, Wood DS, Clark DB. (2004). Major depression associated with earlier alcohol relapse in treated teens with alcohol use disorder. Addict Behav. 29:1035–1038. 15. Tiffany ST. Drug craving and affect. In: Kassel JD, (2010). Substance Abuse and Emotion. Washington DC: American Psychological Association; pp. 83–108. 16. James, R. McKay. (2012). Negative Mood, Craving and Alcohol Relapse: Can Treatment Interrupt the Process? Current Psychiatry Reports. 13(6): 431-433. 17. Raheleh Haghiaght, Nezamaddin Ghasemi, Mehdi Rabiei, Asghar Zerehposh, Ahmadreza Kiani. (2013). The Comparison of Attentional Bias and Difficulty of Emotional States Regulation and Their Correlation with Craving Severity in Drug Abuser Methamphetamines and Crack. Zahedan Journal of Research in Medical Sciences. 16(Suppl 1): 29-34 18. Fals-Stewart, W., & Clinton-Sherrod, M. (2009). Treating intimate partner violence among substance-abusing dyads: The effects of couples therapy. Professional Psychology: Research and Practice, 40(3), 257–263 19. Tobler, A. L., & Komro, K. A. (2010). Trajectories of parental monitoring and communication and effects on drug use among urban young adolescents. The Journal of Adolescent Health, 46(6): 560–568. 20. McCarty, D., Perrin, N. A., Green, C. A., Polen, M. R., Leo, M.C,& Lynch, F. (2010). Methadone maintenance and the cost and utilization of health care among individuals dependent on opioids in a commercial health plan. Drug and alcohol dependence, 111(3): 235-240 21. Asbah Razali, Zainal Madon, Rumaya Juhari & Hasnarul Khadi Abu Samah (2016). International Journal of Pharmacy & Pharmaceutical Research. Vol. 7(4): 326-341. 22. Copello A.G, Templeton L, Velleman R. (2006). Family interventions for drug and alcohol misuse: is there a best practice?. Curr Opin Psychiatry. 19(3):271-276 23. Samira G., Haslinda A., Nobaya A., Ali A. (2010). Enviromental Factors Influencing Relapse Behavior among Adolescent Opiate Users in Kerman (A Province in Iran). Global Journal of Human Social Science. 10(4): 71-76 24. Clapp J.D & McDonnell A.L. (2000). The relationship of perceptions of alcohol promotion and peer drinking norms to alcohol problems reported by college students. J Coll Stud Dev. 41:19–26. 25. Johnston, L.D, O’Malley, P.M Bachman, J.G. (2005). Monitoring the Future National Results on Adolescent Drug Use: Overview of Key Findings, Bethesda, MD: National Institute on Drug Abuse 26. Fauziah Ibrahim & Naresh Kumar. (2009). Factors Effecting Drug Relapse in Malaysia: An Empirical Evidence. Asian Social Science, 5(12):37-44. 27. Mahmud Mazlan, Schottenfeld, R.S. & Chawarski, M.C. (2006). New Challenges and Opportunities in Managing Substance Abuse in Malaysia. Drug and Alcohol Review, 25(5), 473-478. 28. Malhotra, N.K., Hall, J., Sham, M & Crsip, M. 1996. Marketing Research: Applied Orientation (1st Edition). Sydney: Prentice Hall. 29. Agensi Anti Dadah Kebangsaan (2016). Statistik Maklumat Dadah 2016. Kementerian Dalam Negeri, Selangor. 30. Cohen, L., Manion, L. & Morrison, K. (2001). Research Methods in Education (5th ed.). London: Routledge Falmer. 31. Mohd Najib Abdul Ghaffar. (1999). Kaedah Penyelidikan Pendidikan. Skudai: Penerbitan. Universiti Teknologi Malaysia. Edisi Kedua. 32. Fauziah Ibrahim, Ezarina Zakaria, Salina Nen, Norulhuda Sarnon & Siti Mariam Mursidan. (2017). Kadar Kecenderungan Relaps dan Kejayaan Mengekalkan Kepulihan dalam Kalangan Penghuni yang Tamat Menjalani Rawatan dan Pemulihan di CCRC. Laporan Akhir Penyelidikan: UKM-AADK, Selangor Authors: Siti Marziah Zakaria, Nor Hazila Mat Lazim, Suzana Mohd. Hoesni

Paper Title: Life Challenges and Mental Health Issues of Single Mothers: A Systematic Examination Abstract: Abstract: As the number of single mothers worldwide increases, their challenges and health issues were discussed in the previous literature. This systematic analysis aims to reveal mental health problems of single-mothers and discuss the adversities faced by them. Financial hardship was seemingly the most significant problem among the low incomes, unemployed and poor single mothers, which showed that poverty and mental health problems were inextricably related. Several factors were found in this study, which has led the single mothers to poverty, such as low-income employment, large numbers of self-employment, unemployed, low education level, lack of adequate skills and age factor. In addition to that, numerous lines of research have indicated that low social support from the surrounding area was the factor of the distress of single mothers. Previous studies showed that single mothers use negative coping strategies, for example, consuming drugs, cigarettes, alcohol, and anti-depressants to alleviate the effects of stressful life. These coping strategies were found to be harmful to their physical and mental health. Therefore, suggestions and recommendations are provided to improve the lives of single mothers and their children to accomplish quality of life.

Keyword: Mental Health, Single Mother, Systematic Analysis, Well-Being References: 1. World Health Organization (WHO). (2017). Depression and Other Common Mental Disorders. Geneva: World Health Organization. 7. 2. World Health Organization (WHO). (2000). Women’s Mental Health: An Evidence Based Review. Geneva: World Health Organization. 3. World Health Organization (WHO). (2001). Mental Health: New Understanding, New Hope. Geneva: World Health 48-52 Organization. 4. Nicholson, J., Biebel, K., Hinden B., Henry, A., & Stier, L. (2001). Critical Issues for Parents with Mental Illness and their Families. Worcester, MA: Center for Mental Health Services Research, Department of Psychiatry, University of Massachusetts Medical School. 5. Hew, C.S. (2003). The Impact of Urbanization on Family Structure: The Experience of Sarawak, Malaysia. SOJOURN, 18(1), 89- 109. 6. Subramaniam, M., Prasad, R. O., Abdin, E., Vaingankar, J. A., & Chong, S. A. (2014). Single mothers have a higher risk of mood disorders. Annals of the Academy of Medicine, Singapore, 43(3), 145–151. 7. Evans, M. (2011). Single Mothers in Malaysia: Social Protection as an Exercise of Definition in Search of Solution. International Conference of “Social Protection for Social Justice” Institute of Development Studies, UK 8. M. Bakri, M. (2002). Malaysia in the era of globalization. Lincoln: Writer’s Club Press Rohaty. 9. Nor Aini, I., & Selvaratnam, D. P. (2012). Program pembasmian kemiskinan dalam kalangan ibu tunggal: Analisis penyertaan dan keberkesanan. Prosiding Perkem, 1, 248–259. 10. Jayakody, R., & Stauffer, D. (2000). Mental health problems among single mothers: Implications for work and welfare reform. Journal of Social Issues, 56(4), 617-634. 11. Karupiah, P. (2016). Marital status and the influence of emphasized femininity on the romantic relationships of tamil single mothers in Malaysia. Contemporary Perspectives in Family Research, 10, 375–393. https://doi.org/10.1108/S1530- 353520160000010015. 12. Intan Hashimah, M.H., Azman Azwan, A., & Noraida, E. (2015). Stress, Roles and Responsibilities of Single Mothers in Malaysia. SHS Web of Conferences, 18 (3), 1–7. https://doi.org/ 10.1051/shsconf/20151803003. 13. Bull, T., & Mittelmark, M. B. (2009). Work life and mental wellbeing of single and non-single working mothers in Scandinavia. Scandinavia Journal of Public Health, 37, 562–568. https://doi.org/10.1177/1403494809340494 14. Kotwal, N., & Prabhakar, B. (2009). Problems Faced by Single Mothers. Journal of Social Sciences, 21(3), 197–204. https://doi.org/10.1080/09718923.2009.11892771 15. Kim, G. E., Choi, H., & Kim, E. (2018). Impact of economic problems on depression in single mothers: A comparative study with married women. PLoS ONE, 13(8), 1–14. https://doi. org/10.1371/journal.pone.0203004. 16. Faizah, G., & Hazirah, H. (2013). Challenges and Locus Control among Single Mothers in Muar. Journal of Emerging Trends in Educational Research and Policy Studies, 4(5), 760–765. 17. Stack, R. J., & Meredith, A. (2018). The Impact of Financial Hardship on Single Parents: An Exploration of the Journey from Social Distress to Seeking Help. Journal of Family and Economic Issues, 39 (2), 233–242. https://doi.org/10.1007/s10834-017- 9551-6. 18. Wang, J.L. (2004). The difference between single and married mothers in the 12-month prevalence of major depressive syndrome, associated factors and mental health service utilization. Soc Psychiatry Epidemiology, 39, 26–32. https://doi.org/10.1007/s00127-004-0699-7 19. Nurliza, A., Khadijah, A., Arena, C.K., & Chong, S.T (2015). Psychological Well-Being among Single Mothers of Rural and Urban Areas in Selangor. International Journal of Technical Research and Applications, 25(25), 43–46. 20. Siti Rafiah, A.H., & Sakinah, S. (2013). Exploring Single Parenting Process in Malaysia: Issues and Coping Strategies. Procedia - Social and Behavioral Sciences, 84, 1154–1159. https://doi.org/10.1016/j.sbspro.2013.06.718 21. Rohayu, R., Noor Sharipah, S. S., Yusmarwati, Y., Maziana, M., & Abdul Rasid, A. R. (2000). Poverty Alleviation among Single MotheriIn Malaysia: Building Entrepreneurship Capacity. International Journal of Business and Social Science, 2 (17), 92–99. 22. Berkman, L. F., Zheng, Y., Glymour, M. M., Avendano, M., Börsch-supan, A., & Sabbath, E. L. (2015). Mothering alone: cross- national comparisons of later-life disability and health among women who were single mothers. Journal Epidemiol Community Health, 69(9), 865–872. https://doi.org/10.1136/jech-2014-205149 23. Meier, A., Musick, K., Flood, S., & Dunifon, R. (2016). Mothering Experiences: How Single Parenthood and Employment Structure the Emotional Valence of Parenting. Demography, 53(3), 649–674. https://doi.org/10.1007/s13524-016-0474-x. 24. Turner, H. A. (2007). The significance of employment for chronic stress and psychological distress among rural single mothers. American Journal of Community Psychology, 40(3–4), 181–193. https://doi.org/10.1007/s10464-007-9141-0. 25. Turney, R. J., & Brown, R.L. (2010). Social Support and Mental Health. In Scheid, T. L., & Brown, T. N (Eds.) A Handbook for the Study of Mental Health. Cambridge: Cambridge University Press. Second Edition. 26. Mowbray, C., Schwartz, S., Bybee, D., Spang, J., Rueda-Riedle, A., & Oyserman, D. (2000). Mothers with a Mental Illness: Stressors and Resources for Parenting and Living. Families in Society: The Journal of Contemporary Social Services, 81(2), 118– 129. https://doi.org/10.1606/1044-3894.1006 27. Crosier, T., Butterworth, P., & Rodgers, B. (2007). Mental health problems among single and partnered mothers: The role of financial hardship and social support. Social Psychiatry and Psychiatric Epidemiology, 42(1), 6–13. https://doi.org/10.1007/s00127-006-0125-4. 28. Dayang Suria, M. (2017). Survival Strategies of Single Mothers among Indigenous Ethnics in Rural Areas: Case Study in Kota Belud, Sabah. Jurnal Kinabalu, 23, 43-64. 29. Noraida, E., Azman Azwan, A, & Intan Hashimah, M.H. (2015). Formal and Informal Support Systems for Single Women and Single Mothers in Malaysia. SHS Web of Conferences, 18. 30. Dipple H, Smith S, Andrews H, Evans B. (2002). The experience of moth- erhood in women with severe and enduring mental illness. Soc Psychiatry Epidemiol, 37, 336–340. 31. Mullick M, Miller LJ, & Jacobsen T. (2001). Insight into mental illness and child maltreatment risk among mothers with major psychiatric disorders. Psychiatry. Serv. 52: 488–492. 32. Blegen, N. E., Hummelvoll, J.K., & Sverinsson, E. (2010). Mothers with mental health problems: A systematic review. Nursing and Health Sciences, 12, 519–528. 33. Sperlich, S., & Maina, M. N. (2014). Are single mothers’ higher smoking rates mediated by dysfunctional coping styles? BMC Women’s Health, 14(1), 1–7. https://doi.org/10.1186/1472-6874-14-124 34. Richards, L.N., & Schmiege, C.J. (1993). Problems and Strengths of Single-Parent Families: Implications for Practice and Policy. Family Relations, 42 (3), 277–285. Mohd Nasir Selamat, Mukhiffun Mukapit, Siti Fardaniah Abd Aziz , Zafir Khan Mohamed Authors: Makhbul Paper Title: Re-definition of Occupational Safety and Health Performance in Malaysian Manufacturing Industry Abstract: Occupational safety and health (OSH) aspect in organization plays an important role in enhancing workers and job performance. This study aim is to conduct a systematic review of the literature on the definition of OSH performance in order to generalize the concept of OSH in organization. The search strategy targeted several electronic databases and identified more than 1000 potential articles. By focusing on the issues of OSH aspect in organization, few articles were examined (assessed with at least one related OSH aspects, published in Malay and English in peer reviewed literature). At the end, several articles met relevance criteria and were then appraised for methodological strength. The result shows varieties of definition and concept of OSH. The main purpose of implementing OSH at work is to reduce all safety and health problems affecting workers and those that related to workers’ connection with the organization. Therefore, a good implementation of OSH at work is required in order to achieve the organization’s objectives. In conclusion, OSH aspects have respective diversity approaches to enhance workers’ well-being and performance at work. 8. Keyword: Occupational Safety and Health (OSH), Workers performance, Job Performance 53-60 References: 1. Selamat, M. N. & Surinty, L. (2015). An Examination of Commuting Accident in Malaysia. Journal of Occupational Safety and Health, 12 (1), 171-178. ISSN 1675-5456. 2. Selamat, M. N. (2016). Ergonomic Work System and Occupational Safety and Health Performance: Mediating Effects of Psychosocial Work Factors. Doctoral Philosophy Thesis, Universiti Sains Malaysia, Penang, Malaysia. 3. Selamat, M. N. & Mukapit, M. (2018). The Relationship Between Task Factors & Occupational Safety and Health (OSH) performance in the printing industry. Akademika. ISI ESCI Indexed 4. Shan, C. W. (2011). Quantitative approach to site accident in Malaysia. Unpublished bachelor degree dissertation, Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia. 5. Yakubu, D. M., & Bakri, I. M. (2013). Evaluation of safety & health performance on construction sites (KL). Journal of Management and Sustainability, 3(2). 6. Zakaria, N. H., Mansor, N., & Abdullah, Z. (2012). Workplace accident in Malaysia: Most common causes and solutions. Business and Management Review, 2(5), 75-88. 7. Ayers, P. A., & Kleiner, B. H. (2002). New development concerning managing human factors for safety. Managerial Law Journal, 44. 8. Smith, M. J., & Carayon, P. S. (2000). Work organization and ergonomics. Applied Ergonomics, 31, 649-662.Tetrick LE, eds. Handbook of occupational health psychology. Washington, DC: American Psychological Association, 2003:123-42. 9. Selamat, M. N. (2013). The determinant of OSH performance: A study on ergonomic work system. 23rd Conference on Epidemiology in Occupational Health (EPICOH 2.0.13): Improving the Impact. June 18-21, 2013, Utrecht, The Netherlands. Published at the Journal Occupational Environmental Medicine, 2013, 70: A4. doi: 10.1136/oemed-2013-101717.139. 10. Hasse, N., Birgitta, W., Hans, H., Ragnar, W. (2017). A cross-sectional study of factors influencing occupational health and safety management practices in companies. Safety Science 95, 92–103 11. Khon, J. P., Friend, M. A., & Winterberger, C. A. (1996). Fundamental of occupational safety and health. Industrial Technology Department, East Carolina University, Greenville, North Carolina. 12. Archer, R., Borthwick, K., & Tepe-Susanne. (2009). OS&H a management guide. Engage Learning Australia 2009. 13. Hazlina, Y. (2007). Factors associated with chemical safety status in small and medium Printing Enterprises in Penang. Masters Thesis, Universiti Sains Malaysia, Penang, Malaysia. 14. Spector, P. E. (2008). Industrial and organizational psychology. 5th Edition. John Wiley & Sons, LTD. 15. Campbell, J. P., McCloy, R. R., Oppler, S. H., & Sager, C. E. (1993). A theory of performance. In E.Schmitt, W. C. Borman, & Associates, (Eds). Personnel selection in organizations. San Fracisco: Jissey-Bass. 35-70. 16. Motowildo, S. J., Borman, W. C., & Schmit, M. J. (1997). A theory of individual differences in task and contextual performance. Human Performance, 10, 71-83. 17. Ahmadon, B., Rosli, M. Z., Mohd-Saidin, M., & Abdul-Hakim, M. (2006). Occupational safety and health (OSH) management systems: towards development of safety and health culture. Proceedings of the Sixth Asia-Pacific Structural Engineering and Construction Conference (APSEC 2006), 5-6 September 2006, Kuala Lumpur, Malaysia. 18. Carayon, P. (2009). The Balance Theory and the Work System Model… Twenty years later. INTL. Journal of Human-Computer Interaction, 25(5), 313-327. 19. Khoo, T. H. (2012). Safety management practices and safety behavior: A study of SME in NCER, Malaysia. Unpublished Master of Art (Management), Universiti Sains Malaysia, Penang, Malaysia. 20. Salleh, A. L., Abu-Bakar, R., & Keong, W. K. (2008). How detrimental is job stress? A case study of executives in the Malaysian furniture industry. International Review of Business Research Papers, 4(5), 64-73. 21. Seok, J. Y., Hsing, K. L., Gang, C., Shinjea, Yi., Jeawook, C., & Zhenhua, R. (2013). Effect of occupational health and safety management system on work-related accident rate and differences of occupational health and safety management system awareness between Managers in South Korea’s Construction Industry. Safety and Health at Work, 4, 201-209. 22. Ludin, E. (1994). Health and Safety Management. Ministry of Human Resource Bulletin, Special Edition. National OSH campaign towards safe and healthy work culture. 45-59. 23. Donato, M., Enrico, C., & Guido, J. L. M. (2014). Developing, implementing and evaluating OSH interventions in SMEs: A pilot exploratory study. International Journal of Occupational Safety and Ergonomics (JOSE), 20(3), 385-405. 24. Seabrook, K. A., & Winterholer, B. (2006). The American society of safety engineer. http://www.asse.org/practicespecialties/interviews/SeabrookWinterholer.php 25. Cohen, A., & Colligan, M. J. (1998). Assessing OSH Training: A Literature Review, DHHS (NIOSH) Publication, 98-145. 26. Cohen, J. M. (2002). Measuring safety performance in construction. Occupational Hazard, 64(6), 41-45. 27. Grimaldi, J. V., & Simonds, R. H. (2001). Safety management, 5th Edition. Delhi: A.I.T.B.S. Publishers & Distribution. 28. Gerard, I. J. M. Z, Arjella, R., van-Scheppingen, Evelien, H. B., Anja, D., & Annick, S. (2013). The core values that support health, safety, and well-being at work. Safety and Health at Work, 4(4), 187-196. 29. Lateef, Ur-Rehman & Ateekh, Ur-Rehman. (2012). Safety management in a manufacturing company: Six Sigma Approach. Engineering, 4, 400-407. 30. Toellner, J. (2001). Improving safety & health performance: Identifying and measuring leading indicators. Professional Safety, 42-47. 31. Rancour, T., & McCracken, M. (2000). Applying six sigma methods for break through safety performance. Personal Safety, 29- 32. 32. Burke, M. J., Sarpy, S. A., Tesluk, P. E., & Smith-Crowe, K. (2002). General safety performance: A test of a grounded theoretical model. Personnel Psychology, 55, 429-457. 33. Muhamad, s. (2003). Scorecard Approach to Benchmarking Organizational Safety Culture in Construction, Journal of Construction Engineering and Management, 123 (1). 34. Webb, D. A. (1994). The bathtub effect: Why safety programs fail. Management Review, 83(2), 51. 35. Nikolaos, G. (2010). The Measurement of health and safety conditions at work theoretical approaches, tools, and techniques a literature review. International Research Journal of Finance and Economics, 36. 36. Saad, M. S., Said, F., & Abdul-Halim, Z. (2012). The determinants of industrial accidents in the Malaysian manufacturing sector. African Journal of Business Management, 6(5), 1999-2006. 37. Zafir, M. M., Nor-Liza, A., & Zizah, C. S. (2013). Ergonomics and stress at workplace: engineering contributions to social sciences. Jurnal Pengurusan, 37, 125-131. 38. Smith, M. J., & Carayon, P. S. (1989). A balance theory of job design for stress reduction. International Journal of Industrial Ergonomics, 4(1), 67-79. 39. Noblet, A., & Lamontagne, A. D. (2006). The role of workplace health promotion in addressing job stress. Health Promotion International, 21(4), 346-353. 40. Zuraidah, O. (2001). Managing performance in Malaysian organizations; Series Editor: Maimunah Aminuddin. Mc Graw Hill, Kuala Lumpur. 41. Hesselius, P. (2007). Does sickness absence increase the risk of unemployment? The Journal of Socio-Economics, 36, 288-310. 42. Kerr, R., Mc Hugh, M., & McCrory, M. (2009). HSE management standards and stress- related work outcomes. Occupational Medicine, 59, 574-579. 43. Michie, S., & Williams, S. (2003). Reducing work related psychological ill health and sickness absence: A systematic literature review. Occupational and Environmental Medicine, 60, 3-9. 44. Shikdar, A. A., & Sawaqed, N. M. (2003). Worker productivity and occupational health and safety issues in selected industries. Computer and Industrial Engineering, 45, 563-572. 45. Gallagher, C., Elsa U., & Malcolm R. (2003) Occupational safety and health management systems in Australia: barriers to success, Policy and Practice in Health and Safety, 1:2, 67-81, DOI: 10.1080/14774003.2003.11667637 46. Ingalls, Jr. T. S. (1999). Using scoreboard to measures safety performance. Professional Safety, 44(2), 23-29. Authors: Nasrudin Subhi, Nor Jana Saim, Salina Nen, Mastura Mahmud, Norulhuda Sarnon

Paper Title: Contributing Factors in Publications Among Academicians Abstract: The excellence of academicians in universities at present is determined by several indicators, 9. including the high number of publications. Academicians with a high number of publications will often be attentive to colleagues and employers for being able to bring a good reputation to the university. Administrators use publishing as one of the key criteria in measuring the competence of an academician and determining 61-66 promotion. The study aims to explore factors that contribute to the performance of publishing among academic staff in UKM. This study uses a qualitative app inroach to collect and analyze findings. In-depth interviews using semi-structured questions are the primary means of data collection. This study involved a total of 10 informants consisting of two target groups which are excellent in publishing group and less excellent in publishing group. Analysis was conducted thematically. The findings show three main factors contributing to the excellence of publications namely (i) personal (ii) workplace climate, and (iii) interpersonal relationships in the workplace. In conclusion, success in determining excellence in publications requires the balance and well-being of the social environment. The recommendations of this study can be used as means to assist university management to increase publications among the academic staff of the university.

Keyword: publication, academicians, qualitative study, thematic analysis References: 1. Roy, D. K. The rush to publish: where are we heading? Journal of Kathmandu Medical College, 6(4), Issue 22, Oct – Dec, 127- 128. 2017. 2. Jahani, S., Ramayah, T. & Abdullah Effendi, A. Is reward system and leadership important in knowledge sharing among academics? American Journal of Economics and Business Administration, 3(1), 87-94. 2011. 3. Scott, W. R. Organizations: rational, natural and open system. 5th. Edn., Prentice Hall: New Jersey, ISBN: 0132663546, pp:416. 2003. 4. Dodani, S., & LaPorte, R.E. Ways to strengthen research capacity in developing countries: effectiveness of a research training workshop in Pakistan. Public Health, 122(6), 578-587. 2008. 5. Dessi, Y., & Mesfin, F. Researchers’ challenges: findings from in-depth interview among academicians in Haramaya University, Ethiopia. Herald Journal of Education and General Studies, 2(2), 069 – 071. 2013. 6. Norhazwani, Y., & Zainab, A. N. Publication productivity of Malaysian authors and institutions in LIS. Malaysian Journal of Library & Info Science, 12(2), 35 – 55. 2007. 7. Jusoff, K. Reconciling challenges and opportunities in academic scientific witting. Academic Leadership, 8(3), 85 – 90. 2010. 8. 8Ina Suryani, Aizan Yaacob, Noor Hashima, Salleh Abd Rashid & Hazry Desa. Research publication output by academicians inpublic and private universities in Malaysia. International Journal of Higher Education, 2(1), 84 – 90. 2013. 9. Braun, V. & Clarke, V. Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77-101. 2006. 10. Ryan, G.W. & Bernard, H.R. Techniques to Identify Themes. Field Methods,15(1), 85-109. 2003. 11. Goerg, S. J. Goal setting and worker motivation: Individual work goals can increase a worker’s performance, but they need to be chosen wisely. IZA World of Labor, 178, 1-10. 2015. 12. Brailsford I. “We know no such profession as a university teacher” New Zealand academics' teaching capabilities and student performance in the years of academic boom and student strife. History of Education Review, 40(1):30-46. 2011. 13. Rusu, G., & Avasilcai, S. Linking human resources motivation to organizational climate. Procedia- Social and Behavioral Sciences, 124, 51-58. 2014. 14. Danish RQ, Usman A. Impact of reward and recognition on job satisfaction and motivation: An empirical study from Pakistan. International journal of business and management, 5(2):159-171. 2010. 15. Douglas, E. J. & Morris, R. J. (2006). Workaholic or hard worker? Career Development International, 11, 394 - 417. Noremy Md Akhir, Mohammad Rahim Kamaluddin, Aizan Sofia Amin, Rusyda Helma Mohd, Nur Authors: Hafizah Md Akhir Exploring the Coping Strategies that Improve Resiliency among Flood Victims in Kelantan, Paper Title: Malaysia Abstract: The major flood incident in Kelantan in 2014 was an unexpected disaster that caused physical destructions as well as psychological problems. A number of literatures have highlighted coping strategies as one of the resilience factor that can actually protect the flood victims from experiencing psychological distress. With this in mind, this study was conducted explore the coping strategies used by the flood victims in Kelantan. A total of 28 flood victims were selected as potential informants in this study based on predetermined inclusion criteria using a purposive sampling method. A qualitative research design using case study approach was employed in this study. In-depth and face to face interview sessions were carried out using an interview guide. The interviews were analyzed using thematic analyses and four main coping strategies were emerged as themes namely, problem focused coping, emotion focused coping, religious coping and maladaptive coping strategy. The coping strategies used by the victims to improve resiliency were discussing from the context of psychological and social work perspectives. It is anticipated the findings of this study would provide valuable information for the development of crisis intervention programs and modules.

Keyword: Coping strategy, resiliency, flood victims, flood disaster. 10. References: 1. Economic Planning Unit (EPU), State of Kelantan. (Conferences paper) Kelantan Flood Management Conference 2015: 67-73 Resolution and framework for sustainable development. Kubang Kerian, Kelantan: University of Sciences Malaysia. 2015. 2. G. Sikh. Reflections From Flooding Events in Kelantan. (Conference Paper) Kelantan Mental Health Conferences. Kelantan: Kelantan State Health Department. 2015. 3. M. A. Noremy, A. Azlinda, H. Nazirah & M. A. Nur Hafizah. (2017). Investigation of flood victim’s problem during flood disaster December 2014 in Kelantan, Journal of Social Sciences and Humanity, 14 (5), 1-19. 4. K. A. Becker-Blease, H. A. Turner & D. Finkelhor. (2010). Disaster, victimization and children’ mental health. Child Development 81(4), 1040-1052. doi:10.1111/j.1467-8624.2010.01453.x 5. C. T. Taft, C. M. Monson, J. A. Schumm, L. E. Watkins, J. Panuzio & P. A. Resick. (2009). Posttraumatic stress disorder symptoms, relationship adjustment, and relationship aggression in a sample of female flood victims. Journal Family Violence, 24, 389-396. 6. M. K. Lindell & C. S. Prater (2004). Assessing community impacts of natural disasters. Natural Hazards Review, 4(4), 176-186. doi:10.1061/(ASCE)1527-6988(2003)4;4(176). 7. H. Muzairi, M. N. Mohd Zawari & W.M. Wan Nor Arifin,. Exploring emotion disasters and resilience in adolescent affected by flood in Kelantan and the development of peer support group for trauma module. Final Report of the 2014 Flood Disaster Research (Conference paper) Part 1 Socio Economic, pp. 244-247. University of Technology Malaysia: Ministry of Higher Education. 2015. 8. Y. Norizan (2016). Management of psychological elements in disaster preparedness: A qualitative study of flood victims in Kelantan. Malaysian Journal of Psychology, 30(2), 74-81. URL: http://spaj.ukm.my/ppppm/jpm/issue/view/26 9. M. A. Nur Saadah, A. K. Nor Ba’yah, A. R. Roseliza Murni, A. Hilwa, M. A. Noor Amalina. Assistance and disaster preparedness: Evaluation of resilient attributes to promote mental health among adolescents and adults of flood victims in Kelantan. Final Report of the Flood Risk Research Conference 2014. (Conference paper) Part 2 Health & Clinical Sciences, pp.282-284. University of Technology Malaysia: Ministry of Higher Education. 2015. 10. M. T. Siti Uzairiah. Qualitative Study and Interview Analysis. Kuala Lumpur, Malaysia: Aras Publisher. 2017. 11. Y. Norizan, Y. (2016). Management of psychological elements in disaster preparedness: A qualitative study of flood victims in Kelantan. Malaysian Journal of Psychology,30 (2), 74-81. URL: http://spaj.ukm.my/ppppm/jpm/issue/view/26 12. A. Zainuddin. Research Methodology and Data Analysis (Second ed.). Malaysia: UiTM Press. 2012. 13. V. Braun & V. Clarke. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2),77-101. doi:10.1191/1478088706qp063oa 14. J. P. Chaplin. Complete Psychology Dictionary. Jakarta: Raja Grafindo Persada. 2004. 15. S. P. Brown, G. Challagalla & R. A. Westbrook. (2005). Good cope, bad cope: Adaptive and maladaptive coping strategies following a critical negative work event. Journal of Applied Psychology, 90(4), 792-798. doi:10.1037/0021-9010.90.4.792 16. S. Folkman, R.S. Lazarus, R. J. Gruen & A. Logis (1986). Appraisal, coping, health status and psychological symptoms. In K. Gelbrich. Anger, frustration, and helplessness after service failure: Coping strategies and effective informational support, Journal of the Academy of Marketing Science, 38, 567–585. doi:10.1007/s11747-009-0169-6. 17. O. Sarid, O. Anson, A. Yaari & M. Margalith (2004). Coping styles and changes in humoural reaction during academics stress. Health and Medicine, 9, 85-98. doi:10.1080/13548500310001637779 18. R. S. Lazarus & S. Folkman. (1984). Stress, appraisal and coping. In C. S. Carver, M. F. Scheier & J. K.Weintraub. Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56(2), 267-283. 19. V. Khoshtinat. (2012). A review on relationship between religion, spirituality, spiritual transcendent, spiritual intelligence with religious coping. International Research Journal of Applied and Basic Sciences, 3(9), 1916-1934. 20. M. E. Wadsworth & B. E. Compa (2002). Coping with family conflict and economic strain: The adolescent perspective. Journal of Adolescent, 12, 243-274. doi:10.1111/1532-7795.00033 21. G. G. Ano & E. B. Vasconcelles. (2005). Religious coping and psychological adjustment to stress: A meta-analysis. Journal Clinical Psychology, 61, 1-20. doi:10.1002/jclp.20049 22. L. R. Wang, S. C. Chen & J. Chen (2013). Community resilience after disaster in Taiwan: A case study of Jialan Village with the strengths perspective. Journal of Social Work in Disability & Rehabilitation, 12 (1-2), 84-101. doi: 10.1080/1536710X.2013.784551 23. T. Lischetzke & M. Eid (2003). Is attention to feeling beneficial or detrimental to affective well-being? Mood regulation as a moderator variable. Emotion Journal, 3, 361-377. doi: 10.1037/1528-3542.3.4.361 24. E. Ashton, M. Vosvick, M. Chesney, G. F. Cheryl, C. Koopman, K. O’shea, J. Maldonado, M. H. Bachmann, D. Israelski, J. Flamm, D. Spiegel (2005). Social support and maladaptive coping as predictors of the change in physical health symptoms among persons living with HIV/AIDS. AIDS Patient and STDs, 19 (9), 587-598. doi:10.1089/apc.2005.19.587 25. T. F. Hack & L. F. Degner. (2004). Coping responses following breast cancer diagnosis predict psychological adjustment three years later. Psychooncology, 13, 235–47. doi:10.1002/pon.739 26. K. M. Paul, C. P. Andrea, L. K. Elizabeth, A. B. Tracy, B. Michael, A. W. Alexi, P. William & G. P. Holly. (2012). Religious coping and behavioral disengagement: Opposing influences on advance care planning and receipt of intensive care near death. Psychooncology, 21(7), 714–723. doi:10.1002/pon.1967. 27. K. Kanel. A Guide to Crisis Intervention (3rd ed.). California: Thomson Brooks Cole. 2007. Authors: Norhayati Ibrahim, A’isyah Mohd Safien, Ching Sin Siau

Paper Title: Validation of the Malay Mental Help Seeking Attitude Scale Abstract: There is a rise in the incidence and prevalence of mental distress among Malaysians. However, the rate of mental health service utilization is low. As mental help-seeking attitude is a strong predictor for seeking mental health treatment, it is important to validate a feasible and psychometrically sound instrument in the Malaysian context. This study aimed to investigate the reliability and validity of a recently developed help- seeking attitude scale, the Mental Help Seeking Attitude Scale (MHSAS) among Malaysian youth. A total of 261 students from a secondary school (n=127) and a university (n=134) from the Klang Valley, Malaysia participated in this study. They were self-administered the 9-item Malay MHSAS along with the General Help- seeking Questionnaire (GHSQ) and Self-Stigma of Seeking Help Scale (SSOSH). Retest of the MHSAS was conducted with 47 students three months later. Factor analysis was employed to evaluate construct validity, while concurrent validity was determined through bivariate correlation with the SSOSH and GHSQ scales. Paired-samples t-test was conducted to evaluate test-retest reliability. The single dimensionality of the MHSAS’s original version was supported. Factor loadings ranged from .636 to .799, and inter-item correlation ranged from .547 to .726. Results revealed high internal consistency and test-retest reliability was confirmed. The scale also demonstrated acceptable concurrent validity when compared with the GHSQ and SSOSH. The Malay version of the MHSAS demonstrated good psychometric properties to measure help-seeking attitudes in the Malaysian 11. youth population. 74-78 Keyword: mental help-seeking, MHSAS, validation, Malaysia, youth. References: 1. P. S. Wang, M. Lane, M. Olfson, H. A. Pincus, K. B. Wells, and R. C. Kessler, "Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication," Arch Gen Psychiatry, vol. 62, pp. 629-40, Jun 2005. 2. S. Mack, F. Jacobi, A. Gerschler, J. Strehle, M. Hofler, M. A. Busch, et al., "Self-reported utilization of mental health services in the adult German population--evidence for unmet needs? Results of the DEGS1-Mental Health Module (DEGS1-MH)," Int J Methods Psychiatr Res, vol. 23, pp. 289-303, Sep 2014. 3. M. Olfson, B. G. Druss, and S. C. Marcus, "Trends in mental health care among children and adolescents," N Engl J Med, vol. 372, pp. 2029-38, May 21 2015. 4. J. Wang, C. Adair, G. Fick, D. Lai, B. Evans, B. W. Perry, et al., "Depression literacy in Alberta: findings from a general population sample," Can J Psychiatry, vol. 52, pp. 442-9, Jul 2007. 5. Institute of Public Health Malaysia, “National Health and Morbidity Survey 2015,” [Online]. Kuala Lumpur: Ministry of Health Malaysia; 2016 Available: iku.moh.gov.my/images/IKU/Document/REPORT/nhmsreport2015vol2.pdf. [cited 2019 Jan 11]. 6. N. Ibrahim, N. Amit, and M. W. Suen, "Psychological factors as predictors of suicidal ideation among adolescents in Malaysia," PLoS One, vol. 9, p. e110670, 2014. 7. A.F. Abdullah, H.I. Minas, G. Meadows and N. Kumaraswamy, “Common mental disorder and mental health services in primary care setting of Kota Kinabalu- treatment gap, disability and needs,” 21–23 July 2011, [16th MCPM Conf. Kuala Lumpur, Malaysia]. 8. W. D. Shoesmith, A. Borhanuddin, P. Yong Pau Lin, A. F. Abdullah, N. Nordin, B. Giridharan, et al., "Reactions to symptoms of mental disorder and help seeking in Sabah, Malaysia," Int J Soc Psychiatry, vol. 64, pp. 49-55, Feb 2018. 9. A. A. Razak, "Cultural Construction of Psychiatric Illness in Malaysia," Malays J Med Sci, vol. 24, pp. 1-5, Mar 2017. 10. H. C. Ong, N. Ibrahim, and S. Wahab, "Psychological distress, perceived stigma, and coping among caregivers of patients with schizophrenia," Psychol Res Behav Manag, vol. 9, pp. 211-8, 2016. 11. L. H. Wee, N. Ibrahim, S. Wahab, U. Visvalingam, S. H. Yeoh, and C. S. Siau, "Health-Care Workers' Perception of Patients' Suicide Intention and Factors Leading to It: A Qualitative Study," Omega (Westport), p. 30222818814331, Nov 27 2018. 12. E. H. Fischer and J. L. Turner, "Orientations to seeking professional help: development and research utility of an attitude scale," J Consult Clin Psychol, vol. 35, pp. 79-90, Aug 1970. 13. C. S. Mackenzie, V. J. Knox, W. L. Gekoski, and H. L. Macaulay, "An Adaptation and Extension of the Attitudes Toward Seeking Professional Psychological Help Scale1," Journal of Applied Social Psychology, vol. 34, pp. 2410-2433, 2004. 14. K. Fang, A.L. Pieterse, M. Friedlander and J. Cao, “Assessing the psychometric properties of the attitudes toward seeking professional psychological help scale-short form in mainland China” Int J Adv Counselling, vol. 33, pp. 309, 2011. https://doi.org/10.1007/s10447-011-9137-1 15. L. Picco, E. Abdin, S. A. Chong, S. Pang, S. Shafie, B. Y. Chua, et al., "Attitudes Toward Seeking Professional Psychological Help: Factor Structure and Socio-Demographic Predictors," Frontiers in psychology, vol. 7, pp. 547-547, 2016. 16. J. H. Hammer, M. C. Parent, and D. A. Spiker, "Mental Help Seeking Attitudes Scale (MHSAS): Development, reliability, validity, and comparison with the ATSPPH-SF and IASMHS-PO," J Couns Psychol, vol. 65, pp. 74-85, Jan 2018. 17. I. Ajzen, "Nature and operation of attitudes," Annu Rev Psychol, vol. 52, pp. 27-58, 2001. 18. J.E. Hair, R.E. Anderson, R.L. Tatham, and W.C. Black, Multivariate Data Analysis: With Readings. Englewood Cliffs, NJ: Prentice–Hall, 1995. 19. Kline, P. Psychometrics and Psychology. London: Academic Press, 1979. 20. Cattell, R. B. The Scientific Use of Factor Analysis in Behavioral and Life Sciences. New York: Springer, 1978. 21. C. J. Wilson, F. P. Deane, J. Ciarrochi, and D. Rickwood, "Measuring Help-Seeking Intentions: Properties of the General Help- Seeking Questionnaire," Canadian Journal of Counselling, vol. 39, pp. 15-28, 2005. 22. A.P. Tuliao, P.A., and Velasquez, “Revisiting the General Help Seeking Questionnaire: Adaptation, exploratory factor analysis, and further validation in a Filipino college student sample,” Phillip J Psychol, vol. 47, pp. 1-7, 2014. 23. D. L. Vogel, N. G. Wade, and S. Haake, "Measuring the self-stigma associated with seeking psychological help," Journal of Counseling Psychology, vol. 53, pp. 325-337, 2006. 24. S. Sezer, and F. Kezer, “The reliability and validity of Self Stigma of Seeking Help Scale (SSOSH) in a Turkish sample,” Düşünen Adam, vol 26,pp.148-56, 2013. 25. R.L. Ebel, Essentials of Educational Assessment. Oxford, England: Prentice Hall, 1972. 26. Cronbach, L.J. Psychometrika (1951) 16: 297. https://doi.org/10.1007/BF02310555 27. B. D'Avanzo, A. Barbato, S. Erzegovesi, L. Lampertico, F. Rapisarda, and L. Valsecchi, "Formal and informal help-seeking for mental health problems. A survey of preferences of italian students," Clinical practice and epidemiology in mental health : CP & EMH, vol. 8, pp. 47-51, 2012. 28. J. H. Hammer and D. A. Spiker, "Dimensionality, reliability, and predictive evidence of validity for three help-seeking intention instruments: ISCI, GHSQ, and MHSIS," J Couns Psychol, vol. 65, pp. 394-401, Apr 2018. 29. Rickwood D, Deane FP, Wilson CJ, Ciarrochi J. Young people’s help-seeking for mental health problems. Aust e-J Adv Ment Health. 2005;4(3):218-51. doi: https://doi.org/10.5172/jamh.4.3.218 30. P. Corrigan, "How stigma interferes with mental health care," Am Psychol, vol. 59, pp. 614-625, Oct 2004. Authors: Saim, N.J., Ghazinour, M., Richter, J. Teenage Pregnancy in Malaysia: Understanding the Importance of Social Support in Relation to Paper Title: Coping, Resilience and Mental Health Abstract: Losing the social support from family and friends may affect coping, resilience and increase a risk of mental health problems among pregnant teenagers and teenage mothers. This article aims to describe the importance and availability of social support related to coping, resilience and mental health among unwed pregnant teenagers and teenage mothers in Malaysia during their stay in a shelter home. A purposive sampling was employed to select seventeen respondents from 128 unmarried pregnant and teenage mothers; age 10 to 18 years living in four different shelter homes owing that they were pregnancy out of wedlock. The findings are based on analysis of interviews and questionnaires related to social support, ways of coping, resilience and mental health. The study found strong indication in both, the qualitative and quantitative data, that unwed pregnant teenagers and teenage mothers have poor social support in terms of availability and adequacy. Hence, it reflected in their ways of coping, resilience, and put them at risk to develop mental health problems if untreated. The authorities and the staff in shelter homes are advice to take seriously social support aspects, especially from the family since they play a vital role for well-being and mental health of unwed pregnant teenagers and teenage mothers. 12. Keyword: Teenage pregnancy, unwed mothers, social support, Malaysia. 79-87 References: 1. World Health Organization. (2009). Teenage pregnancies cause many health, social problems. Available: http://www.who.int/mediacentre/multimedia/podcasts/2009/teenage-pregnancy-20090213/en/index.html. 2. United Nation Children's Fund, UNICEF. (2008). Young people and family planning: Teenage pregnancy. Available: http://www.unicef.org/malaysia/Teenage_Pregnancies_-_Overview.pdf. 3. R.S. Abu Bakar, M. Abdullah, & K. Maslih, (2012, April 19), 2419 Kes seksual, rogol [2419 Cases of sexual crime, rape]. Utusan Malaysia. Available: http://www.utusan.com.my/utusan/info.asp?y=2012&dt=0419&pub=utusan_malaysia&sec=Dalam_Negeri&pg=dn_04.htm. 4. M. R. Kawi, (2011, November 3). Remaja hamil luar nikah meningkat [The increasing number of teen pregnancy out of wedlock]. Berita Harian. Available: http://www.bharian.com.my/ 5. H. Kashiwase, (2002, July). Shotgun weddings a sign of the times in Japan. Population Today. Available: http://www.prb.org/Articles/2002/ShotgunWeddingsaSignoftheTimesinJapan.aspx. 6. J. G. Silverman, A. Raj, I.A. Mucci, & J.E. Hathaway, “Dating violence against adolescent girls and associated substance use, unhealthy weight control, sexual risk behavior, pregnancy, and suicidality,” Journal of the American Medical Association, 286(5), 2001, pp. 572-579. 7. M.E, Saewyc, L.L. Magee, & E.S. Pettingell, “Teenage pregnancy and associated risk behaviours among sexually abused adolescents,” Perspectives on Sexual and Reproductive Health, 36(3), 2004, pp. 98-105. 8. E.T. Moffit, & E-Risk Study Team, “Teen-aged mothers in contemporary Britain,” Journal of Child Psychology and Psychiatry, 43(6), 2002, pp. 727-742. 9. S. Prawatrungruang, Understanding dropouts in Thai private vocational schools: A case study. Unpublished doctoral dissertation, Illinois State University, New York, 2002. 10. X.-K. Chen, S.W. Wen, N. Fleming, K. Demissie, G. Rhoads, & M. Walker, “Teenage pregnancy and adverse birth outcomes: A large population based retrospective cohort study,” International Journal of Epidemiology 36, 2007, pp. 368-373. 11. K. Omar, S. Hasim, N.A. Muhammad, A. Jaffar, S. M. Hashim, & H.H. Siraj, “Adolescent pregnancy outcomes and risk factors in Malaysia,” International Journal Of Gynaecology And Obstetrics: The Official Organ Of The International Federation Of Gynaecology And Obstetrics, 111(3), 2010, pp. 220-223. 12. S. Thaithae, & R. Thato, “Obstetric and perinatal outcomes of teenage pregnancies in Thailand,” Journal of Pediatric and Adolescent Gynecology, 24(6), 2011, pp. 342-346. 13. N. Akiko, “Marriage for social recognition and subsequent married life,” Social Science Japan, 2005, pp 6-8. 14. S. Chhabra, S. Palaparthy, & S. Mishra, “Social issues around advanced unwanted pregnancies in rural single women,” Journal of Obstetrics & Gynecology, 29(4), 2009, pp. 333-336. 15. A. Fatimah, 2009, June, “Kes ibu tanpa nikah di Selangor berdasarkan rekod di Jabatan Kerja Sosial Perubatan, Pusat Perubatan Universiti Kebangsaan Malaysia [Unwed mother cases in State of Selangor based on the records of the Department of Medical Social Work, Hospital Universiti Kebangsaan Malaysia],” Paper presented at the Seminar Mencegah Gejala Sosial Negeri Selangor, Selangor. 16. N.A. Rahman, “Teenage Marriage in the Malay/Muslim Community of Singapore: Problems, Perceptions and Programmes,” Asian Journal of Social Science, 37(5), 2009, pp. 738-756. 17. N. Sarnon, M.S. Mohamad, F. Ibrahim, K. Alavi, S. Nen, S. Hoesni, et al., “Pregnancy out of wedlock: Understanding adolescent as a basic of family intervention (Hamil luar nikah: Memahami remaja sebagai asas intervensi keluarga),” Journal of Social Sciences and Humanities, 7(1), 2012, pp. 121-130. 18. A.J. Silk, “Child abandonment and homes for unwed mothers in ancient India: Buddhist sources,” Journal of the American Oriental Society, 127(3), 2007, pp. 297-314. 19. T.T. Triwulan, “Analisis hukum Islam terhadap praktik aborsi bagi kehamilan tidak diharapkan (KTD) akibat perkosaan menurut Undang-undang nomor 36 Tahun 2009 tentang kesehatan [Islamic law analysis towards unwanted pregnancies abortions due to raped based on Laws Number 36 year 2009 regarding health],” Semarang: Faculty of Law Universitas Diponegero, 2009. 20. Y. Badiah, & B. H. Mohd Jamil, “ Infanticide,” Malaysian Journal of Psychiatry, 15(2), 2006, pp. 3-10. 21. Penal Code Act 574: Incorporating all amendments up to 1 January 2006, Laws of Malaysia § 312 (2006). 22. E.J. Knorth, A.T. Harder, T. Zandberg, & A.J. Kendrick, “Under one roof: A review and selective meta-analysis on the outcomes of residential child and youth care,” Children and Youth Services Review, 30, 2008, pp. 123-140. 23. R. Emond, “Putting the care into residential care: The role of young people,” Journal of Social Work, 3(3), 2003, pp. 321-337. 24. V. Timonen, & C. O'dwyer, “Living in institutional care: Residents' experiences and coping strategies,” Social Work in Health Care, 48(6), 2009,pp.597-613. 25. S. Cohen, & G. Mckay, Social support, stress and buffering hypothesis: A theoretical analysis In A. Baum, S. E. Taylor & J. E. Singer (Eds.), Handbook of Psychological and Health. New Jersey: Hillsale, 1984. 26. J. Corcoran, C. Franklin, & P. Bennett, “Ecological factors associated with adolescent pregnancy and parenting,” Social Work Research, 24(1), 2004, pp. 29-39. 27. D. J. Martinez, & L.S Abrams, “Informal social support among returning young offenders: A metasynthesis of the literature,” International Jounal of Offender Therapy and Comparative Criminilogy, 57(2), 2013, pp. 169-190. 28. M. N. Lotf Abadi, M. Ghazinour, M. Nojomi, & J. Richter, “The Buffering Effect of Social Support between Domestic Violence and Self-Esteem in Pregnant Women in Tehran Iran,” Journal of Family Violence, 27(3), 2012, pp. 225-231 29. P.A. Bovier, E. Chamot, & T.V. Perneger, “Perceived stress, internal resources, and social support as determinants of mental health among young adults,” Quality of Life Research, 13(1), 2004, pp. 161-170. 30. S. Letvak, “The importance of social support for rural mental health,” Issues in Mental Health Nursing, 23, 2002, pp. 249 – 261 31. L. Theeke, R. Goins, J. Moore, & H. Campbell, “Loneliness, depression, social support, and quality of life in older chronically ill Appalachians,” Journal of Psychology, 146(1-2), 2012, pp. 155-171. 32. S. L. Johnson, A.K. Cuellar, & C. Miller, “Bipolar and unipolar depression: A comparison of clinical phenomenology, biological vulnerability, and psychosocial predictors,” In I. H. Gotlib & C. L. Hammen (Eds.), Handbook of depression: Second edition. New York: Guilford Press, 2009. 33. S. Elsenbruch, S. Benson, M. Rücke, M. Rose, J. Dudenhausen, M.K. Pincus-Knackstedt et al., “Social support during pregnancy: effects on maternal depressive symptoms, smoking and pregnancy outcome,” Human Reproductive, 22(3), 2007, pp. 869-877. 34. J. A. Yozwiak, “Postpartum depression and adolescent mothers: A review of assessment and treatment approaches,” Journal of Pediatric Adolescent Gynecology 23, 2010, pp.172-178. 35. M. N. Loft Abadi, Social support, coping and self-esteem in relation to psychological factors: A study of health issues and birth weight in young mothers in Tehran, Iran. Umea University, Umea, 2012. 36. S. Folkman, & R.S. Lazarus, The concept of coping. In A. Monat & R. S. Lazarus (Eds.), Stress and coping, Columbia University Press, 1991. 37. S. Folkman, & R.S. Lazarus, Stress, appraisal and coping, New York: Springer Publishing, 1984. 38. P.A. Thoits, “Social support as coping assistance,” Journal of Consulting and Clinical Psychology, 54(4), 1986, pp. 416-423. 39. S. Panzarine, “Stressors, coping, and social supports of adolescent mothers,” Journal of Adolescent Health Care 7, 1986, pp. 153- 161. 40. S. Panzarine, E. Slater, & P. Sharps, “Coping, Social Support and Depressive Symptoms in Adolesecent Mothers,” Journal of Adolescent Health, 17, 1995, pp. 113-119. 41. J. G. Hamilton, & M. Lobel, “Types, patterns, and predictors of coping with stress during pregnancy: Examination of the Revised Prenatal Coping Inventory in a diverse sample,” Journal of Psychosomatic Obstetrics & Gynecology, 29(2), June 2008, pp. 97– 104,. 42. S. Milan, I.R. Jeannette, T. Kershaw, J. Lewis, M. Christina, & K. Ethier, “Prevalence, course, and predictors of emotional distress in pregnant and parenting adolescents,” Journal of Consulting and Clinical Psychology, 72(2), 2004, pp. 328-340. 43. K. Tusaie, & J. Dyer, “Resilience: A historical review of the construct,” Holistic Nurse Practise, 18(1), 2004, pp. 3-8. 44. E. Werner, “Risk, resilience and recovery,” Reclaiming Children and Youth, 21 (1), 2012, pp. 18-23. 45. M. Ungar, Nurturing hidden resilience in trouble youth, Toronto: University of Toronto Press, 2004. 46. A.S. Masten, K.M. Best, & N. Garmezy, “Resilience and development: Contributions from the study of children who overcome adversity,” Development and Psychopathology, 2(4), 1990, pp. 425-444. 47. R. L. Woodgate, Conceptual understanding of resilience in the adolescent with cancer: Part I. Journal of Pediatric Oncology Nursing, 16(1), 1999, pp. 35-43. 48. C.P. Barnard, C. P. “ Resiliency: A shift in our perception,” The American Journal of Family Therapy, 22, 1994, pp. 136-144. 49. M. Ungar, “Resilience across cultures,” British Journal of Social Work, 38, 2008, pp. 218 - 235. 50. M. Ungar, Strengths-Based Counseling with At-Risk Youth. California: Corwin Press, 2006. Authors: Tan Kim Hua, Nicholas Sia Heng Hwa, Sheau Tsuey Chong

13. Paper Title: Cyberbullying Victimization and Cyberbullying Perpetration with Self-Esteem as the Moderator Abstract: Cyberbullying is a growing phenomenon with many negative and long-term effects. Past 88-92 literature has not been consistent in the findings with regard to the relationship between cyberbullying victimization and perpetration. The role of self-esteem in its interaction from both aspects of cyberbullying has also been inconclusive. This study therefore sought to examine the relationship between cyberbullying victimization, cyberbullying perpetration with self-esteem as its moderating factor. 120 participants (aged 18 to 25 years old) were recruited to complete the surveys comprising the Cyberbullying and Online Aggression Survey and the Rosenberg Self-Esteem Scale. Hierarchical multiple regression was run to analyse the predictive relationship of the variables. One finding shows that cyberbullying victimization and cyberbullying perpetration have positive correlation which may explain the propagation of the vicious cycle. The other finding did not seem to highlight the role of self-esteem in mediating the perpetration and victimization of cyberbullying. This study nevertheless provides valuable insights to the nature of cyberbullying which can assist in the management of this pervasive social ill in community programmes.

Keyword: cyberbullying, self-esteem, perpetration, victimization References: 1. M. Wong-Lo and L. M. Bullock, "Digital Aggression: Cyberworld Meets School Bullies," Preventing School Failure: Alternative Education for Children and Youth, vol. 55, pp. 64-70, 2011/01/31 2011. 2. Tan, K.H. Cyberbullying: A Cursory Review in Stop Cyberbullying. Bangi: UKM Press, 2018, pp. 17-34 3. P. K. Smith, J. Mahdavi, M. Carvalho, S. Fisher, S. Russell, and N. Tippett, "Cyberbullying: its nature and impact in secondary school pupils," Journal of Child Psychology and Psychiatry, vol. 49, pp. 376-385, 2008.. 4. J. Raskauskas, "Text-bullying: associations with traditional bullying and depression among New Zealand adolescents," Journal of School Violence, vol. 9, pp. 74-97, 2010. 5. J. Snakenborg, R. A. Gable, and R. V. Acker, "Cyberbullying: prevention and intervention to protect our children and youth," Preventing School Failure, vol. 55, pp. 88-95, 2011. 6. J. Raskauskas and A. D. Stoltz, "Involvement in traditional and electronic bullying among adolescents," Development Psychology, vol. 43, pp. 564-575, 2007. 7. R. S. Tokunaga, "Following you home from school: a critical review and synthesis of research on cyberbullying victimization," Computers in Human Behaviour, vol. 26, pp. 277-287, 2010. 8. D. Nikolaou, "Does cyberbullying impact youth suicidal behavious?," Journal of Health Economics, vol. 56, pp. 30-46, 2017. 9. G. W. Wendt, M. Appel-Silva, Y. Kovas, and T. Bloniewski, "Links between cyberbullying, depression and self-esteem in a sample of Brazilian adolescents," The European Proceedings of Social & Behavioural Sciences, vol. 49, pp. 782-793, 2018. 10. G. Gini and T. Pozzoli, "Association between bullying and psychosomatic problems: a meta-analysis," Pediatrics, vol. 123, pp. 1059-1065, 2009. 11. S. Pabian, H. Vandebosch, K. Poels, V. V. Cleemput, and S. Bastiaensens, "Exposure to cyberbullying as a bystander: an investigation of desensitizattion effects among early adolescents," Computers in Human Behaviour, vol. 62, pp. 480-487, 2016. 12. H. Vandebosch and K. V. Cleemput, "Defining cyberbullying: a qualitative research into the perceptions of youngsters," Cyberpsychology & Behaviour, vol. 11, pp. 499-503, 2008. 13. S. Hinduja and J. W. Patchin, Bullying beyond the School Yard. California: Corwin Press, 2008. 14. K. Varjas, J. Talley, J. Meyers, L. Parris, and H. Cutts, "High school students' perceptions of motivations for cyberbullying: an exploratory study," West J Emerg Med, vol. 11, pp. 269-273, 2010. 15. M. Walrave and W. Heirman, "Cyberbullying: predicting victimization and perpetration," Children and Society, vol. 25, pp. 59- 72, 2010. 16. S. A. Hemphill and J. A. Heerde, "Adolescent predictors of young adult cyberbullying perpetration and victimization among Australian youth," Journal of Adolescent Health, vol. 55, pp. 580-587, 2014. 17. E. Rice, R. Petering, H. Rhoades, H. Winetrobe, J. Goldbach, A. Plant, et al., "Cyberbullying perpetration and victimization among middle-school students," American Journal of Public Health, vol. 105, pp. 66-72, 2015. 18. J. W. Patchin and S. Hinduja, "Cyberbullying and self-esteem," Journal of School Health, vol. 80, pp. 614-621, 2010. 19. G. Brewer and J. Kerslake, "Cyberbullying, self-esteem, empathy and loneliness," Computers in Human Behaviour, vol. 48, pp. 255-260, 2015. 20. K. A. Fanti and C. C. Henrich, "Effects of self-esteem and narcissism on bullying and victimization during early adolescence," Journal of Early Adolescence, vol. 35, pp. 5-29, 2014. 21. C. A. Rose, C. D. Slaten, and J. L. Preast, "Bully perpetration and self-esteem: examining the relation over time," Behavioural Disorders, vol. 42, pp. 159-169, 2017. 22. B. Choi and S. Park, "Who becomes a bullying perpetrator after the experience of bullying victimization? the moderating role of self-esteem," Journal of Youth and Adolescence, vol. 47, pp. 2414-2423, 2018. 23. M. Rosenberg, Society and the Adolescent Self-Image. Princeton, NJ: Princeton University Press, 1965. 24. M. Ybarra and K. Mitchell, “Online aggressor-targets, aggressors, and targets: a comparison of associated youth characteristics,” Journal of Child Psychology and Psychiatry, vol. 45, pp. 1308-1316. Authors: M.M. Siti Syairah, Y.S. Kamsani, M.H. Rajikin An Experimental Examination on ohe Effects of Supplementations with Palm Tocotrienol-Rich- Paper Title: Fraction (TRF) and Annatto Δ-Tocotrienol on Body Weight and Pre-Implantation Embryonic Development in Nicotine-Treated Mice Abstract: Supplementation of vitamin E to pre-pregnant mice reduces the hazardous impact of nicotine on pregnancy outcome. There are emerging evidences on vitamin E, particularly tocotrienol (TCT), exerting some roles in pre-pregnancy body weight management and pre-implantation embryonic development. This study investigated the effects of supplementations with palm tocotrienol-rich fraction (palm-TRF) and annatto δ-TCT 14. (> 98% purity) on the pre-partum body weight and embryonic development following nicotine treatment in mice. Thirty-six (4–6 weeks old) female mice (Mus musculus) were divided into 6 groups (G1-G6). All groups were subjected to treatments either with 3 mg/kg bw/day nicotine, 60 mg/kg bw/day palm-TRF, 60 mg/kg 93-96 bw/day annatto δ-TCT or; combination of nicotine concurrently with palm-TRF or annatto δ-TCT for 7 consecutive days. Body weights were recorded daily throughout the treatment period. Superovulation was conducted on Day 7 and 9, followed with cohabitation with fertile males. Animals were euthanized 48 hours post-coitum and embryos were retrieved through uterine flushing. Selected embryos were incubated in M16 medium and observed daily. Results showed that nicotine (G2) decreased the pre-partum body weight (22.2 ± 1.1g vs 29.8 ± 0.6g) (p<0.05) and the number of cleaving embryos at all stages in G2 were significantly decreased (p<0.05) compared to control. Intervention with annatto δ-TCT attenuated the embryonic development, unlike the intervention with palm-TRF. Supplementations with palm-TRF and annatto δ-TCT alone resulted in unchanged body weight and increased in the number of retrieved hatched blastocysts. Present results suggest that future efforts in determining the regulating signaling pathways are important, and the mechanisms of actions by both nicotine and TCT could be elucidated further.

Keyword: δ-tocotrienol, body weight, nicotine, palm-TRF, pre-implantation embryonic development References: 1. Sheppard, A. J., Pennington, J. A. T., Weihrauch, J. L. (1993). Analysis and distribution of vitamin E in vegetable oils and foods. In L. Packer & J. Fuchs (Eds.), Vitamin E in health and disease (pp. 9-31). New York: Marcel Dekker. 2. Ramaswamy, K., Subash, C. G., Ji, H. K. & Bharat, B. A. (2012). Tocotrienols fight cancer by targeting multiple cell signaling pathways. Genes & Nutrition, 7(1), 43-52. doi: 10.1007/s12263-011-0220-3 3. Kobayashi, H., Kanno, C., Yamauchi, K., & Tsugo, T. (1975). Identification of alpha-, beta-, gamma-, and delta-tocopherols and their contents in human milk. Biochimica et Biophysica Acta, 380(2), 282-90. 4. Nehdi, I., Omri, S., Khalil, M. I., & Al-Resayes, S. I. (2010). Characteristics and chemical composition of date palm (Phoenix canariensis) seeds and seed oil. Industrial Crops and Products, 32, 360–365. 5. IUPAC-IUB Joint Commission on Biochemical Nomenclature. Nomenclature of tocopherols and related compounds. (Recommendations 1981). (1982). Eur. J. Biochem. 123, 473–475. 6. 6.Shibata,A.;Nakagawa,K.;Sookwong,P.;Tsuduki,T.;Asai,A.;Miyazawa,T.Alpha-tocopherol attenuates the cytotoxic effect of delta-tocotrienol in human colorectal adenocarcinoma cells. Biochem. Biophys. Res. Commun. 2010, 397, 214–219. 7. Uchida, T.; Abe, C.; Nomura, S.; Ichikawa, T.; Ikeda, S. Tissue distribution of α- and γ-tocotrienol and γ-tocopherol in rats and interference with their accumulation by α-tocopherol. Lipids 2012, 47, 129–139. [CrossRef] 8. 8.T Tan,T B.T VitaminT E:T Tocotrienols—TheT ScienceT BehindT Tocotrienols.T 2014.T AvailableT online:T https:T //assets.kyani.net/documents/us/Tocotrienols_Science_White_Paper-1.12-EN-ALL.pdfT (accessedT onT 2T NovemberT 2018). 9. 9.T Tappel,T A.L.T VitaminT ET asT theT biologicalT lipidT antioxidant.T Vitam.T Horm.T 1962,T 20,T 493–510.T 10. 10.T Burton,T G.W.;T Ingold,T K.U.T VitaminT ET applicationT ofT theT principlesT ofT physicalT organicT chemistryT toT theT explorationT ofT itsT structureT andT function.T Acc.T Chem.T Res.T 1986,T 19,T 194–201. 11. 11.T Esterbauer,T H.;T Dieber-Rotheneder,T M.;T Striegl,T G.;T Waeg,T G.T RoleT ofT vitaminT ET inT preventingT theT oxidationT ofT lowT densityT lipoprotein.T Am.T J.T Clin.T Nutr.T 1991,T 53,T 314S–321S.T 12. 12.T Serbinova,T E.A.;T Kagan,T V.;T Han,T D.;T Packer,T L.T FreeT radicalT recyclingT andT intramembraneT mobilityT inT theT antioxiT dantT propertiesT ofT alpha-tocopherolT andT alpha-tocotrienol.T FreeT Radic.T Biol.T Med.T 1991,T 10,T 263–275.T 13. 13.T Serbinova,T E.A.;T Packer,L.T AntioxidantT propertiesT ofT alpha-tocopherolT andT alpha-tocotrienol.T MethodsT Enzymol.T 1994,T 234,354–366.T 14. 14. Sazli, F.A.R.; Jubri, Z.; Mariati, A.R.; Karsani, S.A.M.; Top, A.G.; Wan, Z.W.N. Gamma-tocotrienol treatment in-creased peroxiredoxin-4 expression in HepG2 liver cancer cell line. BMC Complement. Altern. Med. 2015, 15, 64. 15. Lim, S.W.; Loh, H.S.; Ting, K.N.; Bradshaw, T.D.; Zeenathul, N.A. Cytotoxicity and apoptotic activities of alpha-, gamma- and delta-tocotrienol isomers on human cancer cells. BMC Complement. Altern. Med. 2014, 14, 469. 16. 16. Shin-Kang, S.; Ramsauer, V.P.; Lightner, J.; Chakraborty, K.; Stone, W.; Campbell, S.; Shrikanth, A.G.R.; Krishnan, K. Tocotrienols inhibit AKT and ERK activation and sup-press pancreatic cancer cell proliferation by suppressing the ErbB2 pathway. Free Radic. Biol. Med. 2011, 51, 1164–1174. Authors: Suzana Mohd Hoesni, Siti Marziah Zakaria

Paper Title: Marital Satisfaction and General Happiness among urban Malays in Klang Valley Abstract: Marital satisfaction is a mental state that induces a married individual to feel happy regarding in his or her married life. Therefore, this study was conducted to identify the background factors of married urban Malays and to determine the relationship between marital satisfaction and general happiness among urban married Malay individuals. This study employs an exploratory design using survey method in the form of questionnaire. Each questionnaire contains a set of questions and measurement tools to gather background information, the level of marital satisfaction and general happiness of the respondents. A total of 421 respondents who were Malays and have been married for at least a year, and resided in the Klang Valley area participated voluntarily in this study. In general, this study found that there were positive and significant relationships between general happiness and factors namely marital satisfaction (k <0.01, r = 0.466**), age (k <0.01, r = 0.148**), individual monthly income (k <0.05 , r = 0.118*), family income (k <0.05, r = 0.113*), length of marriage (k<0.05, r = 0.114*) and age of the eldest child (k <0.01, r = 0.137*). The outcome of this study suggests the importance of marital satisfaction in elevating the general happiness of married individuals. 15. Besides that, religious beliefs and values were also found important in achieving marital satisfaction. Suggestions for future researchers and members of the helping profession like counselors, therapists and social workers working with married couples who specifically adhere to certain values and cultures were also 97-101 discussed.

Keyword: marital satisfaction, general happiness, Malays, urban, culture. References: 1. Asoodeh, M. H., Khalili, S., Daneshpour, M., Lavasani, M. G. 2010. Factors of successful marriage: Accounts from self- described happy couples. Procedia-Social and Behavioral Sciences. 5:2042-2046 2. Dinani, P.T., Zarbakhsh, M., Samkhaniyan, E., Hamidi, M and Arkiyan, F. (2014). Study on the relationship between love attitudes and marital satisfaction among married women. European Online Journal of Natural and Social Sciences, 3(3), 468-474. 3. Bradbury, T.N., Fincham, F.D., & Beach, S.H. 2000. Research on the nature and determinants of marital satisfaction, a decade in review. Journal of Marriage and Family, 62, 964-980 4. Williamson, H.C., Nguyen, T.P., Bradbury, T.N. & Karney, B.R. (2015). Are problems that contribute to divorce present at the start of marriage, or do they emerge over time? Journal of Social and Personal Relationships, 33 (8), 1120-1134. 5. Knopp, K., Rhoades, G. K., Allen, E. S., Parsons, A., Ritchie, L. L., Markman, H. J., & Stanley, S. M. (2017). Within and between family associations of marital functioning and child well-being. Journal of Marriage and Family, 79(2), 451-461. 6. Buehler C., Krishnakumar, A., Stone G., Anthony, C., Pemberton, S., Gerard, J. & Barber, K. 1998. Interparental conflict styles and youth problem behavior: A two-sample replication study. Journal Of Marriage And The Family, 60: 119-132 7. Ahmadi, K., & Hossein-abadi, F. (2009). Religiosity, marital satisfaction and child rearing. Pastoral Psychology, 57(5/6): 211- 221. 8. Aluja Anton, del Barrio Victoria & García Luis F. (2007). Personality, social values, and marital satisfaction as predictors of parents' rearing styles. International Journal of Clinical and Health Psychology, 7(3): 725-737. 9. Katz, L. F., & Gottman, J. M. (1993). Patterns of marital conflict predict children's internalizing and externalizing behaviors. Developmental psychology, 29(6), 940. 10. Fowers, B. J., & Olson, D. H. (1993). ENRICH Marital Satisfaction Scale: A Brief Research and Clinical Tool. Journal of Family Psychology, 7(2), 176-185. DOI: 10.1037/0893-3200.7.2.176 11. Fowers, B.J. & Applegate, B. (1995). Do Marital Conventionalization Scales Measure a Social Desirability Response Bias? A Confirmatory Factor Analysis. Journal of Marriage and Family, 57(1), 237-241. 12. Ahmadi, K., Ranjebar-Shayan, H. & Raiisi, F. (2007). Sexual dysfunction and marital satisfaction among the chemically injured veterans. Indian Journal of Urology, 23(4), 377–382. 13. Vanderbleek, L.,Robinson, E.H.,Casado-Kehoe, M. & Young, M.E. (2011). The Relationship Between Play and Couple Satisfaction and Stability. The Family Journal, 19(2), 132-139. 14. Loewenthal, K.M. (2001). An introduction to psychological tests and scales: 2nd edition. Philadelphia: Psychology Press Ltd. 15. Bradburn, Norman M. The Structure of Psychological Well-Being. Chicago: Aldine, 1969. Table: The distribution of avowed happiness in selected studies, 40. Table: Coefficients of association among indicators of social participation, 126. 16. Lewis, McCollam & Joseph (2000). Convergent Validity Of The Depression-Happiness Scale With The Bradburn Affect Balance Scale. Social Behavior And Personality: An International Journal. 28(6), 579-584. 17. Helmes, Goffin & Chrisjohn (2010). Confirmatory Analysis of the Bradburn Affect Balance Scale and its Relationship with Morale in Older Canadian Adults. Canadian Journal on Aging, 29(2), 259-266. 18. Macintosh, R. (1998). A Confirmatory Factor Analysis of the Affect Balance Scale in 38 Nations: A Research Note. Social Psychology Quarterly, 61(1), 83-95. 19. Perkinson, Albert, Luborsky, Moss & Glicksman (1994). Exploring the validity of the Affect Balance Scale with a sample of family caregivers. Journal of Gerontology, 49(5), 264-275. 20. Lord, F.M, & Novick, M.R. (1968). Statistical Theories of Mental Test Scores. Reading MA: Addison -Wesley. 21. Traub, R.E. (1994), Reliability for the Social Sciences: Theory and Applications. Thousand Oaks CA: Sage. 22. Pallant, J. (2016). SPSS Survival Manual: A Step By Step Guide to Data Analysis Using SPSS Program (6th ed.). London, UK: McGraw-Hill Education. Authors: Amalina Ibrahim, Wan Shahrazad Wan Sulaiman, Fatimah Wati Halim Work Intention as Mediator in the Relationship between Work Passion and Organizational Paper Title: Commitment among Teachers in Malaysia Abstract: Organizational commitment among employees is important to determine organizational effectiveness as employees with higher organizational commitment have higher motivation to stay with their organization. In recent years, previous studies have shown that the teachers’ organizational commitment are low and moderate. Therefore, this study focuses on the effect of work passion toward organizational commitment with work intention as the mediator. The objectives of this study was to determine the effect of work passion on work intention and organizational commitment among teachers and to determine the role of work intention as a mediator in the effect of work passion on organizational commitment among teachers. This study employed a cross-sectional survey involving 355 school teachers in Malaysia through multi-stage cluster sampling technique. Data were analyzed using descriptive analysis, while confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to determine the fitness of the model with the data. Findings showed that organizational commitment and work passion among school teachers were moderate, while work intention was at a higher level. SEM analysis showed that the model has a good fit with CMIN/df= 3.22, GFI = 0.95, CFI=0.97, TLI=0.95, RMSEA=0.08. In addition, job factors have a significant direct effect on work intention and organizational commitment. Results also showed that work intention mediated the relationship between work passion and organizational commitment. The results of this imply the importance of work passion and work intention in enhancing organizational commitment among teachers in Malaysia.

16. Keyword: work passion, work intention, organizational commitment, teachers. References: 102-110 1. Minister of Education Malaysia. (2015). Malaysian Education Development Program 2013-2025. (Pelan Pembangunan Pendidikan Malaysia 2013–2025). Available: https://www.moe.gov.my/index.php/my/arkib/dasar/laporan-tahunan-2015 2. Affendi, F. (2014). Level of job satisfaction and organizational commitment among vocational college teachers: A structural equation modeling. (Tahap kepuasan kerja dan komitmen organisasi dalam kalangan guru kolej vokasional: Pendekatan structural equation model.) UTHM, Unpublished Master’s Project. 3. Rabindarang, S. (2012). Relationship of distributive leadership towards organizational commitment and job stress in vocational and technical education. (Hubungan kepemimpinan distributif terhadap komitmen: Organisasi dan tekanan kerja dalam pendidikan teknik dan vokasional.) UPSI, Unpublished Doctoral Thesis. 4. Ibrahim, A, Halim, F. W, & Wan Sulaiman, W. S. W. (2017). Factors influencing organizational commitment among school teachers. (Faktor-faktor yang mempengaruhi komitmen organisasi dalam kalangan guru sekolah). International Research Journal of Education and Sciences, 1(1), 51-54. 5. Bajunid, I. A. (1995). Practices and challenges of education management in Malaysia: A critical review. (Amalan dan cabaran pengurusan pendidikan di malaysia: satu tinjauan kritikal). Jurnal Pengurusan Pendidikan, 5(l), 1-13. 6. NUTP. (2009). Many teachers experience mental health. (Ramai guru sakit jiwa). In Kosmo newspaper, Siti Nor Afzan Kasiman. Available: http://ww1.kosmo.com.my/kosmo/content.asp?y=2009 7. Polly, D., Mims, C., Shepherd, C. E., & Inan, F. (2010). Evidence of impact: Transforming teacher education with preparing tomorrow’s teachers to teach with technology (PT3) grants. Teaching and Teacher Education, 26, 863–870. 8. Halim, F. W. (2003). Personality and its’ correlates with job stress and work life balance among teachers. (Personaliti serta hubungannya dengan tekanan kerja dan kehidupan bekerja di kalangan guru). Jurnal Psikologi Malaysia, 17, 65-83. 9. Halim, R. A. (2009). An exploratory study of distributed leadership in Malaysia. (Kajian eksplorasi distributed leadership di Malaysia). Seminar Nasional Pengurusan dan Kepemimpinan Pendidikan ke-16, Institut Aminuddin Baki. 10. Abdullah, M. K., Sekong, M., & Laji, H. (2017). Emotional intelligence and teachers’ commitment towards organization. (Kecerdasan emosi dan komitmen guru terhadap organisasi). Jurnal Psikologi dan Kesihatan Sosial, 1 42-52. 11. Dee, J. R., Henkin, A. B. & Singleton. C. A. (2006). Organizational commitment of teachers in urban schools: Examining the effects of team structures. Urban Education, 41, 603-27. 12. Allen, N. J., & Meyer, J. P. (1996). Affective, continuance, and normative commitment to the organization: An examination of construct validity. Journal of Vocational Behavior, 49(3), 252-276. http://dx.doi.org/10.1006/jvbe.1996.0043 13. Meyer, J. P., & Allen, N. J. (1991). A three-component conceptualization of organizational commitment. Human Resource Management Review, 1, 61–89. 14. Nguni, S., Sleegers, P., & Denessen, E. (2006). Transformational and transactional leadership effects on teachers' job satisfaction, organizational commitment, and organizational citizenship behavior in primary schools: The Tanzanian case. School Effectiveness and School Improvement, 17(2), 145-177. 15. Louis, K. S. (1998). Effects of teacher quality of work life in secondary schools on commitment and sense of efficacy. School Effectiveness and School Improvement, 9, 1-27. 16. Singh, K. & Billingsley, B. S. (1998). Professional support and its effects on teachers’ commitment. Journal of Educational Research, 91(4), 229-239. 17. Porter, L. W., Steers, R. M., Mowday, R. T., & Boulian, P. V. (1974). Organizational commitment, job satisfaction and turnover among psychiatric technicians. Journal of Applied Psychology, 59(5), 603-609. 18. Gangai, K. N. & Agrawal, R. (2015). Job satisfaction and organizational commitment: Is it important for employee performance? International Journal Management Business Research, 5(4), 269-278. 19. Zigarmi, D. & Nimon, K. (2011). A cognitive approach to work intention: The stuff that employee work passion is made of? Advances in Developing Human Resources, 13(4), 447-461. 20. Perrewé, P. L., Hochwarter, W. A., Ferris, G. R., Mcallister, C. P., & Harris, J. N. (2014). Developing a passion for work passion: Future directions on an emerging construct. Journal of Organizational Behavior, 35(1), 145-150. 21. Vallerand, R. J., Mageau, G. A., Blanchard, C. M. & Koestner, R. (2003). Les passions de l’ame: on obsessive and harmonious passion. Journal of Personality and Social Psychology, 85, 756–767. 22. Nimon, K. & Zigarmi, D. (2014). The work cognition inventory: Initial evidence of construct validity for the revised form. Journal of Career Assessment, 23(1), 117-136. 23. Zigarmi, D., Nimon, K., Houston, D., Witt, D. & Diehl, J. (2012). The work intention inventory: Initial evidence of construct validity. Journal of Business Administration Research, 1(1), 24-42. doi: 10.5430/jbar.v1n1p24. 24. Fishbein, M. & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Boston: Addison-Wesley. 25. Ajzen, I. (1985). From intentions to action: A theory of planned behavior. In Kuhl, J. and Beckman, J. (Eds), Action control: From cognitions to behaviors. New York: Springer 26. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. 27. Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavioral change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132, 249–268. doi:101037/0033-2909.132.2.249 28. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall. 29. Tremblay, M., Cloutier, J., Simard, G., Chenevert, D., Vandenberghe, C. (2010). The role of HRM practices, procedural justice, organizational support and trust in organizational commitment and in-role and extra-role performance. International Journal of Human Resource Management, 21, 405-433. 30. Haar, J. M., Spell, C. & O’Driscoll, M. (2009). Managing work-family conflict: Exploring individual and organizational options. New Zealand Journal of Human Resources Management, 9(3), 200-215. 31. Rahman, Navid Shahzad, Kiran Mustafa, Muhammad Fayaz Khan & Faizan Qurashi. (2016). Effects of organizational justice on organizational commitment. International Journal of Economics and Financial Issues, 6(S3), 188-196. 32. Daud, K. A. K. (2014). The impact of slow career growth on organizational commitment and job satisfaction: A study of a “closed” government agency in Malaysia. RMIT Universitiy: PhD Thesis. 33. Weng, Q., McElroy, J. C., Morrow, P. C., & Liu, R. (2010). The relationship between career growth and organizational commitment. Journal of Vocational Behavior, 77, 391-400. 10.1016/j.jvb.2010.05.003 34. Barbier, M., Hansez, I., Chmiel, N., & Demerouti, E. (2012). Performance expectations, personal resources, and job resources: How do they predict work engagement. European Journal of Work and Organizational Psychology, 37–41. https://doi.org/10.1080/1359432X.2012.704675 35. Wrzesniewski, A., McCauley, C., Rozin, P., & Schwartz, B. (1997). Jobs, careers, and callings: People’s relations to their work. Journal of Research in Personality, 31(1), 21-33. http://dx.doi.org/10.1006/jrpe.1997.2162 36. Geldenhuys, M., Laba, K. & Venter, C. M. (2014). Meaningful work, work engagement and organizational commitment. SA Journal of Industrial Psychology, 40(1), A1098. doi: https://doi.org/10.4102/sajip.v40i1.1098 37. Ozturk, F. (2010). Determinants of organizational citizenship behavior among knowledge workers: The role of job characteristics, job satisfaction, and organizational commitment. Middle East technical university, Turkey: Master Thesis. 38. Eby, L. C., Freeman, D. M., Rush, M. C., & Lance, C. E. (1999). Motivational basis of affective organizational commitment: A partial test of an integrative theoretical model. Journal of Occupational and Organizational Psychology, 72, 463-483. 39. Huang, T. & Hsiao, W. (2007). The causal relationship between job satisfaction and organizational commitment. Social Behavior and Personality: An international Journal, 35, 1265-1276. 40. Liu, S. & Norcio, R. (2008). Mediating effects of job characteristics on job satisfaction and organizational commitment of Taiwanese expatriates working in Mainland China. The Business Review, 9, 62-69. 41. Lee, R. T., & Ashforth, B. E. (1996). A meta-analytic examination of the correlates of the three dimensions of job burnout. Journal of Applied Psychology, 81, 123-133. 42. Dewe, P. J. (1992). Applying the concept of appraisal to work stressors: Some exploratory analysis. Human Relations, 45, 143- 64. 43. Zigarmi, D., Nimon, K. & Shuck, B. (2014). Employee engagement: Job attitude or mediator between job attitude and affect. Proceedings of the Academy of Human Resource Development Conference. 44. Brown, S. P. (1996). A meta-analysis and review of organizational research on job involvement. Psychological Bulletin, 120, 235–255. doi:10.1037/0033-2909.120.2.235 45. Ansari, M. A., Hung, D. K. M. & Aafaqi, R. (2007). Leader‐member exchange and attitudinal outcomes: Role of procedural justice climate. Leadership & Organization Development Journal, 28(8), 690-709. 46. Starnes, B. J., Truhon, S. A., & McCarthy, V. (2005). Organizational trust: Employee-employer relationships. The Human Development and Leadership Division, 6-8, www.asq.org/hd 47. Agho, A. O., Mueller, C. W., & Price, J. L. (1993). Determinants of employee job satisfaction: An empirical test of a causal model. Human Relations, 46(8), 1007-1027. doi: 10.1177/001872679304600806. 48. Veeriah, J., Piaw, C. Y., & Li, S. Y. (2017). The impact of school culture on teachers’ organizational commitment in primary cluster schools in Selangor. Educational Leader, 5, 1-18. 49. LePine, J. A., Johnson, D. E. & Erez, A. (2002). The nature and dimensionality of organizational citizenship behavior: A critical review and meta-analysis. Journal of Applied Psychology, 87(1), 52-65. 50. Organ, D. W. & Ryan, K. (1995). A meta-analytic review of attitudinal and dispositional predictors of organizational citizenship behavior. Personnel Psychology, 48, 775-802. Authors: Norizan Hassan, Rozmi Ismail, Nurul-Azza Abdullah 17. How Low Income People Perceived Poverty? A Preliminary Findings on Poverty Attribution of B40 Paper Title: Group in Malaysia Abstract: Studies on understanding psychological aspects of poverty in specific population like Malaysia are very rare. Thus the causes of poverty especially among B40 groups whether is related to individual (internal) or external factors is questionable. Previous literatures indicated that there are three (3) causal attribution of poverty, that is structuralistic, individualistic, and fatalistic. This study examines the perception of B40 youth in Malaysia with regard to the causes of poverty. A total of 112 B40 youth aged 15 to 25 years old (male = 40, female = 72) in Selangor Malaysia involved in this study. Purposive sampling method was used for selecting of respondent based on the criteria on B40 youth. For the purpose of validating the instrument, a factor analysis was used. The results of this study showed that B40 youth in our sample used three (3) causal attributions of poverty; that is individualistic, followed by structuralistic and fatalistic which supporting the results of previous studies. The implication of the study will contribute to the understanding of the mind of B40 groups in Malaysia.

Keyword: B40 group, attribution, poverty, youth. References: 1. Azlina Mohd Khir & Ma’rof Redzuan. 2013. Atribusi Kemiskinan dalam Kalangan Pelajar Orang Asli di Malaysia. Paper presented at International Conference on Social Science Research (ICSSR) 2013, 4-5 Jun 2013, Penang Malaysia organized by WorldConference.net. 2. Feagin, J.R. 1972. Poverty: We Still believe that God helps those who themselves. Psychology Today 6: 101-129. 3. Furnham, A. 2003. Poverty and wealth. In. Carr, S.C & Sloan, T. S. (Eds.) Poverty and psychology: From global perspective to local practice, page 163–183. New York: Kluwer Academic/Plenum Publishers. 4. Geggie, J., DeFarin, J., Hitchcock, S., & Simone, S. 2000. Family strengths research project. The Family Action Centre, University of Newcastle, Australia. 5. Gursuch, R.L., 1983. Factor Analysis (2nd Ed.). Hillsdale, N.J. Erlbaum. 6. Hair, J. F., Anderson, R. E., Tantham, R. L., & Black W. C. 1998. Multivariate data analysis (5th ed.). New Jersey: Prentice Hall. 7. Heider, F. 1958. The psychology of interpersonal relations. New York: Wiley. 111-115 8. Ige, K.D. 2014. The Layering of Poverty Attribution among Disadvantaged Groups In The Developing World. Mediterranean Journal of Social Sciences 5 (20). 9. Kline, P., 1994. An Easy Guilde To Factor Analysis. New York: Routhledge. 10. Lewis-Beck, M. S. 1994. Factor analysis and related techniques. London: SAGE Publications Ltd. 11. Ljubotina, O.D., & Ljubotina, D. 2007. Attributions of Poverty among Social Work and Non-social Work Students in Croatia. Croat Med Journal. 12. Malaysia Department of Statistic. 2016. Penyiasatan Pendapatan & Kemudahan Asas dan Perbelanjaan Isi Rumah (HIS/HES) 2016. 13. Morcol, G. 1997. Lay explanations for poverty in Turkey and their determinants. The Journal of Social Psychology, 137(6): 728- 738. 14. Murnizam Halik, Mohd Dahlan A. Malek, Ferlis Bahari, Norlizah Matshah & Webley, P. 2009. Attribution of poverty among Malaysian students in the United Kingdom. Southest Asia Psychology Journal 1: 22-30. 15. Nasser, R. & Abouchedid, K. 2001. Causal Attribution Of Poverty Among Lebanese University. 16. Students. Current Research In Social Psychology 6 (14). 17. Nasser, R., Singhal, S. & Abouchedid, K. 2005. Causal Attributions for Poverty among Indian Youth. Current Research In Social Psychology 11 (1). 18. Nishimwe-Niyimbanira, R. 2014. Household Heads Gender Comparison of Perceived Causes of Poverty in a South African Township. Mediterranean Journal of Social Sciences 5 (21): 299 – 304. 19. Rozmi Ismail. 2011. Psikologi Sosial. Bangi: Penerbit Universiti Kebangsaan Malaysia. 20. Samuel, Y.A. & Ernest, K. 2012. Attributions for Poverty: A Survey of Student’s Perception. International Review of Management and Marketing 2 (2): 83-91. 21. Wilson, W.J. 1987. The truly disadvantaged: the inner city, the underclass and public policy. Chicago IL: University of Chicago Press. 22. Wollie, C.W. 2009. Causal attributions for poverty among youths in Bahir Dar, Amhara Region, Ethiopia. Journal of Social, Evolutionar, and Cultural Psychology 3 (3): 251-272. 23. Zwick, W. R., & Velicer, W. F. 1982. Factors influencing four rules for determining the number of components to retain. Multivariate Behavioral Research 17 :253-269. Authors: M. Arul Kumar, S. Gopalsamy

Paper Title: Agricultural Sector FDI and Economic Growth in Saarc Countries Abstract: The study seeks to establish the relationship between foreign direct investment to Saarc region agricultural sector and economic growth with secondary data. SAARC comprises 3% of the world's area, 21% of the world's population and 3.8% (US$2.9 trillion) making up a total of 3% of the world’s area. The country has second in all over the world in terms of agriculture position. The population obliquely all of the member states is over 1.7 billion, accounting for 21% of the world’s total population. In their 42% of the agricultural operation in SAARC nations and also 51% source of livelihood of the South Asians. The study has revealed that India alone accounts for 52 per cent of the agricultural products using the SAARC region peoples. For the present study, a 18. total of 34 groups related to the agricultural products were selected out of the total groups. The techniques employed to analyze the data include descriptive statistic, correlation and linear forecast method. The study also revealed a positive and important relationship between economic growth and foreign direct investment flow to 116-121 the agricultural sector. Thus, the study recommends that policy should focus on flexible trade policies to attract more foreign direct investment (FDI) inflows to SAARC nations. i.e. Afghanistan, Bangladesh, Bhutan, Maldives, Nepal, Pakistan, Sri Lanka including India.

Keyword: Agricultural Sector, FDI, Economic Growth and SAARC countries. References: 1. Manamba Epaphra, Ales H. Mwakalasya. (2017). Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania. Modern Economy,(8),111-140. 2. Raka Saxena, Ranjit Kumar Paul, Simmi Rana, Shikha Chaurasia, Kavita Pal, Zeeshan and Deepika Joshi.(2015). Agricultural Trade Structure and Linkages in SAARC: An Empirical Investigation. Agricultural Economics Research Review, 28(2), 311-328. 3. Arul Kumar, M. Dr. Gopalsamy, S. (2018). FDI Regional Economic integration in SAARC Region. Roots International Journal of Multidisciplinary Researches,4(1).18-20. 4. Akinwale, Adekunle, E.Oludayo and Obagunwa. Busayo,T(2018).Foreign Direct Investment Inflow and Agricultural Sector Productivity In Nigeria. IOSR Journal of Economics and Finance, 9(4), 12-19. 5. Sonawane Shantaram Tarachand,(2017).A study on FDI in agriculture sector in India. International Journal of Multidisciplinary Education and Research, 2(3), 29-30. 6. Sharmin Akhter, (2019).Comparative Analysis of FDI in SAARC and ASEAN countries. IOSR Journal of Economics and Finance (IOSR-JEF), 10(2), 01-05. 7. Abhishek Vijaykumar Vyas,(2015),An Analytical Study of FDI in India (2000-2015). International Journal of Scientific and Research Publications, 5(10), 1-30. 8. Kapil Singh and Ritu Walia, K. (2015).Foreign Direct Investment (FDI) & Agriculture Sector in India.PARIPEX - INDIAN JOURNAL OF RESEARCH, 4(1), 6-8. 9. Intan Maizura Abdul Rashid, Nor'aznin Abu Bakar, Nor Azam Abdul Razak,(2016). Determinants of Foreign Direct Investment (FDI) in Agriculture Sector based on Selected High-income Developing Economies in OIC Countries: An Empirical Study on the Provincial Panel Data by Using Stata, 2003-2012. Advances in Economics and Business, 4(9), 477-481. Authors: A.Paul Williams Impact of FDI as Macroeconomic Variable on the Exchange Rates with Special Reference to the Paper Title: Selected Asian Countries’ Currencies Abstract: Globalization has brought immense benefit for the welfare of the human race. For a globalized world, the economic integration of nations around the world is a prerequisite. This integration of economies has brought in the concept of international trade wherein the countries trade with each other. For a trade to be carried out the buyer has to pay the seller in currency that is accepted by the seller. As of now one of the widely accepted currencies is USD and the exchange rates of most of the currencies are determined in terms of USD. The exchange rate of a country is affected by many macroeconomic variables and one among them is the FDI. This paper has tried to analyse whether FDI as a macroeconomic variable affects the exchange rate of selected Asian countries' currencies. With the integration of economies around the world, it is important to know the factor responsible for the variation in the exchange rates. With this knowledge, the Governments and the Central Banks can plan their policies accordingly that are attractive to the investors. The study has considered countries such as China, India, Phillipines, Qatar and Singapore. The study has used regression to find out the influence of 19. FDI inflows on the exchange rates of respective currencies and correlation has been used to find the extent of relationship between the variables considered. The results show that the FDI inflows affect the exchange rates of 122-125 all the countries considered except Phillipines. Also correlation shows that FDI inflows and Exchange rates of Qatar are not related since Qatar follow fixed exchange rate regime.

Keyword: FDI, Exchange Rates, Fiscal Policy. References: 1. Farhana and Nushrat (2015),”Effects of macroeconomic variables on the exchange rates of Bangladesh”, International journal of scientific and engineering research, pp 1028-1034 2. Fayyaz (2014),”Impact of macroeconomic variables on exchange rates: Empirical evidence from developing asian countries”, SSRN, pp 1-28 3. Ravindran and Soroush (2013),” Influence of macroeconomic variables on exchange rates”, Journal of economics, business and management, pp 276-281 4. Devereux and Charles engel (1999),”The optimal choice of exchange rate regime: price-setting rules and internationalized production”, national bureau of economic research, pp 1-31 5. Chi-wei su(2012),”The relationship between exchange rate and macroeconomic variables in china”, research gate, pp 33-56 Authors: M. Kanaga, K. Uthayasuriyan

Paper Title: Foreign Direct Investment: A Feature Key Drive’s for India’s Growth in it Sector Abstract: The IT sector continues the main drivers of development in India, contributing nearly 72 percentage of its added gross value in 2017-18. However, this sector's growth in 2017-18 was moderate to 8.2 percent compared to 9.7 percent in the past year, although it remains greater than the IT sector, a main driver in FDI is frequently found in the open economy, a growth in investment assumes significant against the backdrop of widening current account deficit and trade deficit the country’s current account deficit is likely touch 2.8 percent of GDP 2018-19 on the IT sector, has increased its contribution to India has been rapidly moving upwards on the technology adoptions curve to improve and deliver leading it has excelled in business developing innovative solution and collaborating larger firms to meet the current needs of the IT sector. which offers a 20. qualified workforce and excellent growth prospects for investors compared to tightly regulated in Foreign Direct Investment, perhaps it needs not only capital investment, but as well as technology. It could be included that the analyzed trend values are preferred to FDI inflows in IT Sector. 126-131

Keyword: FDI, Feature Key, IT Sector, GDP. References: 1. Syed azhar, K.N.marimuthu, “AN OVERVIEW OF FOREIGN DIRECT INVESTMENT IN INDIA”, EXCEL International Journal of Multidisciplinary Management Studies Vol.2 Issue 1, January 2012, ISSN 2249 8834 . 2. Ratan Kirti1, “FDI IMPACT ON EMPLOYMENT GENERATION AND GDP GROWTH IN INDIA” Asian Journal of Economics and Empirical Research ISSN: 2409-2622 Vol. 3, No. 1, 40-48, 2016. 3. Abaukaka Thomas Onimisi, “FOREIGN DIRECT INVESTMENTS AND EMPLOYMENT GENERATION NEXUS IN NIGERIA” Journal of Educational and Social Research MCSER Publishing, Rome-Italy, Vol. 4 No.5 July 2014. 4. Anil Duggal, “FOREIGN DIRECT INVESTMENT IN INDIA” Journal of Internet Banking and Commerce, December 2017, vol. 22, no. 3. 5. Bhavya Malhotra, “FOREIGN DIRECT INVESTMENT: IMPACT ON INDIAN ECONOMY”, Global Journal of Business Management and Information Technology. ISSN 2278-3679 Volume 4, Number 1 (2014), pp. 17-23. 6. Yilmaz Bayar, “FOREIGN DIRECT INVESTMENT INflOWS AND FINANCIAL DEVELOPMENT IN CENTRAL AND EASTERN EUROPEAN UNION COUNTRIES: A PANEL COINTEGRATION AND CAUSALITY”, International Journal of Financial Studies. Int. J. Financial Stud. 2018, 6, 55; doi:10.3390/ijfs6020055. Authors: A.Muthusamy, P. Jansi Rani

Paper Title: FDI, GDP, and CO2 Emission: ARDL Bound Cointegration Relationship Examination Abstract: The study tries to evaluate empirically, the relationship between foreign direct investment (FDI) and environmental impact with GDP in India using annual data over the period 1980-1981 to 2017-18. The genuine effect on the earth, in any case, might be bigger because CO2 emission is one of the numerous contaminations produced by financial exercises. In any case, CO2 is a worldwide air toxin, our finding has some broad ramifications for the worldwide condition too, with India has risen as the fourth most noteworthy in the worldwide positioning of CO2 emissions by the turn of this century. The Autoregressive Distributed Lag (ARDL) Bound Test after which the cointegration and causality tests were analyzed. The error correction models were also predictable to scrutinize the short-run dynamics. The Granger causality test finally deep-rooted the presence of unidirectional causality which long runs from GDP and CO2 to foreign direct investment. The error correction estimates confirmed that the Error-Correction Term is statistically significant and has a negative sign, which confirms that there isn't any problem in the long-run equilibrium relationship between the independent (GDP & CO2) and dependent variables (FDI). The study concluded that FDI had a long-run relationship with GDP and CO2 emission.

Keyword: Foreign Direct Investment, Gross Domestic Product, CO2 Emission, Indian Economy, ARDL Cointegration Analysis, etc. References: 1. Aliyu, M. A. (2005). Foreign Direct Investment and the Environment: Pollution Haven Hypothesis Revisited. Eighth Annual Conference on Global Economic Analysis, 1–35. Retrieved from https://www.gtap.agecon.purdue.edu/resources/download/2131.pdf?q=pollution-haven-hypothesis 2. Baek, J., & Koo, W. W. (2008). A dynamic approach to the FDI-environment nexus: the case of China and India. Journal of East Asian Economic Integration, 13(2), 87–106. 3. Bakhsh, K., Rose, S., Ali, M. F., Ahmad, N., & Shahbaz, M. (2017). Economic growth, CO2 emissions, renewable waste and FDI relation in Pakistan: New evidence from 3SLS. Journal of Environmental Management, 196(February), 627–632. 21. https://doi.org/10.1016/j.jenvman.2017.03.029 4. Blanco, L., Gonzalez, F., & Ruiz, I. (2013). The Impact of FDI on CO2 Emissions in Latin America. Oxford Development Studies, 41(1), 104–121. https://doi.org/10.1080/13600818.2012.732055 132-138 5. Borhan, H., Ahmed, E. M., & Hitam, M. (2012). The Impact of CO2 on Economic Growth in Asean 8. Procedia - Social and Behavioral Sciences, 35(December 2011), 389–397. https://doi.org/10.1016/j.sbspro.2012.02.103 6. Candelon, B. (2006). Testing for short- and long-run causality : A frequency-domain approach. 132, 363–378. https://doi.org/10.1016/j.jeconom.2005.02.004 7. Danish, Wang, B., & Wang, Z. (2018). Imported technology and CO2 emission in China: Collecting evidence through bound testing and VECM approach. Renewable and Sustainable Energy Reviews, 82(September), 4204–4214. https://doi.org/10.1016/j.rser.2017.11.002 8. Dogan, E., & Seker, F. (2016). Determinants of CO2 emissions in the European Union: The role of renewable and non-renewable energy. Renewable Energy, 94(2016), 429–439. https://doi.org/10.1016/j.renene.2016.03.078 9. Engle, R. F., Granger, C. W. J., & Mar, N. (2007). Cointegration and Error Correction : Representation, Estimation, and Testing. 55(2), 251–276. 10. FDI, Growth And The Environment: Evidence From India On CO2 Emission During The Last Two Decades. (2009). Journal of Economic Development, 34(1), 43–58. 11. Gholipour Fereidouni, H. (2013). Foreign direct investments in real estate sector and CO 2 emission. Management of Environmental Quality: An International Journal, 24(4), 463–476. https://doi.org/10.1108/meq-04-2012-0032 12. Hajilary, N., Shahi, A., & Rezakazemi, M. (2018). Evaluation of socio-economic factors on CO2 emissions in Iran: Factorial design and multivariable methods. Journal of Cleaner Production, 189, 108–115. https://doi.org/10.1016/j.jclepro.2018.04.067 13. Hitam, M. Bin, & Borhan, H. B. (2012). FDI, Growth and the Environment: Impact on Quality of Life in Malaysia. Procedia - Social and Behavioral Sciences, 50(July), 333–342. https://doi.org/10.1016/j.sbspro.2012.08.038 14. Hoffmann, R., Lee, C. G., Ramasamy, B., & Yeung, M. (2005). FDI and pollution: A Granger causality test using panel data. Journal of International Development, 17(3), 311–317. https://doi.org/10.1002/jid.1196 15. Inglesi-Lotz, R., & Dogan, E. (2018). The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators. Renewable Energy, 123, 36–43. https://doi.org/10.1016/j.renene.2018.02.041 16. MacDermott, R. (2009). A panel study of the pollution-haven hypothesis. Global Economy Journal, 9(1). https://doi.org/10.2202/1524-5861.1372 17. Matthew, A., & Robert, J. R. (2009). www.econstor.eu. 18. Merican, Y., Yusop, Z., Mohd Noor, Z., & Siong Hook, L. (2007). Foreign direct investment and the pollution in Five ASEAN nations. International Journal of Economics and Management, 1(2), 245–261. 19. Osabuohien, E. S., Efobi, U. R., & Gitau, C. M. W. (2013). External intrusion, internal tragedy: Environmental pollution and multinational corporations in sub-Saharan Africa. In Advances in Sustainability and Environmental Justice (Vol. 12). https://doi.org/10.1108/S2051-5030(2013)0000012010 Authors: A.Muthusamy, S. Karthika

Paper Title: Sector -Wise Performance of FDI Equity Inflows in India 22. Abstract: Foreign Direct Investment (FDI) plays an important role in the development process of a country. It has the potential for contributing to the development through the transfer of financial resources, 139-144 technology and innovative and improved management techniques along with raising productivity. Developing countries like India need substantial foreign inflows to achieve the required investment to accelerate economic growth and development. It can act as a catalyst for domestic industrial development. Further, it helps in speeding up economic activity and brings with it other scarce productive factors such as technical knowledge and managerial experience, which are equally essential for economic development. India has been the most significant beneficiary of remote direct interest in most of its various segments. It likewise assumes a significant job in the advancement of a nation. India is the biggest popularity based nation with the second biggest populace on the planet, with the standard of law and exceedingly instructed English talking work power, the nation is considered as a sheltered spot of assurance for outside financial specialists. The study covers the performance of FDI Equity inflows in India and the sector-wise performance of FDI Equity inflows in India. The samples of sector-wise FDI inflows in India are selected based on the convenient sampling method. A Sample of 10 sectors has been selected based on the availability of data. The inflow of FDI in the media transmission and Constrictions utilizing combined example t’ test P worth is 0.049 (Less than the estimation of 0.05). Henceforth we may accept the invalid speculation with 95% certainty. The Construction (foundation) exercises and Power utilizing combined example t’ test. P worth is 0.016 (Less than the estimation of 0.05). Subsequently, we may accept the invalid theory with 95% certainty.

Keyword: FDI Equity Inflows, Sector-wise, Relationship, Two-tail test. References: 1. www.ibef.com 2. www.dipp.nic.in 3. www.data.gov.com 4. www.fdi.gov.in 5. Priyanka Bedi and Ekta Kharbanda “Analysis of Inflows of Foreign Direct Investment in India- Problems and Challenges” Global Journal of Finance and Management. ISSN 0975-6477 Volume 6, Number 7 (2014), pp. 675-684 6. Abhishek Vijaykumar Vyas “An Analytical Study of FDI in India” International Journal of Scientific and Research Publications, Volume 5, Issue 10. Authors: A. Muthusamy, Raghuveer Negi Foreign Direct Investment and Economic growth in Member Countries of Asia Pacific Trade Paper Title: Agreement Abstract: The economic growth depicts prosperity and self sustainability of nation. Foreign Direct Investment considered as handful tool for growth of host nation is a general perception all over the globe. Now due to global webbed market, countries worldwide are anxious to exploit Asia-Pacific’s huge market and rich culture. The empirical evidence and fact-based case study poses FDI and economic growth on fringe due to variation in during the different span of time. This study attempted to analyze the relationship between FDI and economic growth into Bangladesh, China, India, Lao PDR, Mongolia, Korea Republic and Sri Lanka. It is assumed that blend of developed, emerging and developing economies taking as base for comparison will derive the more satisfactory result. Also, it consists of large market driven economies in the world due to strong market base. To attain the result of GDP growth, Inflation rate and Unemployment rate has taken as economic growth indicator. The Ordinary Least Squares, Augmented Dicky-Fuller and Granger Causality test is used to estimate the effect of FDI on economic growth. The result shows that in spite of consistent pattern in FDI inflow not all the countries have experienced the significant effect of FDI on economic growth of nation. The implications in nation’s policies are discussed in the study.

Keyword: FDI, Economic Growth, GDP, Inflation, Unemployment, OLS, ADF, Granger Causality.

23. References: 1. Alfaro, Laura. (2003). Foreign Direct Investment and Growth: does the sector matter. 2. AnittaPhommahaxay and Bounlert Vanhnalat, Impact of FDI on economic growth in Lao PDR, ICMR Journal, Volume 3, 145-155 Number 2, pages 1-18, 2015, http://icmr.crru.ac.th/Journal/Journal%206/1.pdf 3. Anitta, P., & Mekong Institute,. (2013). Impact of FDI on economic growth of Lao PDR. 4. Balamurali, N., & Bogahawatte, C. (2004). Foreign direct investment and economic growth in Sri Lanka. Sri Lankan Journal of Agricultural Economics, 6(1), 37–50. 5. Borensztein, Eduardo and de Gregorio, Jose and Lee, Jong-Wha, How Does Foreign Direct Investment Affect Economic Growth? (March 1995). NBER Working Paper No. w5057. Available at SSRN: https://ssrn.com/abstract=225836 6. Baldwin, Richard & Braconier, Henrik & Forslid, Rikard, 1999."Multinationals, Endogenous Growth and Technological Spillovers: Theory and Evidence," CEPR Discussion Papers 2155, C.E.P.R. Discussion Papers. https://ideas.repec.org/p/cpr/ceprdp/2155.html 7. Cai, Francis & Cheng, Huifang & Xu, LianZan & Leung, C.K.. (2011). Economic Growth And FDI In China. International Business & Economics Research Journal (IBER). 3. 10.19030/iber.v3i5.3687. 8. Chandana Chakraborty, Peter Nunnenkamp, Economic Reforms, FDI, and Economic Growth in India: A Sector Level Analysis, World Development, Volume 36, Issue 7, 2008, Pages 1192-1212, ISSN 0305-750X, https://doi.org/10.1016/j.worlddev.2007.06.014. (http://www.sciencedirect.com/science/article/pii/S0305750X0800051X) 9. Christopher MacDougall, 2015."Foreign Direct Investment into Mongolia," The Northeast Asian Economic Review, ERINA - Economic Research Institute for Northeast Asia, vol. 3(2), pages 43-53, October. https://ideas.repec.org/a/eri/review/3243- 53.html 10. Ferdausy, Shameema & Rahman, Md. (2008). Foreign Direct Investment in Bangladesh: A Positive Perspective. 4. 11. Gupta, Kanishka & Garg, Ishu (2015). Foreign Direct Investment and Economic Growth in India: An Econometric Approach. Apeejay - Journal of Management Sciences and Technology 2 (3), June - 2015 (ISSN -2347-5005) 12. J. Gunawardana, Pemasiri & Sommala, Sisombat. (2009). Trends and Patterns of Foreign Direct Investment in Lao PDR. International Journal of Business and Management. 3. 10.5539/ijbm.v3n1p41. 13. Jha, Raghbendra. (2003). Recent Trends in FDI Flows and Prospects for India. SSRN Electronic Journal. 10.2139/ssrn.431927. 14. Jimmyn Parc, Jin Sup Jung, (2018) "The effects of conventional and unconventional FDI on the host country: A case study of the Korean automobile industry", Journal of Korea Trade, Vol. 22 Issue: 2, pp.105-120, https://doi.org/10.1108/JKT-09-2017-0087 15. Kyophilavong, Phouphet & Nozaki, Kenji. (2015). Effect of FDI on Lao Economy and its Challenges. Progress Report on the Potentials on the Indochina Economic Zone, Edition: 1, Chapter: CHAPTER 4, Publisher: the Economic and Social Research Institute (ESRI), Editors: the Economic and Social Research Institute (ESRI, pp.59-79). 16. Lai, P. (2002). Foreign direct investment in China: Recent trends and patterns. China and World Economy. 2. 25-32. 17. Mani, Madhavan & Nithyashree, MU. (2016). Make in India - Foreign Direct Investment and its Impact on Economic Growth. International Journal of Social Science & Management. Vol. 5. 36-40 18. M M Mustafa, A & Santhirasegaram, S. (2014). The impact of foreign direct investment on economic growth in Sri Lanka. Journal of Management. 8. 10.4038/jm.v8i1.7551. 19. Mungunzul, Erdenebat & Chang, Taikoo. (2018). The Effect of Foreign Direct Investment on the Economic Development of Mongolia. Journal of Electronic Commerce in Organizations. 16. 12-21. 10.4018/JECO.2018070102. 20. Nair-Reichert, Usha and Weinhold, Diana, (2001), Causality Tests for Cross-Country Panels: A New Look at FDI and Economic Growth in Developing Countries, Oxford Bulletin of Economics and Statistics, 63, issue 2, p. 153-71. 21. Noorbakhsh, Farhad; Alberto Paloni, and Ali Youssef. 2001. “Human Capital and FDI Inflows to Developing Countries: New Empirical Evidence.” World Development, 29, no. 9:1593- 1610. 22. Ridzuan, Abdul Rahim & Ismail, Nor Asmat & Fatah, Abdul & Idham, Mohamad & Pardi, Faridah. (2017). The Impact of Foreign Direct Investment and Trade Liberalization on Economic Growth, Income Distribution and Environmental Quality: The Comparative Analysis between France and South Korea. International Journal of Academic Research in Business and Social Science. 7. 163-182. 10.6007/IJARBSS/v7-i6/2953. 23. Ravinthirakumaran, Kalaichelvi & Selvanathan, Eliyathamby & Selvanathan, Saroja & Singh, T. (2015). Determinants of Foreign Direct Investment in Sri Lanka. South Asia Economic Journal. 16. 233-256. 10.1177/1391561415598458. 24. Rahaman, A., & Chakraborty, S. (2015). Effects of Foreign Direct Investment on GDP: Empirical evidence from developing country. Advances in Economics and Business, 3, 587–592. doi: 10.13189/aeb.2015.031207. 25. Sasi Iamsiraroj, Mehmet Ali Ulubaşoğlu, Foreign direct investment and economic growth: A real relationship or wishful thinking?, Economic Modelling, Volume 51, 2015, Pages 200-213, ISSN 0264-9993, https://doi.org/10.1016/j.econmod.2015.08.009. (http://www.sciencedirect.com/science/article/pii/S0264999315002138) Authors: S. Prasad, A. Paul Williams Sectoral Contribution of FDI in India (With special reference to Automobile, Telecommunication, Paper Title: Services and Computer Hardwares & Softwares sectors) Abstract: After opening of the Indian economy, the contribution of Foreign Direct Investment to the Indian Economy is remarkable. The Foreign Investments not only brings in capital into the host country but also the technological advancements, best practices in managing the company and also efficiency. The Government of India is concentrating on attracting the FDI more than the FII. This is because Foreign Direct Investment is more stable and it has a presence in the host country. On the other hand, FIIs are unstable and they invest in the shares of the company and also they move out the capital when the market conditions are not favourable for them. Also the Government of the day is focusing on attracting more Foreign Direct Investments. This is evident from the jump in the Ease of Doing Business Index rank of India in the recent report. This article tries to analyse the Sectorwise contribution (Automobile, Telecommunication, Services and Computer Hardwares & Softwares sectors) of FDI in the Indian economy. The analytical tools such as regression and correlation have been used. The results show that the computer hardware and software sector has contributed the most to the GDP of India 24. among the sectors considered. The least contributor is the Telecom Sector. The study has also given some suggestions to the policy makers so that the different sectors of the economy remain attractive to the FDI. 156-158

Keyword: FDI, Sectors, Indian Economy, Ease of Doing Business. References: 1. Joo, Bashir & Ali Dhar, Faiza. (2018),” Role of Sectorwise FDI Inflow on Growth of India- An Empirical Analysis”,International Research Journal of Management and Commerce 2. Chengalvala, Sarada. (2017). Empirical analysis of foreign direct investment (FDI) inflows into Indian economy. 4. 54-60. 3. Singhania, Monica & Gupta, Akshay. (2011). Determinants of foreign direct investment in India. Journal of International Trade Law and Policy. 10. 64-82. 10.1108/14770021111116142. 4. Kaur, M., Yadav, S. S., &Gautam, V. (2013). A bivariate causality link between foreign 5. Aykut, Dilek & Sayek, Selin. (2007). The Role of the Sectoral Composition of Foreign Direct Investment on Growth. 6. Lect. Ping Zheng, Sen. (2013). The Variation in Indian Inward FDI Patterns. Management International Review. 53. 10.1007/s11575-013-0178-z. 7. Dash, Ranjan & Parida, Purna. (2012). FDI, services trade and economic growth in India: Empirical evidence on causal links. Empirical Economics. 45. 10.1007/s00181-012-0621 8. Alfaro, Laura. (2003). Foreign Direct Investment and Growth: does the sector matter. Authors: K. Uthayasuriyan Trends in Foreign Direct Investment and Economic Growth of India with Special Reference to Paper Title: Tamil Nadu Abstract: Foreign Direct Investments (FDIs) are welcomed by various host countries with multiple objectives such as capital infusion, technological up-gradation and managerial know-how. This measure is carried out at substantial cost of offering various incentives in terms of providing land for industrial investments, 25. supply of uninterrupted power, ensuring problem free labour relation environment etc. These measures are taken by any government on a basis which will have a specific time frame, in order to not let investment become a drain on the economy of the host country. This study intends to evaluate the impact of FDI on the economic 159-164 growth of India and in the state of Tamil Nadu, the most industrialised and urbanised economy in India. With proactive governance and path breaking policy initiatives and structural reforms, the state has emerged as one of the leading industrialised states of India. The period of this study has been taken for ten years from 2008-09 to 2018-19. The data on the inflow of FDI during this period and the flow of FDI from various source countries have been collected along with the data on various economic parameters pertaining to infrastructure such Gross National Income (GNI), Net National Income (NNI) and Per Capita Net National Income (PCNI). The data collected for the study are entirely the secondary data published by both the state and central governments. The analysed results of the study reveal that the inflow of FDI into India during the study period has been consistent and been growing significantly, as the economy of the country and the dynamic transformation of global economy demanded. This inflow of FDIs has consistently created a positive impact on the economic indicators, making it an essential factor to be very attentively looked after for a sustained growth.

Keyword: trends,FDI, labour,Industry. References: 1. Arindham Banik and Pradip K Bhaunik,Foreign Capital Inflows to China, India and the Caribbean ; Trends, Assessments and the Determinants,2006 2. Assat Razin & Efraim Sadka, Foreign Direct Investment: Analysis of Aggregate Flows, Princeton University Press 2007. 3. Nicholas A Phelps and Jeremy Alden,Foreign Direct Investment and the Global Economy Corporate and Institutional Dynamics of Global Localisation, The Stationery Office 1999. 4. Theodore H Moran, Parental Supervision: The New Paradigm for Foreign Direct Investment and Development, Institute for International Economics, Washington 2001. 5. Nagesh Kumar and Jaya Prakash Predham, Foreign Direct Investment : Externalities and Economic Growth in Developing Countries; Sime Empirical Explorations, Palgrave Macmillan in Association with International Economic Association. 6. De J Gregorio, The Role of Foreign Direct Investment and natural resources in Economic Development, 2003 Authors: Muthusamy, S. Sundararajan

Paper Title: Impact of Foreign Direct Investment on Industrial Growth of India Abstract: In India the Foreign direct investment (FDI) has received a staged improvement from instigate of the Make in India scheme, according to recent survey. There was a incredible increase in FDI inflows (40%) particularly in manufacturing sector from October, 2014 to June, 2019 . The industrial sector is considered to be the one of the dominant sectors that contribute the major Indian GDP. India has been ranked fourteenth in the factory output in the world. This was because of the launch of initiative, which sought for promoting manufacturing segments and be a magnet for foreign investments. More than 56 manufacturing units are benefitted in the entire globe. In the recent times during the year 2014 to 2019 the Industrial production inclined to 3.1 per cent, mainly on account of improvement and to encourage talent augmentation towards the various sectors of the economy. This article brings out the recent efforts taken by the government for encouraging the FDI into various sectors and how it has made a pathway. In the last ten years India has shown a tremendous increase in Foreign Direct Investment into the various sectors in economy. Even though Government of India has make a pathway for attracting FDI on various sectors, this papers focuses on explaining the impact of make in India scheme on FDI. In this paper period of five years has been considered for the analysis. The Statistical Tools like Karl Pearson's Coefficient Correlation and One - Way ANOVA has been used for the analysis of data. To study the relationship between the FDI and IIP correlation is used for the analysis of data. 26.

Keyword: GDP, FDI, Make in India Scheme, Industrial Growth, Manufacturing units. 165-169 References: 1. http://www.makeinindia.com/foreign-direct-investment. 2. Prasad, et. al (2007), Foreign Direct Investments and the Legal Profession in India , Delhi Business Review X Vol. 8, No.1, January- June. 3. Dunning, Lundan (2008), Multinational Enterprises, 2nd Edition, Edward Elgar Publishing Limited, Pp. 2 -8. 4. Narayana (2013), Foreign Investment and Indian Economy (Ed), Manglam Publishers & Distributors, Delhi, Pp. 26 - 27. 5. Singh, Gupta (2013), "Foreign Direct Investment and Industrial Development in India", Thesis submitted to Maharshi Dayanand University Rohtak for the degree of doctor of philosophy in Department of Commerce. 6. Lakshmana Rao, Ravikanth (2016), Make in India and Foreign Direct Investment (FDI) - synergetic effect on Economic Growth, SSRN Journal, September 2015, Pp. 1-8. 7. www.fipb.gov.in 8. Hand Book of Statistics on Indian Economy, Reserve of India, Various issues. 9. www.mospi.nic.in / India Manufacturing Barometer 2019, Building Export Competitiveness, FICCI, Jan 2019. 10. Agarwal J., Khan M.A (2011)., "Impact of FDI on GDP: A comparative study of China and India", International Journal of Business Management, Vol. 6, Issue - 10, 2011, pp. 71-79. 11. Index of Industrial Production, MOSPI, CSO, Government of India. 12. Sharma, Khurana (2013), Role of FDI in Various Sectors, International Journal of Advances in Management and Economics, Vol. 4, Issue - 3, 2013, Pp. 12 - 14. 13. Mahendra Sinha, Arindam, Partha (2018), Foreign Direct Investment and Indian Industries: A Dynamic Panel Study, International Journal of Pure and Applied Mathematics, Volume 118 Issue. 18, 2018,ISSN: 1279-1294, Pp. 1279 - 81. Authors: Listin P T, D Ilangovan Investment Opportunities and Challenges in Tamil Nadu for Industrial Development- An Paper Title: Assessment Abstract: In recent years, significant of Foreign Direct Investment has been increasing especially in the 27. developing countries. These countries are trying their level best to attract more and more FDI. Foreign Direct Investment takes place when a company invests directly in the production or marketing of a product in a foreign country.FDI is defined as an investment involving a long term relationship that reflects the long term interest and 170-172 control of a resident entity in the host country. Industrial investment plays a significant role in the development of a country. Broadly there are two types of foreign investment viz., foreign direct investment and portfolio investment. The developments are easily possible through Foreign Direct Investment (FDI) because it helps to bring close the different economies of the world by investing capital in a country. Capital formation is an important determinant of economic growth. While domestic investments add to the capital stock in an economy, FDI plays a complementary role in overall capital formation and filling up the gap between domestic savings and investment. Foreign investment plays an important role in the long term economic development by augmenting availability of capital, enhancing competitiveness domestic economy through transfer of technology, strengthening infrastructure, raising productivity, generating new employment opportunities and boosting exports. The Government has implemented several reforms in recent years to attract more FDIs. These include improving infrastructure, revising the law on the land acquisition, reforming labour law and rationalizing the process of obtaining environmental clearances. In this article researcher focused on industrial opportunities and challenges in Tamil Nadu for industrial development of the state.

Keyword: Industry, FDI, Portfolio Investment, domestic investment. References: 1. Francis Cherunilam, Business Environment, Himalaya Publishing House,pp no. 600 2. Pallav Manik, Dr Sandeep Kumar ,Growth and performance of FDI in India. 3. Anitha R, Foreign Direct Investment and Economic Growth in India, International Journal of Marketing, Vol.1,Issue8 2012,ISSN 2277 3622. 4. Dr C P SHaheed Ramzan and Hussain V, A Study on Problems and Prospects of Industrial Sector in Tamilnadu, An International Multidisciplinary Journal, Vol 3, Issue no 3, ISSN 2455-314X 5. www.ibef.org. 6. Tamil Nadu Global Investors Meet Agenda 2019 and www.ibef.org 7. Syed Azhar and K N Marimuthu, International Journal of Management Studies,Vol.2, Issue no 1,ISSN2249 8834. 8. Dr J N V Raghuram and Syed Shaaz, FDI Inflow- Trend Analysis, IJMET, Vol 8, Issue 12December2017, pp 10-20. 9. Syed Azhar and K N Marimuthu, International Journal of Management Studies,Vol.2, Issue no 1,ISSN2249 8834 Authors: S. Sridevi, S. Chandramohan Impact of FDI on the Development of an Economy and the Growth in the Value of Exports of a Paper Title: Country Abstract: The flow of FDI into the country is anticipated to be in a position to expand productivity which will ultimately have an influence on the growth in national income in the form of the Gross Domestic Product (GDP) as well as in the form of increased exports. In other words, in order to enhance the country’s overall performance in international trade, investment is genuinely necessary. There is a one-way relationship between FDI and export in which the value changes in FDl have an effect on changes in the value of exports. In the short term, the extend in the expense of FDl reasons a decline in the value of exports. While in the long term, the extend in the expense of FDl will reason an upward jab in the value of exports the increase in price will cause a upward jab in the fee of exports. . It is activated by the idea of FDI is a subsidizing in long term oriented so that the advantages to the economy, which incorporate export in general execution can be obtained in the long term. Hence, foreign countries can be instrumental in advancing exports from the host nations. As an ever increasing number of exports help lead a nation to expand its foreign exchange reserves and fabricate a strong financial position, in this manner, it tends to be appropriately said that FDI can not just build the export base of the domestic country but additionally adds to the overall growth of the host country.

28. Keyword: Export; Import; Economy; Investment; Trade. References: 173-176 1. Ayanwale, A. B. (2007). "FDI and Economic Growth: Evidence from Nigeria". African Economic Research Consortium. 2. Fortanier, F. (August 2007). "Foreign Direct Investment and Host Country Economic Growth: Does the investor's country of origin play a role?". Transnational Corporation. 3. Habib, M. G. (2009). “Causal Relationship between FDI and export for Bangladesh: A Time-Series analysis”. Asian Economic Review. 4. Kumar, G. (2011). “Causality between FDI and economic growth: A comparative study of India and China”. Man and Development. 5. Lam, C. K.-Y. (2011). “Foreign Direct Investment, Financial Development and Economic Growth: Panel data Analysis”. The IUP Journal of Applied Economics. 6. Ljungwall, C. (2007). "Financial Sector Development, FDI and Economic Growth in China". China Center for Economic Research. 7. Ministry of Commerce & Industry, Govt. Of India. (2012, January). Department of Industrial Policy and Promotion. Retrieved from FDI Statistics: http://www.dipp.nic.in/ 8. Mousumi Bhattacharya, S. N. (2011). "The Interrelationship between Merchandize Trade, Economic Growth and FDI Inflows in India”. South-Eastern Europe Journal of Economics. 9. Ramkishen S. Rajen, S. M. (2009). 'How can India Increase its Attractiveness as a Destination for FDI?' In R. S. Rajen Monetary Investment and Trade Issues in India (pp. 127-151). New-Delhi: Oxford. 10. Samrat Roy, K. M. (2009). "Empirical Evidence on the Relationship between Foreign Direct Investment and Economic Growth: A Cross-Country Exploration in Asia". 11. Singh, J. (2011). “Concentration in India’s Manufacturing Industry: Impact of Investment Liberalization”. Man and Development. Authors: M. Surya, B. Sudha, T. Priyanka

Paper Title: FDI in Indian Non-Life Insurance Sector: Boost Market Potential 29. Abstract: FDI brings up the capital inflows from abroad which is invested in the production capacity of the economy and are preferred as external finance because they are non-debt creating, non-volatile and their 177-181 returns depend on the performance of projects financed by investors. It expedites international trade and transfer of information and technology. Thus, ‘FDI acts as a catalyst for the growth nation’. The Indian insurance market is expected to grow up to 125 percent in the next decade which would indirectly be a boost for the Indian Economy. Increased FDI limit up to 100 percent will allow more new players to enter and strengthen the existing companies. This will promote higher competition, innovative products, digital distribution channels and cheaper policy premium for their customers. Therefore, this paper primarily focuses on the FDI in the Insurance sector in India and its significance. In the Budget 2015-16 the government announced, three ambitious Social Security Schemes about Insurance and Pension Sector (a) PradhanMantri Suraksha Bima Yojana (b) PradhanMantri JeevanJyoti Yojana and (c) Atal Pension Yojana. These schemes help to create universal social security system for all Indians, especially the poor and underprivileged. The health insurance scheme Ayushman Bharat will provide good quality health care up to Rs.5 lakh per family per year at government and private hospitals all over India. This scheme will be available for 50 crore Indians and covers 10.74 beneficiaries. In this backdrop, this article aims to analyze the performance of Non-life Insurance sector in India after the increase of FDI from 26 percent to 49 percent (which has come into force from 16 March 2016).

Keyword: FDI, Non-life insurance, Net premium, Capital, and Foreign companies. References: 1. Hasan A (2015) Impact Analysis of FDI on Insurance Sector in India. Int J Econ Manag Sci 4:255. doi:10.4172/21626359.1000255 2. https://www.ibef.org/download/FDI_Factsheet_27May2019.pdf 3. https://static.investindia.gov.in/s3fs-public/inline-files/FDI%20Policy%20with%20Amendments_0.pdf 4. http://www.makeinindia.com/foreign-direct-investment 5. https://www.wallstreetmojo.com/foreign-direct-investment/ 6. Annual reports of IRDA 2016-17 and 2017-18. 7. www.ibef.org Authors: N. Ramar, V. Prabakaran, S.Rajendran, C.K Muthu Kumaran

Paper Title: FDI in India: Leading to Economic Growth Abstract: Foreign Direct Investment (FDI) plays predominant role in the improvement of nation's growth and the global business. Foreign Direct Investment (FDI) is an important tool which is used currently in the overseas market and it is also a key factor which supports the investors to enter into the economy. In the developing countries FDI also enhances the exports made by the manufacturing firms through overflow effects on local companies by the means of exporting activities. There is a direct and indirect effect on the host country's exports to the FDI. New paradigms in the marketing channels can be endorsed due to the help of FDI, access to technology is also possible, product skills and financing could be done easily. Capital is in when domestically available capital is insufficient for the purpose of overall development of the country, foreign capital is seen as a way of filling up this gap. FDI inflows to India remained sluggish, when global FDI flows to EMEs had recovered in 2017- 18, despite sound domestic economic performance ahead of global recovery. This paper gathers evidence through a panel exercise that actual FDI to India during the year 2017-18 fell short of its potential level. An attempt is made through this paper to know the FDI equity inflows from various countries to India. An attempt has been made by the researcher through this paper to examine the economic growth through FDI. For the analysis the statistical tools like one – Way ANOVA, K-S Test has been used and the suggestions and the recommendations are based on the approach.

30. Keyword: FDI, OECD, MNCS, OGL, SIA, FIPB, OCB’s, MIGA, NRI’s, FEMA, FERA, FIIA, GIIN’s, UNCTAD. 182-186 References: 1. Birendra Kumar, Surya Dev (2003), "Low Bargaining Power of Labour Attracts FDI in India", Social Science Research Network, No.431060, 2003. 2. Sebastin (2004), "A Study of the Regional Determinants of Foreign Direct Investment in India, and the case of Gujarat",” Working Paper No. 2004/03/07, 2004, Indian Institute of Management. 3. Peng Hu (2006), “India’s suitability for Foreign Direct Investment”. Working Paper No.553, 2006, International Business with special reference to India, University of Arizona. 4. Peter (2008), "Foreign Direct Investment and Growth of Manufacturing Sector: An Empirical Study on Post Reforms India”, is a doctoral thesis submitted to the University of Mysore, 2005. 5. Arthur, Lokanandha Reddy Irala (2009), "Foreign Direct Investment and Growth of Manufacturing Sector: An Empirical Study on Post Reforms India”, is a doctoral thesis submitted to the University of Mysore, 2005. 6. Reserve Bank of India, Monthly Bulletin, Various Issues. 7. www.rbi.org/ various issues. 8. www. dipp.nic.in/ various issues. 9. Annual Survey of Industries, Ministry of Statistics and program implementation, Government of India. 10. Secretariat for Industrial Assistance, DIPP, Ministry of Commerce & Industry, Govt. of India. 11. Department of Economic Affairs, Statistics, Ministry of Finance, Govt. of India. 12. FDI Statistics, Department of Industrial Policy and Promotion, Ministry of Commerce & Industry, Government of India. 13. R. Anitha (2012). "Foreign Direct Investment And Economic Growth In India". International Journal of Marketing, Financial Services & Management Research. August 2012. Volume 1. Issue:8. ISSN: 2277 3622. Pp. 1 - 6. 14. Chigbu Ezegi, et. al (2015), Impact of Capital Inflows on Economic Growth of Developing Countries, International Journal of Management Science and Business Administration, Vol. 1, Issue - 7, June 2015, Pp. 2-5. Authors: K. Pagavathi, K. Prabhakar Rajkumar 31. The Progress and Achievement of Top Five Services Sectors through the Foreign Direct Investments Paper Title: in India Abstract: Foreign Direct Investment (FDI) plays a very important role in the development of the nation. It is very much vital in the case of underdeveloped and developing countries. A typical characteristic of these developing and underdeveloped economies is the fact that these economies do not have the needed level of savings and income in order to meet the required level of investment needed to sustain the growth of the economy. In such cases, foreign direct investment plays an important role in bridging the gap between the available resources or funds and the required resources or funds. It plays an important role in the long-term development of a country not only as a source of capital, but also for enhancing competitiveness of the domestic economy through transfer of technology, strengthening infrastructure, raising productivity and generating new employment opportunities. In India, FDI is considered as a developmental tool, which helps in achieving self- reliance in various sectors and in the overall development of the economy. India after liberalizing and globalizing the economy to the outside world in 1991, there was a massive increase in the flow of foreign direct investment. The present paper attempts to analyze the significance of the FDI Inflows in Indian service sector since 1991 and relating the growth of service sector FDI in the generation of employment in terms of skilled and unskilled. The services sector is not only the dominant sector in India’s GDP, but has also attracted significant foreign investment flows, contributed significantly to exports as well as provided large-scale employment. India’s services sector covers a wide variety of activities such as trade, hotel and restaurants, transport, storage and communication, financing, insurance, real estate, business services, community, social and personal 187-194 services, and services associated with construction.

Keyword: Foreign Direct Investment, Indian Service Sector, Make in India, Gross Domestic Product Growth. References: 1. BalasundaramManiam and Amitiava Chatterjee. “The Determinants of US Foreign Investments in India: Implications and Policy Issues,” Managerial Finance, Vol. 24, No. 7, 1998, pp. 55-62. 2. Nagesh Kumar, “Liberalization and changing patterns of FDI. Has India’s relative Attractiveness as a host of FDI improved?” Economic Developments in India, 2001, pp. 79-99 3. Balasubramanyam.V.N. and Vidya Mahambre “Foreign Direct Investment in India,” Working Paper No.2003/001, Department of Economics, Lancaster University Management School, International Business Research Group, 2003. 4. Birendra Kumar Nayak and Surya Dev. “Low Bargaining Power of Labour Attracts ForeignDirect Investment in India”, Social Science Research Network, No.431060, 2003. 5. Laura Alfaro, “Foreign Direct Investment and Growth: Does the Sector Matter?”, Working Paper Harvard Business School, April 2003. 6. Sebastin Morris. “A Study of the Regional Determinants of Foreign Direct Investment inIndia, and the case of Gujarat,” Working Paper No. 2004/03/07, 2004, Indian Institute of Management. 7. Rajih Kumar Sahoo, “Foreign Direct Investment and Growth of Manufacturing Sector: An Empirical Study on Post Reforms India”, is a doctoral thesis submitted to the University of Mysore, 2005 Authors: Violet Glady

Paper Title: FDI in Agriculture Sector in India with Special Reference to Academicians Abstract: Agriculture is the backbone of Indian economy. Nearly 70% of the society’s livelihood is dependent on agriculture and account for 19% of India’s GDP. To promote agriculture growth and to eliminate poverty, agricultural investment is mandate. National Savings is not able to meet the requirements of agricultural need for growth and development, thus global investment is inevitable to meet the investment requirement in agriculture. FDI in agriculture sector boosted up to Rs.611.28 Crore till December 2017. According to Indian scenario FDI up to 100% is allowed under the automatic route but subject to certain conditions mentioned in FDI policy. FDI in agriculture sector is inevitable factor that drives agriculture to attain sustainability through foreign investment. Foreign investment in agriculture also enables farmer to implement new techniques in farming that increase the yield and production capacity along with fund inflow. Farmers in India undergoing many turbulence because of inadequate fund, unequal distribution of subsidies, exorbitant interest rates, obsolete technology, traditional farming pattern, inadequate crop rotation, monsoon failure and natural calamities. It is remarkable evidence that FDI in agriculture remove poverty, hunger, ensure growth and development. Agriculture 32. investment can be segregated as private or public and foreign or domestic. Many researches have shown a positive result on going ahead with FDI in many sectors. It is notable that national savings are not able to match 195-199 the growing need of the economy, thus FDI is inevitable factor to promote agriculture and all other sector. This paper concentrates on the FDI inflow in Agriculture sector in India and the challenges faced by the sector in meeting the investment. Both primary and secondary data’s are used to support this study. Primary data’s are with special reference to academicians to analysis their overview of FDI in agriculture. Secondary data’s are pooled from government source and websites. This paper enable to find out the need for FDI in agriculture and how to meet the challenges faced during the critical period.

Keyword: Foreign Direct Investment, Agriculture, poverty, academicians. References: 1. Dr. Anjali Chaudhary (2016). Role of FDI in the growth of Indian Agriculture Sector: A post reform study, Global Journal of Finance and Management. ISSN 0975-6477 ,Vol. 8, No. 2. 2016 2. Dwivedi P. and Badge J. (2013) Impact of FDI Inflow On Service Sector In India: An Empirical Analysis, International Journal of Management Research & Business Strategy. ISSN 2319-345,Vol. 2, No. 3, July 2013 3. Sandeep Kumar &Kavita (2014).Indiastat.com, socio-economic voice. 4. Dr. ShobhitWadhwa & Dr. SuchetaAroraWadhwa. (2014) FDI in agriculture sector in India: status and challenges, Avon Publications, Book – Foreign Direct Investment, 5. OECD. (2000). Glossary of Foreign Direct Investment Terms and Definitions. Available online: http://www.oecd.org/daf/inv/investmentpolicy/2487495.pdf Authors: Kiranpreet Kaur, S.K. Mittal

Paper Title: Scrutiny of Breast Cancer Detection Techniques of Deeplearning and Machine Learning Abstract: Breast cancer is one of the most widely recognized tumors globally among ladies with the data available that one of every eight ladies is influenced by this illness during their lifetime. Mammography is the best imaging methodology for early location of the disease in beginning times. On account of poor complexity and low perceivability in the mammographic pictures, early discovery of the cancer malignant growth is a huge challenge to effective cure of the disease. Distinctive CAD (computer aided detection) supported algorithms have been developed to enable radiologists to give an exact determination. This paper highlights the study of the most widely recognized methodologies of image segmentation created for recognition of calcifications and masses. The principle focal point of this survey is on picture theof strategies and the factors utilized for early bosom disease identification. Surface investigation is the vital advance in any picture division strategies of image segmentation which depend on a nearby spatial variety of color or shading. Subsequently, different techniques for texture investigation for small scale calcification and mass identification in mammography are talked about in the mechanism of mammography. The point of this paper is to audit existing ways to deal with the segmentation of masses and automated detection in mammographic pictures, underlining the key-focuses and primary contrasts among the utilized systems. The key goal is to bring up the preferences and drawbacks of the different methodologies. Conversely with different surveys which just portray and think about various methodologies subjectively, this audit likewise gives a quantifiable examination.In proposed research use deep learning base network for classification of mammography images . In previous approaches use machine learning base learning. The Main drawback of machine learning is selection of features manualy or by functions but in deep learning automatic feature detect and its vary according to image. The demonstration of seven mass recognition techniques is thought about utilizing two distinctive databases of mammography: an open digitized database and a full-field (local) advanced digitized database. The outcomes are given as far as Free reaction Receiver Operating Characteristic (FROC) and Receiver Operating Characteristic (ROC) examination.

Keyword: Computer aided design, Convolutional neural networks, Deep learning, Mammography. References: 10. Abdelhafiz, Dina, Clifford Yang, Reda Ammar, and Sheida Nabavi. "Deep convolutional neural networks for mammography: advances, challenges and applications." BMC bioinformatics 20, no. 11 (2019): 281. 11. Ribli, Dezső, Anna Horváth, Zsuzsa Unger, Péter Pollner, and István Csabai. "Detecting and classifying lesions in mammograms 33. with deep learning." Scientific reports 8, no. 1 (2018): 4165. 12. Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, et al."A survey on deep learning in medical image analysis". 2017. arXivpreprint arXiv:170205747. 200-209 13. Lee JG, Jun S, Cho YW, Lee H, Kim GB, Seo JB, et al. Deep Learning in Medical Imaging: General Overview. Korean J Radiol. 2017;4 (18):570–84. 14. Wang, Juan, Huanjun Ding, Fatemeh Azamian Bidgoli, Brian Zhou, Carlos Iribarren, Sabee Molloi, and Pierre Baldi. "Detecting cardiovascular disease from mammograms with deep learning." IEEE transactions on medical imaging 36, no. 5 (2017): 1172- 1181. 15. Dhungel, Neeraj, Gustavo Carneiro, and Andrew P. Bradley. "Fully automated classification of mammograms using deep residual neural networks." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 310-314. IEEE, 2017. 16. Lotter, William, Greg Sorensen, and David Cox. "A multi-scale CNN and curriculum learning strategy for mammogram classification." In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, pp. 169- 177. Springer, Cham, 2017. 17. Kooi, Thijs, Bram van Ginneken, Nico Karssemeijer, and Ard den Heeten. "Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network." Medical physics 44, no. 3 (2017): 1017-1027. 18. Ahn, Chul Kyun, Changyong Heo, Heongmin Jin, and Jong Hyo Kim. "A novel deep learning-based approach to high accuracy breast density estimation in digital mammography." In Medical Imaging 2017: Computer-Aided Diagnosis, vol. 10134, p. 101342O. International Society for Optics and Photonics, 2017. 19. Yi, Darvin, Rebecca Lynn Sawyer, David Cohn III, Jared Dunnmon, Carson Lam, Xuerong Xiao, and Daniel Rubin. "Optimizing and visualizing deep learning for benign/malignant classification in breast tumors." arXiv preprint arXiv:1705.06362 (2017). 20. Ben-Ari, Rami, Ayelet Akselrod-Ballin, Leonid Karlinsky, and Sharbell Hashoul. "Domain specific convolutional neural nets for detection of architectural distortion in mammograms." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 552-556. IEEE, 2017. 21. Jiang, Fan, Hui Liu, Shaode Yu, and Yaoqin Xie. "Breast mass lesion classification in mammograms by transfer learning." In Proceedings of the 5th international conference on bioinformatics and computational biology, pp. 59-62. ACM, 2017. 22. Dhungel, Neeraj, Gustavo Carneiro, and Andrew P. Bradley. "Fully automated classification of mammograms using deep residual neural networks." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 310-314. IEEE, 2017. 23. Abbas, Qaisar. "DeepCAD: A computer-aided diagnosis system for mammographic masses using deep invariant features." Computers 5, no. 4 (2016): 28. 24. Mammography [Online]. Available at: https://medlineplus.gov/mammography.html[Accessed on 01-07-2019] 25. Kooi, Thijs, Albert Gubern-Merida, Jan-Jurre Mordang, Ritse Mann, Ruud Pijnappel, Klaas Schuur, Ard den Heeten, and Nico Karssemeijer. "A comparison between a deep convolutional neural network and radiologists for classifying regions of interest in mammography." In International Workshop on Breast Imaging, pp. 51-56. Springer, Cham, 2016. 26. Greenspan, Hayit, Bram Van Ginneken, and Ronald M. Summers. "Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique." IEEE Transactions on Medical Imaging 35, no. 5 (2016): 1153-1159. He, K., Zhang, X., Ren, S. & Sun, J. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In Proceedings of the IEEE international conference on computer vision, 1026–1034 (2015). 27. Li, Y., H. Chen, L. Cao, and J. Ma. "A survey of computer-aided detection of breast cancer with mammography." J Health Med Inf 4, no. 7 (2016). 28. Kooi, Thijs, Bram van Ginneken, Nico Karssemeijer, and Ard den Heeten. "Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network." Medical physics 44, no. 3 (2017): 1017-1027. 29. Ahn, Chul Kyun, Changyong Heo, Heongmin Jin, and Jong Hyo Kim. "A novel deep learning-based approach to high accuracy breast density estimation in digital mammography." In Medical Imaging 2017: Computer-Aided Diagnosis, vol. 10134, p. 101342O. International Society for Optics and Photonics, 2017. 30. Yi, Darvin, Rebecca Lynn Sawyer, David Cohn III, Jared Dunnmon, Carson Lam, Xuerong Xiao, and Daniel Rubin. "Optimizing and visualizing deep learning for benign/malignant classification in breast tumors." arXiv preprint arXiv:1705.06362 (2017). 31. Ben-Ari, Rami, Ayelet Akselrod-Ballin, Leonid Karlinsky, and Sharbell Hashoul. "Domain specific convolutional neural nets for detection of architectural distortion in mammograms." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 552-556. IEEE, 2017. 32. Jiang, Fan, Hui Liu, Shaode Yu, and Yaoqin Xie. "Breast mass lesion classification in mammograms by transfer learning." In Proceedings of the 5th international conference on bioinformatics and computational biology, pp. 59-62. ACM, 2017. 33. Dhungel, Neeraj, Gustavo Carneiro, and Andrew P. Bradley. "Fully automated classification of mammograms using deep residual neural networks." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 310-314. IEEE, 2017. 34. Abbas, Qaisar. "DeepCAD: A computer-aided diagnosis system for mammographic masses using deep invariant features." Computers 5, no. 4 (2016): 28. 35. Kallenberg, Michiel, Kersten Petersen, Mads Nielsen, Andrew Y. Ng, Pengfei Diao, Christian Igel, Celine M. Vachon et al. "Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring." IEEE transactions on medical imaging 35, no. 5 (2016): 1322-1331. 36. He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. "Deep residual learning for image recognition." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770-778. 2016. 37. Sun, Wenqing, Tzu-Liang Bill Tseng, Bin Zheng, and Wei Qian. "A preliminary study on breast cancer risk analysis using deep neural network." In International Workshop on Breast Imaging, pp. 385-391. Springer, Cham, 2016. 38. Gallego-Posada, J., D. A. Montoya-Zapata, and O. L. Quintero-Montoya. "Detection and diagnosis of breast tumors using deep convolutional neural networks." Medical Physics43 (2016): 3705-3705. 39. Zhu, Wentao, Xiang Xiang, Trac D. Tran, and Xiaohui Xie. "Adversarial deep structural networks for mammographic mass segmentation." arXiv preprint arXiv:1612.05970 (2016). 40. Arevalo, John, Fabio A. González, Raúl Ramos-Pollán, Jose L. Oliveira, and Miguel Angel Guevara Lopez. "Representation learning for mammography mass lesion classification with convolutional neural networks." Computer methods and programs in biomedicine 127 (2016): 248-257. 41. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2015. CA Cancer J. Clin. 2015, 65, 5–29. 42. Lehman, Constance D., Robert D. Wellman, Diana SM Buist, Karla Kerlikowske, Anna NA Tosteson, and Diana L. Miglioretti. "Diagnostic accuracy of digital screening mammography with and without computer-aided detection." JAMA internal medicine 175, no. 11 (2015): 1828-1837. 43. Faster, R. "Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren [J]." Kaiming He, Ross Girshick, and Jian Sun. 44. Carneiro, Gustavo, Jacinto Nascimento, and Andrew P. Bradley. "Unregistered multiview mammogram analysis with pre-trained deep learning models." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 652- 660. Springer, Cham, 2015. 45. American Cancer Society. Breast Cancer Facts & Figures; American Cancer Society, Inc.: Atlanta, GA, USA, 2015. 46. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521 (7553):436–44. 47. Fonseca, Pablo, Julio Mendoza, Jacques Wainer, Jose Ferrer, Joseph Pinto, Jorge Guerrero, and Benjamin Castaneda. "Automatic breast density classification using a convolutional neural network architecture search procedure." In Medical Imaging 2015: Computer-Aided Diagnosis, vol. 9414, p. 941428. International Society for Optics and Photonics, 2015. 48. Carneiro, Gustavo, Jacinto Nascimento, and Andrew P. Bradley. "Unregistered multiview mammogram analysis with pre-trained deep learning models." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 652- 660. Springer, Cham, 2015. 49. Szegedy, Christian, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. "Going deeper with convolutions." In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1-9. 2015. 50. Faster, R. "Towards Real-Time Object Detection with Region Proposal Networks Shaoqing Ren [J]." Kaiming He, Ross Girshick, and Jian Sun. 51. Simonyan, Karen, and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556 (2014). 52. Zeiler, Matthew D., and Rob Fergus. "Visualizing and understanding convolutional networks." In European conference on computer vision, pp. 818-833. Springer, Cham, 2014. 53. Simonyan, Karen, and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556 (2014). 54. DREAM. The digital mammography dream challenge. [Online]. Available at: https://www.synapse.org/Digital_Mammography_DREAM_challenge. [Assessed on 02-07-2019] 55. Hologic. Understanding ImageChecker® CAD 10.0 User Guide – MAN-03682 Rev002 (2017). 56. Hupse, Rianne, Maurice Samulski, Marc Lobbes, Ard Den Heeten, Mechli W. Imhof-Tas, David Beijerinck, Ruud Pijnappel, Carla Boetes, and Nico Karssemeijer. "Standalone computer-aided detection compared to radiologists’ performance for the detection of mammographic masses." European radiology 23, no. 1 (2013): 93-100. 57. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." In Advances in neural information processing systems, pp. 1097-1105. 2012. 58. Moreira, Inês C., Igor Amaral, Inês Domingues, António Cardoso, Maria Joao Cardoso, and Jaime S. Cardoso. "Inbreast: toward a full-field digital mammographic database." Academic radiology 19, no. 2 (2012): 236-248. 59. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." In Advances in neural information processing systems, pp. 1097-1105. 2012. 60. Lopez, MA Guevara, N. Posada, Daniel C. Moura, Raúl Ramos Pollán, José M. Franco Valiente, César Suárez Ortega, M. Solar et al. "BCDR: a breast cancer digital repository." In 15th International conference on experimental mechanics. 2012. 61. Jamieson, Andrew R., Karen Drukker, and Maryellen L. Giger. "Breast image feature learning with adaptive deconvolutional networks." In Medical Imaging 2012: Computer-Aided Diagnosis, vol. 8315, p. 831506. International Society for Optics and Photonics, 2012. 62. Hubbard, Rebecca A., Karla Kerlikowske, Chris I. Flowers, Bonnie C. Yankaskas, Weiwei Zhu, and Diana L. Miglioretti. "Cumulative probability of false-positive recall or biopsy recommendation after 10 years of screening mammography: a cohort study." Annals of internal medicine 155, no. 8 (2011): 481-492. 63. Fenton, Joshua J., Linn Abraham, Stephen H. Taplin, Berta M. Geller, Patricia A. Carney, Carl D’Orsi, Joann G. Elmore, William E. Barlow, and Breast Cancer Surveillance Consortium. "Effectiveness of computer-aided detection in community mammography practice." Journal of the National Cancer institute 103, no. 15 (2011): 1152-1161. 64. Eurostat. Health Statistics: Atlas on Mortality in the European Union; Office for Official Publications of the European Union: Luxembourg, 2009. 65. Hupse, Rianne, and Nico Karssemeijer. "Use of normal tissue context in computer-aided detection of masses in mammograms." IEEE Transactions on Medical Imaging 28, no. 12 (2009): 2033-2041. 66. Sadaf, Arifa, Pavel Crystal, Anabel Scaranelo, and Thomas Helbich. "Performance of computer-aided detection applied to full- field digital mammography in detection of breast cancers." European journal of radiology 77, no. 3 (2011): 457-461. 67. Gilbert, Fiona J., Susan M. Astley, Maureen GC Gillan, Olorunsola F. Agbaje, Matthew G. Wallis, Jonathan James, Caroline RM Boggis, and Stephen W. Duffy. "Single reading with computer-aided detection for screening mammography." New England Journal of Medicine 359, no. 16 (2008): 1675-1684. 68. Oliveira, Júlia EE, Mark O. Gueld, Arnaldo de A. Araújo, Bastian Ott, and Thomas M. Deserno. "Toward a standard reference database for computer-aided mammography." In Medical Imaging 2008: Computer-Aided Diagnosis, vol. 6915, p. 69151Y. International Society for Optics and Photonics, 2008. 69. R. Gonzalez, R. Woods, Digital Image Processing, 3rd edition, Addison-WesleyLongman Publishing, 2008. Authors: G. Uppili Srinivasan, V. Anandavel

Paper Title: Impact of Foreign Direct Investment in Indian Economic Development Abstract: Foreign direct investment (FDI) is always shows good impact in the growth of Indian economy and Foreign Direct Investment is the wonderful weapon device in the hands of Government of India. Foreign Direct Investment (FDI) plays vital role in an Indian economy. The new economic policy of liberalization, privatization and globalization pointed out in 1991 induced the policy of foreign direct investment. Hence the foreign direct investment is an inevitable one in our economy. FDI plays a multifaceted role in the overall development of any economy. FDI is often preferred over Foreign Institutional Investments (FII) as it considered to be the most beneficial form of foreign investment in an economy. FDI plays a multifaceted role in the complete development of any economy. It provides a new source for capital, can lead to technological up gradation, skill enhancement and allocate efficiency effects. While FDI is forecast to create clear impact on the economy, it has also contributed in certain adverse impact on Indian economy during the past few years. The present study is organized to study the correlation and investigate the impact of FDI on Indian economy. The flow of FDI for the past 15 years was taken for study (2003-2018). The consequences were studied by testing the correlation with the country’s GDP and Stock Market Indices. Sensex and Nifty were calculated as the authenticated representative of Indian Stock Market. The study concludes that flow of FDI into the country plays 34. a dominant role in deciding the stock market movements.

210-213 Keyword: FDI, Indian Economic Development, Sensex, Nifty References: 1. Anitha,R.(2012)” Foreign direct investment and economic growth in India”, International Journal of Marketing, Financial Services & Management Research;Vol.1(8),pp108-125. 2. Chaturvedi, I. (2011),” Role of FDI in Economic Development of India: Sectoral Analysis”, International Conference on Technology & Business. 3. Goel,S., Kumar.P. and Rao,S.(2013),” Trends and Patterns of FDI in India and its economic Growth”, Asian Journal of Multidimensional Research, Vol. 2(3), pp 6-22. 4. Government of India, Economic Survey 2003-04. New Delhi: Ministry of Finance. 5. Government of India. Annual Report 2007-08. New Delhi: Ministry of Commerce. 6. Government of India. Economic Survey 2003-08. New Delhi: Ministry of Finance. Website http://indiabudget.nic.in/es2012- 13/estat1.pdf (accessed on 22/01/2018) 7. Narayanamurthy, V. K., Perumal S. and Rao, K.C.S.(2010),” Determinants of FDI in BRICS Countries: A panel analysis”, Int. Journal of Business Science and Applied Management, Vol. 5(3), 8. Parashar,S.(2015),” Factors affecting FDI inflow in China and India”, University of Alberta Research Experience. 9. Saini, N. and Singhania, M. (2017), “Determinants of FDI in developed and developing countries: a quantitative analysis using GMM”, Journal of Economic Studies, Vol. 45 No. 2, pp. 348-382. 10. Singh, J., Chadha, S. and Sharma. A. (2014),” Role of Foreign Direct Investment in India: An Analytical Study”, International Journal of Engineering and Science, Vol. 1(50), 34-42. Authors: A. Muthusamy, V. Ganesh

Paper Title: Foreign Direct Investment on Export of Leather and Leather Products in India Abstract: Globalization brought the foreign direct investment which often made in developing countries and open economic countries like India. It offers an adept workforce and yield flourishing prospects for the investor. A foreign investment prospers domestic markets and induces to get into global markets as well as to enhance and experience the international trade exposure. FDI also introduces more substantial benefits like inventive products, technology, job opportunity, expansion of trade and helps to build FOREX reserve to satisfy the trade deficit. The leather and leather products industry has got inherent potential for FDI inflow. The leather industry in India considered as a major accord to Indian economy, which accounts for 12.9% of the global leather production. Annually produces around 3 billion sq.ft of hides and skins, contributes 9% of the global footwear production annually produces 2257 million pairs and 11% of the world’s goat and sheep population. 35. The leather and leather products industry is providing employment for more than 4 million people. FDI inflow in leather and leather products industry has reached from $51.58 million to $193.7 million during the years 2005 to 214-217 2019. The study examines the export trade performance of leather industry and the impact of FDI inflow in leather industry. This research work will further analyze the relationship between foreign investment and International trade of leather and leather products in India. The findings and interpretation of the study will provide additional inputs in existing policy framework. To testify this argument two way Anova and correlation are used.

Keyword: Leather, Export, Foreign direct investment, International trade. References: 1. 1.Akhtar G.(2013,Feb). ―Inflows of FDI in India: Pre and Post Reform Period.International Journal of Humanities and Social Science Invention. 2(2), pp.1-11. 2. 2.Goel, S., Kumar.P. and Rao,S. (2013, April). ―Trends and Patterns of FDI in India and its Economic Growth‖. Research in Business Economics and Management. 2(4), pp.130-144. 3. Khan, I. (2012, Aug).‖ Impact of Foreign Direct Investment (FDI) On Indian Economy: A Sectoral Analysis‖. International Journal of Research in Commerce, Economics & Management. 2 (8), pp. 171-178. 4. Balasubramanyam, V. N., & Mahambare, V. (2003). Foreign direct investment in India. 5. Chakraborty, C., & Nunnenkamp, P. (2008). Economic reforms, FDI, and economic growth in India: a sector level analysis. World development, 36(7), 1192-1212. 6. Http://en.wikipedia.org/wiki/foreign_direct_investment. 7. https://dipp.gov.in/publications/fdi-statistics/archives 8. https://commerce-app.gov.in/eidb/ecomq.asp?hs=41 Authors: V. A. Anand, J. Pandilakshmi Effect of Foreign Direct Investment (FDI) Strategy on the Performance of Selected Private Sector Paper Title: Banks in India Abstract: In an accelerate changing economic condition, "Foreign Direct Investment" (FDI) has used as the catalyst for development in the most of growing nations including India. The FDI condition in India has experienced a radical change since the monetary changes in 1991. The positive changes can be especially ascribed to the developing arrangement system. The central purpose of the monetary segment changes has been the making of productive and stable budgetary foundations and advancement of the business sectors, particularly the cash and government protections advertise. Indian banks going worldwide and numerous worldwide banks setting up shops in India, the Indian financial framework is set to include into an absolutely new level it will help the financial framework develop in quality going into what's to come. The present investigation was led to look at the effect of outside direct speculation arrangement on efficiency of chose Indian private part banks during fourteen years from 2004-2005 to 2017-2018. The required information were gathered from optional sources like RBI Data-stockroom, Report on Patterns and Progress of Banking in India, IBA Bulletins, Journals, and Online databases. The compiled testimonies were dissected through inferential factual systems like Co-efficient of Correlation, T- distribution test and Analysis of Variance(ANOVA) with the assistance of statistical packages for social sciences(SPSS). The examination inferred that there is a noteworthy relationship among Total Advances to Total Deposits((TA2TD - dependent variable) and FDI, Staff and Expenditure(independent factors). Henceforth, it is prescribed that FDI in banking area ought to guarantee better capitalization and furthermore offer money related dependability in India.

Keyword: “Reserve Bank of India” (RBI), Efficient, Performance, Disbursement, Co-efficient of Correlation, Capitalisation. 36. References: 1. Garg, Richa. (2013). Job of "Foreign Direct Investment"(FDI) in Indian Banking Sector. "Global Journal of Research in Finance & Marketing", 3 (2), 63-68, ISSN 2231-5985, got to from http://euroasiapub.org/wp-content/transfers/2016/09/7-132.pdf on 218-221 15.07.2016. 2. Ghosh, Chinmoy and Phani, B.V. (2004). The Effect of Liberalization of "Foreign Direct Investment" (FDI) Limits on Domestic Stocks: Evidence from the Indian Banking Sector, 1-33, got to from: http://ssrn.com/abstract=546422 on 2.10.2016. 3. Ilgun, Erkan and Coskun, Ali. (2009). "Outside Direct Investments" (FDI) in "Bosnia and Herzegovina": Banking Sector Example. Alatoo Academic Studies, 4(2), 49-67, got to from http://www.academia.Edu/2992826/remote/direct/investtments/in/bosnia/and/Herze g-ovina/banking/segment/model on 3.01.2017. 4. Tsaurai, K. (2014). Banking area advancement and remote direct speculation. A Case of Botswana, got to from https://www.researchgate.net/production/289656705 Banking area improvement and outside direct venture An instance of Botswana on 15.09.2016. 5. Kumari, Anil and Gupta, Surender Kumar. (2012). Effect of FDI on Indian Banking Sector. "Global Journal of Research in Management", Economics and Commerce, 2 (1), 58-72 got to from https://www.scribd.com/archive/270068131/fdi-on-banking - segment effectspdf on 15.09.2016. 6. Laifi, Jihene. (2007). The determinants of remote direct interest in banking part: does provincial joining understandings matter. Creuset college jean Monnet of Saint Etienne (France), 1-18, got to from https://www.gate.cnrs.fr/uneca07/communications% 20pdf/Laifi-Jihene-Rabat - 2007.pdf on 2.01.2017. 7. Malhotra, S. (2018). Essential Components of Foreign Direct Investment. Gotten to from http://www.shareyouressays.com/information/3-essential segments of-remote direct-inves - tment-fdi/112172 as on 16.05.2018. 8. Patil, J. (2014). Execution assessment of Indian FDI and non-FDI banks: A relative examination. Postulation Submitted in the Department of financial aspects, OsmaniaUniversity, Hyderabad. 9. Patil-Dake J. (2017). Efficiency Performance of Indian Banks with FDI Contents. In: Kamaiah B., Shylajan C., Seshaiah S., Aruna M., Mukherjee S. (eds) Current Issues in Economics and Finance. Springer, Singapore. 10. Reddy, M. M. (2016). Effect of FDI on Performance of Select Private Sector Banks in India. Indian diary of Finance, 10 (3), 52- 65, got to from http://www.indian diary of finance.co.in/index.php/IJF/article/see/89024 on 16.08.2016. 11. Sharma, N. K. S. and Krishna, B. S. (2013). Job of FDI in Banking in creating riches to Indian Economy. Worldwide Journal of Advancements in Research and Technology, 2(5), 276-281, got to from http://www.ijoart.org/docs/Role-of-FDI-in-Banking-in- generatingwealth-to-Indian-Economy.pdf on 16.08.2016. 12. http://reports.choiceindia.com/KnowledgeCenter/KC160220124.pdf, on 4.02.20 16. Authors: T. Selvakumar, A. Gunasekaran, G. Vinayagamoorthi

Paper Title: Growth of Foreign Direct Investment in Indian Textile Sector Abstract: Apart from being a critical driver of economic growth, foreign direct investment (FDI) is a 37. major source of non-debt financial resource for the economic development of India. Foreign companies invest in India to take advantage of relatively lower wages, special investment privileges such as tax exemptions, etc. For 222-227 a country where foreign investments are being made, it also means achieving technical know-how and generating employment. The Indian government’s favorable policy regime and robust business environment have ensured that foreign capital keeps flowing into the country. The government has taken many initiatives in recent years such as relaxing FDI norms across sectors such as defence, PSU oil refineries, telecom, power exchanges, and stock exchanges, among others. The proposed paper deals with the structure and growth in FDI in Indian Textiles sector during the post reforms periods in India.

Keyword: FDI, FPI, Textiles, Garments, Inflow, Ministry of Textiles. References: 1. Christine Heumesser ,Erwin Schmid- Trends in foreign direct investment in the agricultural sector of developing and transition countries: a review- University of Natural Resources and Applied Life Sciences, Vienna Department of Economic and Social Science- July 2012 2. Monism Goliath- Assistant Professor, Department of Agricultural and Resource Economics, Oregon State University. Research assistance from Kweiyang Chen is acknowledged. Materials from an earlier study, “Effects of FDI in Developing Countries: The Case of Food and Agriculture,” by C.H. Bulling and M. Goliath served as a basis for some of the following sections 3. www.fao.org 4. www.unctad.org. 5. Trends and impacts of foreign investment in developing country agriculture-FAO-2013. 6. Ping Lin and Kamala Saggy, “Incentives for Foreign Direct Investment under Imitation” Canadian Journal of Economics, Vol.32, No.5, November 1999, p.1276. 7. Bornschier. V., and C. Chase – Dunn, 1985 “Transnational Corporations and underderdevelopment”, Newyork Pracger. 8. Das S (1987), “Externalities and Technology Transfer through Multinational Corporation: A Theoretical Analysis”, Journal of international economics, 123 pp.188 – 206. 9. Froot, Kenneth A and Stein Jeremy C. (1991) “Exchange Rate and Foreign Direct Investment: And imperfect capital market Aapproach “ Quarterly Journal of Economics 106 (4) , 1991, pp.1191 – 1217. 10. Wheeler, D. AND Mody, A. (192), “International Investment Location decision: The case of US firms”, Journal of International Economics, Vol.33, No.1/2, pp.57 – 76. 11. Campa Jose M (1993) Entry by Foreign firm in the US under exchange rate uncertainity”, Review of Economics and Statistics, 75(4): pp. 622 – 624. 12. Tsai, Pan – Long (1994), “Determinants of Foreign Direct Investment and its Impact on Economic Growth”, Journal of Economic Development, 19, pp. 137 – 163. 13. http://texmin.nic.in/fdi-cell 14. https://www.fdi.finance/sectors/textiles-and-garments 15. http://www.textileassociationindia.org Authors: S. Karpagalakshmi, A. Muthusamy

Paper Title: Impact of FDI Inflows on Export and Growth of an Indian Economy Abstract: FDI may be reflected as a resource for developing countries to get capital inflows, access to foreign technology, management skills and marketing networks. India is the world’s highest rising economies and remains a top market for Foreign Direct Investments (FDI). In a globalizing world, export success can serve as much for the competitiveness of a country’s industry and lead to faster growth. India is the most primary economies globally for foreign investment. It allows FDI of up to 100 percent of the equity shareholding in most sectors under the automatic route. The inflow of FDI into India is projected as able to increase productivity which will ultimately have an impact on the increase in national income in the form of the Gross Domestic Product (GDP) as well as in the form of increased exports. Exports support a country to increase its foreign exchange reserves, and build a strong financial position. FDI is seen as a potent tool of export promotion in the domestic country. This paper examines the most important benefits connected with the inflow of FDI as Export Performance, and GDP Growth. To study the dynamics of co-integration between FDI Inflow, GDP growth, and Export Performance, evidence is taken from country-specific level like Indian Economy where the period of study is from 2009-10 to2018-19. Hence, the paper studies the economic scenario of India for its FDI inflows, 38. GDP growth rate, and its export performance. This paper attempt to analyze a positive correlation between FDI Inflow, GDP growth, and Export Performance by framing Simple Regression and Multiple Regression Models 228-232 erected on the hypotheses formulated and validating the results of the models based on ANOVA and Durbin- Watson test.

Keyword: FDI, export, Global Economics, Inflow, ANOVA. References: [1] Sharma K (2000) Export Growth in India- has FDI Played a Role? Yale University Discussion Paper No.816. [2] Ramkishen S. Rajen, S. M. (2009). 'How can India Increase its Attractiveness as a Destination for FDI?' In R. S. Rajen Monetary Investment and Trade Issues in India (pp. 127-151). New-Delhi: Oxford. [3] Joseph TJ and Reddy N (2009) FDI Spillovers and Export Performance of Indian Manufacturing Firms after Liberalisation Economic and Political Weekly. 44( 52):97-105 [4] Atif, M. A.-u.-R. (2012). "Impacts of Imports, Exports, and Foreign Direct Investment on the Gross Domestic Product Growth". International Conference of Business Management. Lahore. [5] Sultan, Z. A. (2013). A causal relationship between FDI inflows and export: The case of India. Journal of Economics and Sustainable Development, 4(2), 1–9 [6] Sahoo, K., &Sethi, N. (2017). Impact of foreign capital on economic development in India: An econometric investigation. Global Business Review, 18(3), 766–780 Authors: A. Muthusamy, Aravindaraj. K

Paper Title: Foreign Direct Investment (FDI) and its Impact on Hotel and Tourism Services in India 39. Abstract: The Foreign Direct Investment (FDI) is required for a country, when domestic capital is inadequate for the purpose of enhancing economic growth. India needs substantial foreign capital inflows to 233-237 achieve the economic growth and development. In an emerging economy like India, the Hotel & Tourism services contributes significantly to the country’s GDP as well as Foreign Exchange Earnings (FEE). India has significant potential to become a preferred tourist destination globally. Its rich and diverse cultural heritage, abundant natural resources and biodiversity provides numerous tourist attractions. Since 1991, Foreign Direct Investment (FDI) to the developing countries has been the leading source of external financing and has become a key component of national development strategies for almost all the developing countries in the world. Foreign Direct Investment up to 100 percent is allowed in Hotel and Tourism sector under Automatic route. The contribution of FDI in Hotel & Tourism sector is stimulating the economic growth or not, this knowledge thrust of researcher creates the interest in conducting this study. In this paper, an attempt is made to review the concept of FDI and its impact on the Hotel & Tourism sector in India. The study is based on only secondary sources of data and it covers for the period of recent ten years. The study shows a positive correlation between Foreign Direct Investment Equity inflows and Foreign Exchange Earnings (FEE) and Gross Domestic Product (GDP) of Hotel & Tourism sector in India during the period of the study.

Keyword: Foreign Direct Investment, Economic Growth, Host Countries, Home Countries, Foreign Exchange Earnings, Gross Domestic Product. References: 1. Secretariat for Industrial Assistance, (SIA): Various Newsletters, Annual Issue, Ministry of Commerce and Industry, Government of India, New Delhi. 2. India Tourism Statistics, Annual reports,(From 2009 to 2019), Ministry of Tourism, Government of India, New Delhi. 3. Padmasree. K and Bharathi Devi (2011), “The performance of the Indian Tourism Industry in the era of globalization –a conventional study”, African Journal of Hospitality, Tourism and Leisure Vol. 1 (4), pp. 1-9. 4. Akhilesh Sharma et.al (2012), “FDI: An Instrument of Economic Growth & Development in Tourism Industry”, International Journal of Scientific and Research Publications, Volume 2, Issue 10, pp. 1-6. 5. Rupal Patel (2012), “India’s Tourism Industry – Progress and Emerging Issues”, Arth Prabhand: A Journal of Economics and Management, Vol.1 Issue 5, pp. 1-10. 6. Niranjana. C and Vimya K.P (2013), “Foreign Direct Investment: An Exploration of Opportunities in Indian Tourism”, International Journal of Management and Development Studies, Volume No. 2 (2013), Issue No. 12, pp.27-33. 7. www.dipp.gov.in 8. www.tourism.gov.in Authors: Irina Reshetnikova, Olga Yanina, Larisa Semenova, Lesya Bozhko, Oleg Veselitsky Problem of Assessing the Investment Attractiveness of Risk Projects for Developing Artificial Paper Title: Intelligence Abstract: The article discusses the problem of assessing the investment attractiveness of risk projects for developing artificial intelligence, the methods of such assessment and their features. It is shown that due to the lack of relevant statistical, financial, operational information, the models and methods of investment valuation are, for the most part, subjective. The use of only one model or method of assessing investment attractiveness in the field of the development of artificial intelligence projects is insufficient, while the complex use without taking into account systemic aspects is likewise not sufficiently substantiated. To solve the existing problem, it is proposed to comprehensively use the available capabilities of the method of functional cost analysis (FSA), the essence of which is that the development project is decomposed into separate functions, and the necessary resources are measured and fixed for each function. Analysis of the functions of the object and the costs of the implementation of the functions makes it possible to identify the most acceptable variant of the object from the position of its functional content. At the same time, the article considers the possibility of using the functional-cost analysis method in the evaluation, the essence of which is that the development project is decomposed into separate functions, and for each function, all necessary resources are measured and fixed. An analysis of the object’s functions and their costs will help to identify the most economical version of a risky investment project from its functional content. It is reasonably noted that the main resources to support and promote the development of innovative projects are 40. venture companies that invest considerable funds both at the initial stages and at the stages of development and expansion of projects. The amount of financial resources coming from business angels, crowdfunding and 238-243 business accelerators is much smaller and goes mainly to the initial stages of project implementation.

Keyword: artificial intelligence development project, investment attractiveness, valuation methods, functional-cost analysis, venture financing, business-angels, crowdfunding. References: 1. Alamsyah, A., & Nugroho, T. B. A. (2018). Predictive modelling for startup and investor relationship based on crowdfunding platform data. Journal of Physics: Conference Series, 971, 012002. 2. Ayukawa, M. (2012). Applying the Theory of the Firm to Examine a Technology Startup at the Investment Stage. Technology Innovation Management Review, 2(5), 23-27. 3. Berkus, D. (2012). The Berkus Method: Valuing an Early Stage Investment. http://berkonomics .com/?p=1214 4. Berkus, D. (2016). After 20 years: Updating the Berkus Method of valuation. https://berkonomics. com/?p=2752 5. Cantamessa, M., Gatteschi, V., Perboli, G., & Rosano, M. (2018). Startups’ Roads to Failure. Sustainability, 10(7), 2346. 6. Carson, S. A. (2018). Identifying Critical Risk Factors in the Decision-making Process of Angel Investors and Venture Capitalists: A Delphi Research Study. Electronic Theses and Dissertations. Paper 3360. https://dc.etsu.edu/etd/3360 7. Damodaran, A. (2009). Valuing young, start-up and growth companies: estimation issues and valuation challenges. https://ssrn.com/abstract=1418687 or http://dx.doi.org/10.2139/ssrn.1418687 8. de Mello, F. L., & de Souza, S. A. (2019). Psychotherapy and Artificial Intelligence: A Proposal for Alignment. Frontiers in psychology, 10, 263. 9. Ederman, L. F., Manalova, T. S., & Brush, C. G. (2017). Angel Investing: A Literature Review. Foundations and Trends R in Entrepreneurship, 13(4-5), 265–439. 10. Kirshina, N.R., & Lebedinsky, V.I. (2019). Features of evaluating the cost of startups. Materials for the round table "Non- standard standards: is it possible to determine the value of IP?" Library LABRATE.RU (Network resource). http://bit.ly/2XOJWnB 11. Köhn, A. (2017). The determinants of startup valuation in the venture capital context: a systematic review and avenues for future research. Management Review Quarterly, 68. 12. Kunitsyna, N. N., & Khalyavskaya, T. V. (2016). Methods for assessing the pre-investment value of startups that have not reached the level of profitability. Scientific and Technical Journal of St. Petersburg State Polytechnical University, 4 (246), 292- 301 13. Loktionova, Yu.N. (2017) Financial analysis of investment projects: basic directions and methods of carrying out. Social policy and sociology, 16(2(121), 47-55. 14. Loktionova, Yu.N., & Yanina, O.N. (2019) Approaches to measuring innovation in the economy. Social policy and sociology, 18(1 (130), 32-41 15. Mannar, K. (2019). The ROI of AI. https://www.accenture.com/us-en/insights/artificial-intelligence/roi-artificial-intelligence 16. Mezentsev, Yu.A., & Preobrazhenskaya, T.V. (2003). Functional cost analysis. Tools and models: textbook. Allowance. Novosibirsk: NSTU, 122. 17. OECD (2018). Private Equity Investment in Artificial Intelligence. OECD Going Digital Policy Note, OECD, Paris, www.oecd.org/going-digital/ai/private-equity-investment-in-artificial-intelligence.pdf 18. Payne, B. (2011). Valuations 101: The Dave Berkus Method. http://blog.gust.com/248/ 19. Payne, B. (2011b). Valuations 101: The Venture Capital Method. http://blog.gust.com/startup-valuations-101-the-venture-capital- method/ 20. Payne, B. (2011c). Valuations 101: The Risk Factor Summation Method. http://blog.gust.com/valuations-101-the-risk-factor- summation-method/ 21. Payne, B. (2017). Scorecard Valuation Methodology: Establishing the Valuation of Pre-revenue, Start-up Companies. http://etd.lib.metu.edu.tr/upload/12621330/index.pdf 22. Saint-Pierre, J. (2017). A Simple Test of the Value of Artificial Intelligence (AI) for Investments. https://ssrn.com/abstract=3071052 or http://dx.doi.org/10.2139/ssrn.3071052 23. Zhong, H., Liu, C., Zhong, J., & Xiong, H. (2018). Which startup to invest in: a personalized portfolio strategy. Annals of operations research, 263(1-2), 339-360. Authors: Shobha Bhardwaj, Ajay Jain, Vinay Kumar

Paper Title: Diffusion of Strategic Practices in HRM and their Impact Over Productivity of Small Firms Abstract: With the change in time, the practices of HR also get changed to support the businesses in the highly competitive market like by incorporating the technology in daily workplace activities. Although the incorporation of new techniques and methodologies in HR was very limited in past few decades but after analyzing the benefits in every area, HR department incorporate these into their daily functioning like the use of SHRM, HRIS. HRIS system is an application of technology where big data can be managed, retrieved easily by replacing the heavy filing paper work and gives error free result. In this paper after the deep review of literature, the researcher selected six human factors based on infusion of technology in HR practices and their impact over the productivity. This study is conducted to put some light over the technology benefits in small firms, which are lacking in the previous studies. Maximization of profit, high production, good quality and customer satisfaction are the current requirements of every company and to fulfill these requirements technology plays a vital role. Analysis of the information collected from the sample in this research study clearly revealed that requirements of a company could be fulfilled by choosing some selective HR practices along with the strategic point of view for optimization of productivity. PLS-SEM software is used to calculate the statistical value of variables in precise form to analyze this new combination of technology and HR. So, this paper applying quantitative structural analysis method of PLS software to find out the rationale of the study by supporting the concept of right selection of innovative information system in HR practices based on human factor leads to great result.

41. Keyword: SHRM, HR Practice, productivity, human factor, HRIS, PLS-SEM. References: 244-251 1. Ichniowski, C., Shaw, K., & Prennushi, G. (1995). The effects of Human resource management practices on productivity. National Bureau of Economic Research . 2. Ulrich, D. (1997). Measuring Human Resources: An Overview of Practice and a Prescription for results. Human Resource Management , 36 (3). 3. Casse, C., Nadin, S., Gray, M., & Clegg, C. (2002). Exploring human resource management practices in small and medium sized enterprises. Personnel Review , 31. 4. Wright, P. M., Gardner, T. M., & Lisa, M. M. (2003). The Impact of HR practices on the performance of business units. Human Resource Management Journal , 13 (3), 21-36. 5. Singh, K. (2004). Impact of HR practices on the perceived firm performance in India. Asian Pacific Journal of Human Resource , 42 (3). 6. Bell, V. (2006). Productivity—The human factor. Retrieved from http://www.thefabricator.com: https://www.thefabricator.com/article/shopmanagement/productivity-the-human-factor 7. Florkowski, G. W., & Lujan, M. R. (2006). The diffusion of human-resource information-technology innovations in US and non US firms. Personnel Review . 8. Singh, R. K. (2009). Welfare Measures and its impact Manpower Productivity. Retrieved from http://www.indianmba.com/Faculty_Column/FC992/fc992.html 9. Singh, S., Darwish, T. K., Costa, A. C., & Anderson, N. R. (2012, May). Measuring HRM and organisational performance: Concepts, issues, and framework. Management Decision . 10. Abdulai, I. A., & Shafiwu, A. B. (2014). Participatory Decision Making and Employee Productivity. A Case Study of Community Banks in the Upper East region of Ghana. Business and Economics Journal . 11. Stephanie. (2014, December). Statistics How To. Retrieved from www.statisticshowto.datasciencecentral.com: https://www.statisticshowto.datasciencecentral.com/cronbachs-alpha-spss/ 12. Sander, T., & Lee, T. P. (2014). SmartPLS for the Human Resource Field to Evaluate a Model. New Challenges of Economic and Business Development -2014. 13. Onyije, O. C. (2015). Effect of Performance Appraisal on Employee Productivity in a Nigerian University. JOURNAL OF ECONOMICS AND BUSINESS RESEARCH , 21 (2). 14. Katou , A. A., & Budhwar , P. (2015). Human resource management and organisational productivity: A systems approach based empirical analysis. Journal of Organizational Effectiveness: People and Performance , 2 (3). 15. Gamage, A. S. (2015). The Role of HRM in Improving Labour Productivity: An Analysis of Manufacturing SMEs in Japan. Sri Lankan Journal of Human Resource Management , 5. 16. Flores, H. (2017). How HRIS Can Harness Maximum Productivity – Yes, It can be done! Retrieved from http://www.paydayonesource.com/: http://www.paydayonesource.com/hris-can-harness-maximum-productivity-yes-can-done/ 17. Stone , D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The In fl uence of Technology on the Future of Human Resource Management. Human Resource Management Review . 18. Ahmed, H. M. (2016). Technology in Performance Appraisal System with Specific Reference to Group of Companies HSA and its Partners in the Republic of Yemen. IBMRD's Journal of Management & Research , 5. 19. Sarangi, D., & Nayak, D. (2016). Employee Engagement and Its Impact on Organizational Success – A Study in Manufacturing Company, India. Journal of Business and Management , 18 (4), 52-57. 20. Sea, N. (2017, October). RiseSmart. Retrieved from www.risesmart.com: https://www.risesmart.com/blog/5-ways-hr-can- improve-employee-productivity 21. Mayhew, R. (2018). Functions & Practices of Human Resource Management. Retrieved from smallbusiness.chron.com: https://smallbusiness.chron.com/functions-practices-human-resource-management-59787.html 22. Pandey, A. (2018). Role of Artificial Intelligence in HR. Retrieved from pcquest.com: https://www.pcquest.com/role-artificial- intelligence-hr/ 23. Bun, M. J., & Huberts, L. C. (2018). The Impact of Higher Fixed Pay and Lower Bonuses on Productivity. Journal of Labor Research , 39 (1), 1-21. 24. Bhardwaj, S., & Jain, A. (2019). Role of Human Resource Management in Small Scale Electrical industries of Delhi NCR Regions. Journal fo Advance Research in Dynamical & Control Systems , 1145-1158. Authors: A. M. M. Mustafa

Paper Title: Macroeconomic Impact of Foreign Direct Investment in Sri Lanka Abstract: This research is aimed at tracing the impact of Foreign Direct Investment (FDI) in promoting macroeconomic variables such as gross domestic production, industrial production, total domestic investment, exports, imports, Board of Investment approved exports, Board of Investment approved imports and Board of Investment approved employments by using the time series annual data for 1978 - 2018 in Sri Lanka. Multiple Regression Analysis was used to estimate the impact of FDI on selected macroeconomic variables. Estimation method was Ordinary Least Squares. EViews 10 software were used for data analysis. The empirical evidence shows that there is a statistically significant positive impact of FDI on selected macroeconomic variables except in the case of imports. However, this study further reveals that the actual impact on macroeconomic variables can be felt after certain time lag. But the impact on total domestic investment was realized immediately. Further, this research has identified various problems faced in attracting FDI including ideal sector identification and the appropriate recommendations have been presented in order to realize the major benefits from FDI inflow into the country.

Keyword: FDI; Gross Domestic Production; Industrial Production; Total Domestic Investment; Exports; Imports; Employments. References: 1. Agosin, M.R. & R. Mayer. 2000. Foreign Investment in Developing Countries: Does it Crowd in Domestic Investment?, Santiago: Department of Economics, University of Chile. Available at :http://ideas.repec.org/p/unc/dispap/146.html 2. Agrawal, P. 2000. Economic Impact of Foreign Direct Investment in South Asia. India: Indra Gandhi Institute of Development Research. Available at :http://rru.worldbank.org/Documents/PapersLinks/1111.pdf 42. 3. Andersen, P.S. and P.Hainaut. 1998. Foreign Direct Investment and Employment in the Industrial Countries. Switzerland: Monetary and Economic Department, Basle. Available at :http://www.bis.org/publ/work61.htm 4. Athukorala, P. 1995. “Foreign direct investment and manufacturing for export in a new exporting country: The case of Sri 252-259 Lanka.” World Economy.18:543-564. 5. Athukorala, P.P.A.W. 2003. The Impact of Foreign Direct Investment for Economic Growth: A Case Study in Sri Lanka, 9th International conference on Sri Lanka studies, Matara. Available at :www.freewebs.com/slageconr/9thicslsflpprs/fullp092.pdf 6. Balasubramanyam, V.N., M. Salisu & D. Sapsford.1996. Foreign Direct Investment and Economic Growth in EP and IS Countries. The Economic Journal, 106 (Jan): 92-105. 7. Borensztein,E., J. De Gregorio & J.W. Lee. 1998. How does Foreign Direct Investment affect Economic Growth?. Journal of International Economics. 45: 115-135. 8. Chakraborty, C. & P. Basu. 2003. Foreign Direct Investment and growth in India: A cointegration approach, Routledge. Available at : http://www.tandf.co.uk/journals 9. Fernando, R. 1996. Foreign Direct Investment in Sri Lanka: direction for policy. Sri Lanka Journal of Management. 1(4): 312- 340. 10. Fu, X. and V.N. Balasubramanyam. Exports, Foreign Direct Investment and Employment: The Case of China. FED Working Papers Series No. FE20050035. Available at :www.fed.org.cn 11. Institute of Policy Studies of Sri Lanka. 2000. Foreign Direct Investment and Economic Integration in the SAARC Region. Colombo. Available at :http://www.saneinetwork.net/pdf/SANEI_I/SAARCregion.PDF 12. Jahur, M.S. and F.K. Rabbanee. 2002. Foreign Direct Investment and its Impact on Employment Generation for the Youth- A Study of Chittagong Export Processing Zone of Bangladesh. Riyadh, KSA: Paper for presented in the 9th International Conference on Muslim Youth and Globalization. 13. Jansen, K. 1995. The Macroeconomic Effects of Direct Foreign Investment : The Case of Thailand. World Development.23(2): 193210. Available at :http://ideas.repec.org/a/eee/wdevel/v23y1995i2p193-210.html 14. Khan, H. & K.B. Leng. 1997. Foreign Direct Investment, Export and Economic Growth in the three Dragon: Evidence from co integration and causality test. The Singapore Economic Review. 42(2): 40-60. 15. Kohpaiboon, A. 2000. Foreign Trade Regime and FDI- Growth Nexus: A Case Study of Thailand. Research School of Pacific and Asian Studies. Australian National University. Available at :http://rspas.anu.edu.au/economics/publish/papers/wp2002/wp-econ- 2002-05.pdf 16. Leichenko, M.R. & A.R. Erickson. 1997. Foreign Direct Investment and State Export Performance. Journal of Regional Science.37(2): 307-329 17. Lemi, A. 2004. Foreign Direct Investment, Host Country Productivity and Export: The case of US and Japanese Multinational Affliates. Journal of Economic Development 163 29(1) . Available at :http://jed.econ.cau.ac.kr/newjed/full-text/29- 1/Adugna_Lemi.pdf 18. Nishantha, J.A.T.D. 2000. Liberalization and FDI in a small Developing Country – The Case of Sri Lanka. Available at :http://web.kyoto-inet.or.jp/people/nishan/ronbn/keieiron-engl.htm 19. Shaoo, D. & M. Mathiyazhagan. 2003, Economic Growth in India: Does Foreign Direct Investment Inflow Matter?. The Singapore Economic Review. 48(2): 157-171. 20. Sharma, K. 2000. Export Growth in India: Has FDI Played a Role?, Centre Discussion PaperNo.816. New Haven,Connecticut 06520-8269. Available at : http://www.econ.yale.edu/~egcenter/ 21. Soliman, M. 2003. Foreign Direct Investment and LDCs Exports: Evidence from the MENA Region. American University of Sharjah. Available at : http://www.erf.org.eg/tenthconf/Trade_Background/Soliman.pdf 22. Sun, H. 1998. Macroeconomic Impact of direct Foreign investment in China: 1979-1996.UK: Blackwell Publishers Ltd. 23. Sun, H. 2001. Foreign Direct Investment and Export Performance in China. Journal of Regional Scienc. 4l(2): 317-336 24. Sugandh,M.(2018). Foreign Direct Investment An Analysis of Indian Economy.International Journal of Trend in Scientific Research and Development. Volume 2, Issue 6 25. Wilamoski, P. & S. Tinkler. 1999. The Trade Balance Effect of US Foreign Direct Investment in Mexico. Atlantic Economic Journal. 27(1): 24-37 26. Wilhelms, S.K.S. 1998. Foreign Direct Investment and its Determinants in Emerging Economies. African Economic Policy Paper. Available at : http://www.eagerproject.com/discussion9.shtml Authors: A. M. M. Mustafa Impact of Tourism and Foreign Direct Investment on Gross Domestic Production: Forecasts for the Paper Title: Case of Sri Lanka Abstract: Tourism industry is found as the second rapidly growing business after the information and communication technology in the global arena. A number of economies are triumphant in marketing their tourism destinations along with the generation of a considerable amount of foreign currency earnings due to the origination of tourism industrial sector. After economic reforms initiated in Sri Lanka in year 1977 onwards, the governments have thereafter implemented a number of various fruitful policies and development projects so as to promote the tourism industrial sector in pursuit of economic growth and development. This study investigates the Contribution of Tourism and Foreign Direct Investment (FDI) to Gross Domestic Production (GDP) in Sri Lanka. The software such as EViews 10, Excel, and Minitab are used to analyze the data. To achieve its goal, the nonparametric approaches such Nearest Neighbor Fit, Kernal Fit, and Confidence Ellipse to find the relationship were used in this study. Error Correction Mechanism, Co-Integration, and Analysis of Causality are the econometric techniques used to find the relationship. This study employs annual data for the period from 1977 to 2017and forecasted the data from 2018 to 2022 in order to find out the future potential of the contribution. The co-integration regression result revealed that the relationship between Tourism Receipts and Gross Domestic Production has been positively and statistically significant. The Foreign Direct Investment and Gross Domestic Production have been positively and statistically significant. However short run effect impact multiplier of Tourism Receipts is statistically not significant but Foreign Direct Investment statistically significant. The results of Granger Causality tests, in the variables are one-way causal relationships. According 43. to the results of this study suggests that it is vital for Sri Lankan government to implement some of the marketing efforts to develop the tourism industrial sectors as one of the best destinations in Asian region. 260-267

Keyword: Tourism; Gross Domestic Production; Foreign Direct Investment; Co-integration; Causality; Forecasting. References: 1. Central Bank of Sri Lanka. (2018).Economics and Social Statistics of Sri Lanka. Colombo: Central Bank of Sri Lanka. 2. Chai Li,C.,Hasimah,N.I.,Mazlina,B.T. (2013). The effect of tourism receipts on economic growth. Proceeding of the Global Conference on Business, Economics and Social Sciences. Available online at http://www.worldresearchconference.com/gbsr 2013/eproceeding/YG%20DAH%20PDFkan/164.pdf 3. David,J.T.,& Richard,S.(2010).Tourism and Development in the Developing World. New York: Routledge. 4. Dragouni,M., George,F., & N. Antonakakis, (2013). Time-Varying Interdependencies of Tourism and Economic Growth: Evidence from European Countries, FIW Working Paper Available on line at http://www.fiw.ac.at/fileadmin/Documents/Publikationen/Working_Paper/N_128DragouniFilisAntonakakis.pdf 5. Georgantopoulos,G,A. (2013).Tourism expansion and economic development: Var/Vecm analysis and forecast the case of india. Asian Economic and Financial Review, 2013, 3(4):464-482. 6. Jayathilake,P.M.B. (2013). Tourism and economic growth in sri lanka: evidence from cointegration and causality analysis. International Journal of Business, Economics and Law, 2(2). 7. Nahla, A. (2015).Tourism and Economic Growth in South Africa: An ARDL Bounds Testing Approach .Asian Journal of Multidisciplinary Studies, Volume 3, Issue 11. 8. Srinivasan,P., Santhosh Kumar P. K.,&Ganesh,L.(2012). Tourism and Economic Growth in Sri Lanka: An ARDL Bound Testing Approach. The Romanian Economic Journal, XV(45), pp. 211-226. 9. Tosun, C. (2001). Challenges of sustainable tourism development in the developing world:The case of Turkey. Tourism Management, 22, 289-303. Authors: Namita Swain, Ajay Jain

Paper Title: Status of Financial Inclusion in India, Persisting Challenges and Way Forward Abstract: Financial inclusion is a critical pillar of development and has been a major policy thrust for the 44. Indian Government over the decades. However some of the major policy impetuses were received the last one decade resulting in some of the biggest policy interventions for financial inclusion in the world. Pradhan Mantri Jan Dhan Yojana, Direct Benefit Transfer under Digital Banking and Aadhar has been significant interventions 268-272 in this area. Despite these and several areas policy measures as well as technological innovations adopted by RBI and banking sector, even though encouraging, is much less than satisfactory when it comes to their extent and penetration when it comes to usage by marginalized sections, people in the informal economy and those living in remote areas. The significant barriers for achieving inclusive growth are Financial illiteracy, lack of convenience, technology issues and viability. This study aims at integrating some of the results of existing literature on financial inclusion and role played by Government, RBI and the other banks in promoting inclusive growth. It also attempts to analyze the key persisting challenges on the demand as well as supply aspects of financial inclusion. On the basis of its findings the paper proposes a set of preliminary recommendations to strengthen and support financial inclusion in India. It has been observed that the financial sector has still not been able to design appropriate products in a sustainable way that can address the needs of the poor, those who are in the informal economy or to identify key gaps in a huge and diverse country like India where social security is very low for most of population. Technology obviously is playing and still needs to play a far greater role in addressing some of these challenges which the traditional banking models have failed to address.

Keyword: Financial Inclusion; Inclusive Growth; RBI ; Banks; Policy; Technology; Jan Dhan Yojana; Direct Benefit Transfer. References: 1. Ananth S; Creating an Enabling Digital Ecosystem: Issues and Challenges in Financial Inclusion; IIM Bangalore, Working paper no 508, April 2016 2. Alpana Vats,“Promoting Financial Inclusion: An Analysis of the Role of Banks”, Indian Journal of Social development, Vol.7, No.1, June 2007, Pp.107-126 3. Das A, Dutta T; Analyzing Data of Pradhan Mantri Jan Dhan Yojana ; IIT Bombay, Technical Report; MAY 2017 4. Gunthupalli S; Exploring the impacts of “Pradhan Mantri Jan-Dhan Yojana in urban Areas with reference to Mumbai; IOSR Journal of Economics and Finance (IOSR-JEF) 2321-5925, PP 82-86 5. Harpreet Kaur and Kawal Nain Singh; “Pradhan Mantri Jan Dhan Yojana (PMJDY): A Leap towards Financial Inclusion in India”; International Journal of Emerging Research in management and Technology; 2015 6. Kumar V, Singh D; “PMJDY: A Conceptual Analysis and Inclusive Financing” International Journal of Innovative Social Science & Humanities Research, Volume- II, Issue-I, March 2015 7. Madav V, Kapadia S; Financial Literacy and Financial Inclusion in India; International Journal of Pure and Applied Mathematics; Volume 118 No. 18 2018, 1133-1150 8. Raihanath, Pavithran KB; Role Of Commercial Banks In The Financial Inclusion Programme; Journal of Business Management & Social Sciences Research (JBM&SSR)Volume 3, No.5, May 2014 9. Rajasekaran N; Including the Excluded: The Scenario of Financial Inclusion in India; IOSR Journal of Business and Management (IOSR-JBM), Volume 20, Issue 2. Ver. VII (February. 2018), PP 64-69 10. Ravikumar T, Assessing Role of Banking Sector in Financial Inclusion Process in India; http://www.microfinancegateway.org/sites/default/files/mfg-en-paper-assessing-role-of-banking-sector-in-financial-inclusion- process-in-india-may-2013.pdf accessed on 9th August 2019 11. Naik G, Singh C; inancial Inclusion after PMJDY: A Case Study of Gubbi Taluk, Tumkur; Working Paper no 568, IIM Bangalore; March 2018 12. Sami S, Iqbal B; Role of Banks in Financial Inclusion in India, Contaduría y Administración Volume 62, Issue 2, April–June 2017, Pages 644-656 13. Satpathy I, Patnaik BCM; Pradhan Mantri Jan Dhan Yojna (Pmjdy) – A New Direction for Mainstreaming the Financially Excluded; International Journal of Management; Volume 6, Issue 2, February (2015), pp. 31-42 14. Sabri T, Ananth S; Challenges to Financial Inclusion in India: The Case of Andhra Pradesh; Economic and Political Weekly; Vol. 48, Issue No. 07, 16 Feb, 2013 15. Singh R; Saving Mobilization and PMJDY in India; EPRA International journal of economic and business review; Vol-4, Issue 1, January 2016, Page 148-156 16. Thorat, U. (2006). Reading on Financial Inclusion, Indian Institute of banking and finance, New Delhi, Taxman Publications Pvt: Ltd, Pp.261-270 17. Subba Rao K.C.K, “Financial inclusion: An Introspection”, Economic Political Weekly, February 3, 2007, Pp.355-360. 18. World Bank; Making it easier to apply for a bank account: A study of the Indian Market; Policy Research Working Paper 8205; September 2017

Authors: Ram Milan, Diwakar Shukla, Kamlesh Kumar Pandey

Paper Title: Community Detection Algorithms for Big Data using Graph Theory Abstract: Community detection is a nowadays research problem in the Big Data era related to huge volume, variety, and velocity of data. Big data defines data where normal processing, storage, retrieval fails and require some advanced tools to solve these types of problem. An important tool in the analysis of complex network is community detection. Community detection or community mining is a technique which is used to find the same type of relations in a particular group. Community detection is also known as Graph Clustering. This paper represents Big data in the form of graphs and detects community via some graph algorithms like METIS, Spectral Partitioning, hierarchical clustering, Markov Clustering, Genetic Algorithm based community detection algorithm, etc. Community detection is widely used in various types of disease detection, drug 45. formation, species clustering. It can be also used in social networking sites to control crimes by detecting community bad peoples. 273-280 Keyword: Community Detection, Big Data, Graph Clustering, Markov Clustering References: 1. Symeon Papadopoulos et al., “ Community Detection in Social Media Performance and application considerations” Data Mining know Disc (2012) DOI 10.1007/s10618-011-0224-z. 2. Van Dongen, S., “Graph Clustering by Flow Simulation “, Ph.D. Thesis, University of Utrecht, The Netherlands. (2000). 3. Daniel A. Spielman et al. , “ Spectral Partitioning Works Planar graphs and finite element meshes”, February 13, 1996. 4. UthayasankarSivarajahet.al.”Critical analysis of big data challenges and analytical methods”, “Journal of Business Research”, August (2010). 5. Ram Milan, Kamlesh Kumar Pandey et al. “ Application of Graph Theory in Big Data in Digital Era”, “ Proceedings of National Conference on Recent Advancement in Computer Science, Mathematics, Physics & Electronics- ISBN-978-81-936440-7-2. 6. DongshengDuanYuhua Li et al., “Community Mining on Dynamic Weighted Directed Graphs”, CNIKM 09, November 6, 2009, Hong Kong, China. 7. Nan Du, Bin Wu et al. “ Community Detection in Large scale Social Networks”, Joint 9th WEBKDD and 1st SNA-KDD Workshop ’07 August 12, 2007, San Jose, California, USA. 8. R. Saravanakumar et al., “ A Survey on the concepts and challenges of Big Data Beyond the hype”, (2017). 9. Jaseena K.U. et al. “Issues, Challenges, And Solutions: Big Data Mining”, Computer Science & Information Technology (CS &IT ). 10. Kamlesh Kumar Pandey, Ram Milan et al. “ Mining on Relationship in Big Data era Using Apriori Algorithm”, National Conference on Data Analytics, Machine Learning and Security”, 15-16 February 2018, ISBN 978-93-5291-457-9. 11. M.EJ. Newman, M. Girvan, Finding and evaluating community structure in networks, Phys. Rev. E 69 (2) (2004) 026113. 12. Danon L, Diaz-Guilera et al. “ Comparing community structure identification”, J Stat Mech-Theory E,2005 13. Jure Leskovec, Kevin J. Lang et al. “ Empirical comparison of Algorithms for Network Community Detection Detection “, WWW.2010. 14. [14]. Cuijan Wang Wenzhong Tang, Bo Sun Jing Fang et. Al.,” Review on Community Detection Algorithms in Social Networks”, ISBN 978-1-4673-9088-0 (2015) IEEE. 15. Santo Fortunato. Community Detection in Graphs[j]. Physics reports 2009(3). 16. Danon L, Diaz-Guilera A, Duch J, et al. Comparing Communities structure identification. J Stat Mech- Theory E, 2005. 17. Shangfu Gong, Wanlu Chen, PengtaoJia. Survey on algorithms of community detection[j].Application Research of Computers.2013(11). 18. T. Hastie, R Tibshirani, J.H. Friedman, The Elements of Statistical Learning, Springer, Berlin, Germany,2001. 19. Rosvall, M, Bergstrom, C.T: Maps of Random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences 105(4) (2008) 1118-1123. 20. [20].JIERUI XIE, STEPHEN KELLEY, BOLESLAW K. SZYMANSKI Overlapping Community Detection in Networks: the state of the Art and Comparative Study. ACM Computing Surveys, Vol45, no, 2013. 21. I. Derenyi, G. Palla, T. Vicsek, Clique percolation in random networks, Phys. Rev. Lett. 94(16)(2005)160202. 22. Ahn Y Y, Bagrow J P, Lehmann S. Link communities reveal multiscale complexity in networks[j]. . Nature, 2010, 466(7307):761-764. 23. Gregory S. Finding overlapping communities in networks in networks by label propagation. New Journal of Physics, 2012,12 (10):102018. 24. Clauset A. Finding local community structure in networks [J]. Physical review E, 2005,72(2):026132. 25. Raghavan U N, Albert R, Kumara S. Near linear time algorithm to detect community structure in large scale networks. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2007, 76 ( 3 pt 2): 036106 26. Joyce JiyoungWhang, David F. Gleich, Inderjit S. Dhillon. Overlapping community detection using seed set expansion CIKM’13.2013(2099-2108). 27. Lancichinetti, A, Radicchi, F, Ramasco, J.J. Fortunato, S: finding statistically significantly communities in networks. Plos ONE 6(4) ( April 2011 ) e18961+ 28. https://en.wikipedia.org/wiki/K-means_clustering 29. Steve Gregory,” Finding overlapping communities in networks by the label”, Department of Computer Science, University of Bristol, Bristol BS8 1UB, England. 30. M.E.J Newman,” Fast Algorithm for detecting Community structure in Networks”, arxiv:cond-mat/0309508v1”, 22 September 2003. 31. SerafeimTsironis et al., “ Accurate Spectral Clustering For Community Detection in MapReduce Stanford.edu” 32. Zhao Yang et al. ,” A Comparative Analysis of Community Detection Algorithms on Artificial Networks”, Scientific Reports volume6, Article number: 30750 (2016 33. Xingyi Zhang et al., “ A Fast Overlapping Community Detection Algorithm based on weak cliques for Large scale networks”, “IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, VOL. 4, NO. 4, DECEMBER 2017”. 34. Jun Hua et al., “A New Community Detection Algorithm Based on Adding and Deleting Links”, “ IEEE 2 nd International Conference on Big Data Analysis” ,2017. 35. Mehak Mohammad,” community detection in Social Networks Through Girvan Newman Algorithm” 36. FarnazMoradi,” Improving Community Detection Methods for Network Data Analysis”, Thesis for the Degree of Doctor of Philosophy,(2014). 37. Newman M. “Fast algorithm for detecting community structure in networks” ,” Physical review E 2004,69(6):066133.doi:10.1103/PhysREvE.69.066133. 38. Newman M. “Analysis of weighted networks” Physical review E 2004,70 (5):056131. Doi:10.1103/PhysRevE.70.056131. 39. Newman M. “Modularity and community structure in networks “, “ Proceeding of the National Academy of Sciences 2006,103(23):8577-8582. Doi10.1073/pnas.0601602103. 40. Clauset A, Newman ME, “ Moore C. Finding community structure in very large networks. “ Physical review E 2004, 70(6):066111. Doi10.1103/PhysRevE.70.066111. 41. Blondel VD, Guillaume JL et al. “ Fast unfolding of communities in large networks”, “ Journal of statistical mechanics: Theory and experiment 2008. Doi:10.1088/1742-5468/2008/10/P10008. 42. Guimera R, Sales-Pardo M, Amaral LAN, “ Modularity from fluctuations in random graphs and complex networks” Physical review E 2004, 70(2):025101. Doi:10.1103/PhysRevE.70.025101. 43. Zhou Z et al. “ Community detection based on improved modularity”, “ Pattern recognition 2012:638-64. Doi: 10.1007/978-3- 642-33506-8_78. 44. Duch J et al. , “ Community detection in complex networks using external optimization”, “ Physical review E 2005, 72(2):027104. Doi:10.1103/PhyRevE.72.027104. Authors: Sujata R. Kadu, Balaji G. Hogade, Imdad Rizvi

Paper Title: Detection of Tree Crown from Satellite Imagery using Object Based Image Examination Abstract: Detection and delineation of individual tree mainly depends on high resolution satellite images or LiDAR data. Urban green structure, specially urban trees plays a key role in enhancing the life of people. Now a day’s more than half of population is leaving in cities and urban areas. Methods to quantify and monitor trees are not efficient. The traditional methods for forest survey and ground survey are complex because of 46. changes occurs in urban environment. The objective of this research is to extract vegetation using colour based and decision tree method, which can be further sub-classify to obtain area under tree canopy. The results 281-285 obtained through Object-Based Image Analysis (OBIA) method are also compared with existing Gaussian Mixture Model (GMM) method. The overall accuracy achieved thereby is 93.85% using Decision tree- multiresolution segmentation and 93.31% using Decision tree-GMM method.

Keyword: object based image analysis, decision tree, colour based segmentation, Gaussian mixture model, multi resolution segmentation. References: 1. Corina Iovan , Didier Boldo, Matthieu Cord 'Detection, Characterization, and Modeling Vegetation in Urban Areas From High- Resolution Aerial Imagery' IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2008 2. Global risk report 2019, “World economic forum, retrieve 25th March 2019. 3. Walton, J. T. , Nowak, D. J., and Greenfield, E. J. 2008. Assessing urban forest canopy cover using airborne or satellite imagery. Arboriculutre and Urban Forestry, Vol. 34, No. 6, pp. 334–340. 4. Saikat Basu, Sangram Ganguly, Ramakrishna R. Nemani, Supratik Mukhopadhyay, Gong Zhang, Cristina Milesi et al., “A semi automated probabilistic framework for tree-cover delineation from 1- m naip imagery using a high performance computing architecture,” IEEE Transactions on Geosciences and Remote Sensing. 53, no 10, 5690–5708 (2018). 5. Imdad Ali Rizvi and B. Krishna Mohan, “Object-oriented method for automatic extraction of road from high resolution satellite images.,” Iranian Journal of Earth Sciences. 2, 55–62 (2010). 6. L. Monika Moskal, Diane M. Styers and Meghan Halabisky, “Monitoring urban tree cover using object-based image analysis and public domain remotely sensed data.,” Remote Sens. 3, 2243–2262 (2011). 7. Sarika Yadav, Imdad Rizvi, Shailaja Kadam, “Comparative study of object based image analysis on high resolution satellite images for urban development”, International Journal of Technical Research and Applications Special Issue 31, PP. 105- 110,September 2015. 8. Tang Yinggan, Liu Dong and Guan Xinping, “Multi-resolution image segmentation based on Gaussian mixture model.,” Journal of Systems Engineering and Electronics. 17, no 4, 870–874 (2006). 9. Tang Yinggan, Liu Dong and Guan Xinping, “Multi-resolution image segmentation based on Gaussian mixture model.,” Journal of Systems Engineering and Electronics. 17, no 4, 870–874 (2006). 10. Baatz, M. and Schäpe, A. “Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation”. In: XII Angewandte Geographische Informationsverarbeitung, Wichmann-Verlag, Heidelberg, 2000 11. Happ, P. N., Ferreira, R. S., Bentes, C., Costa, G. A .O. P., Feitosa, R. Q., Multiresolution Segmentation: a Parallel Approach for High Resolution Image Segmentation in Multicore Architectures. In: 3rd International Conference on Geographic Object-Based Image Analysis, 2010, Ghent, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Enshede: ITC, 2010. v.XXXVII. 12. M. Saeed,W. C. Karl, T. Q. Nguyen, H. R. Rabiee, “A new multiresolution algorithm for image segmentation.,” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. 5, 2753–2756 (1998). 13. Benz U.C., Hofmann P., Willhauc G ; Lingenfelder I., Heynen M ,” Multi –resolution,object –oriented fuszzy analysis of remote sensing data for GIS-ready information”,ISPRSJ.Photogramm 2004,58,239-258. Authors: Mohammed Matar, Aldhaheri, Mohammed Nussari Impact of Transformational Leadership (Idealized Influence, Inspirational Motivation, Intellectual Paper Title: Stimulation, Individualized Consideration) on Employee Performance Abstract: This study employs structural equations modeling via PLS to analyze the 732 valid questionnaires in order to assess the proposed model that is based on the transformational leadership characteristics to identify its effect on the performance of employees in the government sector in Dubai. The main independent constructs in the model are idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. The dependent construct is employee performance. The study will describe relations among the various constructs. Our work has improved our insight in the importance of transformational leadership. Results indicated that all four independent variables significantly predicted employee performance with a various percentage. The proposed model explained 37% of the variance in employee performance.

Keyword: Transformational Leadership; Employee Performance; Dubai. References: 1. S. Aydogdu & B. Asikgil, (2011). The Effect of Transformational Leadership Behavior on Organizational Culture : An Application in Pharmaceutical Industry. International Review of Management and Marketing, 1(4), pp. 65–73. 2. J. A. Aragón-Correa, V. J. García-Morales & E. Cordón-Pozo, (2007). Leadership and organizational learning’s role on innovation and performance: Lessons from Spain. Industrial Marketing Management, 36(3), pp. 349–359. https://doi.org/10.1016/j.indmarman.2005.09.006 3. M. J. Donate & J. D. Sánchez de Pablo, (2015). The role of knowledge-oriented leadership in knowledge management practices 47. and innovation. Journal of Business Research, 68(2), pp. 360–370. https://doi.org/10.1016/j.jbusres.2014.06.022 4. C. Andriopoulos & M. W. Lewis (2010). Managing Innovation Paradoxes: Ambidexterity Lessons from Leading Product Design Companies. Long Range Planning, 43(1), pp. 104–122. https://doi.org/10.1016/j.lrp.2009.08.003 286-292 5. M. Afacan Fındıklı, U. Yozgat & Y. Rofcanin (2015). Examining Organizational Innovation and Knowledge Management Capacity The Central Role of Strategic Human Resources Practices (SHRPs). Procedia - Social and Behavioral Sciences, 181, pp. 377–387. https://doi.org/10.1016/j.sbspro.2015.04.900 6. M. Heffernan, B. Harney, K. Cafferkey & T. Dundon, (2016). Exploring the HRM-performance relationship: the role of creativity climate and strategy. Employee Relations, 38(3), pp. 438–462. https://doi.org/10.1108/ER-06-2015-0110 7. M. Siddique, (2012). Knowledge management initiatives in the United Arab Emirates: a baseline study. Journal of Knowledge Management, 16(5), pp. 702–723. https://doi.org/10.1108/13673271211262763 8. M. Mathias, (2017). Public leadership in the United Arab Emirates: towards a research agenda. International Journal of Public Sector Management, 30(2), pp. 154–169. https://doi.org/10.1108/IJPSM-09-2016-0151 9. A. Turkyilmaz, G. Akman, C. Özkan & Z. Pastuszak, (2011). Empirical Study of Public Sector Employee Loyalty and Satisfaction. Industrial Management and Data Systems, 111. 10. C. Gavrea, L. Ilies & R. Stegerean, (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300 11. P. J. Richard, T. Devinney, G. Yip & G. Johnson, (2009). Measuring Organizational Performance: Towards Methodological Best Practice. Journal of Management Vol. 35. https://doi.org/10.1177/0149206308330560 12. Ngadiman, A. Eliyana & D. Ratmawati, (2013). Influence of Transformational Leadership and Organization Climate to the Work Satisfaction , Organizational Commitment and Organizational Citizenship Behavior on the Educational Personnel of. European Journal of Business and Management, 5(10), pp. 97–115. 13. M. L. Voon, L. May-Chiun, K. S. Ngui & N. Ayob, (2011). The Influence of Leadership Styles on Employees ’ Job Satisfaction in Public Sector Organizations in Malaysia. International Journal of Business, Management and Social Sciences, 2(1), pp. 24–32. 14. G. Wang, I.-S. Oh, S. H. Courtright & A. E. Colbert, (2011). Transformational Leadership and Performance Across Criteria and Levels: A Meta-Analytic Review of 25 Years of Research. Group & Organization Management, 36(2), pp. 223–270. https://doi.org/10.1177/1059601111401017. 15. J. Rowold & W. Schlotz, (2009). Transformational and transactional leadership and followers’ chronic stress. Leadership Review, 9(1), pp. 35–48. 16. A. H. Aldholay, O. Isaac, Z. Abdullah, I. Alrajawy & M. Nusari (2018). The Role of Compatibility as A Moderating Variable in The Information System Success Model : The Context of Online Learning Usage. International Journal of Management and Human Science (IJMHS), 2(1), pp. 9–15. 17. B. C. Lee, J. O. Yoon & I. Lee, (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), pp. 1320–1329. https://doi.org/10.1016/j.compedu.2009.06.014 18. R. W. Brislin (1970). Back-Translation for Cross-Cultural Research. Journal of Cross-Cultural Psychology Vol. 1. Brislin. https://doi.org/10.1177/135910457000100301 19. B. G. Tabachnick, & L. S. Fidell, (2012). Using Multivariate Statistics (6th ed.). Pearson. 20. R. V Krejcie & D. W. Morgan, (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 21. C. M. Ringle, S. Wende & J.-M. Becker (2015). SmartPLS 3. Bonningstedt: SmartPLS. 22. J. C. Anderson & D. W. Gerbing, (1988). Structural Equation Modeling in Practice : A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), pp. 411–423. 23. J. F. Hair, G. T. M. Hult, C. Ringle & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM) (2nd ed.). London: Thousand Oaks: SAGE. 24. (R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 25. J. F. Hair, W. C. Black, B. J. Babin & R. E. Anderson, (2010). Multivariate Data Analysis (7th ed.). New Jersey: Pearson. 26. J. F. Hair, G. T. M. Hult, C. Ringle & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM) (2nd ed.). London: Thousand Oaks: SAGE. 27. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 28. W. W. Chin, (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 29. Z. Awang, (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 30. J. Cohen (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). London: Routledge. Authors: Rashed Alneyadi, Mohammed Nusari, Ali Ameen, Amiya Bhaumik A Better Understanding of Relationship between Job Satisfaction and Affective Organizational Paper Title: Commitment Abstract: The public sector in UAE is the focus of this paper. Applying the concept of job satisfaction to examine its effect on employees’ affective organizational commitment. The data was collected from 452 officers from 7 sectors in the ministry of interior in UAE and analysed using structural equation modelling via SmartPLS 3.0. The result showed that job satisfaction has a positive impact on affective organizational commitment. The proposed model explained 11.4% of the variance in employees’ affective organizational commitment.

Keyword: Job satisfaction; affective organizational commitment (AOC). References: 48. 1. O. Isaac, Z. Abdullah, T. Ramayah, & M. Mutahar Ahmed, (2017). Examining the Relationship between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 293-296 2. O. Isaac, Z. Abdullah, T. Ramayah, & A. M. Mutahar, (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), pp. 210–241. 3. O. Isaac, Z. Abdullah, T. Ramayah, A. M. Mutahar & I. Alrajawy, (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), pp. 205–223. 4. R. V Krejcie & D. W. Morgan, (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 5. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 6. C. E. Werts, R. L. Linn & K. G. Jöreskog, (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 7. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. Authors: Mansoor Mulla, Ali Ameen, Ibrahim Alrajawy, Amiya Bhaumik Influence of Management Quality and Technology Developments on Islamic Banking Performance Paper Title: in UAE Abstract: A country’s economic growth is said to be based on the finance sector and its performance, which is considered the most prominent factors in boosting an economy. Also, the economic stability and growth greatly depends on the stability and performance of its finance and banking sector. The study aims at examining the effect of quality management and development of technology in determining Islamic banking performance in the context of UAE. The process of evaluation was carried out using questionnaire survey data obtained from 158 valid responses from Customer Service Offers, Bank Managers, Front Line Officers, and Assistant Manager 49. in the Islamic banks in the UAE. Structural Equation Modelling (SEM) was done using PLS3.0 software for determining the importance levels of associations within the tested factors. The goodness of fit of the proposed model showed 41% of variance in the Islamic banking performance. The multivariate analysis revealed that 297-303 quality management has an impact on the Islamic banking performance as compared to technology development, which offers insights into the strategies of Islamic banking sector.

Keyword: Management quality; technology developments; Islamic banking; performance; UAE. References: 1. K. Siraj & S. Pillai (2012). Comparative Study on Performance of Islamic Banks and Conventional Banks in GCC Region. Journal of Applied Finance and Banking. Vol. 2. 2. S. A. Srairi (2009). Cost and profit efficiency of conventional and Islamic banks in GCC countries. Journal of Productivity Analysis, Vol. 34(1), pp. 45–62. 3. S. Haron & N. W. Azmi (2009). ISLAMIC FINANCE BANKING SYSTEM. McGraw-Hill. 4. A. S. Alkhateri, A. E. Abuelhassan, G. S. A. Khalifa, M. Nusari & A. Ameen (2018). The Impact of perceived supervisor support on employees turnover intention : The Mediating role of job satisfaction and affective organizational commitment. International Business Management, Vol. 12(7), pp. 477–492. 5. A. Ameen, H. Almari, & O. Isaac (2019). Determining Underlying Factors that Influence Online Social Network Usage Among Public Sector Employees in the UAE. In Fathey M. Faisal Saeed, Nadhmi Gazem (Ed.), Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing (Recent Tre, Vol. 843, pp. 945–954). Springer Nature Switzerland AG: Springer International Publishing. 6. A. Belouafi & A. Chachi (2014). Islamic Finance in the United Kingdom: Factors Behind its Development and Growth. Islamic Economic Studies. Vol. 22. https://doi.org/10.12816/0004130 7. J. Bley & K. Kuehn (2004). Conventional versus Islamic finance: Student knowledge and perception in the United Arab Emirates. International Journal of Islamic Financial Services. Vol. 5. 8. Q. A. Al-Maamari, R.-N.Kassim, V. Raju, A. Al-Tahitah, A. Ameen, M. Abdulrab, M. Abdulrab (2018). Factors Affecting Individual Readiness for Change: A Conceptual Framework. International Journal of Management and Human Science, Vol. 2(1), pp. 13–18. 9. N. Lwin, A. Ameen & M. Nusari (2019). Mobile Banking Adoption among Customers within Private Commercial Banking Sector in Yangon, Myanmar. International Journal of Management and Human Science (IJMHS), Vol. 3(2), pp. 44–59. 10. D. Cogan (2008). Corporate Governance and Climate Change: The Banking Sector. 11. A. Ameen, H. Almari & O. Isaac (2018). Determining Underlying Factors that Influence Online Social Network Usage among Public Sector Employees in the UAE. In B. A. Saeed F., Gazem N., Mohammed F. (Ed.), 3rd international conference on reliable information and communication technology 2018 (IRICT 2018), Bangi-Putrajaya, Malaysia (3rd ed., Vol. 843, pp. 945–954). Cham: Springer, Cham. 12. Gulf News. (2018). Evolution of technology in the banking sector. 13. S. Sassi & M. Goaied (2013). Financial development, ICT diffusion and economic growth: Lessons from MENA region. Telecommunications Policy, Vol. 37(4–5), pp. 252–261. https://doi.org/10.1016/j.telpol.2012.12.004 14. A. Ameen & K. Ahmad (2011). The Role of Finance Information Systems in anti financial corruptions: A theoretical review. In 11 International Conference on Research and Innovation in Information Systems (ICRIIS’11 (pp. 267–272). Ieee. https://doi.org/10.1109/ICRIIS.2011.6125725 15. A. Ameen & K. Ahmad (2012). Towards Harnessing Financial Information Systems in Reducing Corruption : A Review of Strategies. Australian Journal of Basic and Applied Sciences, Vol. 6(8), pp. 500–509. 16. A. Ameen & K. Ahmad (2013a). A Conceptual Framework of Financial Information Systems to reduce corruption. Journal of Theoretical and Applied Information Technology, Vol. 54(1), pp. 59–72. 17. A. Ameen & K. Ahmad (2013b). Proposing Strategy for Utilizing Financial Information Systems in Reducing Corruption. In 3rd International Conference on Research and Innovation in Information Systems – 2013 (ICRIIS’13) (Vol. 2013, pp. 75–80). 18. A. Ameen & K. Ahmad (2014). A Systematic Strategy for Harnessing Financial Information Systems in Fighting Corruption Electronically. In Knowledge Management International Conference (KMICe) 2014, 12 – 15 August 2014, Malaysia (pp. 12–15). Retrieved from http://www.kmice.cms.net.my/ 19. D. Simandan (2018). Iterative lagged asymmetric responses in strategic management and long-range planning. Time & Society, 0961463X17752652. https://doi.org/10.1177/0961463X17752652 20. J. Kehinde, Akomolafe, O. Oni E. Bosede & A. Mark (2015). Public Debt and Private Investment in Nigeria. American Journal of Economics (Vol. 2015). https://doi.org/10.5923/j.economics.20150505.10 21. W. Al-Ali, A. Ameen, O. Issac, M. Nusari & Ibrhim Alrajawi. (2018). Investigate the Influence of Underlying Happiness Factors on the Job Performance on the Oil and Gas Industry in UAE. International Journal of Management and Human Science (IJMHS), Vol. 2(4), pp. 32. 22. F. Al-Obthani, A. Ameen, M. Nusari & I. Alrajawy (2018). Proposing SMART-Government Model : Theoretical Framework. International Journal of Management and Human Science (IJMHS), Vol. 2(2), pp. 27–38. 23. R. Al-Shamsi, A. Ameen, O. Isaac, A. H. Al-Shibami & G. Sayed Khalifa, (2018). The Impact of Innovation and Smart Government on Happiness: Proposing Conceptual Framework. International Journal of Management and Human Science (IJMHS), Vol. 2(2), pp. 10–26. 24. A. Haddad, A. Ameen & M. Mukred (2018). The Impact of Intention of Use on the Success of Big Data Adoption Via Organization Readiness Factor. International Journal of Management and Human Science (IJMHS), Vol. 2(1), pp. 43–51. 25. A. Soyibo & F. Adekanye (1992). Financial system regulation, deregulation and savings mobilization in Nigeria. In AERC research paper;11. Nairobi: African Economic Research Consortium. 26. P. Molyneux & J. Thornton (1992). Determinants of European Bank Profitability: A Note. Journal of Banking & Finance. Vol. 16. https://doi.org/10.1016/0378-4266(92)90065-8 27. A. L. Webster (1997). The impact of technological change on bank performance. Journal of Economics and Finance, Vol. 21(3), pp. 41–47. 28. W. S. Frame & L. J. White (2009). Technological Change, Financial Innovation, and Diffusion in Banking. Working Paper Series. 29. A. N. Berger & R. DeYoung (2006). Technological Progress and the Geographic Expansion of the Banking Industry. Journal of Money, Credit and Banking, Vol. 38(6), pp. 1483–1513. 30. S. K. dangolani (2011). The Impact of Information Technology in Banking System (A Case Study in Bank Keshavarzi IRAN). Procedia - Social and Behavioral Sciences, Vol. 30, pp. 13–16. https://doi.org/https://doi.org/10.1016/j.sbspro.2011.10.003 31. F. Campanella, M. Peruta & M. Del Giudice (2015). The Effects of Technological Innovation on the Banking Sector. Journal of the Knowledge Economy Vol. 8. https://doi.org/10.1007/s13132-015-0326-8 32. I. Warde (2000). Islamic finance in the global economy. Edinburgh University Press. 33. W. N. MUCHIRA (2013). RELATIONSHIP BETWEEN STRATEGY IMPLEMENTATION AND PERFORMANCE IN COMMERCIAL BANKS IN KENYA. UNIVERSITY OF NAIROBI. 34. M. Cihak & H. Hesse (2010). Islamic Banks and Financial Stability: An Empirical Analysis. IMF Working Papers. Vol. 38. https://doi.org/10.1007/s10693-010-0089-0 35. F. Sufian (2007). The efficiency of Islamic banking industry in Malaysia. Humanomics: The International Journal of Systems and Ethics Vol. 23. https://doi.org/10.1108/08288660710779399 36. F. Sufian & M. A. N. M. Noor (2009). The determinants of Islamic banks’ efficiency changes: Empirical evidence from the MENA and Asian banking sectors. International Journal of Islamic and Middle Eastern Finance and Management, Vol. 2(2), pp. 120–138. https://doi.org/10.1108/17538390910965149 37. H. A. Khrawish (2011). Determinants of Commercial Banks Performance: Evidence from Jordan. International Research Journal of Finance and Economics. Vol. 81. 38. M. Safiullah (2010). Superiority of Conventional Banks & Islamic Banks of Bangladesh: A Comparative Study. International Journal of Economics and Finance. Vol. 2. https://doi.org/10.5539/ijef.v2n3p199 39. A. Samad (2004). Bahrain Commercial Bank’s Performance during 1994-2001. Credit and Financial Management Review. Vol. 10. 40. J. W. Creswell (2003). Research design Qualitative quantitative and mixed methods approaches. Research Design Qualitative Quantitative and Mixed Methods Approaches, pp. 3–26. https://doi.org/10.3109/08941939.2012.723954 41. B. M. Byrne (2010). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming (2nd ed.). Routledge. 42. A. H. Aldholay, Z. Abdullah, T. Ramayah, O. Isaac & A. M. Mutahar (2018). Online learning usage and performance among students within public universities in Yemen. Int. J. Services and Standards, Vol. 12(2), pp. 163–179. 43. A. M. Mutahar, N. M. Daud, T. Ramayah, O. Isaac & I. Alrajawy (2017). Examining the intention to use mobile banking services in Yemen: an integrated perspective of technology acceptance model (TAM) with perceived risk and self-efficacy. Asian Journal of Information Technology, Vol. 15(12). 44. C. M. Ringle, S. Wende & J.-M. Becker (2015). SmartPLS 3. Bonningstedt: SmartPLS. 45. J. C. Anderson & D. W. Gerbing (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, Vol. 103(3), pp. 411–423. https://doi.org/10.1037/0033-2909.103.3.411 46. V. R. Kannana & K. C. Tan (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, Vol. 33(2), pp. 153– 162. 47. C. E. Werts, R. L. Linn & K. G. Jöreskog (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, Vol. 34(1), pp. 25–33. 48. R. B. Kline (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 49. D. Gefen, D. Straub & M.-C. Boudreau (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, Vol. 4(1), pp. 1–79. 50. J. F. J. Hair, G. T. M. Hult, C. Ringle & Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM), 46 Long Range Planning § (2014). London: Thousand Oaks: SAGE. https://doi.org/10.1016/j.lrp.2013.01.002 51. J. F. Hair, W. C. Black, B. J. Babin & R. E. Anderson (2010). Multivariate Data Analysis. New Jersey. 52. C. Fornell & D. F. Larcker (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, Vol. 18(1), pp. 39–50. 53. W. W. Chin (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, Vol. 22(1), pp. 7–16. 54. Z. Awang (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 55. J. Cohen (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Editio). LawreAssociatesnce Erlbaum. 56. M. Hilal (2015). Technological Transition of Banks for Development : New Information and Communication Technology and Its Impact on the Banking Sector in Lebanon. International Journal of Economics and Finance, Vol. 7(5), pp. 186–200. https://doi.org/10.5539/ijef.v7n5p186 Authors: Mansoor Mulla, Osama Isaac, Ibrahim Alrajawy, Amiya Bhaumik Impact of Operational Efficiency and Customer Satisfaction on Banking Performance: Empirical Paper Title: Examination on UAE Islamic Banking Abstract: The primary aim of the research is to examine the effect of operational efficiency and customer satisfaction in case of Islamic banking performance in UAE. Proposed model’s evaluation was done using questionnaire survey data that was obtained from 158 valid responses from Customer Service Officers, Bank Managers, Front Line Officers, and Assistant Manager working in the Islamic banks of UAE. Structural Equation Modelling via PLS3.0 software was used to define the crucial levels of associations and interactions between the tested factors. The proposed model, as evidenced by the goodness of fit of the model to the data, explained 39% of the variance in the Islamic banking performance. The multivariate analysis showed a major impact of operational efficiency on Islamic banking performance as compared to the impact on customer satisfaction. The study results gave insights into the strategies of Islamic banking system.

Keyword: Operational efficiency; customer satisfaction; Islamic banking; performance; UAE References: 1. D. Cogan, (2008). Corporate Governance and Climate Change: The Banking Sector. 2. A. S. Alkhateri, A. E. Abuelhassan, G. S. A. Khalifa, M. Nusari & A. Ameen, (2018). The Impact of perceived supervisor support on employees turnover intention : The Mediating role of job satisfaction and affective organizational commitment. International Business Management, 12(7), pp. 477–492. 3. A. Ameen, H. Almari & O. Isaac, (2019). Determining Underlying Factors that Influence Online Social Network Usage Among 50. Public Sector Employees in the UAE. In Fathey M. Faisal Saeed, Nadhmi Gazem (Ed.), Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing Recent Tre, 843, pp. 945–954. Springer Nature Switzerland AG: Springer International Publishing. 304-309 4. N. Lwin, A. Ameen & M. Nusari, (2019). Mobile Banking Adoption among Customers within Private Commercial Banking Sector in Yangon , Myanmar. International Journal of Management and Human Science (IJMHS), 3(2), pp. 44–59. 5. M. I. Tabash & R. S. Dhankar, (2014). Islamic Finance and Economic Growth : An Empirical Evidence from United Arab Emirates ( UAE ). Journal of Emerging Issues in Economics, Finance and Banking, 3(2), pp. 1069–1085. 6. B. K. Guru, J. Staunton & B. Shanmugam, (2002). Determinants of commercial bank profitability in Malaysia. Journal of Money, Credit, and Banking 17. 7. W. Al-Ali, A. Ameen, O. Issac, M. Nusari & Ibrhim Alrajawi. (2018). Investigate the Influence of Underlying Happiness Factors on the Job Performance on the Oil and Gas Industry in UAE. International Journal of Management and Human Science (IJMHS), 2(4), pp. 32. 8. F. Al-Obthani, A. Ameen, M. Nusari & I. Alrajawy, (2018). Proposing SMART-Government Model : Theoretical Framework. International Journal of Management and Human Science (IJMHS), 2(2), pp. 27–38. 9. R. Al-Shamsi, A. Ameen, O. Isaac, A. H. Al-Shibami & G. Sayed Khalifa, (2018). The Impact of Innovation and Smart Government on Happiness: Proposing Conceptual Framework. International Journal of Management and Human Science (IJMHS), 2(2), pp. 10–26. 10. A. Haddad, A. Ameen, & M. Mukred, (2018). The Impact of Intention of Use on the Success of Big Data Adoption via Organization Readiness Factor. International Journal of Management and Human Science (IJMHS), 2(1), pp. 43–51. 11. B. Guru, B. Shanmugam, N. Alam & J. Perera, (2003). An Evaluation of Internet Banking Sites In Islamic Countries. Journal of Internet Banking and Commerce 8. 12. M. Safiullah, (2010). Superiority of Conventional Banks & Islamic Banks of Bangladesh: A Comparative Study. International Journal of Economics and Finance 2. 13. R. Sensarma, (2006). Are foreign banks always the best? Comparison of state-owned, private and foreign banks in India. Economic Modelling, 23(4), pp. 717–735. 14. J. Williams & N. Nguyen, (2005). Financial liberalisation, crisis, and restructuring: A comparative study of bank performance and bank governance in South East Asia. Journal of Banking & Finance, 29(8), pp. 2119–2154. 15. G. Radmila, V. Dejan & B. Milan, (2014). Market niche for Microfinancing-An evidence from Serbia. In Third International Scientific Conference on employment, education and entrepreneurship. Serbia. 16. P. W. Farris, N. Bendle, P. Pfeifer & D. Reibstein, (2010). Marketing Metrics: The Definitive Guide to Measuring Marketing Performance. Pearson Education. 17. V. Jham & K. M. Khan, (2008). Determinants of performance in retail banking: Perspectives of customer satisfaction and relationship marketing. Singapore Management Review 30. 18. L. Sarigiannidis, E. Keisidou, D. I. Maditinos & E. I. Thalassinos, (2013). Customer satisfaction, loyalty and financial performance: A holistic approach of the Greek banking sector. International Journal of Bank Marketing, 31(4), pp. 259–288. 19. B. O. Ehigie, (2006). Correlates of customer loyalty to their bank: a case study in Nigeria. International Journal of Bank Marketing, 24(7), pp. 494–508. 20. N. Ndubisi, (2006). A structural equation modelling of the antecedents of relationship quality in the Malaysia banking sector. Journal of Financial Services Marketing 11. 21. C. Gavrea, L. Ilies, & R. Stegerean, (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300. 22. W. N. MUCHIRA, (2013). RELATIONSHIP BETWEEN STRATEGY IMPLEMENTATION AND PERFORMANCE IN COMMERCIAL BANKS IN KENYA. UNIVERSITY OF NAIROBI. 23. I. Abu-Jarad, N. Yusof & D. Nikbin, (2010). A review paper on organizational culture and organizational performance. International Journal of Business and Social Science 1. 24. M. Cihak & H. Hesse, (2010). Islamic Banks and Financial Stability: An Empirical Analysis. IMF Working Papers 38. 25. H. A. Khrawish, (2011). Determinants of Commercial Banks Performance: Evidence from Jordan. International Research Journal of Finance and Economics 81. 26. F. Sufian, (2007). The efficiency of Islamic banking industry in Malaysia. Humanomics: The International Journal of Systems and Ethics 23. 27. J. W. Creswell, (2003). Research design Qualitative quantitative and mixed methods approaches. Research Design Qualitative Quantitative and Mixed Methods Approaches, pp. 3–26. 28. B. M. Byrne, (2010). Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming (2nd ed.). Routledge. 29. C. M. Ringle, S. Wende & J.-M. Becker, (2015). SmartPLS 3. Bonningstedt: SmartPLS. 30. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 31. C. E. Werts, R. L. Linn & K. G. Jöreskog, (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 32. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 33. J. F. J. Hair, G. T. M. Hult, C. Ringle & M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM), 46 Long Range Planning § (2014). London: Thousand Oaks: SAGE. 34. J. Cohen, (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Editio). LawreAssociatesnce Erlbaum. 35. UAE Bank Federation. (2015). Role of Banks in the UAE.

36. https://doi.org/https://doi.org/10.1016/j.jbankfin.2005.03.011 Authors: Obeid Alshamsi, Ali Ameen, Mohammed Nusari, Abuelhassan E. Abuelhassan, Amiya Bhumic Towards a Better Understanding of Relationship between Dubai Smart Government Characteristics Paper Title: and Organizational Performance Abstract: The study aims at examining the influence of Dubai smart government characteristics on the governmental organization performance. Online survey was used to collect data for this study, the sample size was determined as 250 users of Dubai smart government services, who are users who got the services from five major strategic or government partners of smart government establishment: Dubai Police, RTA, DEWA, DHA, and Dubai Municipality. PLS (Partial Least Squares) SEM-VB (Structural Equation Modelling-Variance Based) was employed to assess the research model by utilizing the software SmartPLS 3.0. This paper adds to the existing literature of smart government characteristics (Information System Quality, Relationship with Public Agencies, Leadership, Accountability and Transparency, and Productivity) and governmental organization performance (Innovativeness, Efficiency, Collaboration, Communication, and Competition Intensity). The results of this study have the potential to give further insights into Dubai government to improve their organizations performance.

Keyword: Dubai smart government; organizations performance; Dubai; UAE. 51. References: 1. A. M. Mutahar, N. M. Daud, R. Thurasamy, O. Isaac & R. Abdulsalam (2018). The Mediating of Perceived Usefulness and Perceived Ease of Use : The Case of Mobile Banking in Yemen. International Journal of Technology Diffusion, 9(2), pp. 21–40. 310-318 2. A. H. Aldholay, O. Isaac, Z. Abdullah & T. Ramayah (2018). The role of transformational leadership as a mediating variable in DeLone and McLean information system success model : The context of online learning usage in Yemen. Telematics and Informatics, 35(5), pp. 1421–1437. 3. L. Jain, A. Harsh & N. Ichalkaranje, (2015). Transforming e-Government to Smart Government: A South Australian Perspective. In Intelligent Computing, Communication and Devices pp. 9–16. 4. G. Puron-Cid (2015). Smart City: How to Create Public and Economic Value with High Technology in Urban Space. International Journal of E-Planning Research, 4, pp. 74–76. 5. S. Alawadhi, & H. Scholl, (2013). Aspirations and Realizations: The Smart City of Seattle. In Proceedings of the Annual Hawaii International Conference on System Sciences pp. 1695–1703. 6. Smart Dubai Government Establishment. (2017). About Dubai Smart Government. 7. R. Andrews & S.Van de Walle (2013). New Public Management and Citizens’ Perceptions of Local Service Efficiency, Responsiveness, Equity and Effectiveness. Public Management Review Vol. 15. 8. E. Gerrish, (2015). The Impact of Performance Management on Performance in Public Organizations: A Meta-Analysis. Public Administration Review Vol. 76. 9. A. Grosso & G. Van Ryzin (2012). Public Management Reform and Citizen Perceptions of the UK Health System. International Review of Administrative Sciences Vol. 78. 10. U. Hvidman & S. Andersen (2013). The Impact of Performance Management in Public and Private Organizations. Journal of Public Administration Research and Theory Vol. 24. 11. P. Koning & C. Heinrich (2013). Cream-Skimming, Parking and Other Intended and Unintended Effects of High-Powered, Performance-Based Contracts. Journal of Policy Analysis and Management Vol. 32. 12. S. Woolhandler, D. Ariely & D. U. Himmelstein (2012). Why pay for performance may be incompatible with quality improvement. BMJ, 345. 13. R. Giffinger, C. Fertner, H. Kramar, R. Kalasek, N. Milanović & Meijers, E. (2007). Smart cities - Ranking of European medium- sized cities. Vienna University of Technology. 14. F. Al-Obthani, A. Ameen, M. Nusari, & I. Alrajawy (2018). Proposing SMART-Government Model: Theoretical Framework. 1st International Journal of Management and Human Science (IJMHS) Vol. 2. 15. S. Al-Shafi & V. Weerakkody, (2010). Factors affecting e-government adoption in the state of Qatar. In European and Mediterranean Conference on Information Systems 2010 (EMCIS2010) (pp. 1–23). Abu Dhabi, UAE. 16. S. Alawadhi & H. Scholl (2016). Smart Governance: A Cross-Case Analysis of Smart City Initiatives. In 49th Hawaii International Conference on System Sciences (HICSS) pp. 2953–2963. Koloa, HI, USA. 17. R. AlShamsi, A. Ameen & A. A.-. Shibami (2017). The Influence of Smart Government on Happiness: Proposing Framework. In 1st International Conference on Management and Human Science (ICMHS 2017) (p. 2017). Kuala Lumpur, Malaysia. 18. H. Chourabi, T. Nam, S.Walker, J. R. Gil-Garcia, S. Mellouli, K. Nahon, H. Scholl, (2012). Understanding Smart Cities: An Integrative Framework. 45th Hawaii International Conference on System Sciences. 19. W. DeLone & E. R. McLean, (2013). Information Systems Success: The Quest for the Independent Variables AU - Petter, Stacie. Journal of Management Information Systems, 29(4), pp. 7–62. 20. H. Elkadi (2013). Success and failure factors for e-government projects: A case from Egypt. Egyptian Informatics Journal, 14(2), pp. 165–173. 21. D. Al-Ali & A. Ameen, (2018). The Influence of System Quality and Information Quality on User Satisfaction: The Case of Smart Government in UAE. In 2nd International Conference on Management and Human Science (ICMHS 2018), 27-28 November 2018, Kuala Lumpur, Malaysia Vol. 7, pp. 58–74. 22. K. Al-Ali, A. Ameen & I. Alrajawy (2018). The Role of SMART Government on Enhancing Pubic Service Quality: Performance Quality Is a Mediator Factor. In International Conference on Recent Trends in Business and Entrepreneurial Ventures (ICRTBEV2018) (p. 23). 23. S. Albreki & A. Ameen, (2017). The Influence of Quality of Knowledge Management on the Smart Government: Literature Review. In 1st International Conference on Management and Human Science (ICMHS2017) (p. 2017). Kuala Lumpur, Malaysia. 24. N. Odendaal (2003). Information and communication technology and local governance: Understanding the difference between cities in developed and emerging economies. Computers, Environment and Urban Systems Vol. 27. 25. M. do R. M. Bernardo (2017). Smart City Governance: From E-Government to Smart Governance. In Handbook of Research on Entrepreneurial Development and Innovation within Smart Cities pp. 290–326. 26. T. Nam & T. Pardo (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. ACM International Conference Proceeding Series. 27. Smart city. (2018). Driving Forces That Stimulate The Growth Of Smart Cities. 28. R. Škrinjar, V. Bosilj‐Vukšić & M. Indihar‐Štemberger, (2008). The impact of business process orientation on financial and non‐financial performance. Business Process Management Journal, 14(5), pp. 738–754. 29. P. H. Bloch (2011). Product Design and Marketing: Reflections after Fifteen Years. Journal of Product Innovation Management, 28(3), pp. 378–380. 30. N. Lopes (2017). Smart governance: A key factor for smart cities implementation. In IEEE International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 277–282). 31. M. Batey, M. Burd, D. Hughes, I. Moonesar & F. Salem (2018). Creativity and Innovation in the Dubai Government: Exploring Individual, Team and Organisational Factors That Underlie Creativity & Innovation in the Dubai Government. 32. I. Mergel (2013). Social media adoption and resulting tactics in the U.S. federal government. Government Information Quarterly, 30(2), pp. 123–130. 33. J. H. Liu, W.Shi, O. A. Elrahman, (Sam), Ban, X. (Jeff), & Reilly, J. M. (2016). Understanding social media program usage in public transit agencies. International Journal of Transportation Science and Technology, 5(2), pp. 83–92. 34. Khaleej Times. (2016). Over 14 Dubai government entities bag “smart” awards. Authors: Obeid Alshamsi, Ali Ameen, Osama Isaac, Gamal S. A. Khalifa, Amiya Bhumic

Paper Title: Examining the Impact of Dubai Smart Government Characteristics on User Satisfaction Abstract: Information and telecommunication technology (ICT) are today practiced in various public sectors and are considered as a cost-effective and convenient means to encourage openness, transparency, and to reduce corruption. It has also put innovation and ICT more than ever at the heart of smart development. Presently, this phenomenon has also been adopted by governments so as to cope with various problems created by increasing urban populations in their countries. The main objective of this study is to examine the influence of Dubai smart government characteristics on the user satisfaction. Online survey was used to collect data for this study, the sample size was determined as 250 users of Dubai smart government services, who are users who got the services from five major strategic or government partners of smart government establishment: Dubai Police, RTA, DEWA, DHA, and Dubai Municipality. PLS (Partial Least Squares) SEM-VB (Structural Equation Modelling-Variance Based) was employed to assess the research model by utilising the software SmartPLS 3.0. This paper adds to the existing literature of smart government characteristics (Information System Quality, 52. Relationship with Public Agencies, Leadership, Accountability and Transparency, and Productivity) and user satisfaction (Usefulness, Awareness, Service Quality, Trust, and Social Influence). The results of this study have the potential to give further insights into Dubai government to improve their users’ satisfaction. 319-327

Keyword: Dubai smart government; user satisfaction; Dubai; UAE. References: 1. I. M. Hassan, A. A. Mahdi & N. J. Al-Khafaji, (2012). THEORETICAL STUDY TO HIGHLIGHT THE SMART GOVERNMENT COMPONENTS IN 21st CENTURY. International Journal of Computer Science and Mobile Computing, 3(12), pp. 333–347. 2. A. H. Aldholay, Z. Abdullah, T. Ramayah, O. Isaac & A. M. Mutahar (2018). Online learning usage and performance among students within public universities in Yemen. International Journal of Services and Standards, 12(2), pp. 163–178. 3. A. H. Aldholay, O. Isaac, Z. Abdullah & T. Ramayah (2018). The role of transformational leadership as a mediating variable in DeLone and McLean information system success model : The context of online learning usage in Yemen. Telematics and Informatics, 35(5), pp. 1421–1437. 4. Puron-Cid, (2015). Smart City: How to Create Public and Economic Value with High Technology in Urban Space. International Journal of E-Planning Research, 4, pp. 74–76. 5. R. Giffinger, C. Fertner, H. Kramar, R. Kalasek, N. Milanović & E. Meijers, (2007). Smart cities - Ranking of European medium-sized cities. Vienna University of Technology. 6. S. Al-Shafi & V. Weerakkody (2010). Factors affecting e-government adoption in the state of Qatar. In European and Mediterranean Conference on Information Systems 2010 (EMCIS2010) pp. 1–23. Abu Dhabi, UAE. 7. S. Alawadhi & H. Scholl (2016). Smart Governance: A Cross-Case Analysis of Smart City Initiatives. In 49th Hawaii International Conference on System Sciences (HICSS) pp. 2953–2963. Koloa, HI, USA. 8. O. Ashamsi & A. Ameen, (2018). The Impact of Smart Government on The Residents’ Satisfaction in Dubai : The Performance of Dubai Governmental Departments as Mediator Variables. In 2nd International Conference on Management and Human Science (ICMHS 2018), pp. 27-28 November 2018, Kuala Lumpur, Malaysia (p. 2018). 9. H. Chourabi, T. Nam, S. Walker, J. R. Gil-Garcia, S. Mellouli, K. Nahon, … H. Scholl, (2012). Understanding Smart Cities: An Integrative Framework. 45th Hawaii International Conference on System Sciences. 10. W. DeLone & E. R. McLean (2013). Information Systems Success: The Quest for the Independent Variables AU - Petter, Stacie. Journal of Management Information Systems, 29(4), pp. 7–62. 11. H. Elkadi, (2013). Success and failure factors for e-government projects: A case from Egypt. Egyptian Informatics Journal, 14(2), pp. 165–173. 12. A.-O. Fahad & A. Ameen (2017). Toward Proposing SMART-Government Maturity Model: Best Practices, International Standards, and Six-Sigma Approach. In 1st International Conference on Management and Human Science (ICMHS 2017) (p. 2017). Kuala Lumpur, Malaysia. 13. D. Al-Ali & A. Ameen (2018). The Influence of System Quality and Information Quality on User Satisfaction: The Case of Smart Government in UAE. In 2nd International Conference on Management and Human Science (ICMHS 2018), 27-28 November 2018, Kuala Lumpur, Malaysia (Vol. 7, pp. 58–74). 14. K. Al-Ali, A. Ameen & I. Alrajawy (2018). The Role of SMART Government on Enhancing Pubic Service Quality: Performance Quality Is a Mediator Factor. In International Conference on Recent Trends in Business and Entrepreneurial Ventures (ICRTBEV2018) (p. 23). 15. S. Albreki & A. Ameen (2018). Identify the Underlying Factors that Effecting the Relationship between Knowledge Management and Smart Government in UAE. In 2nd International Conference on Management and Human Science (ICMHS 2018), pp. 27-28. 16. N. Odendaal, (2003). Information and communication technology and local governance: Understanding the difference between cities in developed and emerging economies. Computers, Environment and Urban Systems Vol. 27. 17. Smart Dubai Government Establishment. (2017). About Dubai Smart Government. 18. C. A. Dykstra (1939). The Quest for Responsibility. American Political Science Review, 33(1), pp. 1–25. 19. S. Alawadhi & H. Scholl (2013). Aspirations and Realizations: The Smart City of Seattle. In Proceedings of the Annual Hawaii International Conference on System Sciences pp. 1695–1703. 20. M. do R. M. Bernardo (2017). Smart City Governance: From E-Government to Smart Governance. In Handbook of Research on Entrepreneurial Development and Innovation Within Smart Cities (pp. 290–326). 21. Smartcity. (2018). Driving Forces That Stimulate The Growth Of Smart Cities. 22. A. T. Chatfield & J. M. Alanazi (2013). Service quality, citizen satisfaction, and loyalty with self-service delivery options to transforming e-government services. Proceedings of the 24th Australasian Conference on Information Systems. 23. F. D. Davis, (1989). Perceived Usefulness , Perceived Ease Of Use , And User Acceptance. MIS Quarterly, 13(3), pp. 319–339. 24. N. Almuraqab & S. M. Jasimuddin, (2017). Factors that Influence End-Users’ Adoption of Smart Government Services in the UAE: A Conceptual Framework. Electronic Journal of Information Systems Evaluation Vol. 20. 25. L. Carter & F. Bélanger (2005). The utilization of e-government services: citizen trust, innovation and acceptance factors*. Information Systems Journal, 15(1), pp. 5–25. 26. A. Thunibat, N. Azan Mat Zain & N. Ashaari, (2011). Modelling the factors that influence mobile government services acceptance. African journal of business management Vol. 5. 27. M. Dahi & Z. Ezziane (2015). Measuring e-government adoption in Abu Dhabi with technology acceptance model (TAM). International Journal of Electronic Governance Vol. 7. 28. S. Mofleh & M. Wanous (2008). Understanding Factors Influencing Citizens Adoption of e-Government Services in the Developing World: Jordan as a Case Study. J Comput Sci (Vol. 7). 29. H. Abdelghaffar & Y. Magdy (2012). The Adoption of Mobile Government Services in Developing Countries: The Case of Egypt. International Journal of Information Vol. 2. 30. A. Aldholay, O. Isaac, Z. Abdullah, R. Abdulsalam & A. H. Al-Shibami (2018). An extension of Delone and McLean IS success model with self-efficacy. International Journal of Information and Learning Technology, IJILT-11-2017-0116. 31. O. Isaac, Z. Abdullah, T. Ramayah & A. M. Mutahar, (2017a). Internet Usage and Net Benefit among Employees Within Government Institutions in Yemen: An Extension of Delone and Mclean Information Systems Success Model (DMISM) with Task-Technology Fit. International Journal of Soft Computing, 12(3), pp. 178–198. 32. O. Isaac, Z. Abdullah, T. Ramayah & M. Mutahar Ahmed (2017). Examining the Relationship Between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 33. C. M. Ringle, S. Wende & J.-M. Becker (2015). SmartPLS 3. Bonningstedt: SmartPLS. 34. J. F. Hair, G. T. M. Hult, C. Ringle & M. Sarstedt (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM) (2nd ed.). London: Thousand Oaks: SAGE. 35. Joseph F. Hair Jr , William C. Black , Barry J. Babin, R. E. A. (2010). Multivariate Data Analysis (7th ed.). Prentice Hall. 36. C. Fornell & D. F. Larcker (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 37. W. W.Chin (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 38. Z. Awang (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 39. 39. N. Lopes (2017). Smart governance: A key factor for smart cities implementation. In IEEE International Conference on Smart Grid and Smart Cities (ICSGSC) (pp. 277–282). Authors: Mohamad Alhamad, Mohammed Nusari, Ali Ameen, Valliappan Raju, Amiya Bhumic Role of Judicial Specialization on Improving the Organizational Performance within Judicial Paper Title: Institutions in the United Arab Emirates Abstract: In the quest to improve performance, attention has been directed at job specialization. Public 53. organizations in UAE are the focus of this paper, specifically the judicial public organization where judicial specialization is applied. The data was collected from 533 employees analyzed using structural equation modeling via software SmartPLS 3.0. The study examines the judicial specialization’s effect on organizational 328-332 performance. The research will describe relationships among the different constructs. Our efforts have improved our understanding of the role of specialization.

Keyword: Judicial specialization; organizational performance; United Arab Emirates References: 1. Turkyilmaz, G. Akman, C. Özkan & Z. Pastuszak, (2011). Empirical Study of Public Sector Employee Loyalty and Satisfaction. Industrial Management and Data Systems, 111. 2. M. Siddique (2012). Knowledge management initiatives in the United Arab Emirates: a baseline study. Journal of Knowledge Management, 16(5), pp. 702–723. 3. M. Mathias, (2017). Public leadership in the United Arab Emirates: towards a research agenda. International Journal of Public Sector Management, 30(2), pp. 154–169. 4. Gavrea, L. Ilies & R. Stegerean (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300. 5. P. J. Richard, T. M. Devinney, G. S. Yip & G. Johnson, (2009). Measuring Organizational Performance: Towards Methodological Best Practice. Journal of Management, 35(3), pp. 718–804. 6. J. Lee & Q. P. He (2019). Understanding the effect of specialization on hospital performance through knowledge-guided machine learning. Computers & Chemical Engineering, 125, pp. 490–498. 7. C. Lee, J. O. Yoon & I. Lee (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), pp. 1320–1329. 8. O. Isaac, Z. Abdullah, T. Ramayah & A. M. Mutahar, (2017a). Examining the Relationship between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizaional and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 9. B. G. Tabachnick & L. S. Fidell (2012). Using Multivariate Statistics (6th ed.). New York: Pearson. 10. R. V Krejcie & D. W. Morgan (1970). Determining Sample Size for Research Activities Robert. Educational and Psychological Measurement, 38(1), pp. 607–610. 11. J. C. Anderson & Gerbing D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), pp. 411–423. 12. V. R. Kannana & K. C. Tan (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 13. E. Werts, R. L. Linn & K. G. Jöreskog (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 14. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 15. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 16. W. W. Chin (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 17. J. F. Hair, G. T. M. Hult, C. Ringle & M. Sarstedt, (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM) (2nd ed.). London: Thousand Oaks: SAGE. 18. Z. Awang (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: Penerbit Universiti Teknologi MARA. 19. V. Capkun, M. Messner, C. Rissbacher, V. Capkun & M. Messner, (2012). Service specialization and operational performance in hospitals. International Journal of Operations & Production Management, 32(4), pp. 468–495. 20. G. M. Cortes & A. Salvatori (2019). Delving into the demand side: Changes in workplace specialization and job polarization. Labour Economics, 57, pp. 164–176. 21. Lasrado & C. Uzbeck, (2017). The excellence quest: a study of business excellence award-winning organizations in UAE. Benchmarking, 24(3), pp. 716–734. 22. R. Kassem, M. Ajmal, A. Gunasekaran & P. Helo (2018). Assessing the impact of organizational culture on achieving business excellence with a moderating role of ICT. Benchmarking: An International Journal, BIJ-03-2018-0068. 23. Global Innovation Index. (2016). Government institutions effectiveness: Yemen versus Arab countries: Rank among 143 countries, Cornell University, INSEAD, and the World Intellectual Property Organization (WIPO). 24. M. Pinar & T. Girard (2008). Investigating the Impact of Organizational Excellence and Leadership on Achieving Business Performance: An Exploratory Study of Turkish Firms. Advanced Management Journal, 73(1), pp. 29–45. Authors: Mohamad Alhamad, Mohammed Nusari, Ali Ameen, Valliappan Raju, Amiya Bhumic The Influences of Human Capital (Knowledge, Skills, and Competency) on Organizational Paper Title: Performance: A PLS-SEM Technique Abstract: The current research uses structural equations modeling (SEM) via PLS software in order to evaluate the 533 valid questionnaires. This is done for assessing the proposed model based on human capital variables for determining its impact on organizational performance in the UAE’s public sector. The main independent constructs are knowledge, skills and competency. The dependent construct covers organizational performance. The research shall define the relationship between the various constructs. This work has improved our insight into the importance of human capital. The study results have shown prediction of organizational performance by independent variables stating a 32.8% of variance. The results have the potential to give further insights into enhancing public organizations’ performance.

Keyword: Human capital; knowledge; skills; competency; organizational performance; UAE 54. References: 1. S. Comu, H. I. Unsal & J. E. Taylor, (2011). Dual Impact of Cultural and Linguistic Diversity on Project Network Performance. Journal of Management in Engineering, 27(3), pp. 179–187. 333-340 2. K. Niebecker, D. Eager & K. Kubitza (2008). Improving cross‐company project management performance with a collaborative project scorecard. International Journal of Managing Projects in Business, 1(3), pp. 368–386. 3. Z. Nedelko & V. Potočan, (2013). The role of management innovativeness in modern organizations. Journal of Enterprising Communities: People and Places in the Global Economy, 7(1), pp. 36–49. 4. J. A. Aragón-Correa, V. J. García-Morales & E. Cordón-Pozo, (2007). Leadership and organizational learning’s role on innovation and performance: Lessons from Spain. Industrial Marketing Management, 36(3), 349–359. 5. M. J. Donate & J. D. Sánchez de Pablo, (2015). The role of knowledge-oriented leadership in knowledge management practices and innovation. Journal of Business Research, 68(2), pp. 360–370. 6. C. Andriopoulos & M. W. Lewis, (2010). Managing Innovation Paradoxes: Ambidexterity Lessons from Leading Product Design Companies. Long Range Planning, 43(1), pp. 104–122. 7. M. Afacan Fındıklı, U. Yozgat & Y. Rofcanin (2015). Examining Organizational Innovation and Knowledge Management Capacity the Central Role of Strategic Human Resources Practices (SHRPs). Procedia - Social and Behavioral Sciences, 181, pp. 377–387. 8. M. Heffernan, B. Harney, K. Cafferkey, & T. Dundon, (2016). Exploring the HRM-performance relationship: the role of creativity climate and strategy. Employee Relations, 38(3), pp. 438–462. 9. C. Gavrea, L. Ilies & R. Stegerean, (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300. 10. P. J. Richard, T. M. Devinney, G. S. Yip & G. Johnson, (2009). Measuring Organizational Performance: Towards Methodological Best Practice. Journal of Management, 35(3), pp. 718–804. 11. J. B. Barney, (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management. 12. OECD. (2004). OECD Principles of Corporate Governance 2004. France: OECD Publications. 13. G.S. Becker (1993). Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. 14. T. W. Schultz, (1971). Investment in Human Capital: The Role of Education and of Research. Free Press. 15. W. H. A. Johnson, (1999). An integrative taxonomy of intellectual capital: measuring the stock and flow of intellectual capital components in the firm. International Journal of Technology Management, 18(5–8), pp. 562–575. 16. M. A. Youndt, M. Subramaniam & S. A. Snell, (2004). Intellectual Capital Profiles: An Examination of Investments and Returns*. Journal of Management Studies, 41(2), pp. 335–361. 17. W. Wang & C. Chang, (2005). Intellectual capital and performance in causal models: Evidence from the information technology industry in Taiwan. Journal of Intellectual Capital, 6(2), pp. 222–236. 18. J. Yang (2004). Job‐related knowledge sharing: comparative case studies. Journal of Knowledge Management, 8(3), pp. 118–126. 19. P. F. Drucker, (1977). People and performance: the best of Peter Drucker on management. HarperCollins Canada, Limited. 20. A. Toffler (1990). Powershift: knowledge, wealth, and violence at the edge of the 21st century. Bantam Books. 21. I. Nonaka & H. Takeuchi, (1995). The Knowledge-creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press. 22. R. Winter, (1987). Action-Research and the Nature of Social Inquiry: Professional Innovation and Educational Work. Avebury. 23. I. Nonaka, G. von Krogh & S. Voelpel, (2006). Organizational Knowledge Creation Theory: Evolutionary Paths and Future Advances. Organization Studies, 27(8), pp. 1179–1208. 24. M. Hamori, R. Bonet & P. Cappilli, (2011). How organizations obtain the human capital they need. In The Oxford handbook of human capital (pp. 309–322). 25. S. Snell & J. W. J. Dean, (1992). Integrated Manufacturing and Human Resource Management: A Human Capital Perspective. Academy of Management Journal, 35. 26. M. Gaber & A. Fahim, (2018). Strategic human resource management and public employee retention. Review of Economics and Political Science, 3(2), pp. 20–39. 27. B. C. Lee, J. O. Yoon & I. Lee, (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), pp. 1320–1329. 28. O. Isaac, Z. Abdullah, T. Ramayah, & A. M. Mutahar, (2017a). Examining the Relationship Between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizaional and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 29. B. G. Tabachnick & L. S. Fidell, (2012). Using Multivariate Statistics (6th ed.). New York: Pearson. 30. R. V. Krejcie & D. W. Morgan, (1970). Determining Sample Size for Research Activities Robert. Educational and Psychological Measurement, 38(1), pp. 607–610. 31. J. C. Anderson & D. W. Gerbing, (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), pp. 411–423. 32. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 33. C. E. Werts, R. L. Linn & K. G. Jöreskog, (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 34. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 35. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 36. W. W. Chin (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 37. J. F. Hair, G. T. M. Hult, C. Ringle & M. Sarstedt, (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM) (2nd ed.). London: Thousand Oaks: SAGE. 38. V. J. García-Morales, M. M. Jiménez-Barrionuevo, & L. Gutiérrez-Gutiérrez, (2012). Transformational leadership influence on organizational performance through organizational learning and innovation. Journal of Business Research, 65(7), pp. 1040–1050. 39. S. Aydogdu & B. Asikgil, (2011). The Effect of Transformational Leadership Behavior on Organizational Culture : An Application in Pharmaceutical Industry. International Review of Management and Marketing, 1(4), pp. 65–73. 40. K. C. Lee, S. Lee & I. W. Kang (2005). KMPI: measuring knowledge management performance. Information & Management, 42(3), pp. 469–482. 41. C. J. Brungardt, (2009). College graduates’ perceptions of their use of teamwork skills: Soft skill development in Fort Hays State University leadership education. KANSAS STATE UNIVERSITY, Manhattan, Kansas. 42. M. Pinar & T. Girard, (2008). Investigating the Impact of Organizational Excellence and Leadership on Achieving Business Performance: An Exploratory Study of Turkish Firms. Advanced Management Journal, 73(1), pp. 29–45. Authors: Asia Mahdi Naser Alzubaidi, Eman Salih Al-Shamery

Paper Title: Churners Prediction Based on Mining the Content of Social Network Taxonomy Abstract: Churner Customer is a main tricky and one of the most important issues for large companies, due to the straight impact on the incomes of the companies especially in the telecom domain, companies are searching for advance strategies to predict churn/non-churn customer. This research focuses on the construction of a predictive model to identify each customer as churner or not and gain additional insights about their service consumers. The main contribution is to overcome the limitation of independently based on data mining strategies by developing approaches and derived network metrics such as centrality and connectivity between customers to 55. incorporate network mining with traditional data mining. Social network measurements e.g. Leverage, flow Bet, Page Rank, Cluster Coefficients and Eccentricity are joined with other attributes in the original network dataset to enhance the performance of the proposed methodology. The risk of churn can be predictive by preparing an 341-351 extensive cleaning the raw data for churn modeling, It divides customers into clusters based on Gower distance and k-medoids algorithm to help understand and predict churner users, classification model using Extreme Gradient Boosting “XGBoost”, assessment the model performance by computation the centralities metrics as new attributes appended to the original network dataset. Experiments conducted on Telecom shows that with an average value of all statistics accuracy not lower than 98.27%, while the average accuracy for the original dataset with it is clusters is not exceeded than 0.97%. The proposed method for churners detection which combines social impacts and network contents based on clustering significantly improved the prediction accuracy for telecom dataset as compared to prediction using the call log details, network information without implement of clustering , thus validate the hypothesis that combining social network attributes and Call/SMS information of the users for churn prediction could yields substantially improved of customer churn prediction.

Keyword: Churn Prediction, Mobile Social Network Analysis, Churn in Telecom, Social Network Analysis, eXtreme Gradient Boosting algorithm (XGBoost), Centrality Metrics, Mobile Network. References: 1. A. K. Ahmad, A. Jafar, and K. Aljoumaa, “Customer churn prediction in telecom using machine learning in big data platform,” J. Big Data, vol. 6, no. 1, p. 28, Dec. 2019. 2. F. Aldahan and J. S. Grape, “Teknisk-natur vetenskaplig fakultet UTH-enheten,” 2016. 3. K. Dasgupta et al., “Social ties and their relevance to churn in mobile telecom networks,” 2008, p. 668. 4. R. Pagare and A. Khare, “Churn prediction by finding most influential nodes in the social network,” in International Conference on Computing, Analytics, and Security Trends, CAST 2016, 2017, pp. 68–71. 5. J. Manďák, “Proposal and Implementation of Churn Prediction system for Telecommunications Company,” VŠB-TECHNICAL UNIVERSITY OF OSTRAVA FACULTY OF ECONOMICS DOCTORAL, Ostrava, 2018. 6. I. Brandusoiu, G. Toderean, and H. Beleiu, “Methods for churn prediction in the pre-paid mobile telecommunications industry,” in 2016 International Conference on Communications (COMM), 2016, vol. 2016-August, pp. 97–100. 7. G. Gandhi and R. Srivastava, “ANALYSIS AND IMPLEMENTATION OF MODIFIED K-MEDOIDS ALGORITHM TO INCREASE SCALABILITY AND EFFICIENCY FOR LARGE DATASET,” Int. J. Res. Eng. Technol., vol. 03, no. 06, pp. 150– 153, Jun. 2014. 8. N. Gamulin, M. Štular, and S. Tomažič, “Impact of Social Network to Churn in Mobile Network,” Automatika, vol. 56, no. 3, pp. 252–261, Jan. 2015. 9. E. Nankani, “Deep Data Mining with Network Relationships,” western Sydney, 2011. 10. M. Dewing, “Social Media : An Introduction Social Media : An Introduction,” Library of Parliament, no. 2010. pp. 1–2, 2012. 11. M. Jalili et al., “CentiServer: A comprehensive resource, web-based application and R package for centrality analysis,” PLoS One, vol. 10, no. 11, p. 8, 2015. 12. A. K. Mallick and A. Mukhopadhyay, “Different Schemes for Improving Fuzzy Clustering Through Supervised Learning,” in Communications in Computer and Information Science, vol. 1030, Springer Singapore, 2019, pp. 155–164. 13. I. Panapakidis and G. Christoforidis, “Optimal Selection of Clustering Algorithm via Multi-Criteria Decision Analysis (MCDA) for Load Profiling Applications,” Appl. Sci., vol. 8, no. 2, p. 237, Feb. 2018. 14. J. Xiao, Y. Tian, L. Xie, X. Jiang, and J. Huang, “A Hybrid Classification Framework Based on Clustering,” IEEE Trans. Ind. Informatics, no. August, pp. 1–1, 2019. 15. T. Velmurugan, “A State of Art Analysis of Telecommunication Data by k-Means and k-Medoids Clustering Algorithms,” J. Comput. Commun., vol. 06, no. 01, pp. 190–202, Dec. 2017. 16. M. Yan, “Methods of Determining the Number of Clusters in a Data Set and a New Clustering Criterion,” Virginia Polytechnic Institute and State University, 2005. 17. A. Kassambara, Practical Guide to Cluster Analysis in R: Unsupervised Machine Learning. 2017. 18. E. Schubert and P. J. Rousseeuw, “Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms,” arXiv:1810.05691v3[cs.LG], 2018. 19. A. Batra, “Analysis and Approach: K-Means and K-Medoids Data Mining Algorithms,” 5th IEEE Int. Conf. Adv., no. 274, pp. 274–279, 2011. 20. T. Chen and C. Guestrin, “XGBoost,” in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’16, 2016, pp. 785–794. 21. L. Ruisen et al., “Bagging of Xgboost Classifiers with Random Under-sampling and Tomek Link for Noisy Label-imbalanced Data,” IOP Conf. Ser. Mater. Sci. Eng., vol. 428, no. 1, p. 012004, Oct. 2018. 22. R. Santhanam, N. Uzir, S. Raman, and S. Banerjee, “Experimenting XGBoost Algorithm for Prediction and Classification of Different Ramraj S, Nishant Uzir, Sunil R and Shatadeep Banerjee Experimenting XGBoost Algorithm for Prediction and Classi fi cation of Different Datasets,” Int. J. Control Theory Appl., vol. 9, no. March, pp. 651–662, 2017. 23. M. Hassan Elbedawi Omar, M. Borrotti, and A. Corti, “Customer Churn prediction based on eXtreme Gradient Boosting classifier,” IMATI-CNR, Milano, 2018. 24. T. Chen and C. Guestrin, “XGBoost: A Scalable Tree Boosting System,” in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD ’16, 2016, vol. 19, no. 6, pp. 785–794. Authors: Toirova Guli Ibragimovna , Yuldasheva Mavjuda Rakhimovna, Elibaeva Lola Suleymanovna

Paper Title: Importance of Interface in Creating Corpus Abstract: The article discusses the author's corps and its significance in modern glossary, the world of Pushkin's author's corps, the Czech writer's corps, Shakespeare's author's corps and their shortcomings. The interface of the author's corps is made up of different designs and structures, and the author is responsible for its completeness, the interface should be attractive and impressive. The creation of the interface is based on the design of the national or modern features, the interface should involve the life and works of the artist in photoes. The Corpus of Linguistics is a very rapidly developing branch of the world of computational linguistics, which has achieved great success in this regard. The Corpus of Linguistics is also taught as a science in world universities. The subject of this discipline is the 56. theory and practice of building a corpus, such as body features and the basics of programming. The Corpus of Linguistics deals with general theory and practice of computational linguistics, the formation of the language 352-355 body, and computer technologies. The article tells about modern information technologies that have created tremendous opportunities for language functionality. Computer translation, editing, analysis, electronic dictionary and thesaurus are proof of our opinion. Especially the creation of modern electronic dictionaries and the culture of their use is one of the effective ways of learning a language. In particular, the role of language buildings created and developing at a fast pace throughout the world when demonstrating the ability and ability to master the language is very large. The purpose of the article is to study the linguistic foundations of the Uzbek language corpus, to study the linguistic value of the linguistic corpus, the history of corpus linguistics, to study the author's linguistics of the corpuses, its features in the social, lexicological, educational and other fields. The article gives an idea about the interface, the content of the corpus, its flawless functioning and at first glance the importance of the author’s personality, creative heritage, classification.

Keyword: Interface, the author’s corps, mathematical modeling, morphologic and semantic annotation, information, linguistic base, artificial intelligence, сomputer linguistics, corpus linguistics, language corpus, special software, e-library, lexical, morphological, grammatical, semantic symbols, problems with linguistic markup. References: 1. Sh.M. Mirziyoyev (2017) Report of the President of the Republic of Uzbekistan at the 72nd session of the United Nations General Assembly September 19, 2017. http://www.uza.uz/ru/politics/prezident-uzbekistana-shavkat-mirziyeev-vystupil-na-72-y-ses-20- 09-2017 2. Ahmedova M.B. (2018) Genetic and structural specifications of the “spirituality” nominative units in the Uzbek language // International Scientific Journal “ Theoretical and Applied Science.- USA, Philadelphia, 2018.- Volume 66.-P. 331-333( Impact factor- 3.04) 3. Vanyushkin A.S., Grashchenko L.A. (2017) Evaluation of key word extraction algorithms: tools and resources // New information technologies in automated systems. - 2017. - № 20. - pp. 95-102. 4. Nikolaev I.S., Mitrenina O.V., Lando T.M. (2006) Applied and Computational Linguistics - M.URSS, 2016. - 320 p. 5. Nedoshivina E.V. (2006) Corps Texts Programs: A Review of Core Corps Managers. Teaching manual. - St. Petersburg. - 2006. 26 p. 6. Rakhilina E.V., Marushkina A.S. (2015) Corpus studies of the peculiarities of speech of non-standard speakers ("Russian hermetic") // Acta Linguistica Petropolitana. Proceedings of the Institute of Linguistic Studies. 2015. T. XI. № 1. S. 621-639. 7. Leech G.( 1991) The State of Art in Corpus Linguistics // English Corpus Linguistics / Aimer K., Altenberg K.(eds.) – London, 1991. – P. 8-29. 8. Кутузов А.Б. (1968) Корпусная лингвистика. − (Электрон ресурс): Лицензия Creative commons Attribution Share-Alike 3.0 Unported (Электрон ресурс) - //lab314.brsu.by/kmp-lite/kmp-video/CL/CorporeLingva.pdf. 9. Bloomfield L. Language. - M .: Progress, 1968. - 608 p. 10. Fries Ch.C. The structure of English. An introduction to the construction of English sentences. – L.,1969.-С.98 11. Bongers H. (1947) The history and principles of Vocabulary control. – Woerden: WOCOPI, 1947.-С.74 12. Francis N., Kucera G. (1967) Computational analysis of modern American English. - M., 1967 13. Melchuk, IA (1985) Word order in the automatic synthesis of a Russian word (preliminary reports) // Scientific – Technical Information. 1985, №12. -C.12-36 14. Hamroyeva Sh. (2018) Linguistic basis for the creation of the Uzbek language. 2018.-52 б. 15. Hamroyeva Sh. (2017) Use in education from the соrpus “Language and literary education” Journal. September 2017, № 9. Б.49- 50. 16. Hamroyeva Sh. (2018) Сorpus creation principles. Journal "Scientific Bulletin of Science". 2018. № 3. 17. Tairova G. (2015) Some of the differences between paradigmatic and discursive systems. // IMPACT: International Jurnal of Research in Humanities, Arts and Leteratura. (impact: ijrhal) Vol. 3, Issue 12, Dec 2015, 1-4. (№ 12 Index Copernicus Impact Factor - 1,7843) 18. Tairova G. (2016) Phatics - actual problems of linguistics uzbek research // Iranian Journal of Social Sciences and Humanities Research. UCT. J. Soc. Scien. Human. Resear. (UJSSHR). – Takestan, Iran, 2016, Volume 4, Issue 2. – P.16-19. (№5 Global Impact Factor, Impact Factor – 0,765). 19. Tairova G. (2017)Systematic and informative in uzbek discourse// UCT Journal of Social Sciences and Humanities Research.(UJSSHR). – Takestan, Iran, 2017, Volume 5 Issue 2 June. – P.1-6. (№5 Global Impact Factor, Impact Factor –2,758). 20. Tairova G. (2013) Izosign – graphic expression of the discourse as pragmatical situational system 10th International Conference on Crossroad of Civilzations: Aspeets of Lenguage, Culture and Society. – Japan, 2013. – P. 525-529. 21. Casares J.(1969) Dissionario ideologico de la lengua Espanola.– Barselona,1969. –887 c. 22. March F.A. (1958) March’s Thesaurus Dictionary. – N.Y., 1958.– 1312 p. 23. Roget P.M. (1952) Thesaurus of English words and phrases. – Lnd., 1952. – 1258 р. 24. http://www.dialog-21.ru/media/2138/zakharov.pdf Zakharov V.P. Corps of the Russian language. 25. Mamontova V. V. (2008) Corpus of parallel texts and database for the study of translation correspondences: problems and procedures for the formation Address of the article: www.gramota.net/materials/1/2008/8-2/50.html 26. Antonova A., Alexey M. ()Building a Web-based parallel corpus and filtering out machinetranslated text. https://www.aclweb.org/anthology/W11-1218 27. Resnik, Philip and Noah A. Smith. (2003) The web as a parallel corpus. Computational Linguistics, 29:349– 380. 28. Wang W., Liu Y., Harper M. P. (2002) “Rescoring effectiveness of language models using different levels of knowledge and their integration”, in Proc. ICASSP, Orlando, FL, May 2002. Authors: Azimova Shakhnoza Samukdjanovna Problems of Ensuring Innovative Development of Credit Activities of Commercial Banks and Ways Paper Title: of their Solution Abstract: This article analyzes the problems of credit activities of commercial banks in Uzbekistan and offers recommendations for their elimination.

Keyword: bad loans, innovation, overdraft, credit risk, diversification, investment, assets, reserve contributions, forfeiting, ekskro-accounts, online lending, POS-lending. References: 57. 1. Decree of the President of the Republic of Uzbekistan No. 4947 of february 7, 2017 «Strategy of action in five priority areas of the development of the Republic of Uzbekistan for 2017-2021». www.lex.uz 2. Andreeva, A.V. The role of financial innovation in the development of the banking services market [Text] / А.V. Andreeva // 356-360 Banking services. - 2010. - No. 6. - P.32. 3. BAKHTISHODOVICH, BOBUR SOBIROV, et al. "The role of social media, user generated platforms and crowd sourcing in the development of tourism destinations." Journal of Hospitality Management and Tourism 6.4 (2015): 30-38. 4. Sobirov, Bobur. "Innovative development of tourism in Uzbekistan." American Journal of Economics and Business Management 1.1 (2018): 60-74. 5. Sobirov, Bobur. "The concept of the tourist economic zone. Case of Uzbekistan." World Scientific News 98 (2018): 34-45. 6. Abdurakhmanov, K., Zokirova, N., Shakarov, Z., & Sobirov, B. (2018). DIRECTIONS OF INNOVATIVE DEVELOPMENT OF UZBEKISTAN. National Academy of Managerial Staff of Culture and Arts Herald, (3). 7. Mishchenko A.V. Lending activities of commercial banks in Russia: specifics of management and regulation. Diss. for a job. student Art. Ph.D. - Rostov - on - Don, 2013 .-P.15. 8. Vorobyova I.S. Credit innovations in the banking sector (on the example of car loans) / Abstract. for a job. student step. Cand. econ. Sciences. Russian University of Economics G.V. Plekhanova, 2014 .-30p. 9. Decree of the President of the Republic of Uzbekistan PD-3270 dated september 12, 2017 "On measures to further develop and increase the stability of the banking system of the republic." www.lex.uz 10. www.cbu.uz (Annual reports of Central Bank of the Republic of Uzbekistan) 11. Bank Management Textbook. ed. prof. O.I. Lavrushin. - M .: KNORUS. 2016 .-P. 275. 12. Annual reports of Asakabank and Turonbank (www.asakabank.uz www.turonbank.uz) 13. www.spot.uz 14. Decree of the President of the Republic of Uzbekistan No. 3620 of March 23, 2018 “On additional measures to increase the availability of banking services”. www.lex.uz 15. Bank Management Textbook. ed. prof. O.I. Lavrushin. - M .: KNORUS. 2016 .-768p. 16. Allen F., Gale D. Comparing Financial Sestems. – Cambridge, Mass: MIT Press, 2000. – 519 р. 17. Scott J.A., Dinkelberg W.C., Dennis W.J. Credit, Banks and Small Business – the New Century – Washington: NFIB Research Foundation, 2003. – 96 p. Authors: Norkhudjaev F.R, Alikulov. A. Kh, Abdurakhmonov. Kh. Z, Tursunov. T. Kh

Paper Title: Examination of Thermophysical Processes in the Creation of Metal Layered Compositions Abstract: The article describes the creation of a technological basis for production by casting on gasified models of metal laminates for various metalworking and other tools. The obtained metal layered composition of the type of foundry structural steel - working insert which represent the connection between tool and foundry structural steels. Microstructural studies of metal layered compositions with a solid working element of non- heat-resistant tool steel were carried out. A mechanism has been developed for the formation of a compound of metal layered compositions.

Keyword: mathematical model, thermophysical processes, metal layered composition, liquid metal, diffraction method, disordered zone. References: 1. Вайнгард У. Введение в физику кристаллизации металлов. М.: Мир, 1967.– 170 с. 2. Лисовский А.Ф. О механизме массопереноса жидких металлов в спеченных композиционных материалах // Инж. - физ. журнал. – Москва, 1979. - №6. - C. 977-979. 3. Хрущев Б.И. Структура жидких металлов. – Ташкент Фан, 1979. –111 с. 4. Norknudznaev F. R., Nazarov A. M., Koveshnikov S. V., Mavlonov Sh. A., Khurbanbaev Sh. Z., Ataullaev A. O. The fiber- 58. optical sensor for chromate-graphic measurements // International Journal of Advanced Research in Science, Engineering and technology.–India, 2016. - Vol.3, Issue 8. - pp. 2463-2467. 5. Архаров В. И., Новохатский И. А., Ершов Г. С., Коваленко А. М. Диффузия водорода в расплавленном железе // ДАН 361-366 СССР.- 1970. - Т.190.6- С. 1122-1127. 6. Новохатский И. А., Архаров В. И. Определение относительных долей структурных составляющих металлических расплавов // ФММ. – М., 1971.- Т.31, .- С. 1263-1267. 7. Новохатский И. А., Архаров В. И., Ершов Г.С., Келупко В. С. О распределении растворенных элементов между структурными составляющими расплавленого железа // ДАН СССР. – М., 1970. - Т.194, 4. - С. 1402-1410. 8. Мелвин - Хьюз Э. А. Физическая химия. - М.: Изд. ИЛ, 1962. - 1148 с. 9. Клейнер М. К. Локальные тепловые потоки в замкнутом пространстве с переменной структурой стенок // Черная металлургия: Изв. ВУЗов – Москва, 1973. - №4. - С.153. 10. Бокштейн С. З. Строение и свойства металлических сплавов. - М.: Металлургия, 1971. - 496 с. 11. Арсентьев П.П., Коледов Л. А. Металлические расплавы и их свойства. - М.: Металлургия, 1999. - 376 с. 12. Вайберг В.К., Соседов В. Н., Кушнир А. Н. Исследование роста трещин методом акустической эмиссии // Дефектоскопия 1975.-№3. – С. 127 – 129. 13. Иванова В. С., Маслов Л. И., Параев С. А. Акустическая дагностика разрушения стали // Сб. докл. IX Всесоюзн. акустич. конф. Секция Б, 1977 М.: Акустический институт, 1977. – С. 181-184. 14. Лошак М. Г. Прочность и долговечность твердых сплавов. Киев: Науковадумка, 1964. – 328 с. 15. Свойства элементов: Справочник / Под. ред. Г.В. Самсонова - М.: Металлургия, 1976. – 476 с. 16. Шанк Ф. А.Структура двойных сплавов.– М.: Металлургия, 2014.-232 с. 17. Норхуджаев Ф. Р. Разработка теоретической и технологической основы производства и термической обработки металлических слоистых композиций. : Дис...д-ра. техн.наук. – Ташкент, 2016. – 210 с. 18. Norknudznaev F. R., Nazarov A. M., Yakubov L. E. Sintered powder composition on the basis of Mo – TiC. India. International Journal of Advanced Research in Science, Engineering and technology, 2016. - Vol.3, Issue 7, July. pp. 2347-2350.

Authors: Allambergenov Akhmet Janabergenovich, Paper Title: Formation of Technological Competence in Students: Essence and Content Abstract: This article reveals the essence and content of formation of technological competence in students.

Keyword: technology, competence, knowledge, ability, culture, technological competence, technological worldview 59.

References: 367-369 1. Standards for Technology Literacy. Content for the Study of Technology Education, Association and its Technology for all American Project, Reston< Virginia, 2000, 248 p. 2. “Güring” firm and its products [Electronic resource]. - 2011. 3. P.K. Engelmeyer. Creative person and environment in the field of technical inventions. St. Petersburg, 1911. - 116 p. 4. A.I. Rakitov. Prolegomena to the idea of technology // Questions of Philosophy. - 2011. - № 1. - pp. 3–14. 5. Technological competence of a specialist // Psychophysiology of a person: Russian-English-Russian encyclopedia / Comp. E.V. Trifonov [Electronic resource]. - 14th ed. - 2011. 6. Yu.S. Dorokhin. Formation of technological competence in future teachers in the study of disciplines of specialized training: abstract of dis. ... cand. ped. sciences: 13.00.08; Tula State Pedagogical University. - Tula, 2010. - 23 p. 7. A.N. Sergeev. Technological training of future teachers in the context of paradigmatic transformation of education (on the example of the specialty: 050502.65 – technology and entrepreneurship): abstract of dis .... doctor of ped. sciences: 13.00.08; Tula State Pedagogical University. - Tula, 2010. - 50 p. 8. O.A. Smolina. Formation of technological competence in future service specialists in higher education establishment: abstract of dis. ... cand. ped. sciences: 13.00.08; South-Ural State University. - Chelyabinsk, 2010. - 26 p. 9. E.A. Milerian. Psychology of formation of general polytechnic labor. – Moscow: Pedagogy, 1973. 10. E.M. Kalitsky. Formation of industry-wide technological knowledge and skills in students of secondary vocational schools (on the example of training metalworkers): abstract of dis. ... cand. ped. sciences: 13.00.02; APS of the USSR, Scientific Research Institute. Content and methods of teaching. - Moscow, 1978. - 23 p. 11. S.F. Ekhov. The change of the paradigm of technological education as an objective necessity // Technological education: problems and prospects of interaction between the university and the school: monograph / responsible ed. P.A. Petryakov; Novgorod State University. - V. Novgorod, 2008. - pp. 13–27. 12. A.V. Koklevsky. Formation of technological competence in future specialists in the process of military training in a classical university: theory and practice. - Minsk: RIHE, 2015. - 228 p. 13. Technological system of training students in secondary vocational schools / Ye.A. Milierian [and others]. - Yerevan: Luys, 1985. - 192 p. 14. V.D. Simonenko. Technological culture and education (cultural-technological concept of the development of society and education). - Bryansk: BPTU publishing house, 2001. - 214 p. 15. R. Boyatzis. Competent Manager. Model of effective work; trans. from English. - Moscow: HIPPO, 2008. - XII, 340 p. Authors: Davlatov Oybek Ganievich

Paper Title: Development of Information Security Competency in Students Abstract: This article describes methodological aspects of developing students’ information security competencies. In the article, the author clarifies the essence of the concept of “information security”, its various aspects, the relationship between the development of information security competency and information- analytical competence, as well as the methodological conditions of information-analytical function. In addition, he substantiates the importance of vitagenic education technology in the development of students’ information- analytical competency, and, on the basis of experimental materials, the correlation between the components of development of students’ information security competency.

60. Keyword: information, information attack, security, competence, competent, vitagenic, component

References: 370-373 1. Temur tuzuklari. / Translated from Persian by A.Saguni and H.Karomatov. – Tashkent: Publishing House of Literature and Art named after G.Gulam, 1996. – 34 p. 2. Streltsov A.A. The content of the concept of “provision of information security” // Information Society. – 2001. – No.4. – p.12. 3. Raimov Sh.U. Provision of information security is one of the most important areas of the national security strategy. / Current archive of the Academy of State and Social Construction under the President of the Republic of Uzbekistan, 2006. 4. Verbitsky A.A. Active learning in higher school: a contextual approach. – Moscow, Higher School. Publ., 1991. – 207 p. (in Russian). 5. Min-kyu Choi, Rosslin John Robles, Chang-hwa Hong, Tai-hoon Kim. Wireless Network Security: Vulnerabilities, Threats and Countermeasures. School of Multimedia, Hannam University, Daejeon, Korea. International Journal of Multimedia and Ubiquitous Engineering. Vol.3, No.3, July 2008. 6. Stamp Mark. Information security: principles and practice. USA, 2011. – 240 p. 7. Stavroulakis Peter, Stamp Mark. Handbook of Information and Communication Security. – 2010. – 178 p. Authors: Ergasheva Yu. A., Vasieva D. I., Murtazova S. B. Political Persecutions and Ideological Pressure on the Creative Intellectuals of Uzbekistan in Post- Paper Title: War Decades Abstract: In the article the questions of political persecutions and ideological pressure on the creative intellectuals of Uzbekistan, impact of policy of repressions of the Soviet power on cultural life of society are considered. Problems of conceptual and ideological interdependence of the repressive nature of the Soviet power and antinational orientation of the Soviet "cultural policy", the destroying impact of repressive policy on the spiritual life of people are analyzed and also the tragic fate of the representatives of the national creative intellectuals, scientists, literary figures, artists who suffered from persecutions and repressions is considered.

61. Keyword: political persecutions, ideological pressure, repressions, spiritual culture, science, literature, art, creative intellectuals, scientists, national culture. 374-377 References: 1. The Communist Party of Uzbekistan in resolutions and resolutions of congresses. – Tashkent, 1968, p. 260. 2. Mukhitdinov N. the Years spent in the Kremlin. - Tashkent, 1994, p. 48. 3. East truth, on August 1951, 10. 4. East truth, on February 1952, 24. 5. The Communist Party of Uzbekistan in resolutions and resolutions of congresses. – Tashkent, 1968, p. 454. 6. TsGA RUZ, t. 2356, оп. 1, 311, l. 18. 7. Fan va Turmush, 1993, No. 5-6, p. 9 8. Saidnosirova Z. Oybegim mening. Tashkent, 1994, p. 128. 9. Shukrullo. Qasosli dunyo. - Tashkent, 1994, p. 12. 10. Shukrullo. Your dreams: Verses and poems. - Tashkent, 1980, p. 78. 11. Pravda Vostoka. May 1989, 21. Authors: Khakimova Gulnora Abdumalikovna 62. Paper Title: Some important features of Renaissance Dramas: Themes, Style and Character Examination Abstract: Renaissance was one of the main periods of the growth in English literature, arts, economy, language development and others. Renaissance gave birth to individualism and worldliness, freed the minds of people. This topic is of great interest for scholars to analyze and find out new features. As it is stated in the article Renaissance period in English literature provoked drama and poetry, some pieces of them must be analyzed thoroughly.

Keyword: Renaissance, drama, poetry, theatre, culture, patriotism, spirit, revival of knowledge, plays, Jacobean period. 378-379 References: 1. Braunmuller A.R. and Michael Hattaway.” English Renaissance Drama”, Cambridge University Press,1992 2. Pacheco, Emma. The Power that Women Hold in The Duchess of Malfi. Final AE Project,2012 3. Wigham, Fred. “Sexual and Social Mobility in The Duchess of Malfi” Academic Search Premier.Web.18 Nov 2012. 4. Dympna, Callaghan, The Duchess of Malfi (New York: Sy.Martin’s, 2000),p.4, citing Merry E. Weisner, Women and Gender in Early Modern Europe (Cambridge: Cambridge University Press,1993),p.166 5. Jankowsiki, Theodora A. “Defining/Confining the Duchess:Negotiating the Female Body in John Webster’s The Duchess of Malfi” Studies in Philogy 90.87(1990):228-230. Academic Serach Premier. Web. 18 Nov 2012. Authors: C.Kathiravan, V. Suresh, Padmaja Bhagavatham, V.Palanisamy

Paper Title: An Examination on Customer Satisfaction Towards Air-Conditioner User in Chennai City Abstract: The article tries to find out the customer satisfaction towards air-conditioner users in Chennai city. Two objective of this study is reached through proper methodology. Sample size was 200. Convenience sampling technique was used in this study. Reliability of this tool is 0.82 and 0.88. Analysis was done through path analysis. It is found that there is influence of brand preference and factors determining purchase of air- conditioner on customer satisfaction towards air-conditioner. Research also identified that there is influence of customer satisfaction on brand loyalty towards air-conditioner. Hence, it is concluded that distributers and marketers require to framework best pricing strategies, star ratings, warranty and guarantee, product quality etc.

Keyword: Convenience Sampling Technique, Customer Satisfaction, Brand Preference, Brand Loyalty And 63. Factors Determining Purchase of Air-Conditioner. References: 380-384 1. Aslıhan Nasır, Sema Yoruker, Figen Güneş and Yeliz Ozdemir (2006) Factors Influencing Consumers Laptop Purchases, 6th Global conference & Business & Economics, 1-8.

2. Cooper, D.R.T &T Schindler,T P.S.T (2001),T BusinessT ResearchT Methods,T 7thT edn.,T Irwin/T McGraw-Hill,T Singapore.

3. Davis,T D.T &T Cosenza,T R.M.T (1988),T BusinessT ResearchT forT DecisionT Making,T 2ndT edn.,T PWS-Kent,T Boston.

4. FarbodT SouriT (2017)T InvestigateT TheT RelationshipT BetweenT BrandT Equity,T BrandT LoyaltyT AndT CustomerT Satisfaction.T

InternationalT JournalT OfT ScientificT &T TechnologyT Research,T VolumeT 6,T IssueT 06,T ISSNT 2277-8616,T pp-225-231.

5. GopiT KrishnanT (2017)T analysisT ofT user’sT perceptionT ofT consumerT durableT products:T anT empiricalT studyT withT referenceT toT TamilT

Nadu,T departmentT ofT managementT studiesT St.T Peter’sT InstituteT ofT higherT educationT andT research,T ppT 1-182.

6. HeT XihaoT (Stephen)T andT JiaqinT YangT (2009)T SocialT influenceT onT Consumers’T PurchasingT BehaviourT andT relatedT marketingT

strategyT -T aT crossT –T nationT comparativeT study. 7. Ritesh K. Patel (2013) a study on consumer preference towards purchase of electronic consumer durables from retail malls, elk Asia pacific journal of marketing and retail management, ISSN 0976-7193 (Print) ISSN 2349-2317 (Online) Volume 4 Issue 3. 8. Srivastava, & T, N. (2008) Statistics for Management (1 st Edition Ed.), New Delhi: Tata McGraw Hills. Authors: Bharati Dixit, Arun Gaikwad

Paper Title: Facial Features Based Hybrid Methods for Emotion Recognition Abstract: Effective human machine interaction systems are need of the time so the work carried out deals with one of such significant HMI tasks- automatic emotion recognition. The experimentation carried out for this study is focused to facial expressions based emotion recognition. Two techniques of emotion recognition based on hybrid features are designed and experimented using JAFFE database. The first technique referred as "Hybrid Method1" is designed around feature descriptor obtained through local directional number & principal component analysis and feed forward neural network used as classifier. The second technique referred as "Hybrid Method 2" is designed around feature descriptor obtained through histogram of oriented gradients, local binary pattern and Gabor filters. PCA- principal component analysis is used for dimensionality reduction of feature descriptor and k-nearest neighbors as classifier. The average emotion recognition accuracy achieved 64. through method 1 and method 2 is 85.24% and 93.86% respectively. Effectiveness of both the techniques is compared on the basis of performance parameters such as accuracy, false positive rate, false negative rate and 385-389 emotion recognition time. Emotion recognition has wide application areas so the work carried out can be applied for suitable application development.

Keyword: Emotion Recognition, Facial expressions, Local directional number Histogram of oriented gradients, Hybrid Features. References: 1. K. Oatley, et al., "The Experience of Emotions in Everyday Life ," Journal of Cognitive Emotions, vol. 8, pp. 369-381, 1994 2. A.N. Ratna et al., "Comparative Analysis Of Machine Learning KNN, SVM and Random Forests Algorithm For Facial Expression Classification, " International Seminar On Application For Technology Of Information And Communication (Isemamtic), pp. 163-168, 2016. 3. F. Nacer et al., "Exemplar-Based Facial Expression Recognition," Elsevier Information Science, vol. 460, pp. 318-330, 2018. 4. B. Allaert, et al., "Impact Of Face Registration Techniques On Facial Expression Recognition," Research Article Signal Processing: Image Communication, vol. 61, pp. 44-53, 2018 5. Junkai Chen, et al., "Facial Expression Recognition in Video with Multiple Feature Fusion,” IEEE Transactions on Affective Computing. vol. 1, pp.1-13, 2016. 6. D. Hong-Bo, et al., "A New Facial Expression Recognition Method Based On Local Gabor Filter Bank And PCA Plus LDA ," International Journal Of Information Technology, vol. 11, Issue 11, pp. 86-96, 2005. 7. Othmane El Meslouhi, et al., "Unimodal Multi-Feature and One dimensional Hidden Markov Models for Low Resolution Face Recognition," International Journal of Electrical and Computer Engineering, vol. 7, Issue 4, pp. 1915-1922, 2017 8. A.T. Madhumita, et al., “Image Based Facial Macro-Expression Recognition Using Deep Learning,” International Conference on Digital Image Computing: Techniques and Applications - DICTA on small Datasets, Australia, pp.1-7, 2017. 9. Paul Ekman, et al., “Unmasking the Face” published by Maylor Books in 2003. 10. Adin Ramirez, et al., " Local Directional Number Pattern for Face Analysis: Face and Expression Recognition,” IEEE Transactions On Image Processing, vol. 22, Issue 5, pp. 1740-1752, May 2013. 11. YaxinSun et al., "Cognitive Facial Expression With Constrained Dimensionality Reduction," Journal of Neurocomputing, vol. 22, pp. 397-408, 2017. 12. M. Hongying, et al., "Time-Delay Neural Network for Continuous Emotional dimension Prediction From Facial Expression Sequences," IEEE Transactions On Cybernetics, vol. 46, Issue 4, 916-929, 2016. 13. N. Dalal, et al., "Histograms of oriented gradients for human detection, " IEEE Computer Society Conference on pattern recognition and Computer Vision, 2005. 14. Z. Baochang, et al., "Local Derivative Pattern Versus Local Binary Pattern: Face Recognition with High-Order Local Pattern Descriptor " IEEE Transactions On Image Processing, vol.19, Issue 2, pp. 533-544, 2010. 15. International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 2, February 2012) 6 Detection of Misbehaving Nodes in Ad Hoc Routing Isha V. Hatware , Atul B. Kathole , Mahesh D. Bompilwar 16. International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013 39 ISSN 2229-5518 “SURVEY OF TOPOLOGY BASED REACTIVE ROUTING PROTOCOLS IN VANET” Atul B.Kathole , Yogadhar Pande. 17. Z. Ligang, et al., "Facial Expression Recognition Using Facial Movement Features," IEEE Transactions On Affective Computing, vol.2, Issue 4, pp. 219-229, 2011. 18. S. L. Happy, et al., "Automatic facial expression recognition using features of salient facial patches," IEEE transactions on Affective Computing, vol. 6, Issue 1, pp.1-12, 2015. 19. Y. Jian, et al., "Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition,” IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 26, Issue 1, pp. 131-137, 2004. 20. S. Venkatramaphani kumar et al., "Face Recognition with Modular Two Dimensional PCA under Uncontrolled Illumination variations " International Journal of Electrical and Computer Engineering, vol. 6, Issue 4, pp. 1610-1616, 2016. 21. D. Coomans, et al., "Alternative K-Nearest Neighbour Rules In Supervised Pattern Recognition: Part 1. K-Nearest Neighbour Classification By Using Alternative Voting Rules" Analytica Chimica Acta., vol. 136, pp. 15–27, 1982. 22. B. S. Everitt, et al., “Miscellaneous Clustering Methods, in Cluster Analysis," 5th Edition, John Wiley & Sons, Ltd, Chichester, UK, 2011. 23. Standard Dataset Available: http://www.kasrl.org/jaffe_download.html Authors: Ajim A. Mokashi, Piyusha S. Hirpurkar

Paper Title: Hydraulic Scaling and Similitude from Model to Prototype Abstract: In this paper, the corresponding diameter of sediment in prototype is determine by using Shield's parameter. This simulation has been undertaken to similitude the relationship between prototype and its model. A model and prototype are designed to be similitude geometrically, dynamically and kinematically. The studies regarding sediment transport similitude for hydraulic modeling, a very few researcher gives the predictive methodologies. Firstly Shield was started to consider sediment particle motion after taking into account, the forces act on the sediment particles and then afterward apply the principles of similitude similarity. The sediment used in undistorted model(tiling flume) is sieved river sand. The mechanical sieve shaker, analysis was used to determine the mean particle size (d50=0.828mm) and the corresponding diameter of sediment in prototype is determine by using Shield's parameter which predict sediment size (d50=41.43mm). 65. Keyword: Sediment, Similitude, Model, Prototype, Shield's parameter, Hydraulic modeling. 390-392 References: 1. D.H.Swart, Hydraulic methods and modeling. "Hydraulic structures, equipment and water data acquisition systems", Vol. I,(1996), pp. 1-8,1996. 2. Dattatray Kisan Rajmane, "Simulation from Proto to Model", IJLTEMAS, Volume IV, Issue VIII, (2015), pp. 90-94. 3. George A. Griffiths, "Downstream hydraulic geometry and hydraulic similitude", water resources research, Vol. 39, NO. 4, (2003), pp.1-6. 4. Gokcen Bombar and Mehmet ukru Guney, "Experimental investigation of sediment transport in steady flows", Academic Journals Scientific, Research and Essays Vol. 5(6), (2010), pp. 582-591. 5. R. J. Garde and K. G. Ranga Raju, "Mechanics of sediment transportation and alluvial stream problems", revised third edition, new age international (p) limited publishers,2000(57-86) 6. R. J. Keller, "Experimental methods and physical modeling. Hydraulic structures", equipment and water data acquisition systems, Vol. I, (1981), pp. 224-244. 7. Valentin Heller, "Scale effects in physical hydraulic engineering models", Journal of Hydraulic Research. Vol. 49, No. 3, (2011), pp. 293–306 Authors: Tahseen A. Wotaifi, Eman S. Al-Shamery Mining of Completion Rate of Higher Education Based on Fuzzy Feature Selection Model and Paper Title: Machine Learning Techniques 66. Abstract: In the context of the great change in the labor market and the higher education sector, great attention is given to individuals with an academic degree or the so-called graduates class. However, each educational institution has a different approach towards students who wish to complete their university degree. 393-400 This study aims at (1) identifying the most important factors that directly affect the completion, and (2) predicting the completion rates of students for university degrees according to the system of higher education in the United States. Unlike previous studies, this project contributes to the use of the fuzzy logic technique on three methods for feature selection, namely the Correlation Attribute Evaluation, Relief Attribute Evaluation, and Gain Ratio Method. Since these three methods give different weight to the same attribute, the fuzzy logic technique has been used to get one weight for the attribute. A great challenge faced throughout this study is the curse of dimensionality, because the college scorecard dataset launched by the US Department of Education contains approximately (8000) educational institutions and (1825) features. Applying the method used in this study to identify important features lead to their reduction to only (79). Accordingly, two models have been used to predict the completion rates of students for their university studies which are the Random Forest and the Support Vector Regression with a Mean Absolute Error (MAE) value of (0.068) and (0.097) respectively.

Keyword: Completion Prediction of Students, Fuzzy-Selection Method, Filter Method, Mining Higher Education, Random Forest, and Support Vector Regression. References: 1. Daud, A., Aljohani, N. R., Abbasi, R. A., Lytras, M. D., Abbas, F., & Alowibdi, J. S. (2017). Predicting student performance using advanced learning analytics. In Proceedings of the 26th International Conference on World Wide Web Companion (pp. 415–421). 2. Agrawal, M., Ganesan, P., & Wyngarden, K. (2017). Prediction of Post-Collegiate Earnings and Debt. CS. 3. Wotaifi, T. A., & Al-Shamery, E. S. (2018). FUZZY-FILTER FEATURE SELECTION FOR ENVISIONING THE EARNINGS OF HIGHER EDUCATION GRADUATES. Compusoft, 7(12), 2969–2975. 4. Alharbi, Z., Cornford, J., Dolder, L., & De La Iglesia, B. (2016). Using data mining techniques to predict students at risk of poor performance. In 2016 SAI Computing Conference (SAI) (pp. 523–531). 5. Wright, E., Hao, Q., Rasheed, K., & Liu, Y. (2018). Feature Selection of Post-graduation Income of College Students in the United States. In International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (pp. 38–45). 6. Slater, S., Joksimović, S., Kovanovic, V., Baker, R. S., & Gasevic, D. (2017). Tools for educational data mining: A review. Journal of Educational and Behavioral Statistics, 42(1), 85–106. 7. Baradwaj, B. K., & Pal, S. (2012). Mining educational data to analyze students’ performance. ArXiv Preprint ArXiv:1201.3417. 8. Baepler, P., & Murdoch, C. J. (2010). Academic analytics and data mining in higher education. International Journal for the Scholarship of Teaching and Learning, 4(2), 17. 9. Jović, A., Brkić, K., & Bogunović, N. (2015). A review of feature selection methods with applications. In 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 1200–1205). 10. Hall, M. A. (1999). Feature selection for discrete and numeric class machine learning. 11. Refaeilzadeh, P., Tang, L., & Liu, H. (2009). Cross-validation. Encyclopedia of Database Systems, 532–538. 12. Robnik-Šikonja, M., & Kononenko, I. (1997). An adaptation of Relief for attribute estimation in regression. In Machine Learning: Proceedings of the Fourteenth International Conference (ICML97) (Vol. 5, pp. 296–304). 13. Luo, B., Zhang, Q., & Mohanty, S. D. (2018). Data-Driven Exploration of Factors Affecting Federal Student Loan Repayment. Retrieved from http://arxiv.org/abs/1805.01586 14. Boulesteix, A.-L., Janitza, S., Kruppa, J., & König, I. R. (2012). Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2(6), 493–507. 15. Kumar, M., & Thenmozhi, M. (2006). Forecasting stock index movement: A comparison of support vector machines and random forest. In Indian institute of capital markets 9th capital markets conference paper. 16. Li, Y., Bontcheva, K., & Cunningham, H. (2009). Adapting SVM for data sparseness and imbalance: a case study in information extraction. Natural Language Engineering, 15(2), 241–271. 17. Alasadi, S. A., & Bhaya, W. S. (2017). Review of Data Preprocessing Techniques in Data Mining. Journal of Engineering and Applied Sciences, 12(16), 4102–4107. 18. Thakur, M. (2007). The impact of ranking systems on higher education and its stakeholders. Journal of Institutional Research, 13(1), 83–96. 19. Eckel, P. D., & King, J. E. (2004). An overview of higher education in the United States: Diversity, access and the role of the marketplace. American Council on Education. 20. Buchmann, C., & DiPrete, T. A. (2006). The growing female advantage in college completion: The role of family background and academic achievement. American Sociological Review, 71(4), 515–541. 21. Wotaifi, T. A., & Al-Shamery, E. S. (2018). FUZZY-FILTER FEATURE SELECTION FOR ENVISIONING THE EARNINGS OF HIGHER EDUCATION GRADUATES. Compusoft, 7(12), 2969–2975. Authors: K. Krishnakumar, P. Ranjitha

Paper Title: An Examination on E-Service Quality in Online Shopping Abstract: Online shopping is the use of internet as means of communication with consumers, the field of e-commerce, e-service quality in online shopping has experienced a rapid growth in the recent years. The empirical study is attempted to focus on the e-service quality of online shopping in Salem city consumers. The major objectives of the research were to know the perception of online buyers about online service quality, to know the factors influencing and identify the problems of online shopping of e-service quality; with the help of structured questionnaire for primary data with sample size of 100 respondents. The statistical tools used for this 67. research study were the following: Percentage Analysis, One-sample t-test, Ranking Analysis and Chi-square test. 401-413

Keyword: Website Design, Service Ability, Privacy, Trust, Perceived Value. References: 1. Nazil Mohammadi Ahranjani (2015), “Investigating the effect of electronic service quality on customer trust to retailers”, International journal of Asian social science, Vol.5, Iss.9, pp.503-513. 2. Swaha Bhattacharya, Moumita Pal (2015), “perceived service quality and customer loyalty towards Flipkart.com – A study on young adults belonging to Kolkata city”, Indian journal of psychological science, Vol.5, Iss.5, pp.36-41. 3. Pooja Jain Dr.K.Anil kumar (2015), “Investigating the moderating role of switching cost in the relationship of e-service quality, perceived customer value, satisfaction and loyalty towards online travel agencies”, International journal in management and social science, Vol.3, Iss.3, pp.323-333. 4. Buyung Ramadhoni (2015), “Relationship between- service quality, E-Satisfaction, E-trust, E-Commitment in building customer E-Loyalty: A Literature Review”, International journal of business and management invention, Vol.4, Iss.2, pp.1-9. 5. Ahmad salih alnaser (2014), “E-Service quality conceptual approach”, Journal of advanced social research, Vol.4, Iss.4, pp.1-9. 6. Mohammad AI-Nasser, Rushami Zien Yusof (2013), “E-Service quality and its effect on consumers perceptions trust”, American journal of economics and business administration, Vol.1, Iss.2, pp.44-52. 7. Mohd Shoki Md.Ariff (2013), “Electronic service quality of Iranian internet banking”, Integrative business and economics, Vol.2, Iss.2, pp.555-571. 8. Saeed Behjati (2012), “Interrelation between E-Service quality and E-Satisfaction and loyalty”, European journal of business and management, Vol.4, Iss.9, pp.75-85. 9. Ramin Azadavar, Darush shahbazi (2011), “The role of security as a customer perception on customers online purchasing behavior”, International conference on software and computer, Vol.9, Iss.2, pp.174-181. 10. Kuang-Wen Wu (2011), “Customer loyalty explained recovery service quality: Implications of the customer relationship Re- Establishment for consumer electronics e-tailers”, Contemporary management research, Vol.7, Iss.1, pp.21-44. 11. Godwin J.Udo, Kallol K. Bagchi (2008), “Assessing web service quality dimensions: the e-service approach”, Information system, Vol.09, Iss.2, pp.313-322. 12. Gwo-Guang Lee (2005), “Customer perceptions of E-Service quality in online shopping” International journal of retail and distribution management, Vol.33, Iss.2, pp.161-176. 13. Bagher Abbaspour, Noor HazarinaHashim (2015), “The influence of website quality dimensions on customer satisfaction in travel website”, International journal of science commerce and humanities, Vol.3, Iss.5, pp.08-17. 14. Wang Lianqiang (2014), “A Study on the factors affecting the service quality of online transactions based on association analysis”, International conference on education, management and computing technology, Vol.18, Iss.4, pp.502-509. 15. www.wikipedia.com 16. www.ssrn.com Authors: Hadab Khalid Obayes, Nabeel Al – A'araji, Eman AL-Shamery

Paper Title: Examination and Forecasting of Drug consumption Based on Recurrent Deep Learning Abstract: The provision of pharmaceutical drugs in quantities appropriate to consumption is an important point in the pharmaceutical industry and storage of medicines, as the production of large quantities of unnecessary drugs leads to a longer storage of drugs. Meanwhile most medicines have a short shelf life. When the amount of production is less than required, this affects the satisfaction of the customer and the marketing of the drug. Time series analysis is the appropriate solution to this problem. Deep learning has been adapted for the purpose of time series analysis and a prediction of the required quantities drugs. A recurrent neural network with Long-Short Term Memory LSTM has been used by deep learning. The proposed methodology is based on the seasonal number of prescription required quantities with the number of quarters as indicators. The aim of the research is to forecast the drugs amount needed for one year. The proposed method is assessed using two types of evaluation. The first one is based on MSE and the visualization of the actual data and forecasted data. The proposed method has reached a low value of MSE and the visualization graph is semi-identical, whereas the second evaluation method compares the result of the proposed method with traditional forecasting method. Multiple linear regression is a traditional prediction method used with the data set, whose results are relatively good and promising compared to the results of the traditional method.

Keyword: Drugs consumption forecasting, DNN, LSTM, Recurrent long-short term memory-deep learning based drug analysis and forecasting, RNN. References: 68. 1. M. J. Iqbal, M. I. Geer, and P. A. Dar, “Evaluation of Medicines Forecasting and Quantification Practices in Various Evaluation of Medicines Forecasting and Quantification Practices in Various Public Sector Hospitals Using Indicator Based Assessment Tool,” J. Appl. Pharm. Sci., vol. 7 (12), no. December 2017, pp. 072–076, 2018. 414-420 2. P.-A. Cornillon, W. Imam, and E. Matzner-LZber, “Forecasting time series using principal component analysis with respect to instrumental variables Forecasting time series using principal component analysis with respect to instrumental variables,” Comput. Stat. Data Anal., vol. 52, no. July, pp. 1269 – 1280, 2008. 3. I. A. Gheyas and L. S. Smith, “A Neural Network Approach to Time Series Forecasting,” Proc. World Congr. Eng., vol. II, no. 1, pp. 1–5, 2009. 4. G. Lai, W.-C. Chang, Y. Yang, and H. Liu, “Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks,” SIGIR, no. July, 2018. 5. K. N. Mahajan, “Business Intelligent Smart Sales Prediction Analysis for Pharmaceutical Distribution and Proposed Generic Model,” vol. 8, no. 3, pp. 407–412, 2017. 6. Y. Tech, “A Deep Learning Algorithm to Forecast Sales of Pharmaceutical Products,” no. September, 2017. 7. R. Guseo et al., “Pre-launch forecasting of a pharmaceutical drug,” Int. J. Pharm. Healthc. Mark., vol. 11, no. 4, pp. 412–438, 2017. 8. A. Papana, D. Folinas, and A. Fotiadis, “Forecasting the consumption and the purchase of a drug,” Int. Conf. SUPPLY Chain. Funct., vol. 2, 2016. 9. N. K. Zadeh, M. M. Sepehri, and H. Farvaresh, “Intelligent Sales Prediction for Pharmaceutical Distribution Companies : A Data Mining Based Approach,” Hindawi Publ. Corp., vol. 2014, 2014. 10. T. Pham, T. Tran, and D. Phung, “Predicting healthcare trajectories from medical records : A deep learning approach Predicting healthcare trajectories from medical records : A deep learning approach,” no. October, 2017. 11. E. AL-Shamery and A. AL-haq, “An Optimized Feed Forward Neural Network for Reducing Error Based Stoch Market Prediction,” J. Eng. Appl. Sci., vol. 13, no. Special Issue 5, pp. 4616–4621, 2018. 12. F. Jiang et al., “Artificial intelligence in healthcare : past , present and future,” stroke Vasc. Neurol., vol. first publ, 2017. 13. E. AL-Shamery and A. AL-haq, “Enhancing Prediction of NASDAQ Stock Market Based on Technical Indicators,” J. Eng. Appl. Sci., vol. 13, no. Special Issue 5, pp. 4630–4636, 2018. 14. H. Khalid Obayes, N. Al – A’araji, and E. AL-Shamery, “Deep Neural Network for Enhancing Drug-Utilization Clustering,” Int. J. Eng. Technol., vol. 8, pp. 290–298, 2019. 15. J. Koutn and K. Greff, “A Clockwork RNN,” arXiv, vol. 1402.3511v, 2014. 16. I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. Aaron, 2016. Authors: Abdhesh Kumar Singh, Pramod Pathak , Saumya Singh

Paper Title: Disruption in Indian Cellular Telecom Market: Critical Success Factors Abstract: Cellular telephony is today acting as fulcrum in driving the socio-economicdevelopment of a country. The objective of this paper is to delve deeper into the Indian telecom market’s opportunities and challenges in the fast changing technology and cost ecosystemandspecifically factoring in the critical success factors of an aggressive new telecom operator - Reliance Jio. This also encapsulates what government has been doing to take the telecom forward to meet its visions. This encompasses the data inputs from online secondary sources along with voice of customers with the help of primary data (data collected during Dec 2018-Feb 2019) basis a questionnaire based field survey and interview of industry experts.

Keyword: Telecom Marketing, Rural Telecom, Disruption, Competition, Jio, India. References: 1. Aithal Rajesh K and Mokhopadhyay Arunabha, 2002, Rural Telecom in India: Marketing Issues and Experiences from Other Countries” cisco.com, 2013 2. Constantiou Ioanna D. (Telematics and Informatics, Copenhagen Business School, Denmark, 2009) 3. Gupta,R.,&Jain,K.Adoption behaviour ofruralIndiaformobiletelephony:Amultigroupstudy. Telecommunications Policy 69. (2015), http://dot.gov.in/national-telecom-policy-1994 (accessed, 6/6/2019) 4. https://economictimes.indiatimes.com/industry/services/retail/reliance-retail-may-use-5k-jio-points-for-e-comm- connect/articleshow/67069324.cms?from=mdr 421-426 5. https://main.trai.gov.in/sites/default/files/A_TwentyYear_Odyssey_1997_2017.pdf 6. https://www.business-standard.com/article/companies/airtel-staff-count-shrinks-by-1-805-in-a-year-100-000-telecom-jobs- at-risk-117103101163_1.html 7. https://www.businesstoday.in/sectors/telecom/mukesh-ambani-reliance-jio-plans-hire-80000-employees-this-financial- year/story/275742.html 8. https://www.cisco.com/c/en/us/solutions/collateral/service-provider/vni-service-adoption- forecast/Cisco_BhartiAirtel_CS.html 9. https://www.ibef.org/industry/telecommunications.aspx 10. Katrina Kosec, Leonard Wantchekon, 2018 11. McKinsey Report on “Global flows in Digital Age: How Trade, Finance, People and Data connect the World Economy ”, P- 122,Apr,2014(https://qtxasset.com/cfoinnovation/field/field_p_files/white_paper/WP_McKinsey%20Global%20Institute_G lobal%20Flows%20in%20a%20Digital%20Age.pdf) 12. mospi.gov.in, India in figures, 2018, p6, p12 of 37). 13. Randolph A Jaramillo (2002) 14. Telecomwatch.in (Feb 2019, Mar 2019) 15. TRAI (https://main.trai.gov.in/release-publication/reports/performance-indicators-reports)-The Indian Telecom Services Performance Indicators, January-March 2012 – 2019, Dec 2018, Jun 2018) 16. usof.gov.in 17. YEBOAH ASIAMAH, Responsibility (CSR) And Ethics in the Telecommunication Industry in Ghana: A case Study of MTN Ghana Authors: S. Gopalsamy, AV. Karthick

Paper Title: Security enhancement of Online Accounting Data from Cyber Attacks Abstract: The growing use of digital technology among businesses has highlighted the significance and function of cybersecurity as a fresh dimension of risk management, not least because cyber threats and hazards have drawn considerable public attention. Users typically do not understand the precise place of their information or the other jointly recorded information sources with theirs. The exchange of data on cybersecurity lists a comprehensive list of prospective advantages for government and private sector organizations. Cloud Accounting (CA) plays a predominant role in corporate finance. CA is a type of lease based accounting services. Client access the accounting package anywhere in the world. The major issue in Accounting is to secure accounting data. The aim of this is to provide a deep understanding of security vulnerabilities and solutions in online accounting with specific reference to cloud accounting. The proposed efficient double secured accounting environment for business using bio-metric based Iris, Rivest Shamir Adleman (RSA) and Advanced Encryption Standard (AES) algorithms provides the double standard highest security for online accounting applications. The author designing a prototype model to solve the issues related to security in the cloud accounting problem, this 70. model is used to tackle the intruders from data hijacking. The results suggested that the proposed system gives an enhanced security mechanism in terms of high privacy and confidentiality. The major contribution of the 427-431 study is the use of protecting valuable data from intruders.

Keyword: data; security; accounting; corporate finance; biometric; Iris; encryption; client. References: 1. Ahmed Mihoob, Carlos Molina Jimenez and Santosh Shrivastava, “A Case for Consumer Centric Resource Accounting Models”, IEEE 3rd International Conference on Cloud Computing, pp. 506-512, 2010. 2. Ahmed Mihoob, Carlos Molina Jimenez, and Santosh Shrivastava, “Consumer Side Resource Accounting in the Cloud”. IFIP, pp. 58-72, 2011. 3. Akhil Behl, Kanika Behl, “An analysis of Cloud Computing Security Issues”, IEEE, pp. 109- 114, 2012. 4. Akshita Bhandari, Ashutosh Gupta, Debasis Das, “Secure Algorithm for Cloud Computing and Its Applications”, IEEE, pp.188- 192, 2016. 5. Anane Nadjia, Anane Mohamed, “AES IP for Hybrid Cryptosystem RSA-AES”, 12th International Multi-Conference on Systems, Signals & Devices, IEEE, pp.1-6, 2015. 6. B.Venkatesh, V.Karthik, M.Gowtham, “Enhancing Network Security In Cloud Computing Using Cipher Cloud Mechanism”, Proc. of ICICST, pp. 253- 256, 2016. 7. Bogdan, Iuliana, “Traditional Accounting Vs. Cloud Accounting”, AMIS, pp. 106-125, 2013. 8. Ceslovas Christauskas, Regina Miseviciene, “Cloud Computing Based Accounting for Small to Medium Sized Business”, Inzinerine Ekonomika-Engineering Economics, pp. 14-21, 2012. 9. AV.Karthick, Dr.M.Ayisha Millath, “Management of Digital Libraries for Active Learning Environment: Trends and Challenges”, Library Philosophy and Practice, 2019. 10. Ewnetu Bayuh Lakew, Lei Xu, Francisco Hernandez-Rodriguez, Erik Elmroth, Claus Pahl, “A Synchronization Mechanism for Cloud Accounting Systems”, IEEE International Conference on Cloud and Autonomic Computing, pp. 111-120, 2014. 11. Francis Pol C. Lim, “Impact of Information Technology on Accounting Systems”, Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, pp. 93- 106, 2013. 12. Francisco Airton Pereira da Silva, Paulo Anselmo da Mota Silveira Neto, “Monext: An Accounting Framework for Infrastructure Clouds”, IEEE 12th International Symposium on Parallel and Distributed Computing, pp. 26-33, 2013. 13. Francisco Airton Silva, Paulo Neto, Vinicius Garcia, Fernando Trinta and Rodrigo Assad, “Accounting Federated Clouds based on the JiTCloud Platform”, 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, pp. 186-187, 2013. 14. Igor Ruiz Agundez, Yoseba K. Penya and Pablo G. Bringas, “A Flexible Accounting Model for Cloud Computing”, Annual SRII Global Conference, pp. 277- 284, 2011. 15. Igor Ruiz Agundez, Yoseba K. Penya and Pablo G. Bringas, “Cloud Computing Services Accounting”, International Journal of Advanced Computer Research, pp. 7-17, 2012. 16. Jan Mazur, “Fast Algorithm for Iris Detection”, Springer-Verlag Berlin Heidelberg, pp. 858–867, 2007. 17. Jiao Feng, “Cloud Accounting: the transition of accounting infor- mation model in the big data background”, In International Conference on Intelligent Transportation, Big Security and Smart City, pp. 207 – 211, 2015. 18. Juan M. Colores Vargas, Mireya Garcia Vazquez, Alejandro Ramirez Acosta, Hector Perez Meana and Mariko Nakano Miyatake, “Video Images Fusion to Improve Iris Recognition Accuracy in Unconstrained Environments”, Springer-Verlag Berlin Heidelberg – MCPR, pp. 114-125, 2013. 19. K.Berlin, S.S.Dhenakaran, “A Novel Encryption Technique For Securing Text Files”, Proc. of ICICST, pp. 179- 182, 2016. 20. Keke Gai, Longfei Qiu, Min Chen, Hui Zhao,Meikang Qiu, “SA-EAST: Security-Aware Efficient Data Transmission for ITS in Mobile Heterogeneous Cloud Computing”, ACM Transactions on Embedded Computing Systems, pp.60-82, 2017. 21. Mihalache D, Arsenie Samoil, “Cloud Accounting”, Ovidius University Annals, Economic Sciences Series, pp. 782-787, 2011. 22. Otilia Dimitriu, “Cloud Accounting – A New Player in the Economic Context”, Economy and Management, pp. 727- 732, 2014. 23. Otilia Dimitriua, Marian Matei, “A New Paradigm for Accounting through Cloud Computing”, Emerging Markets Queries in Finance and Business, pp. 840-846, 2014. 24. Otilia Dimitru, Marain Matel, “The expansion of accounting to the Cloud”, SEA – Practical Application Science, pp. 237- 240, 2014. 25. Patil Madhubala R, “Survey on Security Concerns in Cloud Computing”, IEEE, pp. 1458 – 1462, 2015. 26. P. Ravi Kumar, P. Herbert Raj, P. Jelciana, “Exploring Data Security Issues and Solutions in Cloud Computing”, ICSCC - ScienceDirect - Procedia Computer Science, pp. 691–697, 2018. 27. Syed Asad Hussain, Mehwish Fatima, Atif Saeed, Imran Raza, Raja Khurram Shahzad, “Multilevel classification of security concerns in cloud computing”,Elsevier BV - Applied Computing and Informatics, pp. 57-65, 2016. 28. Talal Halabi, Martine Bellaiche, “A broker-based framework for standardization and management of cloud security-SLAs”, Computers and Security, pp.1-41, 2018. 29. Valentina Casola, Alessandra De Benedictis, Massimiliano Rak, Umberto Villano, “Security by design in Multi-Cloud Applications: An Optimization Approach”, Information Sciences, pp.1-47, 2018. 30. Varun Bhardwaj, Anamika Sharma, Gaurav Somani, “Client-Side Verifiable Accounting in Infrastructure Cloud”, IEEE, pp. 361- 366, 2015. 31. Wenjun Tang, “Key Technology analysis and application research of Accounting Informationization under Cloud Environment”, International Conference on Intelligent Transportation Big Data and Smart City, pp. 507 – 510, 2015. 32. Yaliang Zhao, Laurence T. Yang, Jiayu Sun, “A Secure High-Order CFS Algorithm on Clouds for Industrial Internet of Things”, IEEE Access, 2018. 33. Yan Yang, Xingyuan Chen, Hao Chen, Xuehui Du, “Improving Privacy and Security in Decentralizing Multi Authority Attribute Based Encryption in Cloud Computing”, IEEE Access, pp.1-17, 2018. 34. Zhang Cancan, “Challenges and Strategies of Promoting Cloud Accounting”, Eastern Academic Forum, pp. 90-94, 2014. 35. Zhengping Wu, Nailu Chu, Peng Su, “Improving Cloud Service Reliability - A System Accounting Approach”, IEEE Ninth International Conference on Services Computing, pp. 90 – 97, 2012. 36. Mozhdeh Sadighi, “Accounting System on Cloud: A Case Study”, 11th International Conference on Information Technology: New Generations, pp. 629- 632, 2014. 37. Minh T. Nguyen, Pavel. B. Khorev, “Information risks in the cloud environment and cloud-based secure information system model”, International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE), IEEE xplore, 2019. 38. AV. Karthick, E. Ramaraj, R. Kannan, “An efficient Tri Queue job Scheduling using dynamic quantum time for cloud environment”, International Conference on Green Computing, Communication and Conservation of Energy (ICGCE), pp. 871- 876, 2013. 39. AV.Karthick, E. Ramaraj, R. Ganapathy Subramanian, “An Efficient Multi Queue Job Scheduling for Cloud Computing”, World Congress on Computing and Communication Technologies, pp. 164-166, 2014. 40. Erik Elmroth, Fermn Galan Marquezy, Daniel Henriksson, and David Perales Ferrera, “Accounting and Billing for Federated Cloud Infrastructures”, Eighth International Conference on Grid and Cooperative Computing, pp. 268 – 275, 2009. Authors: Kavitha Rani Mari, Suriyavathana Muthukrishnan, Punithavathi Manogaran, Anandhi Eswaran Screening of Phytochemical Compounds and Assessment of Antiurolithiatic Activity of Pisonia Paper Title: Alba Leaves Extracts against DNA Damage Abstract: This work investigate the Phytochemical constituents of Pisoniaalba (PA) leaves using standard protocols and to determine its DNA damage inhibition and Antiurolithiatic capability. Dried leaves of Pisoniaalba were used to screen and quantify the phyto constituents in different organic solvents extracts that are analysed by GCMS, FTIR and HPTLC. In the presence of PUC18 plasmid DNA, the DNA damage inhibition 71. assay was performed by photolysing H2O2 with UV radiation and agarose gel electrophoresis with irradiated DNA. The invivo antiurolithic assay was performed by nucleation method. Pisoniaalbain's phytochemical 432-435 analysis reveals the existence of secondary metabolite components including glycosides, resins, phenols, terpenoids, flavonoids, tannins, steroids, and alkaloids, etc.. ELPA express the maximum quantity of phenols, flavonoids, alkaloids and terpenoids which were 30.44 ±0.65 mg TAE/g extract, 28.51 ± 1.19 mg RE/g extract, 28.08 ± 0.08 mg of AE/g of extract, 29.94 ± 0.32 mg RE/g extract respectively. The GC-MS assessment findings confirmed the presence of nine ELPA phyto compounds accompanied by eleven ALPA phytoc ompounds. It was also observed that Pisoniaalba leaves prevents DNA damage in UV and H2O2 treated plasmid DNA. The invitro Antiurolithiatic research indicates that ELPA was more efficient in blocking calcium oxalate nucleation. From the obtained results it was proven that the Pisonia alba leaves has potential secondary metabolites with therapeutic role mainly against urolithiasis. Both invitro and in vivo analysis demonstrates that ELPA significantly reduces crystal formation that are causative of renal stones. These evidences suggest that Pisoniaalbacan be further investigated for the prevention and treatment of urolithiais.

Keyword: ALPA, DNA fragmentation, ELPA, urolithiasis, Pisoniaalba, Nucleation References: 1. Alok S, Jain SK, Verma A, Kumar M, Sabharwal M. Pathophysiology of kidney, gallbladder and urinary stones treatment with herbal and allopathic medicine: A review. Asian Pacific Journal of Tropical Disease. 2013 Dec 1;3(6):496-504. 2. Broustas CG, Lieberman HB. DNA damage response genes and the development of cancer metastasis. Radiation research. 2014 Jan 7;181(2):111-30. 3. Madan S, Ahmad S. In vitro inhibition of calcium oxalate nucleation by extract-based fractions of aerial parts and roots of Aervalanata (Linn.) Juss. exSchult. Indian Journal of Pharmaceutical Sciences. 2018 Jan 30;79(6):957-64. 4. Nagal A, Singla RK. Herbal resources with antiurolithiatic effects: a review. Indo Glob J Pharm Sci. 2013;3(1):6-14. 5. Neha U, Kant TS, Anant S, Ankit S, Kumar MS. Antiurolithiatic effect of TerminaliabelliricaRoxb. fruits on ethylene glycol induced renal calculi in rats. Indo American Journal of Pharmaceutical Research. 2015;5(5):2031-40. 6. Rosa M, Usai P, Miano R, Kim FJ, Agrò EF, Bove P, Micali S. Recent finding and new technologies in nephrolithiasis: a review of the recent literature. BMC urology. 2013 Dec;13(1):10. 7. Tiwari A, Soni V, Londhe V, Bhandarkar A, Bandawane D, Nipate SO. An overview on potent indigenous herbs for urinary tract infirmity: urolithiasis. Asian J Pharm Clin Res. 2012;5(1):7-12. 8. Thillaivanan S, Samraj K, Parthiban P. A Review on Anti–Arthritic Herbs in Siddha Medicine. International Journal of Pharmaceutical Research. 2013 Oct;5(4):13. 9. Vimalavalli1 S, RajiSugumarV.Anti-Diabetic Activity of PisoniagrandisR.Br. leaves against streptozotocin (STZ) induced diabetes mellitus in rats. Int J Phytopharm.2015 ;6(3):156-160. 10. VisnupriyaC, and Fauzia Ahmed. Potency of two commonly available plants Pisoniaalbaandmukiamaderasapatana in the health industry.Int j Current Micro Applied Sci.2017 Jan; 6(1):721-732. Authors: Ritu Garg, R. K. Singh

Paper Title: Detecting Model Clones using Design Metrics Abstract: The cloning in software is a frequent phenomenon that leaves a negative impact among the product lines or the version control where the developer is involved in the evolution of software system due to any enhancement or changing requirements that leads to a release of new version. With the advent of MDD, identification of clones shifted from code to models to tackle risks at early stages. Due to the renaming of model elements, some model clones are missed that reports secondary clones instead of primary. So, in order to increase recall of clones in models we have proposed a hybrid approach based on the tree, lexical and metric approaches and validated it using SDMetric tool followed by analysis of detection of exact, renamed clones and modified clones. It provides one to one mapping in the form of corresponding primary clones with maximal matching that helps to reduce the domain for comparison of code at the implementation level. Such clones need to be identified among the versions and the stable part with least changes acts as a pattern and can be reused by the product lines.

Keyword: Cloning Model Clones Reengineering Software Evolution Software Maintenance. References: 1. Fowler, Martin, Kent Beck, Refactoring: improving the design of existing code, Addison-Wesley Professional, 1999. 2. D. Rattan, M. Singh, R. Bhatia, Design and development of an efficient software clone detection technique, Diss. 2015. 3. H. Störrle, Effective and efficient model clone detection, Software, Services, and Systems, Springer International Publishing 72. (2015) 440-457. 4. C. K. Roy, James R. Cordy, A survey on software clone detection research, Queen’s School of Computing TR 541.115 (2007) 64- 68. 5. Jeremy R. Pate, Robert Tairas, Nicholas A. Kraft. Clone evolution: a systematic review, Journal of software: Evolution and 436-443 Process 25.3 (2013) 261-283. 6. F. Mondal, Analyzing Clone Evolution for Identifying the Important Clones for Management. Diss. 2017. 7. N. H. Pham, et al, Complete and accurate clone detection in graph-based models, Proceedings of the 31st International Conference on Software Engineering, IEEE Computer Society, 2009. 8. F. Deissenboeck, et al., Model clone detection in practice., Proceedings of the 4th International Workshop on Software Clones. ACM, 2010. 9. D. Rattan, R. Bhatia, M. Singh, Software clone detection: A systematic review, Information and Software Technology 55.7 (2013) 1165-1199. 10. MdR Islam, Minhaz F. Zibran, A Comparative Study on Vulnerabilities in Categories of Clones and Non-Cloned Code, Software Analysis, Evolution, and Reengineering (SANER), 2016 IEEE 23rd International Conference on. Vol. 3. IEEE, 2016. 11. H. Störrle, Towards clone detection in UML domain models, Proceedings of the Fourth European Conference on Software Architecture: Companion Volume. ACM, 2010. 12. Https://msdn.microsoft.com/en-us/library/dd409416.aspx. 13. Http://www.sdmetrics.com/downman.html. 14. M. Stephan, A mutation analysisbased model clone detector evaluation framework, Diss. 2014. 15. M. Stephan, J. R. Cordy, Model Clone Detector Evaluation Using Mutation Analysis, ICSME (2014) 633-638. 16. G. Mahajan, M. Bharti, Implementing a 3-way approach of clone detection and removal using PC Detector tool, Advance Computing Conference (IACC), 2014 IEEE International IEEE 2014. 17. U. Mansoor, Handling High-Level Model Changes Using Search Based Software Engineering, (2017). 18. Keivanloo, Source Code Similarity and Clone Search. Diss. Concordia University, 2013. 19. P. V. Kavita, an analysis of OO design quality measurement tool for UML 20. Fowler, Martin, Kent Beck, Refactoring: improving the design of existing code, Addison-Wesley Professional, 1999. 21. D. Rattan, M. Singh, R. Bhatia, Design and development of an efficient software clone detection technique, Diss. 2015. 22. H. Störrle, Effective and efficient model clone detection, Software, Services, and Systems, Springer International Publishing (2015) 440-457. 23. C. K. Roy, James R. Cordy, A survey on software clone detection research, Queen’s School of Computing TR 541.115 (2007) 64- 68. 24. Jeremy R. Pate, Robert Tairas, Nicholas A. Kraft. Clone evolution: a systematic review, Journal of software: Evolution and Process 25.3 (2013) 261-283. 25. F. Mondal, Analyzing Clone Evolution for Identifying the Important Clones for Management. Diss. 2017. 26. N. H. Pham, et al, Complete and accurate clone detection in graph-based models, Proceedings of the 31st International Conference on Software Engineering, IEEE Computer Society, 2009. 27. F. Deissenboeck, et al., Model clone detection in practice., Proceedings of the 4th International Workshop on Software Clones. ACM, 2010. 28. D. Rattan, R. Bhatia, M. Singh, Software clone detection: A systematic review, Information and Software Technology 55.7 (2013) 1165-1199. 29. MdR Islam, Minhaz F. Zibran, A Comparative Study on Vulnerabilities in Categories of Clones and Non-Cloned Code, Software Analysis, Evolution, and Reengineering (SANER), 2016 IEEE 23rd International Conference on. Vol. 3. IEEE, 2016. 30. H. Störrle, Towards clone detection in UML domain models, Proceedings of the Fourth European Conference on Software Architecture: Companion Volume. ACM, 2010. 31. Https://msdn.microsoft.com/en-us/library/dd409416.aspx. 32. Http://www.sdmetrics.com/downman.html. 33. M. Stephan, A mutation analysisbased model clone detector evaluation framework, Diss. 2014. 34. M. Stephan, J. R. Cordy, Model Clone Detector Evaluation Using Mutation Analysis, ICSME (2014) 633-638. 35. G. Mahajan, M. Bharti, Implementing a 3-way approach of clone detection and removal using PC Detector tool, Advance Computing Conference (IACC), 2014 IEEE International IEEE 2014. 36. U. Mansoor, Handling High-Level Model Changes Using Search Based Software Engineering, (2017). 37. Keivanloo, Source Code Similarity and Clone Search. Diss. Concordia University, 2013. 38. P. V. Kavita, an analysis of OO design quality measurement tool for UML using SDMetrics, International Journal of Innovation in Engineering Research and Management ISSN 2348-4918, ISO 2000-9001 certified, E 4.3 (2017). 39. Ragkhitwetsagul, Chaiyong, J.Krinke, D. Clark., Similarity of source code in the presence of pervasive modifications, Source Code Analysis and Manipulation (SCAM), 2016 IEEE 16th International Working Conference on IEEE 2016. 40. Al Hussein, Abdullah, An Object-Oriented Software Metric Tool to Evaluate the Quality of Open Source Software, International Journal of Computer Science and Network Security (IJCSNS) 17.4 (2017) 345 Authors: M.V. Ramesh, P.Sowjanyaa

Paper Title: IoT Based Energy Meter with Theft Detect Abstract: The idea of this paper is to have energy meter design using IoT (Internet of Things) and implementing based on microcontroller. The buyer has the possibility of pre paying/ post paying the electricity usage on schedule. If not paid, the utility centres can switch off the supply remotely. The monitoring of the electrical energy consumption can be made easy by the customer on their mobile/PC.Power theft is detected by using current sensors. Theft detected will be notified on service provider end. The IoT operation is performed by Wi-Fi unit. The meter data is send to webpage that can be accessed from IP address. IoT has made a virtual network between the human and this physical world and has drastically changed the way business works. This can be accomplished by sending the ideal stage between the gadgets for data transmission. In this paper, IoT technology is utilized in distribution system to detect the power theft.

Keyword: IoT, Energy meter, Microcontroller, WIFI, Power theft. References: 1. Win Hlaing, Somchai Thepphaeng, Varunyou Nontaboot, Natthanan Tangsunantham, Tanayoot Sangsuwan, Chaiyod Pira. 73. Implementation of WiFi-Based Single Phase Smart Meter for Internet of Things (IoT) .5th IEEE Congress, Pattaya, Thailand, 8- 10 March 2017. 2. Dineshkumar.K,Prabhu Ramanathan, Sudha Ramasamy.Development of ARM Processor based Electricity Theft Control System 444-448 using GSM Network. International Conference on Circuit, Power and Computing Technologies [ICCPCT], 2015. 3. Nabil Mohammad, Anomadarshi Barua and Muhammad Abdullah Arafat.A Smart Prepaid Energy Metering System to Control Electricity Theft.2013 International Conference on Power, Energy and Control (ICPEC). 4. Mohammad Hossein Yaghmaee,Hossein Hejazi.Design and Implementation of an Internet of Things Based Smart Energy Metering.2018 the 6th IEEE International Conference on Smart Energy Grid Engineering. 5. R. E. Ogu and G. A. Chukwudebe,Development of a Cost-Effective Electricity Theft Detection and Prevention System based on IoT Technology.2017 IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON). 6. Landi.C.; Dipt.diIng.dellInf., SecondUniv.diNapoli, Aversa,Italy; Merola,p.; Ianniello,G, ARM –based energy management system using smart meter and webserver, IEEE Instrumentation and measurement Technology conference Binjiang, pp.1-5, May 2011. 7. Garrab,A.;Bouallegue,A.;Ben Abdallah, A new AMR approach for energy saving in smart grids using smart meter and power line communication,IEEE first conference on Renewable energies and vehicular Technology(REVET),pp.263-269,march 2012. 8. B.Ravali, R.P.ManikantaKumar, V.Aditya, CH.Amrutha, N.Veeraiah,IoT Based Energy Meter Reading, Theft Detection and Energy Control Using GSM ,International Journal of Engineering Research in Computer Science and Engineering (IJERCSE) Vol 5, Issue 3, March 2018. 9. Srujana Uddanti, Christeena Joseph, P.C.Kishoreraja.IoT Based Energy Metering and Theft Detection.International Journal of Pure and Applied Mathematics Volume 117 No. 9 2017, 47-51. 10. Dr. S.S. Sayyed, Roshani Choudhari, Prashant Tribhuvan, Sagar Salvi, Anuradha Amte Theft Detection and Disconnection in Automated Electricity Energy Meter: A Survey Internal (IJRASET) ISSN: Volume 6 Issue I, January 2018. Authors: Tushar Kumar

Paper Title: Effect of Rapping System Malfunctions on ESP Performance 74. Abstract: In an attempt to improve Electrostatic precipitator (ESP) performance, the functioning of rapping system plays a vital role. Malfunctioning of rapping system will lead to reentrainment of fly ash into the 449-452 gas stream and back corona in some cases. Proper upkeep of Rapping system and optimization of rapping frequency will lead to minimise reentrainment as well as avoidance of back corona. This paper explains various factors associated with Rapping system malfunctioning, its impact on ESP performance, identification of issues and ways to address issues related to ash removal from collecting plates. Some of the issues can be identified using V-I curve analysis while others can be identified by visual inspection during shut down of ESP. Keyword: ESP performance Rapping system V-I Curve Back corona References: 1. Electrostatic Precipitation by Sabert Oglesby, Jr. and Grady B. Nichols, Marcell Dekker Inc, New York. 2. Electrical Operation of Electrostatic Precipitators by Ken Parker, IEE London. 3. Electrostatic Precipitators, James H. Turner,Phil A. Lawless, Toshiaki Yamamo to David W. Coy, Research Triangle Institute, Research Triangle Park, NC 27709. 4. ESP Design and Industrial Applications by Kjell Porle, ICESP XIII, Bangalore. Authors: Dennis Paulino, Arsénio Reis, Hugo Paredes, Hugo Fernandes, João Barroso

Paper Title: Usage of Artificial Vision Cloud Services as Building Blocks for Blind People Assistive Systems Abstract: This study has the objective of select the best service at image processing and recognition, running in the cloud, and best suited for usage in systems to aid and improve the daily lives of blind people. To accomplish this purpose, a set of candidate services was built, including Microsoft Cognitive Services and Google Cloud Vision. A test mobile app was developed to automatically take pictures, which are sent to the online cloud services for processing. The results and the functionalities were evaluated with the aim to measure their accuracy and relevance. The following variables were registered: relative accuracy, represented by the ratio of the number of accurate results vs. the number of results shown; confidence degree, representing the service accuracy (when provided by the service); and relevance, identifying situations that can be useful in the daily lives of the blind people. The results have shown that these two services, Microsoft Cognitive Services and Google Cloud Vision, provided good accuracy and significance, in supporting systems to help blind people in their daily tasks. It was chosen some functionalities in two APIs of services running in the cloud like face identification, image description, objects, and text recognition.

Keyword: Blind people Cloud services Image recognition Mobile apps Android References: 1. WHO, 2016. “WHO | Blindness: Vision 2020 - The Global Initiative for the Elimination of Avoidable Blindness” http://www.who.int/mediacentre/factsheets/fs214/en/ 2. R Manduchi, Mobile Vision as Assistive Technology for the Blind: An Experimental Study, 13th International Conference on Computers Helping People with Special Needs (ICCHP) (2012). 3. V Santos, L Amaral, H Mamede, Information Systems Planning - How to enhance creativity?, CENTERIS'2011 - Conference on Enterprise Information Systems 75. 4. A Reis, D Paulino, H Paredes, J Barroso, Using Intelligent Personal Assistants to Strengthen the Elderlies’ Social Bonds, Universal Access in Human–Computer Interaction, Human and Technological Environments 01 (2017) 593-602. 5. B Gonçalves, T Rocha, A Reis, J Barroso, AppVox: An Application to Assist People with Speech Impairments in Their Speech 453-458 Therapy Sessions, Recent Advances in Information Systems and Technologies 03 (2017) 581-591. 6. W Xindong, Z Xingquan, W Gong-Qing, D Wei, Data Mining with Big Data, IEEE Transactions on Knowledge and Data Engineering 26 (2014). 7. P Domingos, A Few Useful Things to Know about Machine Learning, Communications of the ACM 55 (2012) 78-87. 8. Y Bengio, Deep Learning of Representations: Looking Forward, Lecture Notes in Computer Science 7978 (2013) 1-37. 9. K Hallman, Artificial Intelligence, Zygotes, and Free Will, Res Cogitans 6 (2015) 2155-4838. 10. R Kamberov, C Granell, V Santos, Sociology Paradigms for Dynamic Integration of Devices into a Context-Aware System, Journal of Information Systems Engineering & Management 2 (2017) 2468-4376. 11. INESC TEC, 2016. “ Olha o CE4BLIND”, https://www.inesctec.pt/csig/noticias-eventos/nos-na-imprensa/olha-o-ce4blind-quer- dizer-tecnologias-para-aumentar-a-autonomia-dos-invisuais plural-singular/ 12. T Rocha, H Fernandes, A Reis, D Paulino, H Paredes, J Barroso, Assistive Platforms for the Visual Impaired: Bridging the Gap with the General Public, Recent Advances in Information Systems and Technologies 03 (2017) 602-608. 13. INESC TEC, 2016. “INESC TEC”, https://www.inesctec.pt/ 14. Reis A., Barroso I., Monteiro M., Khanal S., Rodrigues V., Filipe V., Paredes H., Barroso J., 2017. “Designing Autonomous Systems Interactions with Elderly People”. Universal Access in Human–Computer Interaction. Human and Technological Environments, 01/2017: pages 603-611; , ISBN: 978-3-319-58699-1, DOI:10.1007/978-3-319-58700-4_49 15. T Adão, M Luís, H Paredes, J Barroso, Navigation module of Blavigator prototype, World Automation Congress 2012, http://ieeexplore.ieee.org/document/6320942/ 16. Adão T., 2011. “Módulo de Navegação para Cegos (Smartvision)”, UTAD, http://hdl.handle.net/10348/2094 17. Clarifai, 2016. “Clarifai”, https://www.clarifai.com/technology 18. Microsoft, 2016. “Microsoft Cognitive Services - APIs”, https://www.microsoft.com/cognitive-services/en-us/apis 19. Google, 2016. “Vision API - Image Content Analysis | Google Cloud Platforms” https://cloud.google.com/vision/ 20. ABBYY, 2016. “Abby Cloud OCR SDK” ,http://ocrsdk.com/ 21. P. B. Kruchten, The 4+1 View Model of architecture, IEEE Software 12 (1995) 42–50. 22. D. E. Perry, A. L. Wolf, The three views (processing, data, and connection) in software architecture by Perry and Wolf, ACM SIGSOFT Software Engineering Notes 17 (1992) 40–52 Authors: Deepthi Vaddella, Cheepirisetti Sruthi, Bharath Kumar Chowdary, Somula Ramasubbareddy

Paper Title: Proactive Healthcare Monitoring using IOT 76. Abstract: Internet of Things (IOT) is a figuring technique, where each question is provided with sensors, small scale controllers and handsets for enabling correspondence and is made with fitting convention stacks that 459-464 encourage them associating with each other and speaking with the clients. In IOT based human services, different circulated gadgets consolidate, examine and impart continuous medicinal information to the cloud, therefore making it conceivable to assemble, store and break down the gigantic amount of information in numerous new structures and enact setting based cautions. This novel information obtaining worldview licenses consistent and present medicinal data access from any associated gadget over the net. As the majority of the gadgets utilized in IOT are limited in battery control, it's best to limit the capacity utilization to fortify the lifetime of the social insurance framework. This work clarifies the execution of an IOT situated In-doctor's facility human services framework utilizing ZigBee work convention. The medicinal services framework execution can sporadically screen the physiological parameters of the In-doctor's facility patients. Hence, IOT spectred gadgets in the meantime upgrade the standard of consideration with customary perception and cut back the estimation of consideration and effectively take part in information combination and investigation of the equivalent.

Keyword: In-doctor's facility human services framework utilizing ZigBee work convention. References: 1. Koppar, and Venugopalachar Sridhar, “A workflow solution for electronic health records to improve-healthcare delivery efficiency in rural India,” In eHealth, Telemedicine, and Social Medicine, 2009. 2. Bhatia, Gresha, and Algenti Lala, “Implementation of Cloud computing technology for the improvement of entire healthcare services in India,” In Advances in Technology and Engineering (ICATE), 2013 International Conference on, pp. 1–5, IEEE, 2013. 3. Perumalraja, “Smart wireless healthcare monitoring for drivers community,” ICCSP, 2014 International Conference on, pp. 1105–1108, IEEE, 2014 4. Chipara, Octav, and Gruia-Catalin Roman, “Reliable clinical monitoring using wireless sensor networks: experiences in a step- down hospital unit,” In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, ACM, pp. 155–168, 2010 5. B. Srivastava, Chenyang Lu, “Wireless sensor networks for healthcare,” Proceedings of the IEEE, vol. 98, no. 11,pp. 1947–1960, 2010 6. Robert SH, Emil Jovanov, and Y. T. Zhang, “Guest editorial introduction to the special section on m-health: Beyond seamless mobility and global wireless health-care connectivity,”, Information Technology in Biomedicine, IEEE Transactions on, vol. 8, no. 4, pp. 405-414, 2004. 7. Khambete; “National efforts to improve healthcare technology management and medical device safety in India”; 7th International Conference on IET, pp. 1–5, 2012. 8. Hung, K., “Wearable medical devices for tele-home healthcare,” In Engineering in Medicine and Biology Society, IEMBS’04. 26th Annual International Conference of the IEEE, vol. 2, pp. 5384–5387, 2004 Authors: Arathi B N, Shona M, Pankaja R

Paper Title: Smart Waste Isolation and Monitoring Framework using IoT Abstract: Commonly, in our places ,we see that the garbage canisters or dustbins set at open spots are over-burden. It leads to unhealthy conditions for individuals just as grotesqueness to that particular place leaving awful stench. To evade every single such circumstance , a venture called Smart Garbage Segregation and Monitoring System is developed. Interfacing of the dustbins with microcontroller based architecture is done, which involves sensors that shows the exact location of garbage on android device. At the point when waste achieves the threshold level the sensor sends the signal to the microcontroller unit which in turn forwards signal to the client via Wi-Fi along with location of bins utilizing GPS module. So consistent observing of trash canisters will keep the environment clean. The primary point of this task is to decrease human resources and efforts alongside the upgradation of a smart city vision.

77. Keyword: Solid Waste, Sensors, Wi-Fi, GPS, Arduino. References: 465-467 1. Prakash, Prabhu,“IoT based management system for smart cities”, International Journal of Innovative Research in Science, Engineering and Technology, vol 4, Issue 2, February 2016. 2. Kanchan Mahajan, Prof J. S. Chitode,”Waste Bin Monitoring system Using Integrated Technologies”, International Journal of Innovative Research in Science, Engineering and Technolgy(An ISO 3297:2007 Certified Organization) Vol 3, Issue 7, July 2014. 3. Prof.R.M.Sahu, Akshay Godse, Pramod Shinde, Reshma Shinde,” Garbage and Street Light Monitoring System using Internet of Things”, International Journal of Innovative Resarch in Electrical, Electronics, Instrumentation and Control Engineering, Vol 4, Issue 4, 4 April 2016. 4. M. Al-Maaded, N. K. Madi, Ramazan Kahraman, A. Hodizic, N. G. Ozerkar, An overview of Solid Waste Management and Plastic Recyling in Qatar, Springer Journal of polymer and the Environment, March 2012, Volume 20, Issue 1, pp 186-194 5. Raghumani Singh, C. Dey, M. Solid Waste Management of Thoubal Municipality, Manipur- a case study Green Technology and Environment Conservation (GTEC 2011), 2011 International Conference Chennai 21-24. 6. Vikrant Bhor,”Smart Garbage Management System International Journal of Engineering Research & Technology(IJERT), Vol 4 Issue 03, March- 201552000. 7. Ms. S. N. Patil, Ms. S. S. Jagdale, Ms. A. T. Gharall Asst.Prof. R. B. Tapase,”Wireless ECG Monitoring. Authors: Prachi Verma, Satinder Kuma, Sanjeev K.Sharm

Paper Title: Understanding the Factors Affecting Consumer’s Acceptance of E–Healthcare Services 78. Abstract: E-health platforms are fast becoming popular as they provide faster and hassle free services to the consumers and also proving to be time and cost effective. With the help of Technology Acceptance Model 468-473 (TAM) present research is an attempt to study the elements attracting the consumers’ technology adoption in healthcare and also to identify and propose a conceptual model. Primary data was collected from 298 respondents from the various private hospitals of Punjab and Union Territory using a questionnaire with five point likert scale. The exploratory and confirmatory factor analysis was done using AMOS 21.The factor analysis explored four factors which were named as Perceived usefulness, Perceived ease of use, Behavioral intention and risk. Model fit indices of the default model were chi-square degree of freedom-806.310/316,RMR- 0.54, GFI-0.835, AGFI-0.803, NFI-0.896, TLI-0.926, RMSEA-0.07`suggest a good fit model. The study suggests the important factors responsible for technology acceptance for e-Health care consumers

Keyword: Acceptance, consumer, E-health, hospitals, technology References: 1. Thielst, C. B. “Social media: ubiquitous community and patient engagement”. Frontiers of health services management, 2011, 28(2), 3-14.. 2. Raitoharju, R. “When acceptance is not enough-taking TAM-model into healthcare”. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences ,2005.,(pp. 150c-150c). IEEE. 3. Davis, F. D,”A technology acceptance model for empirically testing new end-user information systems: Theory and result” (Doctoral dissertation, Massachusetts Institute of Technology) 1985. 4. Meyers, S. “Concierge'medicine. Who really pays for gold standard access to doctors?”. Trustee: the journal for hospital governing boards, 2003,56(1), 12-4. 5. Holden, R. J., & Karsh, B. T. “The technology acceptance model: its past and its future in health care”. Journal of biomedical informatics,2010 43(1), 159-172. 6. Kassirer JP. “Patients, physicians, and the Internet”. Health Affairs. 2000 19(6):115-23. 7. Lazarus, R. S., & Launier, R “Stress-related transactions between person and environment”. In Perspectives in interactional psychology,1978 (pp. 287-327). Springer, Boston, MA. 8. Gagnon, M. P., Orruño, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. , “Using a modified technology acceptance model to evaluate healthcare professionals' adoption of a new telemonitoring system”. Telemedicine and e-Health,2012 18(1), 54-59. 9. Legris, P., Ingham, J., & Collerette, P.,Why do people use information technology? A critical review of the technology acceptance model. Information & management,2003, 40(3), 191-204. 10. Bagozzi, R. P., “The legacy of the technology acceptance model and a proposal for a paradigm shift”. Journal of the association for information systems, 2003,8(4), 3. 11. Yarbrough, A. K., & Smith, “T. B.Technology acceptance among physicians: a new take on TAM”. Medical Care Research and Review, 2007,64(6), 650-672. 12. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R “User acceptance of computer technology: a comparison of two theoretical models”. Management science,1989, 35(8), 982-1003. 13. Taylor, S., & Todd, P. A., “Understanding information technology usage: A test of competing models”. Information systems research,1995, 6(2), 144-176. 14. Susanto, T. D., & Aljoza, M. “Individual acceptance of e-Government services in a developing country: Dimensions of perceived usefulness and perceived ease of use and the importance of trust and social influence”. Procedia Computer Science,2015, 72, 622- 629. 15. Chiou, Y. W., & Fang, G. D. “A study of web portal user behavior. Web J. Chin. Manage.2005, Rev, 8(1), 43-60 16. Kuo, Y. F., & Yen, S. N. “Towards an understanding of the behavioral intention to use 3G mobile value-added services”. Computers in Human Behavior,2009, 25(1), 103-110. 17. Bauer, R. A. “Consumer behavior as risk taking”. Chicago, IL, 1960,384-398. 18. Doolin, B., Dillon, S., Thompson, F., & Corner, J. L., "Perceived risk, the Internet shopping experience and online purchasing behavior: A New Zealand perspective”. Journal of Global Information Management (JGIM),2005, 13(2), 66-88. 19. Dowling, G. R. “Perceived risk: the concept and its measurement. Psychology & Marketing”,1986, 3(3), 193-210. 20. Huang, W. Y., Schrank, H., & Dubinsky, A. J. , “Effect of brand name on consumers' risk perceptions of online shopping”. Journal of Consumer Behaviour: An International Research Review,2006 4(1), 40-50. 21. Rindfleisch, A., & Crockett, D. X., “Cigarette smoking and perceived risk: a multidimensional investigation”. Journal of Public Policy & Marketing,1999, 18(2), 159-171. 22. Van der Heijden, H., Verhagen, T., & Creemers, M., “Understanding online purchase intentions: contributions from technology and trust perspectives”.2003, European journal of information systems, 12(1), 41-48. 23. Berdie, D. R., Anderson, J. F., & Niebuhr, M. A. 1986. Questionnaires: Design and use. 24. Nunally, J. C., & Bernstein, I. H. ,1978. Psychometric theory. 25. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. 2006. Multivariate data analysis (Vol. 6). 26. Tavares, Jorge, and Tiago Oliveira. "Electronic health record patient portal adoption by health care consumers: an acceptance model and survey." Journal of medical Internet research ,201618, no. 3, e49. 27. Zhao, Y., Li, K., & Zhang, L. “A meta-analysis of online health adoption and the moderating effect of economic development level. International journal of medical informatics.”2019 doi:10.1016/j.ijmedinf.2019.04.015(Accepted Manuscript) Authors: Nagaraj M. Lutimath, Chethan C, Basavaraj S Pol

Paper Title: Prediction of Heart Disease using Machine Learning Abstract: Machine learning is one of the fast growing aspect in current world. Machine learning (ML) and Artificial Neural Network (ANN) are helpful in detection and diagnosis of various heart diseases. Naïve Bayes Classification is a vital approach of classification in machine learning. The heart disease consists of set of range disorders affecting the heart. It includes blood vessel problems such as irregular heart beat issues, weak heart muscles, congenital heart defects, cardio vascular disease and coronary artery disease. Coronary heart disorder is a familiar type of heart disease. It reduces the blood flow to the heart leading to a heart attack. In this paper the 79. UCI machine learning repository data set consisting of patients suffering from heart disease is analyzed using Naïve Bayes classification and support vector machines. The classification accuracy of the patients suffering 474-477 from heart disease is predicted using Naïve Bayes classification and support vector machines. Implementation is done using R language.

Keyword: Naïve Bayes Classification, Support Vector Machines, UCI machine learning repository data set, R Studio References: 1. Moloud Abdar,”Using Decision Trees in Data Mining for Predicting Factors Influencing of Heart Disease”, Carpathian Journal of Electronic and Computer Engineering 8/2 , 2015,pp. 31-36. 2. Jyoti, S., U. Ansari and D. Sharma, Sunita Soni, “Intelligent and Effective Heart Disease Prediction System using Weighted Associative Classifiers”, .International Journal on Computer Science and Engineering (IJCSE),3: 23852392, 2011, pp. 2385- 2392. 3. Rupali, M and R.Patil, “Heart Disease Prediction System using Naive Bayes and Jelinek-mercer smoothing”,.International Journal of Advanced Research in Computer and Communication Engineering, May 2014. Vol. 3, Issue 5,pp. 6787-6789. 4. Ali Mirza Mahmood1, 2* Mrithyumjaya Rao Kuppa, “Early detection of clinical parameters in heart disease by improved decision tree algorithm”, Second Vaagdevi International Conference on Information Technology for Real World Problems, 2010, pp. 2429. 5. František Babič, Jaroslav Olejár, Zuzana Vantová, Ján Paralič, “Predictive and Descriptive Analysis for Heart Disease Diagnosis”, Proceedings of the Federated Conference on Computer Science and Information Systems, Prague, 2017, ISSN 2300- 5963 ACSIS, Vol. 11,, DOI: 10.15439/2017F219, pp. 155–163. 6. R. El-Bialy, M. A. Salamay, O. H. Karam, and M. E. Khalifa, "Feature Analysis of Coronary Artery Heart Disease Data Sets", Procedia Computer Science, ICCMIT 2015, vol. 65, pp. 459–468, doi: 10.1016/j.procs.2015.09.132. 7. L. Verma, S. Srivastaa, and P.C. Negi, "A Hybrid Data Mining Model to Predict Coronary Artery Disease Cases Using Non- Invasive Clinical Data", Journal of Medical Systems, vol. 40, no. 178, 2016, doi: 10.1007/s10916-016-0536-z. 8. R. Alizadehsani, J. Habibi, M. J. Hosseini, H. Mashayekhi, R. Boghrati, A. Ghandeharioun, B. Bahadorian, and Z. A. Sani, "A data mining approach for diagnosis of coronary artery disease", Computer Methods and Programs in Biomedicine, vol. 111, no. 1, 2013, pp. 52-61, doi: 10.1016/j.cmpb.2013.03.0. 9. Ch. Yadav, S. Lade, and M. Suman, "Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining", International Journal of Computer Applications, vol. 87, no. 4, 2014, pp. 9-13. 10. František Babič, Jaroslav Olejár, Zuzana Vantová, Ján Paralič, “Predictive and Descriptive Analysis for Heart Disease Diagnosis”, Proceedings of the Federated Conference on Computer Science and Information Systems, Prague, 2017, ISSN 2300- 5963 ACSIS, Vol. 11,, DOI: 10.15439/2017F219, pp. 155–163. Authors: Jarupula Saikumar A Need for Technological Intervention: Children as Rag Pickers in Waste Management of Paper Title: Hyderabad City Abstract: Child labour is a universal problem and it not only hampers the growth and development of the children but also the progress of the nation. Though different nations have come up with various policies and regulations to tackle the problem of child labour, it is still rampant and in India the progress toward the elimination of the child labour is at snail place. In India only after 1971 "International Year of Child" the problems and issues of the children started giving attention on various platforms of the society. The work has been carried out with 250 sample size of the children who are involved with the waste management at various dump yards of Hyderabad city of Telangana state of India. Though government has come up with various 80. policies and regulations to curb the problem of child labour, in reality, the situation is otherwise and the children are visible everywhere in collecting the rag and waste. 478-481

Keyword: Child labour, Rag- Picking, Waste Management, Hyderabad. References: 1. Global estimates of child labour (2012 - 2016) by ILO, Geneva, 2017 2. State of the child workers in India by UNESCO and V V Giri labour Institute 3. Old city turns child labour hub (2017) by Ramana N.V 4. India's challenge in Waste Management by Down to Earth, 2019 5. Solid Waste Management in India 6. Over 4.5 lakh child labourers engaged in various e-waste activities in India. ASSOCHAM study, TOI (22 April, 2014). 7. "Problems of working children" by B.Kumar. A.P.H Publishing corporation, New Delhi. Authors: Punithavathi Manogaran, Suriyavathana Muthukrishnan, Kavitha Rani Mari, Anandhi Eswaran

Paper Title: HPLC Characterization and Assessment of Antioxidant Status of Vetiveria Zizanioides Roots Abstract: Vetiveria zizanioides has been assigned for the extraction of phenolic acids and flavonoids for soluble, glycoside and wall-bound fractions. There was the largest number of phenolic acids and flavonoids in the methanolic extract that constitutes the cell wall-bound portion. Free radicals can induce biomolecules to oxidize, resulting in cell damage and countless illnesses. The present study investigates the role of enzymatic antioxidants, i.e. catalase, superoxide dismutase, glutathione peroxidase,glutathione reductase.Vitamin Eand C enzyme activity was nonenzymaticantioxidant action by spectrophotometric method. The enzymatic glutothi-one peroxidase antioxidant was found to be exampling than the rest while Vitamin E, notified found to be best activity ratherthan Vitamin C.The reversed highperformance liquid chromatographic techniquewas created and validated for the concurrent identification of free phenolic acids and flavonoids using a photodiode array 81. detector with gradient elution.(Caffeicacid, Hydroxy benzoic acid, Rutin, Quercetin, Para- cumaric acid and Kaempferol) in the methanolic root extract of Vetiveria zizanioides. 482-485

Keyword: Vetiveria Zizanioides, enzymatic antioxidants, Non-enzymatic antioxidants, HPLC analysis. References: 1. Chomchalow N, Production of Medicinal and Aromatic Plants in Southeast Asia. AU Journal of technology. 2000 Oct 4(1): 84- 94. 2. Dipjyoti C. HPLC quantification of phenolic acids from Vetiveria zizanioides (L.) Nash and its antioxidant and antimicrobial activity. Journal of pharmaceutics. 2013 Mar 11;2013. 3. Edziri HL, Smach MA, Ammar S, Mahjoub MA, Mighri Z, Aouni M, Mastouri M. Antioxidant, antibacterial, and antiviral effects of Lactucasativa extracts. Industrial Crops and Products. 2011 Jul 1;34(1):1182-5. 4. Florence AR, Joselin J, Brintha TS, Sukumaran S, Jeeva S. Preliminary phytochemical studies of select members of the family Annonaceae for bioactive constituents. BiosciDiscov. 2014;5(1):85-96. 5. Fukumoto LR, Mazza G. Assessing antioxidant and prooxidant activities of phenolic compounds. Journal of agricultural and food chemistry. 2000 Aug 21;48(8):3597-604. 6. Gülçin İ, Elmastaş M, Aboul-Enein HY. Antioxidant activity of clove oil–A powerful antioxidant source. Arabian Journal of chemistry. 2012 Oct 1;5(4):489-99. 7. Martin M, Guiochon G. Effects of high pressure in liquid chromatography. Journal of Chromatography A. 2005 Oct 7;1090 (1- 2):16-38. 8. Sutapun W, Suppakarn N, Ruksakulpiwat Y. Study of Characteristic of VetiverFiberBefore and after Alkaline Treatment. In Advanced Materials Research 2010 Aug 11;123:1191-1194. 9. Sachan A, Ghosh S, Mitra A. An efficient isocratic separation of hydroxycinnamates and their corresponding benzoates from microbial and plant sources by HPLC. Biotechnology and applied biochemistry. 2004 Oct;40(2):197-200. 10. Xiang Y, Liu Y, Lee ML. Ultrahigh pressure liquid chromatography using elevated temperature. Journal of Chromatography A. 2006 Feb 3;1104 (1-2):198-202. 11. Ganesan Vijaiyan Siva. Spectrochim. Acta, Part A., 2014, vol. 127, pp. 61–66. Authors: S. Balamurugan, M. Selvalakshmi

Paper Title: E-Commerce Pricing Opportunities: And How to Exploit Them Abstract: In today’s competitive era of E-commerce, companies are struggling to provide a satisfactory price level to meet customer’s demands. One of the most important metric to meet customer’s expectations is the price which will ultimately clinch the deal. The present study is to discuss about the different price strategies and its impact on e-marketing. By understanding these pricing strategies, more efficient marketing strategies will be available, that will drive internet and e-commerce. A detailed analysis is done on the pricing strategies and its difference for effective implementation in e-commerce. The e-retailers should try to offer discounts and to reduce customers search cost for more business than brick and mortar store.

Keyword: E-commerce, Pricing strategy, Smart pricing, cost. References: 1. Benjamin R, Wiganot R. “Electronic Markets and Virtual Value Chains on the Information Superhighway”. Sloan Management Review, 36(2), PP 31-41.(1995 January) 2. Brown M, Pope, N, Voges, K. “Buying or browsing? An exploration of shopping orientations and online purchase intentions”. European Journal of Marketing, 37 (10/11), PP 1666-1684.(2003) 3. Choi. S, Stahi D, Whinston A, “ The Economics of Electronic Commerce” Indiana polis: Macmillan Technical publishing. (1997) 4. Freund C.L., Weinhold D. “The Effect of the Internet on International trade Journal of International Economics”, 62(1). PP 171- 189.(2004) 5. Mckey J., Marshall, P. “Strategic Management of E-business “.Brisbane, John Wiley & Sons.(2004) 6. Totonchi J, Manshady K, “Relationship between Globalization and E-commerce. International Journal of e-education, e-business, e-management and e-learning”, 2(1), 83.(2012) 7. Koo DM & Ju SH , “International effects of atmospherics and perceptual curiosity on emotions and online shopping intentions, Computers in Human Behavior”, 26 (2010), PP 377-388 82. 8. Alam S.S. & Yasin N.M , “An Investigation into the Antecedents of customer satisfactions of online shopping’ Journal of Marketing Development and Competitiveness”, 5(1), (2010) 9. A. Day. “A Model of Monitoring web site effectiveness”. Internet Research: Electronic Net working applications and policy, Vol 486-488 7, No.2, (1997), PP 109-115. 10. S.E. Kim, T. Shaw and H. Schneider, “Website design bench marking within Industry groups, Internet Research”, Vol.13, No.1 (2003), PP 17-26. 11. M.Y Kiang and R.T.Chi “A framework for analyzing the potential benefits of Internet Marketing”, Journal of Electronic Commerce Research, Vol 2, No.4 (2001), PP 157-163. 12. R.R. Ruckman, http://www.imgrind.com/10-advantages of internet Marketing/ 10, Advantages of Internet Marketing, (2012) January 19. 13. T.S.H Teo, V.K.G Lim and R.Y.C. Lai., “Intrinsic and extrinsic motivation in internet usage” omega, Vol.27, (1999), PP 25-37. 14. T.S.H Tes, “Usage and effectiveness of online marketing tools among Business –to –Consumer”, B2C, firm in Singapore,” International Journal of Information Management, Vol.25 (2005) PP 203-213. 15. Cha.J “Internet as a unique shopping Channel to sell both real and virtual items: A comparison of factors affecting purchase intention” Journal of Electronic Commerce Research, (2011). 12 (2) 115-132 16. Chen. I.D., Gillenson M. L., and Sherrell, D.I. “Enticing online consumers: An extended technology acceptance perspective”. Information and Management (2002) 39(8). 705-719 17. Heijden, H.Vander., Verhagen, T., and Creamers M. “Understanding online purchase intentions : Contributions from technology and trust perspectives” European Journal of Information Systems (2003) 12(1), 41-48. 18. Joines J.I., Scherer. C.W and Scheufele “Exploring Motivations for consumer web and their implications for e-commerce” Journal of Consumer Marketing (2003), 20(2): 90-108 19. Kim. S.Y and Lim, Y.J. “Consumers perceived importance of and satisfaction with internet shopping” Electronic Markets (2001). 11 (3): 148-154. 20. Kovimaki. T. “Consumer satisfaction and purchasing behaviour in web-based shopping” (2001) Electronic Markets 11(3): 186- 192. 21. Lohse. G. Bellman S., and Johnson E “Consumer buying behaviour on the Internet: Findings from panel data”. Journal of Interactive Marketing (2000): 14(1) 15-29. 22. Phang C.W.S., Kankanhalli A., Ramakrishanan. K and Raman K.S. “Customers preference of online store visit strategies: An Investigation of demographic variables” European Journal of Information Systems (2010). 19 (3): 344-358 23. Rohm. A.J. and Swaminathan. V. “A typology of online shoppers based on shopping motivations” Journal of Business Research (2004). 57(7)., 748-757 Authors: Neeta Pandey, Ram Bharose Phytoremediation of Potentially Toxic Element via Absorbtion and Translocation by Naturally Paper Title: Grown Plants Calotropis Procera and Solanum Nigrum from Polluted Agricultural Field Near by 83. Industrial Area, Chinhat Lucknow U.P.(India) Abstract: Phytoremediation is an eco-friendly and has beeen defined as the in situ use of plants to stabilise, remediate, and reduce or restore contaminated soil. Current research was conducted to know the best 489-493 accumulator plants Forcontaminated agricultural land, of potentially trace elements in soil and plants. Total Fe, Cu, Zn and Pb, have been estimated in soil and plant species of contaminated and control site. Two plants species calotropis procera and solanum nigrum from contaminated and non-contaminated area has been taken. It is revealed that Solanum Nigrum and CalotropisProcera growing in contaminated area can accumulate some of the PTE (Potentially Toxic Elements) like Fe, Cu, Zn and Pb. Surprisingly, naturally grown plants show highly accumulated metals and which can be used as a best accumulator plant species in the heavily contaminated area.We suggest the cultivation of these plants species because it can be used as a best accumulator plant species. This research will show in selection of best plant species for growing in contaminated area.

Keyword: Accumulation, Translocation, Toxic Elements Fe, Cu, Zn and Pb. References: 1. Anderson,P.J.: 1914, ‘The effect of dust from cement mills in the setting of fruit’, plant world17, 57. 2. Barman, S.C. and Lal, M.M.: 1994, ‘Accumulation of heavy metals (Zn, Cu, Cd, and Pb) in soil and cultivated vegetables and weeds grown in industrially polluted fields’, Indian J. Environ. Biol.15(2), 107. 3. Buchaure, M.J.: 1973, ‘Contamination of soil and vegetation near a Zinc smelter by Zn, Cd, Cu and Pb’, Environ. Sci. and Technol. 7(2), 131. 4. Cataldo, D.A. and Widung, R.E.: 1978, ‘Soil and plant factors influencing the accumulation of heavy metals by plants’, Environ. Hlth. Perspectives 27, 149. 5. Chambers, J.C. and Siddle, R.C.: 1991, ‘Fate of heavy metals in abandoned lead zinc tailing ponds: I Vegetation’, J. Environ. Qual. 20, 745. 6. Chaney, R.L.: 1973, ‘Crop and food chain effects of toxic elements in sludge and effluents: Recycling municipal sludge’s and effects on land’, U.S. EPA, Washington, D.C., 129-141. 7. Chang, A.C., Page, A.L., Foster, K.W. and Jones, T.E.: 1982, ‘Comparison of cadmium and zinc accumulation by four cultivars of barley grown in sludge amended soils’, J. Environ. Qual. 11, 409.Clisjsters, H. and Van Assche, F.: 1985, ‘Inhibition of photosynthesis by heavy metals’, Photosyn. Res.7, 31. 8. Czaja, A.T.: 1962, ‘Uber Das Problem Der Zementstaubwirk-Ungen and Pflanzen’, Staub 22, 228. 9. Eepstein, E. and Jefferies, R.L.: 1964, ‘The genetic basis of selective ion transport in plants’, ann. Rev. Plant Physiol. 29, 511. 10. Faucherre, J., Pinart, A.M. and Dutof, A.: 1985, Mecanismebiogeochemique de contamination des vegetaux par le plomb, le cadmium et le zinc C.R. contract C. Comm. Europe, January. 11. Gestring W.D. and Jarnell, W.M.: 1982,’Plant availability of phosphorus and heavy metals in soils amended with chemically treated sewage sludge’, J.Environ Qual. 11, 669. 12. Kabata-Pendias, A. and Pendias, H.: 1992, Trace Elements in soil and Plants, 2ndedn., CRC Press, Boca Raton, Fla. 13. Leita, L., Nobili, M.D., Pardini, G., Ferari, F. and Sequi, P.: 1989, ‘Anomalous contents of heavy metals in soil and vegetation of mine area in south west Sardinia’, Water, Air and Soil Pollut. 48, 423. 14. Mc Nichol, R.D. and Beckett, P.H.T.: 1985, ‘Critical tissue concentrations of potentially toxic elements’, Plant Soil 85, 107. 15. Mitchell, R.L., Reith, J. W.S. and Johnston, I.M.: 1957, ‘Trace element uptake inrelation to soil content’,J.Sci. Food Agri, 8(Suool. Issue), 51. 16. Olaniya, M.S., Bhoyar, R. V. and Bhide, A.D.: 1991, ‘Effect of solid waste disposal on land, Indian’, J. Environ. Hlth. 34(2), 143. 17. Rao, D.N. and Singh, S.N.: 1978, ‘Effect of cement dust pollution on soil properties and on wheat plants’, Indian J. Environ.Hlth. 20(3), 258. 18. Ray, M.: 1990, ‘Accumulation of heavy metals in plants grown in industrial areas’, Indian Biologist, Vol. XXII, No. 2. 19. Roberts, R.D. and Johnson, M.S.: 1978, ‘Dispersal of heavy metals from abandoned mine workings and their transference through terrestrial food chains’, Environ. Poll. 16, 293. 20. Villanueva, V.R. and Santerre, A.: 1989, ‘On the mechanism of adaptive metabolism of healthy-resistant trees from forest polluted areas’, Water, Air, and Soil Pollut. 48, 59. 21. Xian, X.: 1989, ’Response of kidney bean to concentration andf chemical from of cadmium, Zinc and Lead in polluted soils’, Environ. Poll. 57, 127. 22. Yassoglou, N. Kosmas, C. Asimakopoulos, J. and Kallinou, C.: 1987, ‘Heavy metal contamination of roadside soils in the greater Athens area’, Environ. Poll. 47, 293. Authors: Jin-Keun Hong

Paper Title: Event Characteristics of Crypto Currency and Security Abstract: Recently, there has been a continuous occurrence of a security incident on a crypto currency exchange. This background is not related to the current social situation. This is because the social interest in crypto currency provides an attacker with a chance to attack. In this paper, we have started to investigate the relationship between crypto currency and security incidents of block chain. This paper focuses on analysis of crypto currency event of block chain. In this paper, we analyzed the amount of Google data retrieval around specific keywords during a specific period. And we analysis the relevance of this keyword to specific keywords related to security. For example, we analyzed the decrypted bitch coin or etherium, the nice money exchange, nicehash, coincheck, BTCglobal, BITGRAIL, Blackwallet. We are focused on the relationship between the time of the security incident and the public awareness of the related crypto currency exchange. According to the results of the study, it can be assumed that a security incident 84 occurred at a certain point in each exchange. Through this study, we were able to confirm public interest in crypto currency miners. I was able to confirm the degree of interest by time. Cryptographic digger was mainly 494-498 focused on BitMiner, CGMiner, MultiMiner, and BFGMiner. Most of the public interest in these mining equipment is peaking in December 2017. We also looked at public interest in cryptic bit coin and etherium, mainly in December 2017. The results of this paper can be used to analyze the point of time of the attack on the crypto currency exchange. Crypto currency exchange attacks will continue to occur in the future. If so, when is this attack going to take place? At that point, we need to know at what point the exchange will have public interest. At that point, we should also look at the exchange for vulnerabilities. Keyword: crypto currency, miner, attack, block chain, security References: 1. Ridhanshi Bhatia, Praveen Kumar, Shilpi Bansal, Seema Rawat, “Blockchain the technology of crypto currencies,” in ICACCE2018, https://doi.org/10.1109/ICACCE.2018.8441738 2. Lei Xu, Chunxiao Jiang, Nengqiang He, Zhu Han, Abderrahim Benslimane, “Trust based collaboriative privacy management in online social networks,” IEEE Transaction on Information Forensics and Security, 14(1), pp. 48-60, 2019, https://doi.org/10.1109/TIFS. 2018. 2840488 3. Jose A. Concepcion Sanchez, Jezabel Molina Gil, Pino Caballero Gil, Ivan Santos Gonzales, “Fuzzy logic system of identity theft detection in social networks,” in ICBA2018, https://doi.org/10.1109/ Innovate -Data.2018.00017 4. Marc Kaeske, Olaf Zukunft, “A comparative evaluation of big data framework for graph processing,” in ICBDA2018, https://doi.org/ 10.1109/Innovate-Data.2018.00012. 5. Michael M. Tadesse, Hongfei Lin, Bo Xu, Liang Yang, “Personality predictions based on user behaviour on the Facebook social media platform,” IEEE Acess:1-1, 2018, https://doi.org/10.1109/ACCESS. 2018.2876502 6. Hugo Rosa, David Matos, Ricardo Ribeiro, Luisa Coheur, Joao P. Carvalho, “A deeper look at detecting cyberbullying in social networks,” in IJCNN2018, http://doi.org/10.1109/IJCNN. 2018. 8489211 7. Youyang Qu, Shui Yu, Longxiang Gao, Wanlei Zhou, Sancheng Peng, “A hybrid privacy scheme in cyber physical social networks,” IEEE transaction on computational social systems, 5(3), pp. 773-784, 2018, https://doi.org/ 10.1109/TCSS.2018.2861775. 8. Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef, “Argumentation models for cyber attribution,” in IEEE/ACM ASONAM2016, https://doi.org/ 10.1109/ASONAM.2016.7752335 9. Shancang Li, Shanshan Zhao, Yong Yuan, Qindong Sun, Kewang Zhang, “Dynamic security risk evaluation via hybrid Bayesian risk graph in cyber physical social system,” IEEE Transaction on computational social systems, pp. 1-9, 2018, https://doi.org/10.1109/ TCSS.2018.2858440 10. Tien D. Phan, A. Nur Zincir Heywood, “A language model for compromised user analysis,” in NOMS2018, https://doi.org/10.1109 /NOMS.2018.8406317 11. Alexei Suleimanov, Maksim Abramov, Alexander Tulupyev, “Modelling of the social engineering attacks based on social graph of employees communications analysis,” in ICPS2018, https://doi.org/ 10.1109/ICPHYS.2018.8390809. Authors: Zhanfan Zhao, Byung-Hun Jeon, Ju-Ri Kim

Paper Title: Generalized Property Graphs(GPG) of Property-Value Structures for Knowledge Model Abstract: As a popular emerging technology, knowledge graphs (KGs) have become a platform of Web- based knowledge applications and services. Two dominant graph-based knowledge models, RDF and LPG, are widely used to construct large-scale KGs. It is argued that these models have some limitations to cope with complicated knowledge structures. This paper proposes a noble generalized property graph model that can seamlessly realize knowledge structures with compact expressiveness and robust formalism. Since the proposed graph model is compatible with RDF and LPG, it can be practically applied to KGs with effective performance.

Keyword: property graph, knowledge graph, attribute-value matrices. References: 1. Pavlić, Mile, Ana Meštrović, and Alen Jakupović, “Graph-based formalisms for knowledge representation.” Proceedings of the 17th world multi-conference on systemics cybernetics and informatics (WMSCI 2013), 17th ed. vol. 2, 2013. 2. Ringler, Daniel, and Heiko Paulheim, “One knowledge graph to rule them all? Analyzing the differences between DBpedia, YAGO, Wikidata & co.” Joint German/Austrian Conference on Artificial Intelligence (Künstliche Intelligenz), Springer, Cham, vol. 10505, 2017, pp. 366-372 3. Paulheim, Heiko, “Knowledge graph refinement: A survey of approaches and evaluation methods.” Semantic web, 3rd ed. vol. 8, 2017, pp. 489-508. 4. Das, Souripriya, et al, “A Tale of Two Graphs: Property Graphs as RDF in Oracle.” EDBT, vol. 82, 2014, pp. 762-773. 5. Margitus, Michael, Gregory Tauer, and Moises Sudit, “RDF versus attributed graphs: The war for the best graph representation.” 2015 18th International Conference on Information Fusion Washington, DC, IEEE, 18th, 2015, pp. 200-206. 6. Hoffart, Johannes, et al, “YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia.” Artificial Intelligence, vol. 194, 2013, pp. 28-61. 7. Heath, Tom, and Christian Bizer, “Linked data: Evolving the web into a global data space.” Synthesis lectures on the semantic web: theory and technology, 1th ed. vol. 1, 2011, pp. 1-136. 85. 8. Kanmani, A. Clara, T. Chockalingam, and N. Guruprasad, “RDF data model and its multi reification approaches: A comprehensive comparitive analysis.” 2016 International Conference on Inventive Computation Technologies (ICICT), IEEE, vol. 1, 2016, pp. 1-5. 499-505 9. Hernández, Daniel, Aidan Hogan, and Markus Krötzsch, “Reifying RDF: What works well with wikidata?.” Proceedings of the 11th International Workshop on Scalable Semantic Web Knowledge Base Systems, CEUR Workshop Proceedings, vol. 1457, 2015, pp. 32-47. 10. Hartig, Olaf, and Bryan Thompson. Foundations of an alternative approach to reification in RDF. arXiv preprint arXiv:1406.3399, 2014. 11. W3C, RDF 1.1 concepts and abstract syntax. W3C Recommendation 25 February 2014, https://www.w3.org/TR/rdf11-concepts/. 12. Rodriguez, Marko A., and Peter Neubauer, “Constructions from dots and lines.” Bulletin of the American Society for Information Science and Technology, 36th ed. vol. 6, 2010, pp. 35-41. 13. Hartig, Olaf, “Reconciliation of RDF* and property graphs.” arXiv preprint arXiv:1409.3288, 2014, pp. 1-18. 14. Studer, Rudi, V. Richard Benjamins, and Dieter Fensel, “Knowledge engineering: principles and methods.” Data & knowledge engineering, Issues 1-2, vol. 25, 1998, pp. 161-197. 15. Carpenter, Bob. The logic of typed feature structures: with applications to unification grammars. logic programs and constraint resolution. Cambridge University Press, 2005, pp. 32. 16. Rouces, Jacobo, Gerard de Melo, and Katja Hose, “FrameBase: Enabling integration of heterogeneous knowledge.” Semantic Web, 6 ed. vol. 8, 2017, pp. 817-850. 17. Levine, Robert D., and Walt Detmar Meurers, “Head-Driven Phrase Structure Grammar: Linguistic approach, formal foundations, and computational realization.” Encyclopedia of language and linguistics, vol. 2, 2006, pp. 1-24. 18. Bonnotte, Isabelle, “The role of semantic features in verb processing.” Journal of Psycholinguistic Research, 3th ed. vol. 37, 2008, pp. 199-217. 19. Ma, Minhua, and Paul Mc Kevitt, “Visual semantics and ontology of eventive verbs.” International Conference on Natural Language Processing. Springer, Berlin, Heidelberg, vol. 3248, 2004, pp. 187-196. 20. Fellbaum, Christiane. WordNet. The Encyclopedia of Applied Linguistics. 2012. 21. Bergman, Michael K. A Knowledge Representation Practionary: Guidelines Based on Charles Sanders Peirce. Springer. 2018. 22. Khoo, Christopher SG, and Jin‐Cheon Na, “Semantic relations in information science.” Annual review of information science and technology, 1th ed. vol. 40, 2006, pp. 157-228. 23. Véronis, Jean, and Nancy Ide, “A feature-based model for lexical databases.” Proceedings of the 14th conference on Computational linguistics, Association for Computational Linguistics, vol. 2, 1992, pp. 588-594. 24. Chein, Michel, and Marie-Laure Mugnier. Graph-based knowledge representation: computational foundations of conceptual graphs. Springer Science & Business Media. 2008. 25. Sowa, John F, “Conceptual graphs.” Foundations of Artificial Intelligence, vol. 3, 2008, pp. 213-237. 26. Schuler, Karin Kipper. VerbNet: A broad-coverage, comprehensive verb lexicon. University of Pennsylvania. 2005. 27. Rula, Anisa, et al, “On the diversity and availability of temporal information in linked open data. International Semantic Web Conference.” Springer, Berlin, Heidelberg, vol. 7649, 2012, pp. 492-507. Authors: Yang-Ha Chun

Paper Title: Factors on Learning Satisfaction with a Focus on E-learning in the Military Abstract: The Department of National Defense in South Korea is taking steps to develop smart learning to prepare for the information age, but as of yet there have not been any sufficient empirical analyses on learning satisfaction. The Department of National Defense in South Korea is taking steps to develop smart learning to prepare for the information age, but as of yet there have not been any sufficient empirical analyses on learning satisfaction. The findings of this study showed the following factors as positively affecting learning satisfaction with e-learning in the military: learning motivation, ease of the use environment, learning support level of the organization, content feasibility, and instructor-learner interaction. Similarly with the official education centers and universities, learning motivation was proven to be the most important factor in e-learning education in the military. Also, as factors that reflect the nature of the military, ease of the use environment and learning support level of the organization were identified as factors that affect learning satisfaction. This result suggests the importance of the infrastructure and setting for e-learning in the military. The factors of content feasibility and infrastructure-learner interaction were also shown to affect learning satisfaction. Suggesting further investment in the design and development of e-learning contents and an increased proactiveness of the instructors to improve learning satisfaction.

86. Keyword: e-learning, Higher education, Satisfaction of learning References: 506-510 1. Gloria C. Alaneme, Peter O. Olayiwola, Comfort O. Reju, “Combining traditional learning and the e-learning methods in higher distance education: Assessing learners' preference” in 2010 4th International Conference on Distance Learning and Education, San Juan, PR, USA https://doi.org/10.1109/ICDLE.2010.5606008 2. Michael Leyer, Jürgen Moormann, Minhong Wang, “Is Learning-by-Doing via E-learning Helpful to Gain Generic Process Knowledge?” 2014 IEEE 14th International Conference on Advanced Learning Technologies, Athens, Greece, https://doi.org/10.1109/ICALT.2014.206 3. Rachael Gallagher, “Design technology” Electronics Education., 26 – 27, 1991. https://doi.org/10.1049/ee.1991.0026 4. Garrison, D. R. & Anderson, T. E-Learning in the 21 st Century: “A Framework for Research and Practice”, Taylor & Francis, New York. 2003. 5. Sun-Ok Park, Geunjoo Lee. “Analysis of the Determinants of Satisfaction on Cyber Education for Centeral Official Education Institute.” Journal of Korean society and public administration, 2012. Vol. 23 No. 1, pp. 167-182. 6. Davis F. D. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quartly, 1989. Vol. 13, pp. 319-340. 7. Chih-Ming Chen, Ting-Chun Huang, Tai-Hung Li, Chia-Meng Huang, “Personalized E-Learning System with Self-Regulated Learning Assisted Mechanisms for Promoting Learning Performance” Seventh IEEE International Conference on Advanced Learning Technologies, 2007, . https://doi.org/10.1109/ICALT.2007.205 8. B. Wolman. Dictionary of behavioral science. SD Academic press. 1989. pp. 28. 9. Gloria C. Alaneme, Peter O. Olayiwola, Comfort O. Reju, “Combining traditional learning and the e-learning methods in higher distance education: Assessing learners' preference” International Conference on Distance Learning and Education, San Juan, PR, USA, 187 – 190, 2010, https://doi.org/ 10.1109/ICDLE.2010.5606008 10. Bailey, J.E. & Pearson, S.W. “Development of a tool for measuring and analyzing computer user satisfaction.” Management science. 1983. 29, pp.530-545. Authors: Seok Heon Yun

Paper Title: Simplified Quantification Method on Rebar Work Abstract: It is important to calculate quantity in a very detailed manner, but it is also important to calculate it as efficiently as possible within the margin of error as possible. Currently, the quantity takeoff is carried out in a very complex process and needs to be improved in efficiency. In this study, we investigated the research cases of quantity takeoff process, and analyzed current approximate cost estimate status and problems. In order to draw up an efficient QTO method of rebar work, overseas cases are surveyed. The error level in simplified rebar QTO method on the domestic cases are analyzed and applicability of the simplified QTO method for rebar work is reviewed. The purpose of this study was to analyze the error level of QTO of rebar works by using the simplified calculation method, and to analyze the applicability of rebar construction in Korea. According to an 87. analysis of existing case sites, the average quantity of rebar compared to the volume of concrete was 12.23% and the standard deviation was 1.32.nd the standard deviation. The actual deviation of these mean values is analyzed 511-515 to be within 1.5%. The results showed that the error occurred within 3 to 6% of the surcharge rate applied when calculating quantity of rebar, and that there was little difference between the detailed and simplified results.

Keyword: Rebar, Simplified Quantity Takeoff, Construction Cost, Cost Estimation References: 1. R. I. Carr, “Cost Estimating Principles” Journal of Construction Engineering and Management, 115(4), 1989, pp. 545-551. Available: https://doi.org/10.1061/(ASCE)0733-9364(1989)115:4(545) 2. D. Garold Oberlender, M. Steven Trost, “Predicting accuracy of early cost estimates based on estimate quality” Journal of Construction Engineering and Management. 127(3), 2001, pp. 173-182, https://doi.org/10.1061/(ASCE)0733- 9364(2001)127:3(173) 3. A. Akintola, F. Eamon, “A survey of current cost estimating practices in the UK” Construction Management and Economics, 18(2), 2000, pp. 161-172, Available: https://doi.org/10.1080/014461900370799 4. M. Kamal, W. David, F. Habib, “Building Construction Detailed Estimating Practices in Saudi Arabia” Journal of Construction Engineering and Management, 120(4), 1994, pp. 774-784, Available: https://doi.org/10.1061/(ASCE)0733-9364(1994)120:4(774) 5. N. Hae Ra, Y. Seok Heon, “A Case Study on the Educational Facility Project for the Improvement of Work Item’s Structure in BoQ” Journal of Architectural Institute of Korea, 33(8), 2017, pp. 47-54, Available: http://www.riss.kr/link?id=A103329745 6. C. HunHee, K. TaeKyung, L. YooSub, C. MoonYoung, “Study on the Reformation of the BoQ Structure for Public Building Projects in Korea” Journal of Architectural Institute of Korea, 15(9), 1999, pp. 123-131, Available: http://www.riss.kr/link?id=A3397343 7. P. HongTae, P. ChanJeong, “Work Management Model to Integrate Schedule and Bill of Quantity” Journal of the Korean Institute of Construction, 2(4), 2002, pp. 153-161, Available: http://www.riss.kr/link?id=A76122610 8. M. SungWoo, K. JongSoo, K. KiNam, “Adjustment of Cost Estimate Considering the Correlation between Construction Activities” Journal of Korean Society of Civil Engineers, 27(1), 2007, pp. 109-115, Available: http://www.riss.kr/link?id=A76575499 9. S. Jung, “A study on the construction of text recognition system for accumulating unit cost of construction statement in the construction field” master’s thesis, Chung-Ang University, 2010. 10. S. AReum, K. KiSu, Y. SeokHeon, “Improvement of Quantity Take-Off and BOQ Information through the PBS based QDB System” Journal of the Architectural Institute of Korea. 31(2), 2015, pp. 73-80, Available: http://www.riss.kr/link?id=A100319864 11. H. Zhang, X. Zhang, “Analysis on price adjustment coefficient of unbalanced bid model under the pricing pattern of Bill of Quantities” in 2008 International Conference on Management Science and Engineering 15th Annual Conference, Long Beach, CA, USA, 2008. Available: https://doi.org/10.1109/ICMSE.2008.4669137 12. H. Odeyinka, S. Kelly, S. Perera, “An evaluation of the budgetary reliability of bills of quantities in building procurement” in Construction and Building Research Conference of the Royal Institution of Chartered Surveyors, Cape town, Republic of South Africa, 2009. Available: http://nrl.northumbria.ac.uk/id/eprint/94 13. L. Qingli, T. Zhifang, “Construction project cost management under the mode of bill of quantities” in the 17th International Symposium on Advancement of Construction Management and Real Estate, Berlin, Heidelberg, 2014. Available: https://doi.org/10.1007/978-3-642-35548-6_79 14. M. Martinez, N. Marin, M. Amparo VM, “An intelligent system for the acquisition and management of information from bill of quantities in building projects”, Expert Systems with Applications, vol. 63, 2016, pp. 284-294, Available: https://doi.org/10.1016/j.eswa.2016.07.011 15. J. Damian, “Reinforcement Estimates” Yourspreadsheets, 2019. Available: http://www.yourspreadsheets.co.uk/reinforcement- estimates.html Authors: Sunghyuck Hong, Jungsoo Han, Guijung Kim

Paper Title: IoT Hacking Attacks and Countermeasure Abstract: IoT (Internet of Things) means the technology of connecting to the Internet by adding communication functions to all objects. IoT is physical constraints and limited resources which means are a vulnerability for hacking attacks. Therefore, IoT needs countermeasures of the hacking attack. These IoT devices are becoming a target of hacking. Hacking attacks on IoT devices are causing privacy and personal information leakage, and hacked devices are also used for DDoS(Distributed DoS) attacks. To overcome IoT physical constraints, various methods on each sensor in a wireless sensor networks are proposed. We analyzed various characteristics of sensor nodes and listed pros & cons. In addition, countermeasures on each IoT attacks were suggested. By analyzing such cases of hacking damage, I have identified the common weaknesses of IoT devices and looked for countermeasures. Therefore, it contributes to secure communication over a wireless sensor networks.

Keyword: Internet of Things , malware attack , network security, network vulnerability, hacking attack References: 1. J. Guo, Y. Peng, X. Peng, Q. Chen, J. Yu and Y. Dai, "Traffic forecasting for mobile networks with multiplicative seasonal ARIMA models” 2009 9th International Conference on Electronic Measurement & Instruments, Beijing. 2009. 88. https://doi.org/10.1109/ICEMI.2009.5274287 2. S. Singh and N. Singh, "Internet of Things (IoT): Security challenges, business opportunities & reference architecture for E- commerce” 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Noida. 2015. 516-520 https://doi.org/10.1109/ICGCIoT.2015.7380718 3. J. Habibi, D. Midi, A. Mudgerikar and E. Bertino, "Heimdall: Mitigating the Internet of Insecure Things” in IEEE Internet of Things Journal,vol.4 no.4, 2017, pp.968-978. https://doi.org/10.1109/JIOT.2017.2704093 4. C. Kolias, G. Kambourakis, A. Stavrou and J. Voas, "DDoS in the IoT: Mirai and Other Botnets” in Computer., vol.50 no.7 ,2017, pp. 80-84. https://doi.org/10.1109/MC.2017.201 5. T. S. Gopal, M. Meerolla, G. Jyostna, P. Reddy Lakshmi Eswari and E. Magesh, "Mitigating Mirai Malware Spreading in IoT Environment” 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, 2018. https://doi.org/10.1109/ICACCI.2018.8554643 6. S. Sezer, "T1C: IoT Security: - Threats, Security Challenges and IoT Security Research and Technology Trends” 2018 31st IEEE International System-on-Chip Conference (SOCC), Arlington, VA. 2018. https://doi.org/10.1109/SOCC.2018.8618571 7. W. Razouk, "Zigbee Security within the Framework of IoT” 2014 IEEE 7th International Conference on Service-Oriented Computing and Applications, Matsue. 2014. https://doi.org/10.1109/SOCA.2014.57. 8. H. Sinanović and S. Mrdovic, "Analysis of Mirai malicious software” 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, 2017. https://doi.org/10.23919/SOFTCOM.2017.8115504 9. D. Minoli, K. Sohraby and J. Kouns, "IoT security (IoTSec) considerations, requirements, and architectures” 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Las Vegas NV .2017. https://doi.org/10.1109/CCNC.2017.7983271 10. P. McNeil, "Secure IoT deployment in the cement industry” 2017 IEEE-IAS/PCA Cement Industry Technical Conference, Calgary, AB. 2017. https://doi.org/10.1109/CITCON.2017.7951862 11. F. Rahman, M. Farmani, M. Tehranipoor and Y. Jin, "Hardware-Assisted Cybersecurity for IoT Devices” 2017 18th International Workshop on Microprocessor and SOC Test and Verification (MTV), Austin, TX. 2017. https://doi.org/10.1109/MTV.2017.16

89. Authors: Dong-Hee Hong, Hong-Ryang Jung, Cheong-Hwan Lim, Woo-Taek Lim, Young-Cheol Joo Paper Title: Needs According to the Problems of Mammography Education Abstract: Mammography is a difficult technique, but there is no phantom for education. Therefore, we analyze the need and necessity to produce the phantom that meets the training needs. Data collection was performed by 199 independent radiological technologists in the breast and breast clinic of six hospitals except Jeju Island. The independent t-test and one-way ANOVA were conducted to determine the relationship between the demographic characteristics of the radiologist and the mothers' Duncan was used for statistical analysis. There was no statistically significant difference in perception and attitude according to demographic and statistical characteristics. Attitudes and attitudes according to job characteristics were influenced only by working style, by mammography education, and by education need. The results of the questionnaire showed that the education conditions of most mammography radiologists were difficult and the training of mammography was necessary.

Keyword: Clinical, Education, Mammography, Needs, Problems References: 1. J.M. Yang JM. Public Health Lecture, Seoul, 167, 1992. 2. H. R. Jung, “A Research Study on the Education System for Radiological Technologists and the Public health policy”, Journal of 521-524 radiological science and technology, vol. 27(4), 2004, pp. 67-74 3. H.S. Kim, A Study on the Satisfaction degree for Clinical Practics of Radiotechnology Students, Journal of radiological science and technology, vol. 27(4), 2004, pp. 75-83 4. E.O. Han “Survey and study on the safety management of radiation: centering on the radiation workers in medical institutions”, Department of Health Education The Graduate School of Ewha Womans University, 2002. 5. S.G. Kang. “Knowledge on Radiation Protection, Recognition and Performance on Radiation Protective Behavior in Operating Room Nurse”, Department of Nursing Graduate School, Dong-A University, 2012. 6. H.C. Cho. “Study on perception and behavior about radiation safety management and measurement of radiation dose for workers who work in the angiography room”, Department of Environment and Occupational Health Graduate School of Public Health Korea University, 2004. 7. Food and Drug Administration. Guideline for reducing radiation dose of patients, 2011. 8. J.H Kim, S.J. Ko, S.S Kang, S.Y. Choi, C. S. Kim. “Analysis of Radiation/ Radioactivity-Related Knowledge, Perception and Behaviors of Radiological Technologists”, Journal of Radiological Science and Technology, vol.34(2),2011, pp.123-129 9. H.S. Kim. “Knowledge, awareness and awareness of radiological Behavior Research”, Yonsei University Graduate School of Public Health Graduate Thesis, 2001. 10. G.E. Jeon. “Survey of Radiation Workers’ Knowledge, Perception, and Behavior for Radiation”, Department of Public Health Graduate School of Chonnam National University, 2013. 11. G.N. Choi, G.S. Jeon, Y.W. Kim. “Radiation Exposure Dose on Persons Engaged in Radiation-related industries”, Journal of the Korean Society of Radiology, vol. 6(1), 2012, pp. 27-37 Authors: Jin-keun Hong, Jung-Soo Han

Paper Title: Relational Characteristics of Maliciousness and Hacker in a Cyberattack Abstract: Cyber security threats are increasing day by day. However, this threat is sophisticated and intelligent. Therefore, artificial intelligence-based learning algorithms are emerging to effectively respond to cybersecurity threats. However, there has yet to be any interest or approach in studying the likelihood of an attack by efficiently analyzing the causes of the attack by individuals, religious groups, and hackers subordinate to state agencies. An idea in this study is to analyze hacker tendencies. And the link to how hacker tendencies affect attacks is being sought by the intelligence algorithm, which provides a sample of the predictive model as a preliminary study. Therefore, this study required a study on what an attacker's individual is influenced by, how a hacker subordinate to a religious group is affected by an attack from a religious group, and how a hacker subordinate to a national institution is affected by an attack from a state institution. In this study, however, we briefly focused on the factors that affect these attacks. In this study, we proposed an intelligent simplified model that predicts threats with the goal of producing results on whether or not an attack by combining the pattern of attack with 90. inputs and weighing factors. Therefore, three groups of attackers were analyzed. From this, a simple intelligent algorithm model was presented The results of this study are expected to help derive the correlation between future hacker attack propensity analysis and intelligent algorithm. Future research will implement a threat 525-530 analysis system that can more specifically derive attack propensity factors and apply them to intelligent algorithms (weights, f functions) to determine whether an attack is possible or not.

Keyword: cyberattack, learning, hacker, analysis, malicious. References: 1. Ryan Williams, Sagar Samtani, Mark Patton, Hsinchun Chen, “Incremental Hacker Forum collection and classification for proactive cyber threat intelligence,” in ISI2018. https://doi.org/ 10.1109/ISI. 2018.8587336 2. Mengyun Tang, Haichang Gao, Yang Zhang, Yi Liu, Ping Zhang, Ping Wang, “Research on Deep Learning Techniques in Breaking Text Based Captchas and Designing Image based Captcha,” IEEE Transactions on Information Forensics and Security, 13(10), pp. 2522-2537, 2018. https://doi.org/ 10.1109/TIFS.2018.2821096 3. S Sandhya, Sohini Purkayastha, Emil Joshua, Akash Deep, “Assessment of website security by penetration testing using wireshark,” in ICACCS2017, https://doi.org/10.1109/ICACCS. 2017.8014711 4. Taro Ishitake, Ryoichiro Obukata, Tetsuya Oda, Leonard Barilli. “Application of deep recurrent neural networks for prediction of user behavior in tor networks,” in WAINA2017, https://doi.org/10.1109/ WAINA.2017.63 5. George Hurlburt, “Shining light on the dark web,” IEEE Journal & Magazines, pp. 100-105, 2017, https://doi.org/10.1109/MC.2017.110 6. Tetsuya Oda, Ryoichiro Obukata, Masafumi Yamada, Taro Ishitake, Masahiro Hiyama, Leonard Barolli, “A neural network based user identification for tor network,” in CISIS2016, https://doi. org.10.1109/CISIS.2016.89 7. Taro Ishitaki, Tetsuya Oda, Leonard Barolli, “Application of neural networks and friedman test for user identification in tor networks,” in BWCCA2015, https://doi.org/10.1109/BWCCA.2015.88 8. Taro Ishitake, Donald Elmazi, Yi Liu, Tetsuya Oda, Leonard Barolli, Kazunori Uchida, “Application of Neural Networks for Intrusion Detection in Tor Networks,” in IEEE 29th ICAINAW2015, https://doi.org/10.1109/WAINA.2015.136 9. Poonam Patel, Krishnan Kannoorpatti, Bharanidharan Shanmugam, Sami Azam, Kheng Cher Yeo, “A theoretical review of social media usage by cyber criminals,” in ICCCI2017, https://doi.org/10.1109/ICCCI.2017.8117694 10. Andrew J. Park, Richard Frank, Alexander Mikhaylov, Myf Thomson, “Hackers hedging bets – a cross community analysis of three online hacking forums,” in ASONAM2018, https://doi.org/10.1109/ ASONAM.2018.8508613 11. Ivan Del Pozo, Mauricio Iturralde, Felipe Restrepo, “Social engineering – application of psychology to information security,” in FiCloudW2018, https://doi.org/10.1109/ASONAM.2018.8508613 12. Ericsson Marin, Jana Shakarian, Paulo Shakarian, “Mining key hackers on darkweb forums,” in ICDIS2018, https://doi.org/ 10.1109/ICDIS.2018.00018 Authors: Aisiri A P, C.M Patil

Paper Title: Feature Analysis on Retinal Blood Vessels for Human Authentication Abstract: Security plays a crucial role in protecting the important documents and systems from imposters. A biometric system extracts from the desired person the physiological or mannerism-based characteristics on which the system chooses whether to authorize or deny access. Even though the biometric modalities like fingerprint, face and voice are widely used, there is a demand for high security in certain fields like military and operation centers. This paper takes the datasets from kaggle and presents an idea about to authentication of a person using retinal blood vessels and template matching method based on user IDs and performance analysis is made. Also a scope to authenticate the retinal blood vessels of the person using the geometrical features like fractal dimensions, tortuosity, width, length, bifurcations etc is given and the performance analysis is done.

Keyword: Retina, User ID, Template Matching, Retinal Recognition and Geometric Characteristics. 91. References: 1. Michael Zimmerman “Biometrics and User Authentication” Copyright SANS Institute 2019. 2. B.M.S.Rani and Dr.A.Jhansi Rani “Biometric Retinal Security System for User Identification and Authentication in 531-534 Smartphones” International Journal of Pure and Applied Mathematics Volume 119 No. 14 2018, 187-202. 3. A. M. R. R. Bandara and P. W. G. R. M. P. B. Giragama “A Retinal Image Enhancement Technique for Blood Vessel Segmentation Algorithm”978-1-5386-1676-5/17/$31.00 ©2017 IEEE 4. https://en.wikipedia.org/wiki/Canny_edge_detector 5. T.S. Sasikala , K. Siva Sankar “ Unimodal Biometric Based Security Application by Exploiting Retina” International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-8, Issue-2S, December 2018. 6. Retinal Recognision – The Ultimate Biometric 7. https://resources.infosecinstitute.com/retinal-recognition-ultimate-biometric/#gref 8. Wahyudi Setiawan, Mohammad Imam Utoyo, and Riries Rulaningtyas “Retinal vessel segmentation using a modified morphology process and global thresholding”AIP Conference Proceedings 2021, 060031 (2018). 9. Jasem Almotiri , Khaled Elleithy and Abdelrahman Elleithy “Retinal Vessels Segmentation Techniques and Algorithms: A Survey”Appl. Sci. 2018, 8, 155. 10. Shan Zhu and Kai-Kuang Ma “A New Diamond Search Algorithm for Fast Block-Matching Motion Estimation” IEEE Transactions on Image Processing, vol. 9, no. 2, February 2000. 11. Maria del Pilar Angeles, Adrian Espino-Gamez “Comparison of methods Hamming Distance, Jaro, and Monge-Elkan” Copyright (c) IARIA, 2015. ISBN: 978-1-61208-408-4. Authors: Kavuluru Venugopal, Abhilasha Ambatipudi The Human Resource (HR) Factor and the Impact of Construction and Demolition (C&D) Waste on Paper Title: Environment: An Integrated Remedial Method Abstract: Around the globe, all the quarters are seriously concerned about the environment. The construction sector in particular, whilst contributing to largely socio-economic advancement of a country has become a foremost exploiter of natural non-renewable resources and a polluter of the atmosphere, contributing to environmental deprivation and waste generation in the process of acquirement of raw material and its deployment. Therefore, to combat the situation of regulating construction and demolition wastes a strong and stringent organizational and governmental policy is necessitated. But for implementation of the policy, enlightening the persons involved a sound and efficient HR is essential which only can implement waste management practices successfully aligning concerned departments for environmental sustainability are discussed in the paper. 92.

Keyword: HRM, C&D waste management, environmental sustainability. 535-538 References: 1. Green HRM Practices- A Review by A. Anton Arulrajah; senior lecturer Department of Management, Eastern University. Prof. H.H.D.N.P. Opatha,senior professor, Department of HRM, University of Sri Jeyeyewardenapura. Dr. N.N.J. Nawaratne, senior lecturer. Department of HRM, University of Colombo. 2. The Impact of Construction and the Built Environment. Version 1:December 2016;briefingnote 33,produced on behalf of WILLMOTT DIXON by WD Re-Thinking Ltd. 3. Managing Knowledge within the Leading Irish Construction Organizations: Current Practices and Future Directions by Brian Graham and Ken Thomas. 4. Best Practice: Environmental Management Environmental Guidelines for Major Construction Sites: EPA publication downloaded from http://WWW.epa.vie.gov.au 5. Challenges Facing the Green Building Industry by Geoff Bilau. (Official July/August 2008) article. 6. Green Human Resource Management: Policies and Practices by Shoeb Ahmad.Cogent business and management. Management Review article from http/dxdoi.org/10.108/23311975.2015.1030817 7. Changing Behavior: Successful Environmental Programmes in the Workplace Wiley online Library: Business Strategy and Environment by William Young; Matthew Davis, llona M.Mc Neill: Bindu Malhotra. Sally Russell; Kerrie Unsworth, Chris.W.Clegg. First Published.28 December 2013.DOI:10.1002/bse.1836. 8. Environmental Issues During Construction chapter 51. MDT Environmental Manual.October.2010. 9. A Study of Construction Material Waste Management Practices By Construction Firms in Nigeria by A.A.Dania, J.O.Kehinde and K.Bala, department of Building, Ahmedu Bello University, Zaria, Kaduna state Nigeria: [email protected] 10. Environmental Standards for Construction and Demolition Waste Disposal Sites by Marie Ryam, senior environmental scientist; issue date May 2010.Government of New Found Land and Labrador. Department of Environment and Conservation. 11. Construction’s Impact on the Environment by Sourceable-March 1st 2016 article web source 12. Environmental Constraints in Construction and How to Overcome Them. E-posted on April28 2017 by Shannon Menard, e-Sub; construction soft ware. 13. The Environmental Impacts of Construction Projects and the Next Steps Forward for the Industry. E posted on January 13.2017 by Tyler. 14. Construction and Environment Eng. Rehman Ahmad. Head, Waste Disposal Unit; Environmental Control Directorate. Environment & Wildlife. Kingdom of Bahrain 15. How does Construction Impact Environment? June 21 2017, article web source 16. Human Activities that Affect the Ecosystem by David Weed mark. Updated June 21, 2017, article web source. 17. Impact of construction Material on Environment (steel & concrete) by Heera Lamite & Sridhar Kare: University College of Boras, School of Engineering Authors: Nithin.S.S, L. Padma Suresh

Paper Title: A Relative Method of Video Coding using Different Wavelets with SPIHT Abstract: Lossy or lossless data compression is needed to Bring down the storage size and greater transmission rate. Wavelet transform is one of the ideal methods used for video compression. Different types of wavelet transforms are now available. In this paper, video is compressed by different wavelets and modified version of SPIHT. Totally seven types of wavelets are used here to compress the video, MSPIHT is used as encoding technique. They are (i) Video coding using duabechies wavelet and MSPIHT (VDM) (ii) Video coding using haar wavelet and MSPIHT (VHM) (iii) video coding using bi orthogonal wavelet and MSPIHT (VBM) (iv) video coding using symlet wavelet and MSPIHT (VSM) (v) video coding using coiflet wavelet and MSPIHT (VCM) (vi) video coding using demeyer wavelet and MSPIHT (VDMM) and (vii) video coding using Mexican hat wavelet and MSPIHT (VMHM). Then we calculate the PSNR and compression ratio for knowing 93. the performance of the system.

539-543

Keyword: (EWT) Empirical wavelet transforms, VHM, VDM, VBM, VSM, VCM, VDMM, VMHM and PSNR References: 1. Daubechies, W. Sweldens, 1998, “Factoring wavelet into lifting steps”, J. Fourier Anal. Appl., Vol.4(3), pp.247–269. 2. IyyapanDhasarathan, VimalRathinasamy, Tang Chi, “Wavelet Based SPIHT Compression for DICOM Images”, Linnaeus University, School of Computer Science, Physics and Mathematics, 2011. 3. Madhuri A., “Digital Image Processing”, an Algorithmic Approach”, PHI, New Delhi, pp. 175-217, 2006. 4. Swapna Devi, Niveditta “A New Method for Color Image Quality Assessment”, International Journal of Computer Applications , Volume 15– No.2, February 2011 5. Wavelets and different multi resolution techniques. 6. Woods R. E., Gonzalez R. C Digital Image Processing, Second Edition, ISBN: 0-20-118075-8 Authors: Abhijit J. Patankar, Kotrappa Sirbi, Kshama V. Kulhalli

Paper Title: Preservation of Privacy using Multidimensional K-Anonymity Method for Non-Relational Data Abstract: Mining of huge data having complexity is a challenging issue also maintaining Privacy of data is also equally important ,sometimes there is a need to release data for use of researchers or for the purpose of gaining knowledge or earn money this release of data includes releas e of all attributes of personal data. when this type of data like Insurance record data, Medical diagnosis data, funding scheme data is release even if we remove sensitive attribute like Name for hiding personal details still data re-identification is possible by linking public data like voters data with these released data and by linking the quasi identifiers we are able to get sensitive information about person like critical disease, financial position etc. by applying k–Anonymization using multiple dimensions of attributes we are able to hide these sensitive attributes by generalising and 94. suppressing the Quasi identifiers so that when linking with public database is done no records are re-identified, also we obtained results for quality measures for anonymisation and observed that the value of k once we start 544-547 increase after some threshold anonymity starts decreasing so there is a need to choose proper value of k on non- relational data.

Keyword: re-identification References: 1. Pingshui Wang, Jiandong Wang1, Xinfeng Zhu1, Jian Jiang, “Reserch on Privacy Preserving Data Mining”, International Conference on Biological and Biomedical Sciences Advances in Biomedical Engineering, Vol.9, pp.251-257, 2012. 2. Charu C. Aggarwal, “A General survey of Privacy-Preserving Data Mining Models And Algorithms”, IEEE, pp 11-52,2008. 3. Sweeney L., “K-anonymity: A Model for protecting privacy”, International Journal of Uncertainty, Fuzziness and Knowledge based system, 10(5), pp.557-570, 2002. 4. Slava kisilevich, Lior Rokach, Yuval Elovici, Bracha Shapira,”Efficient Multi-dimensional Suppression for k-anonymity”, IEEE transaction, pp1-14,2009. 5. Kshitij Pathak, Nidhi Maheshwarkar, “Performance issues of various K-anonymity Strategies”, IJCTEE ,ISSN:2231-2307, Vol.1,Issue 2, pp18-22,2011. 6. LeFevre K, DeWitt D J, Ramakrishnan R,“Mondrian multidimensional K- anonymity”, IEEE International Conference on Data Engineering(ICDE06), Atlanta, GA, USA, pp1- 11,April 2006. 7. Hall M., Frank E., Holmes G., Pfahringer B., Reutemann P., Witten I. “The WEKA data mining software: an update”, ACM SIGKDD Explorations Newsletter, v.11 n.1, pp10- 18june 2009 [doi:10.1145/1656274.1656278]. 8-1 Qian Wang, Cong Xu, Min Sun, “ Multi-dimensional K-anonymity based on Mapping for Protecting Privacy”, Journal of Software, Vol. 6, No. 10, pp1937-1947,October 2011 . 8-2 Qian Wang, Cong Xu, Min Sun, “ Protecting Privacy by Multi- dimensional K- anonymity”, Journal of Software, Vol. 7, No. 8, August 2012,pp1873-1880. 9 Yongbin Yuan, Jing Yang, Sheng Lan “P-sensitive k-anonymity Based on Nearest Neighborhood Search in Privacy Preserving”, Journal of Information and Computational Science 9: 5(May 2012) ,pp1385-1393. 10 Gionis A, Tassa T., “k-Anonymization with Minimal Loss of Information”, Knowledge and Data Engineering, IEEE Transactions, pp. 206-219, 2009. 11 Madhan Subramaniam, Senthil R., “An Analysis on Preservation of Privacy in DataMining”, International Journal on Computer Science and Engineering Vol. 02, No. 05, 2010,pp1696-1699. 12 Abdullah H. Wahbeh, Qasem A. Al- Radaideh, Mohammed N., “A Comparison Study between Data Mining Tools over some Classification Methods”, International Journal of Advanced Computer Science and Applications, December 2011. 13 C. Blake, C. Merz., “UCI repository of machine learning databases”, 1998. http://www.ics.uci.edu/mlearn/M1Repository.html. 14 Samarati, Latanya Sweeney, “Protecting privacy when disclosing information: k-Anonymity and its enforcement through generalization and suppression”, IEEE Transactions on Knowledge and Data Engineering, 2001 15 Accuracy-Constrained Privacy- Preserving Access Control Mechanism for Relational Data Zahid Pervaiz, Walid G. Aref, Senior Member, IEEE, Arif Ghafoor, Fellow, IEEE, and Nagabhushana Prabhu, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL.26, NO. 4, APRIL 2014. 16 Liu, Kai-Cheng & Kuo, Chuan-Wei &Liao, Wen-Chiuan & Wang, Pang-Chieh. (2018). Optimized Data de-Identification Using Multidimensional k-Anonymity. 1610-1614. 10.1109/TrustCom/BigDataSE.2018.00235. Authors: Abhijit Roy, Anup Kumar Saha Modeling of Liquid Hot Metal Sloshing in Ladles During Transportation by Locomotives (A Bond Paper Title: Graph Method) Abstract: Safe and secure transportation of liquid hot metal in steel plants is very challenging. About ninety percent of transportation is by means of locomotives. Sloshing is a common phenomenon in open container liquid transportation due to external excitation. Non-linear sloshing dynamics of liquid hot metal in ladle due to locomotive movement is the prime consideration of this paper. Liquid hot metal inside the ladle has been considered in the line of an equivalent mechanical system. Resulting forces and moments acting on the ladle inside wall are considered equal in all senses. An equivalent mechanical dynamic system representation of sloshing by bond graph modellinghas been formulated by keeping records in a satisfactory way.Future research scopes has been identifiedin parallel with an outline mapped. Hot metal liquid has two distinct components of the hydrodynamic pressure in consideration of rigid containershas been identified. Bottom segment of the molten metal column moves unison with the ladleandis directlyproportional with the acceleration of the ladle. Whereas the second one ‘convective’ pressure at the free surface, particularly experiences the sloshing tendency due to external forces.

Keyword: Bond graph Dynamics Locomotives Modeling Simulation Sloshing 95. References: 1. RanjitKarmakar, A.Mukherjee, Dynamics of Electric Overhead Travelling Cranes, Mech.Mach.Theory 25 (1990) 29-39. 548-551 2. Quang Hieu Ngo, Keum-Shik Hong, Il HyoJung, Adaptive control of an axially moving system, Journal of Mechanical Science and Technology 23 (2009)3071-3078. 3. Abhijit Roy, A.K. Saha, Bond Graph Modeling and Simulation of Liquid Metal Sloshing in Ladle, International Conference on Bond Graph Modeling and Simulation, ICBN 978-1-5108-2425-6 (2016) 191-197. 4. R.A. Ibrahim, V.N. Pilipchuck, T. Ikeda, Recent Advances In Liquid Sloshing Dynamics, Applied Mechanics Reviews54 (2001) 133-199. 5. Sir G. G. Stokes, Discussion of a Differential Equation Relating to Breaking of Railway Bridges, Mathematics Physics Paper2 (1849) 179. 6. E. Lightfoot, Shock loading effects in overhead travelling cranes-review of dynamic stress allowances. Engng 181 (1956) 169. 7. R.A. Ibrahim, Liquid Sloshing Dynamics, Cambridge University Press, New York, ISBN-13 978-0-5II-12492-I,Ch.5 Equivalent Mechanical models (2005) 296-334. 8. Bamdad Mahdi, Taheri Farzin, Abtahi Niloofar, Dynamic analysis of a Hybrid Cable-Suspended Planar Manipulator, IEEE International Conference on Robotics and Automation (ICRA) (2005) 1621-1626, Washington State Convention Center Seattle, Washington, May 26-30, 2015. 9. A.Mukherjee, R.Karmakar, A.K. Samanta Roy, Modeling and Simulation of EngineeringSystems, ISBN 81-88237-96-5 Publisher: I.K.International Publishing House Pvt Ltd.2006. 10. Cao Lingzhi, Lu Liping, Cui Guangzhao, Wei Shangbei, Lou Feipeng, Miao Weipu, Sequential modeling and control of the dynamic load in crane lifter, pp 4844-48482009 Chinese Control and Decision Conference, 2009. 11. T.X. Wu, D.J. Thompson,Vibration Analysis of Railway Track with Multiple wheels on the Rail,Journal of Sound and Vibration239 (2001) 69 – 97. Shegelman I. R., Vasilev A. S., Sukhanov Y. V., Galaktionov O. N., Kuznetsov A. V., Anuchin A. S., Authors: Shtykov A. S. Use of Knowledge Base for Improving Equipment for Preparatory Works in Forest Areas (By Paper Title: 96. Example of Increment Borer and Tree Caliper) Abstract: The forest complex of the Russian Federation undergoes a transition from extensive model of harvesting and forestry to the intensive one. Such a transition requires a quality forest and technological 552-560 preparation of forest areas for logging operations. The key basic material for such preparation is the assessment of qualitative and quantitative indicators of stands of forest resources of forest enterprises, which includes the assessment of stand age structure, growth course of different wood species, stand qualitative structure and a number of other inventory indicators. The need to enhance the quality of forest and technological preparation of forest areas necessitates the raise of requirements for inventory instruments. In this regards, over the last years there has been increased attention of researchers and developers to the elaboration of existing and development of new types of inventory instruments. Their development based on the fundamentally new patented technological and technical solutions which is the principal indicator of the level of these intellectual property objects. The authors develop the patentable objects of intellectual property on the basis of methodology of functional and technological analysis and synthesis of new technical solutions applying the built knowledge bases on improved or newly created objects of technology based on the expanded patent-information search. Considering the example of inventory instruments (increment borers and tree caliper), the effectiveness of knowledge base use with application of the functional and technological analysis as an instrument for establishment of new intellectual property was demonstrated.

Keyword: intellectual property, forest area, timber harvesting, logging operations, patent, forest inventory. References: 1. Almetov, A. N. (2001). Russian Patent no. 2163865 “Borer for extraction of wood core.” 2. Almetov, A. N. & Mazurkin, P. M. (2000). Russian Patent no. 2158676 “Cutting part of drill for wood core extraction.” 3. Aleixo da Silva, J. A., Borders B. E & Brister G. H. (1994). Estimating tree volume using a new form factor. Commonwealth Forestry Review, 73, 14–17. 4. Almetov, A. N. (2001). Improvement of the design of the borer for wood core extraction from growing trees of various species (Doctoral dissertation). Yoshkar-Ola, p. 174. 5. Andersen, H. E., Reutebuch, S. E. & McGaughey, R. J. (2006). A rigorous assessment of tree height measurements obtained using airborne lidar and conventional field methods. Canadian Journal of Remote Sensing, 32, 355–366. 6. Anuchin, N. P. (1982). Forest inventory (5th ed.). Moscow: Lesnaya Promyshlennost. 7. Artemiev, O. S. (2013). Russian Patent no. 135406 “A device for measuring the diameter of the tree trunk.” 8. Artemiev, O. S. & Artemiev, I. S. (1997). Methods of growing tree parameters assessing with machine vision system. In Forest Inventory and Forest Management (pp. 133-135). Krosnoyarsk: KGTA. 9. Artemiev, O. S. & Naidenko, E. A. (2014). Russian Patent no. 143336 “Device for remote measurement of a growing tree trunk diameter.” 10. Artemiev, O. S. & Zaichenko, L. P. (2004). Russian Patent no. 2226669 “Device measuring diameter of trunk of growing tree.” 11. Baginskiy, V. F. (2013). Forest inventory. Gomel: GGU im. F. Skoriny. 12. Bartalev, S. A., Lupian, E. A., Neishtadt, I. A. & Savin, I. Yu. (2005). Remote assessment of agricultural land parameters through satellite data of MODIS spectroradiometer. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli Iz Kosmosa, 2(2), 228- 236. 13. Bollandsås, O. M &. Næsset, E. (2007). Estimating percentile-based diameter distributions in unevensized Norway spruce stands using airborne laser scanner data. Scandinavian Journal of Forest Research, 22, 33–47. 14. Brooks, J. R., Jiang, L. & Ozçelik, R. (2008). Compatible stem volume and taper equations for Brutian pine, Cedar of Lebanon and Cilicica fir in Turkey. Forest Ecology and Management, 256, 147–151. 15. Brown, P. M. (2007). А modified increment borer handle for coring in locations with obstructions. Tree-Ring Research, 63(1), 61–62. 16. Bugaev, V. A. & Serikov, M. T. (2000). Recreational forest management. In Forest Inventory and Forest Management (pp. 143-149). Krosnoyarsk: SibGTU. 17. Case, B. S. & Hall, R. J. (2008) Assessing prediction errors of generalized tree biomass and volume equations for the boreal forest region of west-central Canada. Canadian Journal of Forest Research, 38, 878–889. 18. Chasmer, L., Hopkinson, C. & Treitz, P. (2006). Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar. Canadian Journal of Remote Sensing, 32, 116–125. 19. Davydov, V. F., Illarionov, G. P., Shalaev, V. S., Komarov, E. G. & Mukhin, A. S. (2002). Russian Patent no. 2183847 “Procedure of plantation evaluation.” 20. Kasianov, A. E. & Kharin, O. A. (2005). Russian Patent no. 2254708 “Method of forest assessment on drainage lands.” 21. Kazakov, V. I., Galanov, V. N., Beglova, G. N., Berezin, A. S. & Anisimova, G. V. (2002). Russian Patent no. 2189731 “Tree measuring fork.” 22. Kliuev, G. V. (2013). Research in the field of increment borers improvement. Inzhenerny Vestnik Dona, 4(27), 45. 23. Kliuev, G. V. (2014). Methodic principles of justification of promising equipment for forest inventory. Inzhenerny Vestnik Dona, 1(28), 49. 24. Kliuev, G. V. (2016). Inventory instrument as a method of rational forest utilization. Inzhenerny Vestnik Dona, 3(42), 48. 25. Kliuev, G. V., Shegelman, I. R. & Vasilev, A. S. (2015a). Russian Patent no. 157061 “Hammer incremental.” 26. Kliuev, G. V., Shegelman, I. R. & Vasilev, A. S. (2015b). Russian Patent no. 157144 “A drill with holder, dynamometer.” 27. Leeuwen, M. & Nieuwenhuis, M. (2010). Retreival of forest structural parameters using LiDAR remote sensing. European Journal of Forest Research, 129, 749-770. 28. Lukashevich, V. M., Shegelman, I. R. & Vasilev, A. S. (2013). Russian Patent no. 134847 “Borer age for extracting a core of wood.” 29. Luoma V., Saarinen N., Wulder M., White J., Vastaranta M., Holopainen M. & Hyyppä J. (2017). Assessing precision in conventional field measurements of individual tree attributes. Forests, 8, 38. Retrieved from: https://www.mdpi.com/1999- 4907/8/2/38/htm 30. Lupian, E. A., Savin, I. Yu., Bartalev, S. A., Tolpin, V. A., Balashov, I. V. & Plotnikov, D. E. (2011). “VEGA” satellite service of vegetation status monitoring. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli Iz Kosmosa, 8(1), 190- 198. 31. Martynov, A. N., Melnikov, E. S., Koviazin, V. F., Anikin, A. S., Minaev, V. N. & Beliaeva, N. V. (2008). The fundamentals of forest management and forest inventory. St. Petersburg: Lan. 32. Mazurkin, P. M. & Kudriavtseva, A. E. (2015). Russian Patent no. 2540557 “Method to measure diameter of tree trunk and device for its realisation.” 33. Mazurkin, P. M. & Meteleeva, O. A. (2004). Russian Patent no. 2237402 “Method for measurement of annular rings on tree trunk cut.” 34. Mazurkin, P. M., Sadovin, D. V. & Meteleeva, O. A. (2005). Russian Patent no. 2265841 “Method for analyzing of tree trunk saw cut.” 35. Mazurkin, P. M., Sadovin, D. V. & Pirogova, E. S. (2004). Russian Patent no. 2236115 “Method for measuring radius of tree trunk saw cut.” 36. Mazurkin, P. M. & Tishin, D. V. (2017). Russian Patent no. 2633791 “Drill for wood core recovery.” 37. Moshkalev, A. G., Knize, A. A., Ksenofontov, N. I. & Ulanov, N. S. (1982). Stand commodity pattern inventory. Moscow: Lesnaya Promyshlennost. 38. Næsset, E. (2004). Practical large-scale forest stand inventory using a small-footprint airborne scanning laser. Scandinavian Journal of Forest Research, 19, 164–179. 39. Næsset, E. (2007). Airborne laser scanning as a method in operational forest inventory: status of accuracy assessments accomplished in Scandinavia. Scandinavian Journal of Forest Research, 22, 433–442. 40. Nagimov, Z. Ya., Shevelina, I. V. & Korostelev, I. F. (2019). Devices, instruments and equipment for forest inventory. Ekaterinburg: UGLTU. 41. Petrovskiy, V. S. (2015). Russian Patent no. 2557167 “Method of determining dimensional technological parameters of tree trunks.” 42. Petrovskiy, V. S., Filipov, M. V. & Murzinov, Yu. V. (2009). Russian Patent no. 2363149 “Electronic forest tree calipper.” 43. Pogorelov, A. V., Steblovskiy, A. S., Kuznetsov, K. V. (2012). Russian Patent no. 124788 “Geographic information system of land monitoring.” 44. Shavnin, A. G., Shavnin, V. A., Shavnin, S. A., Zvezdin, V. K. & Kuznetsov, V. P. (1995). Russian Patent no. 2050114 “Method for assessment of volumes of growing tree trunks.” 45. Shegelman, I. R., Lukashevich, V. M., Vasilev, A. S. & Sukhanov, Yu. V. (2013). Russian Patent no. 135575 “The guide device for the auger age.” 46. Shegelman, I. R., Sukhanov, Yu. V., Vasilev, A. S. & Lukashevich, V. M. (2014). Russian Patent no. 142445 “A device for guiding the auger.” 47. Shegelman, I. R., Vasilev, A. S. & Kliuev, G. V. (2014a). Russian Patent no. 141050 “A drill for wood research.” 48. Shegelman, I. R., Vasilev, A. S. & Kliuev, G. V. (2014b). Russian Patent no. 142442 “Hammer incremental.” 49. Sukhikh, V. I., Sidorenko, V. V. & Borovikov, N. Z. (1974). Modern forest management and forest inventory. Pushkino: VNIShSh. 50. Tesliuk, N. K. (1978). Measurement inventory methods. Moscow: Lesnaya Promyshlennost. 51. Tiurin, A. V. (1945). Forest inventory. Moscow: Goslesbumizdat. 52. Toropov, A. S., Anisimov, S. E., Volkova, L. P., Zhidkova, E. V. & Kondakov, I. A. (2004). Russian Patent no. 2242755 “Measuring fork.” 53. Vagin, A. V., Murakhtanov, E. S., Ushakov, A. I. & Kharin, O. A. (1978). Forest Inventory and Forest Management. Moscow: Lesnaya Promyshlennost. 54. Vasilev, A. S. & Shegelman, I. R. (2017). Russian Patent no. 169677 “Borer age.” 55. Vasilev, A. S., Shegelman, I. R. & Kliuev, G. V. (2015). Russian Patent no. 149945 “Borer-dynamometer.” 56. Vasilev, A. S., Shegelman, I. R. & Lukashevich, V. M. (2013). Russian Patent no. 134478 “The guide device for the auger.” 57. Vasilev, A. S., Shegelman, I. R., Lukashevich, V. M. & Sukhanov, Yu. V. (2015). Russian Patent no. 157121 “A drill for the removal of the core timber.” 58. Vasilev, A. S., Shegelman, I. R., Lukashevich, V. M. & Sukhanov, Yu. V. (2017). Russian Patent no. 168058 “Calliper marker.” 59. Vasilev, A. S., Shegelman, I. R., Sukhanov, Yu. V., & Lukashevich, V. M. (2015). Russian Patent no. 157145 “Calliper- borer.” 60. Vastaranta, M., Wulder, M., White, J., Pekkarinen, A., Tuominen, S., Ginzler, C., ... Hyyppä, H. (2013). Airborne laser scanning and digital stereo imagery measures of forest structure: Comparative results and implications to forest mapping and inventory update. Canadian Journal of Remote Sensing, 39, 382–395. 61. West, P. W. (2009). Tree and Forest Measurement. Retrieved from: http://www2.ca.uky.edu/Forestry/FOR250/Tree%20and%20Forest%20Measurement%20book.pdf 62. Williams, R. J., Zerihun, A., Montagu, K. D., Hoffmann, M., Hutley, L. B. & Chen, X. (2005). Allometry for estimating aboveground tree biomass in tropical and subtropical eucalypt woodlands: towards general predictive equations. Australian Journal of Botany, 53, 607–619. 63. Wulder, M. A., White, J. C., Nelson, R. F., Næsset, E., Ørka, H. O., Coops, N. C., … Gobakken, T. (2012). Lidar sampling for large-area forest characterization: A review. Remote sensing of Environment, 121, 196-209. 64. Zagreev, V. V., Gusev, N. N., Moshkalev, A. G. & Selimov, Sh. A. (1991). Forest Inventory and Forest Management. Moscow: Ekologiya. 65. Zakamenskiy, V. A. & Zakamenskiy, S. V. (2003). Russian Patent no. 2203532 “Apparatus for detecting rot in tree trunks.” 66. Ziganshin, R. A. (2014a). Russian Patent no. 2531329 “Method of determining completeness of multi-storeyed, mixed, and uneven-aged timber stands.” 67. Ziganshin, R. A. (2014b). Russian Patent no. 2535725 “Method of site class determination of complex, mixed, uneven- aged plantations.” Authors: Anju Bala, Rajender Singh Chhillar Automatic Test Cases Generation using Multistage-Based Genetic Algorithm for Object Oriented Paper Title: Testing Abstract: Software testing is a major phase that takes place under the construction of software designing. Basically, testing is a process that assists in the determination of work that it reached to the desired output or not. It generally depends on the validation and verification procedure, whereas in simple terms a software testing process is to discover the bugs, errors, faults of the developed software and manage it. It is also considered as the risk based activity. The testing criterion is different at each level and it is completed in various steps. The life cycle of software testing is composed of various steps as the feasibility study, data gathering and specification, design or framework, unit testing, integration and system testing. At last the maintenance is occurring to finalize 97. the software application. In software engineering several kinds of testing strategies are utilized as black box, white box, regression testing, static, dynamic and so on. There are enormous advantages of software testing. The 561-573 common advantages are to investigate software quality, access the huge pool for verification, deducted the construction cost, improve the reusability, aimed at the basic competencies, increase the demand of the product, balance the time period for the development of software and boost the competitiveness. But there are also certain vulnerabilities related to the large investments, software tools, training, need of more manpower, most time consuming of test preparations, need of more testing space, hidden errors impact on the entire code and cost. In the proposed work, the performance is reliant on the better way. Test case generation is a procedure to generate software corresponding various test case generations and validate various test cases. So that research work identifies the quality of software. This process also declined the maintenance cost (MC) of a software system. In the proposed architecture design, Multi-stage Genetic algorithm has various benefits as it is highly effective in higher dimensional spaces, more memory efficient and versatile. Basically, Multi-stage GA is applied in several real-time applications as in the text categorization, classification of test cases and regression related issues. In the research work, mutants compare various existing techniques and performance parameters are like as mutants, accuracy rate, time consumption and number of events. The planned approach is best in terms to enhance the accuracy rate and achieved it in a reduced time period. Several techniques are used to compare the number of events fire. So that, the architecture accuracy rate has achieved this based on the number of events. The multistage GA test case is an intelligent approach and supportive to various languages like .Net, Java, C++ and Project Management used in an automatic test case. It helps to improve the quality of software and based on the mutants. Basically, mutants are like failure (Some time it is passed or sometimes it fails). The reduced number of mutants increased the software quality.

Keyword: SDLC (Software Development Life Cycle), OOPS (Object Oriented Programming System), GA (Genetic Algorithm), PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization), BCO (Bee Colony Optimization. References: 1. Binder, R. V. (1994). Testing object-oriented systems: a status report. American Programmer. 2. Kapfhammer, G. M. (2004). Software testing. In In The Computer ScienceHandbook. 3. Ivar, J., Magnus, C., Patrik, J., & Gunnar, O. (1992). Object-oriented software engineering, a use case driven approach. MA.: Addis 4. Dalal, S., & Chhillar, R. S. (2012). Software Testing-Three P'S Paradigm and Limitations. International Journal of Computer Applications, 54(12). 5. Luo, L. (2001). Software testing techniques. Institute for software research international Carnegie mellon university Pittsburgh, PA, 15232(1-19), 19. 6. Blaha, M. (2005). Object-Oriented Modeling and Design with UML: For VTU, 2/e. Pearson Education India. 7. Jalote, P. (2012). An integrated approach to software engineering. Springer Science & Business Media. 8. www.selfgrowth.com/articles/top-10-benefits-of-software-testing) 9. Malik, S., & Nigam, C. (2017). A Comparative study of Different types of Models in Software Development Life Cycle. 10. Pohl, K. (2010). Requirements engineering: fundamentals, principles, and techniques. Springer Publishing Company, Incorporated. 11. Davis, A. M., Bersoff, E. H., & Comer, E. R. (1988). A strategy for comparing alternative software development life cycle models. IEEE Transactions on software Engineering, 14(10), 1453-1461. 12. Malik, S., & Nigam, C. (2017). A Comparative study of Different types of Models in Software Development Life Cycle. 13. Munassar, N. M. A., & Govardhan, A. (2010). A comparison between five models of software engineering. IJCSI, 5, 95-101. 14. Ruparelia, N. B. (2010). Software development lifecycle models. ACM SIGSOFT Software Engineering Notes, 35(3), 8-13. 15. Bonissone, P. P. (1997). Soft computing: the convergence of emerging reasoning technologies. Soft computing, 1(1), 6-18. 16. Kurhe, A. B., et al., (2011). Soft Computing and its Applications. BIOINFO Soft Computing, Volume 1, Issue 1. 17. Kim, M. Y., & Cheon, Y. (2008, April). A Fitness Function to Find Feasible Sequences of Method Calls for Evolutionary Testing of Object-Oriented Programs. In Software Testing, Verification, and Validation, 2008 1st International Conference on (pp. 537- 540). IEEE. 18. Liang, Y. C., & Smith, A. E. (2004). An ant colony optimization algorithm for the redundancy allocation problem (RAP). IEEE Transactions on reliability, 53(3), 417-423. 19. Davidović, T., Teodorović, D., & Šelmić, M. (2015). Bee colony optimization-Part I: The algorithm overview. Yugoslav Journal of Operations Research, 25(1), 33-56. 20. Shi, Y., & Eberhart, R. C. (1999). Empirical study of particle swarm optimization. In Evolutionary computation, 1999. CEC 99. Proceedings of the 1999 congress on (Vol. 3, pp. 1945-1950). IEEE. 21. Jamil, M. A., Arif, M., Abubakar, N. S. A., & Ahmad, A. (2016, November). Software Testing Techniques: A Literature Review. In Information and Communication Technology for The Muslim World (ICT4M), 2016 6th International Conference on (pp. 177- 182). IEEE. 22. Nouman, M., Pervez, U., Hasan, O., & Saghar, K. (2016, May). Software testing: A survey and tutorial on white and black-box testing of C/C++ programs. In Region 10 Symposium (TENSYMP), 2016 IEEE (pp. 225-230). IEEE. 23. Larrea, M. L. (2017). Black-Box Testing Technique for Information Visualization. Sequencing Constraints with Low-Level Interactions. Journal of Computer Science & Technology, 17. 24. Henard, C., Papadakis, M., Harman, M., Jia, Y., & Le Traon, Y. (2016, May). Comparing white-box and black-box test prioritization. In Software Engineering (ICSE), 2016 IEEE/ACM 38th International Conference on (pp. 523-534). IEEE. 25. Shin, K. W., & Lim, D. J. (2018). Model-based automatic test case generation for automotive embedded software testing. International Journal of Automotive Technology, 19(1), 107-119. 26. Dalal, S., and Chhillar, R. S. (2012). Case studies of most common and severe types of software system failure. International Journal of Advanced Research in Computer Science and Software Engineering, 2(8). 27. Le Lann, G. (1997, March). An analysis of the Ariane 5 flight 501 failure-a system engineering perspective. In Engineering of Computer-Based Systems, 1997. Proceedings., International Conference and Workshop on (pp. 339-346). IEEE. 28. Gray, J., and Siewiorek, D. P. (1991). High-availability computer systems. Computer, 24(9), 39-48. 29. Rahideh M, Mazloum SZ. Combination System Optimization of Solar Collector/ Photovoltaic with Genetic Algorithms. Medbiotech Journal. 2019;03(02):58-64. 30. Hosseini Naghavi AB, Alishah O, Gorji AM. Investigation of the Genetic Diversity of Cultivars and Lines of Tetraploid Cottons by the use of Quantitative Morphologic Properties of Fibers. Medbiotech Journal. 2019;03(02):65-9. 31. Amanlou M, Mostafavi SM. In sillico screening to aim computational efficient inhibitors of caspase-9 by ligand-based pharmacophore modeling. Medbiotech Journal. 2017;01(01):34-41. 32. Mostafavi SM, Bagherzadeh K, Amanlou M. A new attempt to introduce efficient inhibitors for Caspas-9 according to structure- based Pharmacophore Screening strategy and Molecular Dynamics Simulations. Medbiotech Journal. 2017;01(01):1-8. 33. Salehi, S., & Mo'tadel, M. (2015). Model presentation to feasibility measurement of knowledge management implementation with ANP approach (case study of Post bank) . UCT Journal of Research in Science, Engineering and Technology, 3(4), 17-23. 34. Freitas, M. D. C., & Mira da Silva, M. (2018). GDPR Compliance in SMEs: There is much to be done. Journal of Information Systems Engineering & Management, 3(4), 30. 35. Mendoza, D. J., & Mendoza, D. I. (2018). Information and Communication Technologies as a Didactic Tool for the Construction of Meaningful Learning in the Area of Mathematics. International Electronic Journal of Mathematics Education, 13(3), 261-271. https://doi.org/10.12973/iejme/3907

98. Authors: Pawan Kumar Tanwar, Ajay Khunteta, Vishal Goar Paper Title: Applying Multi Property Tree for Multi Keyword Rank Searching and Dynamic Update in Cloud Abstract: Various types of data structures are used for keyword searching like binary tee, KBB tree, inverted tree, inverted index, Multi Property Tree (MPT). These data structures are used for searching keywords in cloud space after getting instructions from data user. On the basis of MPT data structure the authors have introduced a search scheme called MPTsearch algorithm. Experiments show that the proposed scheme performs better than linear search. It also achieves lower time consumption and computing overhead for queries and trapdoor formation. Moreover this scheme not only fulfills the searching part but also plays vital role in dynamic update (insertion and deletion) of data provided by the data owner.

Keyword: Multi Property Tree, MPTsearch algorithm, dynamic update. References: 1. Perrig, D. Wagner and D. X. Song ‘‘Practical techniques for searches on encrypted data,’’ In the Proc. of ieee sympo. for Sec. and Priva., Berkeley, USA, May 2000, pp. 44-55. 2. W. Jonker, Hartel P. and R. Brinkman, “Conjunctive wildcard search over encrypted data,” In the proceedings of workshop for secure data management, Seattle, USA, 2011, pp. 114-27. 3. R. Ostrovsky, S. Kamara, J. Garay and R. Curtmola, “Searchable symmetric ncryption: Improved definitions and efficient constructions,” Jou. of Comp. Sec., volume 19, number 5, pp. 895-934, Jan. 2011. 4. G. Persiano, R. Ostrovsky, G. Di Crescenzo and D. Boneh, “Public key encryption with keyword search”, in Proceedings of euro crypt, Switzerland, 2004, pp. 506-22. 5. Waters, Shi E. and E. Shen, “Predicate privacy in encryption systems”, in Th. of Crypt., San Francisco, USA, Springer, 2009, pp. 457-73. 6. B. Waters and D. Boneh, “Conjunctive subset and range queries on encrypted data,” In the Proceedings of Theory crypt. Conference, The Netherlands, 2007, pp. 535-54. 7. F. Monrose, Kamara S. and L. Ballard, “Achieving efficient conjunctive keyword searches over encrypted data,” in the proceedings of International Conference for Info. and Comm. Sec., China, 2005, pp. 414-26. 8. P. J. Lee, D. J. Park and K. Kim, “Public key encryption with conjunctive field keyword search,” in Proceedings of Int. workshop of Info. Sec. Application, South Korea, 2004, pp. 73-86. 9. P. J. Lee and Y. H. Hwang, “Public key encryption with conjunctive keyword search and its extension to a multi- user system,” In 574-578 Proc. of Int. Conf. of Pairing Based Crypt., Tokyo, Japan, 2007, pp. 2-22. 10. J. Chen, L. Zhu and C. Liu, “Efficient searchable symmetric encryption for storing multiple source data on cloud,” in the proceedings of IEEE trust com / Big Data SE/ISPA, FINLAND, August 2015, pp. 451-58. 11. S. Zhou, J. Wu, Lin Y., Xiao S. and W. Zhang, “Privacy preserving ranked multi keyword search for multiple data owners in cloud computing,” ieee Transaction for Computing, volume 65, number. 5, pp. 1566-77, May 2016. 12. Waters, Sahai A. & J. Katz, “Predicate encryption supporting disjunctions, polynomial equations, and inner products,” In proceedings of International Conference, Theory Application Cryptography Tech., Turkey, 2008, pp. 146-62. 13. B. Waters, Staddon J. & P. Golle, “Secure conjunctive keyword search over encrypted data,” In the proceedings of International Conference, Application of Crypt. and Network Sec., Heidelberg, Germany, 2004, pp. 31-45. 14. W. Lou, K. Ren, M. Li, C. Wang and N. Cao, “Privacy-preserving multi-keyword ranked search over encrypted cloud data” in Proceedings of ieee infocom, shanghai, China, Apr. 2011, pp. 829-37. 15. Q. Wang, X. Sun, X. Wang and Z. Xia, “A secure and dynamic multi keyword ranked search scheme over encrypted cloud data,” Ieee Transaction for Para. Distr. Sys., volume 27, Number 2, pp. 340-52, Jan. 2016. 16. Roeder, Papamanthou C. & S. Kamara, “Dynamic searchable symmetric encrypt.”, in proceedings of ACM Conf. for Comp. and Communication System, Raleigh,USA, 2012, pp. 965-76. 17. Papamanthou and Kamara S., “Parallel and dynamic searchable symmetric encryption,” in proceedings of Int. Conf. for Fin. Crypt. & Data Sec., 2013, pp. 258-74. 18. Liu X. F., Quan H. Y., Y. Q. Zhang and L. L. Zhang ‘‘Efficient conjunctive keyword search over encrypted medical records,” (Chinese), J. Software, vol. 27, no. 6, pp. 1577-91, June 2016 19. W. Sun et al., “Privacy preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in proceed. of ASIACCS, Hangzhou, China, 2013, pp. 71–82 20. Y. T. Hou, W. Lou, H. Li and W. Sun, “Privacy preserving keyword search over encrypted data in cloud computing,” in secure cloud computing, USA: Springer-Verlag, 2014, pp. 189–212 21. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Design of new multi keyword ranked search scheme and validation for cloud computing,” in proc. of AICTC - 16, Aug. 12 &13, 2016, Bikaner, India 22. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Performance evaluation of multi keyword ranked search schema 23. called BDMRS-CM & EDMRS-BM in cloud computing”, An Int. Journal of Engg. Sci., Issue July 2017, Vol. 24 pp 42-51 24. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Design and Analysis of Search Algorithm with B-tree and Commutative key RSA for dynamic Updation in Cloud Computing”, IJCAR (Int. Journal of Current Adv. Research) Vol 7, Issue 7(H), pp 14414-418, July 2018 Authors: Vikas kumar tomar, RajeshKumar, J P Kesari

Paper Title: Concentrated Solar Thermal Steam Cooking System: An Application in DTU Hostel Abstract: Feasibility study of Concentrated Solar Thermal Steam Cooking System has performed for climatic conditions of Delhi by taking the case of DTU boys hotel mess to replace LPG cooking system. Energy requirement for mass cooking in DTU mess is calculated to be 288981 KWh which till now is fulfilled by 15 LPG cylinders each of capacity of 14kg. An attempt is made to fulfill this requirement with solar energy using 99. Scheffler Dish, although it is also known that complete energy requirement cannot be fulfilled due to unavailability of solar radiations at night, in monsoon and sometimes in winter. Almost 50% of energy requirement i.e.143880 KWh can meet by this system using 25 Scheffler Dish of 16m2. Calculations for CO2 579-583 emission due to burning of LPG in DTU hostel mess is also done which comes out to be 189 tonne and it is shown that with implementation of such a cooking system almost 50% of CO2 emission can be controlled. Effect of DNI, optical efficiency and temperature difference of feed water and steam is shown in this work. Cost of this project that is bear by DTU is around 62 lakhs with payback period of 2.84 years. This system has proposed with keeping in mind that it could prove a model to encourage other institutions in Delhi for implementing this technology for mass and collective cooking.

Keyword: Scheffler Dish; Collective cooking;Performance; Efficiency;Incident angle modifier; Cosine loses; References: 1. S. A. Kalogirou, Solar thermal collectors and applications, Progress in Energy and Combustion Science 30 (2004) 231–295. 2. VDafle, N.N.Shinde., Design, Development & Performance Evaluation Of Concentrating Monoaxial Scheffler Technology For Water Heating And Low Temperature Industrial Steam Application, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622, 2 (6) (2012) 848-852. 3. A. C Kashyap., J. P Kesari., Feasible Study of a Solar Crematorium in India, IJISR 1 (4) 2014. 4. M. R Phate., D. M Gadakari., S. S Acachut., A. D Tajne., Experimental Analysis of 2.7 m2 Scheffler Reflector, IJETT12 5. S.Wu, L Xiao., Y.Cao, Y Li., A parabolic dish/AMTEC solar thermal power system and its performance evaluation, Applied Energy 87 (2010) 452–462 6. K.S Reddy., G Veershetty., Viability analysis of solar parabolic dish stand-alone power plant for Indian conditions, Applied Energy 102 (2013) 908–922. Authors: Christopher Gomez, Aditya Saputra, Hiroki Matsui Tree-stem Volume Calculation from SfM-MVS to Improve Estimates in the Timber Industry in Paper Title: Indonesia Abstract: Spatial Analysis is often thought through the cartographic two dimensions of space, with eventually a 3D component and any form of data associated to it. This concept inherited from eras from data mapping on paper has been driving recent computational development in spatial analysis, however spatial analysis can free itself from this virtual plane, we human evolve on and use any space vertical, reversed, spherical, tubular to investigates all sorts of issues, like the production of timber from trees for instance. As Indonesia is a forestry nation, being able to effectively assess the usable amount of timber available. In the present contribution we aimed to show the loss that can be miscalculated using DBH traditional measurement, and to do so we used a photographic based Structure from Motion method combined with Wavelet Decomposition Analysis. The data shows that the DBH method is correct between 60 to 80%, when considering large-scale variations between DBH and SfM-obtained data, showing that the estimates for the timber industry could be improved, even without the use of expensive laser-based equipment.

Keyword: Structure from Motion; Multiple-View-Stereo- photogrammetry; Photogrammetry; Geographical Information System; Tree stem measurement; Wavelet decomposition. References: 1. Chave, J., C. Andalo, S. Brown, M.A. Cairns, J.Q. Chambers, D. Eamus, H. Folster, F. Fromard, N. Higuchi, T. Kira, J-P. Lescure, B.W. Nelson, H. Ogawa, H. Puig, B. Riera, T. Yamakra. 2005. “Tree Allometry and Improved Estimation of Carbon Stocks and Balance in Tropical Forests”. Oecologia 145: 87-99. 2. Edson, C., and M.G. Wing. 2011. “Airborne Light Detection and Ranging (LiDAR) for Individual Tree Stem Location, Height, and Biomass Measurements”. Remote Sensing 3: 2494-2528. 3. Feldpausch, T. R., L. Banin, O.L. Phillips, et al. 2011. “Height-diameter allometry of tropical forest trees”. Biogeosciences 8: 1081-1106. 4. Fonstad, M. A., J.T. Dietrich, C.B. Courville, J.L. Jensen, P.E. Carbonneau. 2013. “Topographic structure from motion: a new development in photogrammetric measurement”. Earth Surface Processes and Landforms 38: 421-430. 100. 5. Greenberg, J. A., S.Z. Dobrowski, S.L. Ustin. 2005. “Shadow allometry: Estimating tree structural parameters using hyperspectral image analysis”. Remote Sensing of Environment 97: 15-25. 6. Gomez, C. 2018. “Understanding Volcanic Geomorphology from Derivatives and Wavelet Analysis: case study at Miyakejima 584-588 Volcano, Izu Islands, Japan”. Journal of Volcanology and Geothermal Research 354: 57-66. 7. Gomez, C. 2013. “Tamagawa hanrangen ni okeru tochi hifuku no hensen to jishin no yure no kankei (The role of landcover change for earthquake impacts – in Japanese) Tokyo, Japan”. Centre for Spatial Information Science (CSIS) Days 2013, 22,23 Nov 2013 proceedings A11: 17. 8. Gomez, C. 2012. “Multi-scale analysis of Merbabu and Merapi volcanoes using wavelet decomposition”. Environmental Earth Sciences 67:1423-1430. 9. Gomez, C., K. Kataoka, A. Saputra, P. Wassmer, A. Urabe, J. Morgenroth, A. Kato. 2017. “Photogrammetry-based Texture Analysis of a Volcaniclastic Outcrop-peel : Low-cost Alternative to TLS and Automation Potentialities using Haar Wavelet and Spatial-Analysis Algorithms”. Forum Geografi 31: 16-27. 10. Gomez, C., Y. Hayakawa, H. Obanawa. 2015. “A study of Japanese landscapes using structure from motion derived DSMs and DEMs based on historical aerial photographs: New opportunities for vegetation monitoring and diachronic geomorphology”. Geomorphology 242: 11-20. 11. Henning, J. G., P.J. Radtke. 2006. “Detailed Stem Measurements of Standing Trees from Ground-Based Scanning Lidar”. Forest Science 52: 67-80. 12. James, M. R., and S. Robson. 2012. “Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application”. Journal of Geophysical Research 117: F03017. 13. Kato, A., J. Morgenroth, D. Kelbe, C. Gomez, J. van Aardt. 2013. “Ground Truth Measurement of Trees Using Terrestrial Laser for Satellite Remote Sensing”. Melbourne, Australia: IEEE International Geoscience and Remote Sensing Symposium (IGARSS) proceedings. 14. Liang, X., V. Kankare, X. Yu, J. Hyppa, M. Holopainen. 2014. “Automated Stem Curve Measurement Using Terrestrial Laser Scanning”. IEEE Transactions On Geoscience and Remote Sensing 52(3): 1739-1748. 15. Lourakis, M.I.A. and A.A. Argyros. 2009. “SBA: A software package for generic sparse bundle adjustment”. ACM Trans. Math. Softw. 36 (1). Doi: 10.1145/1486525.1486527. 16. Lowe, D.G. 2004. “Distinctive image features from scale-invariant key-points”. International Journal of Computer Vision 60: 91- 110. 17. Millanei, A., Dorafshan, S. M. H. G., & Bayrami, A. (2016). Sunnite Religious View about Jurisprudence Nature of Istisna Contract. UCT Journal of Social Sciences and Humanities Research, 4(1), 25-27. 18. Morgenroth, J., and C. Gomez. 2014. “Assessment of tree structure using a 3D image analysis technique – a proof of concept”. Urban Forestry and Urban Greening, 13: 198-203. 19. Osada, N. 2012. “Crown exposure to light and tree allometry of 11 tree species in a snowy cool-temperate forest in Japan”. Plant Ecology 213: 783-794. 20. Özer, G., Ergün, U., & İnan, L. E. (2018). Headache in Multiple Sclerosis from A Different Perspective: A Prospective Study. Journal of Clinical and Experimental Investigations, 9(1), 9-13. 21. Ranjbari, M. H., Shaheri, A., Dalili, R., & Soroush, R. (2015). Optimal allocation of distributed generation using an analytical method with consideration of technical and economic parameters. UCT Journal of Research in Science, Engineering and Technology, 3(1), 9-17. 22. Saputra, A., C. Gomez, I. Delikostidis, P. Zawar-Reza, D.S. Hadmoko, J. Sartohadi, M.A. Setiawan. 2018. “Determining earthquake susceptible areas southeast of Yogyakarta, Indonesia-Outcrop analysis from structure from motion (SfM) and geographic information system (GIS). Geosciences 8: 132. 23. Urban, J., K. Holusova, L. Mensik, J. Cermak, P. Kantor. 2013. “Tree allometry of Douglas fir and Norway spruce on a nutrient- poor and a nutrient-rich site”. Trees 1: 97-110. 24. Wang, X., C. Wang, Q. Zhang, X. Quan. 2010. “Heartwood and sapwood allometry of seven Chinese temperate tree species”. Annals of Forest Science 67(410): 1-10. 25. Westoby, M. J., J. Brasington, N.F. Glasser, M.J. Hambrey, J.M. Reynolds. 2012. “Structure-from-Motion photogrammetry: A low-cost, effective tool for geosciences applications”. Geomorphology 179: 300-314.. Authors: Md.Mosfiqur Rahman , Masuma Parvin , Sayedul Anam , M.A Rubi

Paper Title: Forecasting of Agricultural Loan in Bangladesh Abstract: The agriculture sector is important to meet up the challenges of twentieth century in Bangladesh. It has huge contribution to our life. This sector secures the food security, export earnings and poverty reduction (Agricultural and MSME finance’2017, BB). In this paper, we forecast the agricultural loan disbursement, overdue and recovery in Bangladesh. Moreover, we have discussed the flaw of loan disbursement, recovery and overdue and that of the way out.

Keyword: Time series, ARIMA, ACF, PACF, ADF, Stationary, Autoregressive, Moving average.

References: 1. Anam S.,Rahman A., Haque M.M., and Hadi S. R. (2014) “The Impact of Transportation Cost on Potato Price: a Case Study of Potato Distribution in Bangladesh”. The International Journal of Management, Vol. 1, No. 03, pp. 01-12, ISSN 2277- 5846. 2. Anam S, Khan, Uddin., “Developing StochasticLinear Programming Model for Production”. International Journal of Economic Perspective, 2017, Volume 11, Issue 4, 851-866. 3. Rahman MM, Anam S, Chakrabarty AK, “Forecasting of International Tourists Arrival in Saarc Region and Prospect of Bangladesh”. International Journal of Engineering & Technology(UAE), 7 (3.19) (2018) 161-168. DOI:10.14419/ijet.v7i3.19.17006 4. Raymond Y.C. Tse (1997) “An application of the ARIMA model to real-estate prices in Hong Kong” Journal of Property Finance, Vol. 8, No. 2, pp.152 – 163. 5. Alauddin M, Biswas, “Agricultural Credit in Bangladesh: Trends, Patterns, Problems and Growth Impacts”. The Jahangirnagar Economic Review, Vol. 25, June 2014, ISSN 1990-2492. 6. Sarker, Ruhul Amin. 2006. “Rural Financing and Agricultural Credit in Bangladesh: Future Development Strategies for Formal Sector Banks”, The University Press Limited, Dhaka. 7. Miah, M. A. Kabir, Alam, A.K.M. Ashraful and Rahman, A.H.M.A. 2006. Impact of Agricultural Credit on MV Boro Rice 101. Cultivation in Bangladesh. Journal of Agriculture and Rural Development 4(1&2), 161-168. 8. Rahman, M.W, ,Luo, J, and Cheng, E., 2011, “Policies and Performances of agricultural/rural credit in Bangladesh: What is the influence on agricultural production?” African Journal of Agricultural Research, 6(31): 6440-6452 Annual Report, “Bangladesh 589-594 Bank 2016-2017”. 9. Altman. Default recovery rates and LGD in credit risk modeling and practice: An updated review of the literature and empirical evidence. Working paper, Stern School of Business, New York University, 2006. 10. Asarnow and D. Edwards. Measuring loss on defaulted bank loans: A 24-year study. Journal of Commercial Lending, 77(7):11– 23, 1995. 11. Bellotti and J. Crook. Modelling and predicting loss given default for credit cards.Working paper, Quantitative Financial Risk Management Centre, 2007. 12. Caselli, S. Gatti, and F. Querci. The sensitivity of the loss given default rate to systematic risk: New empirical evidence on bank loans. Journal of Financial Services Research, 34(1):1–34, 2008. 13. Nurgaliyevа, S. A., Zeynolla, S. Z., Galiyeva, A. N., & Espolova, G. K. (2018). On the issue of modernization of the system of professional development of teachers of high schools of Kazakhstan. Opción, 34(85), 308-326. 14. Dermine and C. Neto de Carvalho. Bank loan losses-given-default: A case study. Journal of Banking and Finance, 30:1291–1243, 2006. 15. Felsovalyi and L. Hurt. Measuring loss on latin american defaulted bank loans: A 27-year study of 27 countries. Journal of Lending and Credit Risk Management, 80:41–46, 1998. 16. Matias, N. R., and Sousa, M. J. (2017). Mobile Health, a Key Factor Enhancing Disease Prevention Campaigns: Looking for Evidences in Kidney Disease Prevention. Journal of Information Systems Engineering & Management, 2(1), 3. https://doi.org/10.20897/jisem.201703 17. Franks, A. de Servigny, and S. Davydenko. A comparative analysis of the recovery process and recovery rates for private companies in the UK, france and germany. Standard and Poor’s report, 2004. 18. Gourieroux, A. Monfort, and A. Trognon. Pseudo-maximum likelihood methods: theory. Econometrica, 52:681–700, 1984. 19. Grunert and M. Weber. Recovery rates of commercial lending: Empirical evidence for german companies. Journal of Banking and Finance, 33:505–513, 2009. 20. Rabbani, M., Bagherzadeh, N., & Rafiei, H. (2014). Calculating raw material and work-in-process inventories in MTO. MTS production, UCT Journal of Research in Science, Engineering and Technology, 2(3): 109-116. 21. O’Shea, S. Bonelli, and R. Grossman. Bank loan and bond recovery study; 1997-2000.Fitch IBCA, 2001. 22. ]Md. Ariful Islam, Md. Rayhan Islam, Mahmudul Hasan Siddiqui, Luthful Karim. Importance of Agricultural Credit for Rural Development of Bangladesh: A descriptive Approach. International Journal of Business and Economics Research.Vol.2,No.1,2014,pp.68-83.doi:10.11648/j.ijefm.20140201.18 Authors: Deler Singh, Gurvinder Kaur Professional Communication Skills in English for Non-native English Speaking Engineers: 102. Paper Title: Challenges and a Proposed Teaching Framework Abstract: Communicating effectively in English does not come naturally to undergraduate engineering 595-599 students in India and presumably everywhere where English is not the first language or the mother tongue. In India, English is used as official language in most of the states. It is also the medium of instruction in most educational institutes. Teaching methods and objectives to be achieved while imparting knowledge of English language mainly focus on ability of students to reproduce the learned facts in written form in the examination. Focus on the oral communication and development of English as a medium to share and express original ideas is not really observed at school or university level. Employers worldwide have acknowledged that the conventional engineering curriculum that is focused on imparting technical knowledge has proved to be inadequate in equipping engineers with the adequate employability skills. The objective of this paper is to present a framework for design, teaching and evaluation of a course on communication skills/professional communication for engineering students. A proposed pedagogical framework has been discussed and illustrated as appendices. Guidelines regarding improving communication skills have been made keeping in mind that rather than emphasizing upon incorporating a course on communication skills in the engineering education, communication should be made an integral part of the curriculum.

Keyword: Pedagogy, interpersonal communication, communication barriers, Intercultural differences; Group discussion; Interviews; Blog writing; Panel discussions. References: 1. ABET. Criteria for Accrediting Engineering Programs, 2016-2017. Retrieved from http://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering-programs-2016-2017/#students. 2. Aspiring minds Employability Quantified, National employability report-Engineers Annual report 2016. Retrieved from http://www.aspiringminds.com/research-reports. Accessed on 15 May 2017. 3. Ayokanmbi, F. M. (2011). Competencies for global engineers and technologists. Journal of Industrial technology, 27(1), 1-6. 4. Blom, A & Saeki, H. (2011) Employability and Skill Set of Newly Graduated Engineers in India. The World Bank. 5. Chun, M. (2010). Taking teaching to (performance) task: Linking pedagogical and assessment practices. Change, 42(2), 22-29. 6. Craig, W. O. Preparing the Engineering Technology Graduate for the Global Marketplace. The Technology Interface Journal, 10 (3), 2008. 7. Fisher, Ann. (1998). The High Cost of Living and Not Writing Well. Fortune, 244. 8. Gimenez, J. (2014). Multi-communication and the business English class: Research meets pedagogy. English for Specific Purposes, 35, 1-16. http://dx.doi.org/10.1016/j.esp.2013.11.002 9. Hart-Rawung, P., & Li, L. (2008). Globalization and business communication: English communication skills for Thaia utomotive engineers. World Academy of Science, Engineering, and Technology, 24, 320-330. 10. http://www.tribuneindia.com/news/bathinda/dummy-admissions-on-rise-in-city/389107.html. 11. Huckin, Thomas N. & Olsen, Leslie A. (1991). Technical Writing and Professional Communication for Nonnative Speakers of English. New York: McGraw-Hill International. 12. Joungtrakul, N. (2013). Thai engineers’ readiness to cope with the free flow of skilled labor in the ASEAN Economic Community. HRD Journal, 4(1), 6-21. 13. Laohachaiboon, S. (2011). Intercultural communication obstacles in a Japanese company: a case study into cross-cultural effect and difficulties in English communication of Thai employees at Toyota Tsusho (Thailand) Co., Ltd. (Unpublished master’s thesis). Thammasart University, Bangkok, Thailand. 14. Marina, O. & Rajprasit, K. (2014). Investigating the impact of personality factors on perceived communication mobility of non- native English speaking Thai professionals in international companies. PASAA, 47, 61-96. 15. Mehra, D. & Virgandham, V. (2013). Communication skills for enhanced employability of engineers: A review of literature. The Confluence Journal, 3, 70-76. 16. Mercer, J. A. A. (2006). Madness to our method: Congregational studies as a cross-disciplinary approach to contextualizing teaching and learning in theological education. Teaching Theology and Religion, 9(3), 148-155. 17. National Board of Accreditation. (2012). Manual for accreditation of Engineering Graduate Programs. Retrieved from www.nbaind.org/Files/engineering-programs.pdf. 18. Perry, D. (2002). Do you Have the Skills Most in demand Today? Career Journal from the Wall Street Journal. Retrieved from http://www.careerjournal.com/columnist/perspective/20020520-fmp.html. 19. Puranik, A. (2015, August 11). 97% engineering graduates cannot speak English fluently: Survey. Retrieved from http://www.hindustantimes.com/education/97-engineering-graduates-cannot-speak-english-fluently-survey/story- GQEkTYwI4AX5zc7oeXkz1M.html. 20. R. Freisinger. (1982). The Personal Connection: Journal Writing across the Curriculum in Fulwiler, T. & Young, A. (eds), Language Connections: Writing and Reading Across the Curriculum, National Council of Teachers of English, Illinois. 21. Raina, R. & Pande, N. (2012). Communication competence of Indian engineers in IT & ITeS sector. The Indian Journal of Industrial Relations, 47(3), 511-526. 22. Rajprasit, K., Pratoomrat, P., Wang, T., Kulsiri, W., & Hemchua, S. (2014). Use of the English language prior to and during employment: Experiences and needs of Thai novice engineers. Global Journal of Engineering Education, 16(1), 27-33. 23. Riemer, M.J. (2002). English and communication skills for the global engineer. Global Journal of Engineering Education, 6(1), 91-100. 24. Tahaineh, Y. S. (2010). Arab EFL university students’ errors in the use of prepositions. MJAL, 2(1), 76-112. 25. Tanaka, J. (2002). Academic difficulties among East Asian international graduate students: influences of perceived English language proficiency and native educational/sociocultural background. (PhD’s thesis). Indiana University. 26. Thakur, S., Kaur, S., Thakur, P. V., & Nanda, D. R. (2013). English teaching to engineering students difficulties and solutions. Journal of Literature, Languages and Linguistics, 2, 55-59. 27. The Hindu. (2016, October 01). About 70 percent Indians live in rural areas: Census report. Retrieved from http://www.thehindu.com/news/national/About-70-per-cent-Indians-live-in-rural-areas-Census-report/article13744351.ece. 28. The Japan Times. (2009). Japan Times Forum on English Education: Engineers Must Have English Skills to Succeed. Retrieved from http://www.sci.kanagawa-u.ac.jp/pdf/2009_times01.pdf. 29. The Tribune. (2017, April 9). Dummy Admissions on Rise in city. Retrieved from Yu, H. (2008). Contextualize technical writing assessment to better prepare students for workplace writing: Student-centered assessment instruments. Journal of Writing and Communication, 38(3), 265-284. Authors: S. Nithya, G. Vinayagamoorthi, S. Josephin Arulmozhi

103. Paper Title: Impact of FDI in Insurance Sector Abstract: One of the most hanging traits during the last many years is the amazing increase of FDI in the 600-604 international economic system panorama. This excellent improvement of FDI in 1990 around the globe make FDI a important and critical phase of development technique in each created and creating nations and preparations are configuration with a selected cease intention to animate internal streams. FDI offers a win-win situation to the host and the nations of origin. The international locations are straightforwardly inspired by way of welcoming FDI, in mild of the fact that they advantage a great deal from such kind of task. As a rule FDI alludes to capital inflows from abroad that put sources into the era limit of the economic system and are normally favoured over other sort of outer fund due to the fact they're non-obligation making non-risky and their earnings rely upon the execution of the undertakings financed by the economic professionals. FDIinflow encourages the creating countries to created sincere, expansive and compelling association situation for task troubles and, assembles human and institutional abilties to execute the identical. The safety phase is of massive importance to each developing economic system; in includes the sparing propensity, which thusly produces lengthy haul investible assets for basis constructing. This present day Paper's locations are to explore the Indian Insurance part, to realize blessings of expanded outdoor direct undertaking restrain in protection section, to recognize the Government arrangement with respect to protection department in India, to understand Issues in FDI in Insurance Sector.

Keyword: FDI, insurance sector in india, inflow, outflow, investment limits. References: 1. Evans Sam, Sharma Shashwat, Doshi Sanjay,(2014)Higher FDI in Indian Insurance Sector-a buzz for the Industry,Retrieved from http:/www.kpmg.com/Global/en/Issues andInsights/articlespublications/Documents/fdi-cap-increase-for-indian-insurers-v2.pdf 2. Kapoor Harsha,(2013)FDI in Insurance for a better future,Retrieved fromhttp://www.avizare.com/assets/FDI%20in%20Insurance%20%20For%20a%20Better%20Future.pdf 3. Mishra Vinay. V, Bhatnagar Harshida, (2014)Foreign Direct Investment in Insurance Sector in India,Retrieved fromwww.academia.edu 4. Rhea Jinhal, (2014)benefitsof FDI in insurance sector in India,Retrievedfrom https://storify.com/rheajind/benefits-of-fdi-in- insurance-sector-in-india. Authors: GS Naveen Kumar, VSK Reddy

Paper Title: A Scheme for Shot Detection and Video Retreival using Spatio Temporal Features Abstract: There has been a revolution in multimedia with technological advancement. Hence, Video recording has increased in leaps and bounds. Video retrieval from a huge database is cumbersome by the existing text based search since a lot of human effort is involved and the retrieval efficiency is meager as well. In view of the present challenges, video retrieval based on video content prevails over the existing conventional methods. Content implies real video information such as video features. The performance of the Content Based Video Retrieval (CBVR) depends on Feature extraction and similar features matching. Since the selection of features in the existing algorithms is not effective, the retrieval processing time is more and the efficiency is less. Combined features of color and motion have been proposed for feature extraction and Spatio-Temporal Scale Invariant Feature Transform is used for Shot Boundary Detection. Since the characteristic of color feature is visual video content and that of motion feature is temporal content, these two features are significant in effective video retrieval. The performance of the CBVR system has been evaluated on the TRECVID dataset and the retrieved videos reveal the effectiveness of proposed algorithm.

Keyword: Shot Transition, Selective Frames, Integrated Feature Extraction, Feature Matching, Retrieval References: 1. C. Cotsaces, N. Nikolaidis, and I. Pitas, “Video Shot Detection and Condensed Representation”, IEEE Signal Processing Magazine, March, 2006, pp. 28-37, 2006. 104. 2. Chen, Ling, and Yuhong Wang. "Automatic key frame extraction in continuous videos from construction monitoring by using colour, texture, and gradient features." Automation in Construction (2017), Elsevier, 355-368. 3. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, vol. 60, pp. 605-608 91-110, 2004. 4. Gharbi, Hana, Mohamed Massaoudi, SahbiBahroun, and EzzeddineZagrouba. "Key frames extraction based on local features for efficient video summarization." In International Conference on Advanced Concepts for Intelligent Vision Systems, pp. 275-285. Springer, Cham, 2016. 5. GS Naveen Kumar, and V. S. K. Reddy. "Key Frame Extraction Using Rough Set Theory for Video Retrieval." In Soft Computing and Signal Processing, pp. 751-757. Springer, Singapore, 2019. 6. Guru, D. S., MahamadSuhil, and P. Lolika. "A novel approach for shot boundary detection in videos." In Multimedia Processing, Communication and Computing Applications, pp. 209-220. Springer, New Delhi, 2013. 7. Hannane, Rachida, AbdessamadElboushaki, KarimAfdel, P. Naghabhushan, and Mohammed Javed. "An efficient method for video shot boundary detection and keyframe extraction using SIFT-point distribution histogram." International Journal of Multimedia Information Retrieval 5, no. 2 (2016), Springer, 89-104 8. J. H. Yuan, H. Y. Wang, and B. Zhang, “A formal study of shot boundary detection”, Journal of Transactions on Circuits and Systems for Video Technology, vol. 17, no. 2, pp. 168-186, February 2007. 9. Kabbai, Leila, AymenAzaza, MehrezAbdellaoui, and Ali Douik. "Image matching based on lbp and sift descriptor." In 2015 IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15), pp. 1-6. IEEE, 2015. 10. Li, Jun, et al. "A divide-and-rule scheme for shot boundary detection based on SIFT." JDCTA 4.3 (2010): 202-214. 11. Lina Sun and Yihua Zhou, "A key frame extraction method based on mutual information and image entropy," 2011 International Conference on Multimedia Technology, Hangzhou, 2011, pp. 35-38Liu, Gentao, et al. "Shot boundary detection and keyframe extraction based on scale invariant feature transform." Computer and Information Science, 2009. ICIS 2009. Eighth IEEE/ACIS International Conference on. IEEE, 2009. 12. Liu, Huayong, and HuifenHao. "Key frame extraction based on improved hierarchical clustering algorithm." In 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 793-797. IEEE, 2014. 13. Liu, Xin, and Jin Dai. "A method of video shot-boundary detection based on grey modeling for histogram sequence." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 4 (2016): 265-280. 14. Lu, Zhe-Ming, and Yong Shi. "Fast video shot boundary detection based on SVD and pattern matching." IEEE Transactions on Image processing 22, no. 12 (2013): 5136-5145 15. Mohamadzadeh, Sajad, and Hassan Farsi. "Content based video retrieval based on HDWT and sparse representation." Image Analysis & Stereology 35, no. 2 (2016): 67-80. 16. Montazer, Gholam Ali, and DavarGiveki. "Content based image retrieval system using clustered scale invariant feature transforms." Optik 126, no. 18 (2015): 1695-1699. 17. Nasreen, Azra, and G. Shobha. "Reducing redundancy in videos using reference frame and clustering technique of key frame extraction." In International Conference on Circuits, Communication, Control and Computing, pp. 348-440. IEEE, 2014. 18. Qu, Zhong, Lidan Lin, TengfeiGao, and Yongkun Wang. "An improved keyframe extraction method based on HSV colour space." JSW 8, no. 7 (2013): 1751-1758.Ren, Liping, et al. "Key frame extraction based on information entropy and edge matching rate." Future Computer and Communication (ICFCC), 2010 2nd International Conference on. Vol. 3. IEEE, 2010. 19. Saravanan, D., & Vengatesh, K. J. (2015). Video content reterival using historgram clustering technique. Procedia Computer Science, 50, 560-565. 20. Thakre, K. S., A. M. Rajurkar, and R. R. Manthalkar. "Video partitioning and secured keyframe extraction of MPEG video." Procedia Computer Science 78 (2016), Elsevier, 790-798. 21. Upesh Patel, Pratik Shah, and PradipPanchal, "Shot Detection using Pixel wise Difference with Adaptive Threshold and Colour Histogram Method in Compressedand Uncompressed Video" International Journal of Computer Applications (0975- 8887), Volume 64– No.4, February 2013 22. Wu, Zhonglan, and Pin Xu. "Shot boundary detection in video retrieval." Electronics Information and Emergency Communication (ICEIEC), 2013 IEEE 4th International Conference on. IEEE, 2013. 23. Xu, Jingwei, Li Song, and RongXie. "Shot boundary detection using convolutional neural networks." In 2016 Visual Communications and Image Processing (VCIP), pp. 1-4. IEEE, 2016. 24. Yuan, Jinhui, et al. "A formal study of shot boundary detection." IEEE transactions on circuits and systems for video technology 17.2 (2007): 168-186. 25. Zhao Guang-sheng , A Novel Approach for Shot Boundary Detection and Key Frames Extraction, 2008 International Conference on Multimedia and Information Technology,IEEE. Authors: K. Chitradevi

Paper Title: Determinants of FIIs Net Investment in India Abstract: Indian stock market has witnessed spectacular change in the recent decade. The market has undergone huge reform in the past few years. The linkage of stock market with macroeconomic variables has always been an area of interest among investors and policy makers. The stock market and its indicators in the form of indices, reflect the potential, the direction and health of the economy. There is an extensive group of macroeconomic variables that influences the stock prices in the share market. The stock market of emerging economy like India carries huge expectation of the investors. The Indian stock market improves with the increase in the inflow of foreign investment. FIIs investment is volatile by nature and also FIIs flows have positive and negative impact in the market as well as the economy. Hence, there is a need to determine the push and pull factors behind any change in the FIIs, so that it will become easy to frame the policies by considering the variables that attract foreign investment.. It becomes really important for any investor to understand the key economic factors which have high influence on FIIs investment Indian stock market improves with the increase in the inflow of foreign investment. Hence, there is a need to determine the push and pull factors behind any change in the FIIs, so that it will become easy to frame the policies by considering the variables that attract 105. foreign investment. The foreign investor’s participation in Indian stock market increases the liquidity of local markets and lowers the cost of capital. It becomes really important for any investor to understand the key economic factors which have high influence on FIIs investment. Hence, an attempt has been made to analyse the 609-611 factors determining behaviour of FIIs net investment.

Keyword: FDI,. References: 1. Amita (December 2014), Determinants of FIIs: Evidence from India, IJITKM Volume 8 Number 1 June-Dec 2014 pp. 85-95 (ISSN 0973-4414) 2. T. Mohanasundaram, P. Karthikeyan, V. Krishnamoorthy, Macroeconomic Dynamics of Foreign Institutional Investments in India, IJMRR/ Jan 2015/ Volume 5/Issue 1/Article No4/39-47, ISSN: 2249-7196 3. http://mospi.nic.in/Mospi_New/upload/iip/IIP_main.htm?status=1&menu_id=89 4. http://www.indianmba.com/Occasional_Papers/OP203/op203.html 5. http://www.investopedia.com/ 6. http://www.sebi.gov.in/sebiweb/investment/statistics.jsp?s=fii 7. http://www.slideshare.net/soumeetsarkar/foreign-capital \ 8. https://www.cdslindia.com/publications/FIIreports.html 9. https://www.quora.com/Effect-of-FII-on-indian-economy Authors: Mohammed Matar, Aldhaheri, Mohammed Nussari

Paper Title: The Role of Internal and External Motivation on Employee Performance Abstract: This study employs structural equations modeling via PLS to analyze the 732 valid questionnaires in order to assess the proposed model that is based on the organizational motivation 106. characteristics to identify its effect on the performance of employees in the government sector in Dubai. The main independent constructs in the model are intrinsic motivation and external motivation. The dependent 612-616 construct is employee performance. The study will describe relations among the various constructs. Our work has improved our insight in the importance of organizational motivation. Results indicated that both independent variables significantly predicted employee performance with a various percentage. The proposed model explained 37.7% of the variance in employee performance.

Keyword: Intrinsic motivation; extrinsic motivation; employee performance; Dubai.. References: 1. G. G. Bear, J. C. Slaughter, L. S. Mantz & E. Farley-ripple, (2017). Rewards , praise , and punitive consequences : Relations with intrinsic and extrinsic motivation. Teaching and Teacher Education, vol. 65, pp. 10–20. https://doi.org/10.1016/j.tate.2017.03.001 2. H. Liang, M. Wang, J. Wang & Y. Xue, (2018). How intrinsic motivation and extrinsic incentives affect task effort in crowdsourcing contests : A mediated moderation model. Computers in Human Behavior, 81, pp. 168–176. https://doi.org/10.1016/j.chb.2017.11.040 3. Turkyilmaz, G. Akman, C. Özkan, & Z. Pastuszak, (2011). Empirical Study of Public Sector Employee Loyalty and Satisfaction. Industrial Management and Data Systems, 111. 4. Gavrea, L. Ilies & R. Stegerean (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300. 5. P. J. Richard, T. Devinney, G. Yip & G. Johnson, (2009). Measuring Organizational Performance: Towards Methodological Best Practice. Journal of Management Vol. 35. https://doi.org/10.1177/0149206308330560 6. R. W. Brislin, (1970). Back-Translation for Cross-Cultural Research. Journal of Cross-Cultural Psychology Vol. 1. Brislin. https://doi.org/10.1177/135910457000100301 7. L. A. Hayduk & L. Littvay (2012). Should researchers use single indicators , best indicators , or multiple indicators in structural equation models ? BMC Medical Research Methodology, 12(1), pp. 1–17. https://doi.org/10.1186/1471-2288-12-159 8. B. G. Tabachnick & L. S. Fidell, (2012). Using Multivariate Statistics (6th ed.). Pearson. 9. R. V Krejcie & D. W. Morgan (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 10. C. M. Ringle, S. Wende & J.-M. Becker, (2015). SmartPLS 3. Bonningstedt: SmartPLS. 11. J. C. Anderson & D. W. Gerbing (1988). Structural Equation Modeling in Practice : A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), pp. 411–423. 12. J. F. Hair, G. T. M. Hult, C. Ringle & M. Sarstedt, (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). London: Thousand Oaks: SAGE. 13. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 14. J. F. Hair, W. C. Black, B. J. Babin & R. E. Anderson (2010). Multivariate Data Analysis (7th ed.). New Jersey: Pearson. 15. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 16. W. W. Chin (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 17. Z. Awang (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 18. J. Cohen, (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). London: Routledge. 19. W. W. Chin (1998b). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-358). New Jersey: Lawrence Erlbaum Associates. Mahwah, NJ: Lawrence Erlbaum. 20. M. S. Lemos, & L. Veríssimo, (2014). The relationships between intrinsic motivation , extrinsic motivation , and achievement , along elementary school. Procedia - Social and Behavioral Sciences, 112(Iceepsy 2013), pp. 930–938. https://doi.org/10.1016/j.sbspro.2014.01.1251 21. Y. Li, K. M. Sheldon & R. Liu, (2015). Dialectical thinking moderates the effect of extrinsic motivation on intrinsic motivation. Learning and Individual Differences, 39, pp. 89–95. https://doi.org/10.1016/j.lindif.2015.03.019 22. I. Vilnai-yavetz & O. Levina, (2018). Motivating social sharing of e-business content : Intrinsic motivation , extrinsic motivation , or crowding-out effect ? Computers in Human Behavior, 79, pp. 181–191. https://doi.org/10.1016/j.chb.2017.10.034. 23. B. Kuvaas, R. Buch, A. Weibel, A. Dysvik & C. G. L. Nerstad, (2017). Do intrinsic and extrinsic motivation relate differently to employee outcomes ? Journal of Economic Psychology, 61, pp. 244–258. https://doi.org/10.1016/j.joep.2017.05.004 The Relationship between Transformational Leadership and Organizational Performance: The Case Authors: of Government Sector in UAE Paper Title: Nayef Alateibi, Ahmed Hamoud Al-Shibami, Ali Ameen, Amiya Bhaumik, Ibrahim Alrajawy Abstract: This study employs structural equations modeling via PLS to analyze the 392 valid questionnaires in order to assess the proposed model that is based on the transformational leadership characteristics to identify its effect on the performance of organizations in the government sector in the United Arab Emirates. The main independent constructs in the model are idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. The dependent construct is organizational performance as a second-order construct to learning & growth, and internal process. The study will describe relations among the various constructs. Our work has improved our insight in the importance of transformational leadership. Results indicated that all four independent variables significantly predicted performance with a various percentage. The proposed model explained 46.5% of the variance in performance.

Keyword: Transformational leadership; organizational performance; UAE. 107. References: 1. Avolio, B. J., Bass, B. M., & Jung, D. I. (1999). Re-examining the components of transformational and transactional leadership 617-627 using the Multifactor Leadership Questionnaire. Journal of Occupational and Organizational Psychology, 72(4), 441-462. 2. A. Ameen, & K. Ahmad, (2011). The Role of Finance Information Systems in anti-financial corruptions: A theoretical review. In 11 International Conference on Research and Innovation in Information Systems (ICRIIS’11 (pp. 267–272). 3. A. Ameen & K. Ahmad, (2012). Towards Harnessing Financial Information Systems in Reducing Corruption : A Review of Strategies. Australian Journal of Basic and Applied Sciences, 6(8), pp. 500–509. 4. A. Ameen, & K. Ahmad, (2013). A Conceptual Framework of Financial Information Systems to reduce corruption. Journal of Theoretical and Applied Information Technology, 54(1), pp. 59–72. 5. A. S. Alkhateri, A. E. Abuelhassan, G. S. A. Khalifa, M. Nusari & A. Ameen, (2018). The Impact of perceived supervisor support on employees turnover intention : The Mediating role of job satisfaction and affective organizational commitment. International Business Management, 12(7), pp. 477–492. 6. A. Ameen, H. Almari, & O. Isaac, (2019). Determining Underlying Factors that Influence Online Social Network Usage Among Public Sector Employees in the UAE. In Fathey M. Faisal Saeed, Nadhmi Gazem (Ed.), Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing Recent Tre,843, pp. 945–954. Springer Nature Switzerland AG: Springer International Publishing. 7. Haddad, A., Ameen, A., & Mukred, M. (2018). The Impact of Intention of Use on the Success of Big Data Adoption Via Organization Readiness Factor. International Journal of Management and Human Science (IJMHS), 2(1), 43–51. 8. Heffernan , M., Harney, B., Cafferkey, K. and Dundon, T. (2016), "Exploring the HRM-performance relationship: the role of creativity climate and strategy", Employee Relations, Vol. 38 No. 3, pp. 438-462. 9. Turkyilmaz, A., Akman, G., Ozkan, C. and Pastuszak, Z. (2011), "Empirical study of public sector employee loyalty and satisfaction", Industrial Management & Data Systems, Vol. 111 No. 5, pp. 675-696. 10. Kaplan, R. and Norton, D. (1996), "strategic learning & the balanced scorecard", Strategy & Leadership, Vol. 24 No. 5, pp. 18- 24. 11. Y.-S. Wang, H.-H. Lin & P. Luarn, (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), pp. 157–179. 12. A. F. Baharuden, O. Isaac & A. Ameen, (2019). Factors Influencing Big Data & Analytics (BD&A) Learning Intentions with Transformational Leadership as Moderator Variable: Malaysian SME Perspective. International Journal of Management and Human Science (IJMHS), 3(1), pp. 10–20. 13. P. Marylin, A. Ghosh, O. Isaac, S. J. V. Aravinth, & A. Ameen, (2019). The Impact of Emotional Intelligence on Work Life Balance among Pharmacy Professionals in Malaysia. International Journal of Management and Human Science (IJMHS), 3(1), pp. 29–34. 14. O. Isaac, Z. Abdullah, T. Ramayah & M. Mutahar Ahmed, (2017). Examining the Relationship Between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 15. O. Isaac, Z. Abdullah, T. Ramayah & A. M. Mutahar, (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), pp. 210–241. 16. O. Isaac, Z. Abdullah, T. Ramayah, A. M. Mutahar, & I. Alrajawy, (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), pp. 205–223. 17. B. G. Tabachnick & L. S. Fidell, (2007). Using Multivariate Statistics. PsycCRITIQUES, 28, pp. 980. 18. R. V Krejcie, & D. W. Morgan, (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 19. C. M. Ringle, S. Wende & J.-M. Becker, (2015). SmartPLS 3. Bonningstedt: SmartPLS. 20. J. C. Anderson & D. W. Gerbing, (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), pp. 411–423. 21. J. F. J. Hair, G. T. M. Hult, C. Ringle, & M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS- SEM), 46 Long Range Planning 328 (2014). London: Thousand Oaks: SAGE. 22. R. E. Schumacker & R. G. Lomax, (2004). A Beginner’s Guide to Structural Equation Modeling. New York: Lawrence Erlbaum. 23. J. F. Hair, W. C. Black, B. J. Babin, & R. E. Anderson, (2010). Multivariate Data Analysis. New Jersey. 24. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 25. C. E. Werts, R. L. Linn, & K. G. Jöreskog, (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 26. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 27. C. Fornell, & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 28. Z. Awang, (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 29. J. Cohen, (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Editio). LawreAssociatesnce Erlbaum. 30. C. M. Ringle & M. Sarstedt, (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems, 116(9), pp. 1865–1886. Authors: Salem Alkutbi, Ibrahim Alrajawy, Ali Ameen, Ahmed Hamoud Al-Shibami, Amiya Bhaumik Integrating Technological Acceptance Model and End-User Computing Satisfaction to Explain the Paper Title: Intention to Continue Using Car Navigation Systems in UAE Abstract: This research uses modelling of structural equations via PLS to assess the 167 suitable questionnaires so as to evaluate the recommended model that utilizes the technology acceptance model TAM and end-user computing satisfaction theories to identify factors that affect driver intention to continue using car navigation systems among UAE’s drivers with private licenses. The research will describe relationships among accuracy, content, format, timeliness, ease of use, perceived usefulness, and intention to continue using car navigation systems. Our efforts have improved our understanding of the use of satellite navigation technology. Results suggested that all seven hypotheses are supported. The recommended model also clarified 20% of the variance in the intention to continue using car navigation systems.

Keyword: intention to continue using car navigation systems; TAM; EUCS; UAE. References: 108. 1. S. Alkhateri, A. E. Abuelhassan, G. S. A. Khalifa, M. Nusari & A. Ameen, (2018). The Impact of perceived supervisor support on employees turnover intention : The Mediating role of job satisfaction and affective organizational commitment. International Business Management, 12(7), pp. 477–492. http://doi.org/10.3923/ibm.2018.477.492. 628-634 2. A. Ameen & K. Ahmad, (2011). The Role of Finance Information Systems in anti financial corruptions: A theoretical review. In 11 International Conference on Research and Innovation in Information Systems (ICRIIS’11 (pp. 267–272). Ieee. http://doi.org/10.1109/ICRIIS.2011.6125725 3. A. Ameen & K. Ahmad, (2013). A Conceptual Framework of Financial Information Systems to reduce corruption. Journal of Theoretical and Applied Information Technology, 54(1), pp. 59–72. 4. A. Ameen & K. Ahmad, (2014). A Systematic Strategy for Harnessing Financial Information Systems in Fighting Corruption Electronically. In Knowledge Management International Conference (KMICe) 2014, 12 – 15 August 2014, Malaysia pp. 12–15. Retrieved from http://www.kmice.cms.net.my/ 5. A. Ameen & K. Ahmad, (2012). Towards Harnessing Financial Information Systems in Reducing Corruption : A Review of Strategies. Australian Journal of Basic and Applied Sciences, 6(8), pp. 500–509. 6. Venkatesh And Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model : Four Longitudinal Field Studies, pp. 186–204. 7. F. D. Davis, (1989). perceived Usefulness, Perceived ease of use, and User Acceptence of inforamtion technology, 13(3), pp. 319–340. 8. C. Chang, (2013). Exploring the determinants of e‐learning systems continuance intention in academic libraries. Library Management, 34(1/2), pp. 40–55. http://doi.org/10.1108/01435121311298261 9. S. Sahadev & K. Purani, (2008). Modelling the consequences of e‐service quality. Marketing Intelligence & Planning, 26(6), pp. 605–620. http://doi.org/10.1108/02634500810902857Ha. 10. M. Khalifa, & K. N. Shen, (2008). Explaining the adoption of transactional B2C mobile commerce. Journal of Enterprise Information Management, 21(2), pp. 110–124. http://doi.org/10.1108/17410390810851372 11. [M. Kocaleva & S. Zdravev, (2014). Research on UTAUT Application in Higher Education Institution. International Conference on Information Technology and Development of Education. 12. Y.-S. Wang, H.-H. Lin & P. Luarn, (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16(2), pp. 157–179. http://doi.org/10.1111/j.1365-2575.2006.00213.x 13. O. Isaac, Z. Abdullah, T. Ramayah, & M. Mutahar Ahmed, (2017). Examining the Relationship Between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. http://doi.org/10.3923/ajit.2017.100.124 14. O. Isaac, Z. Abdullah, T. Ramayah, A. M. Mutahar & I. Alrajawy, (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), pp. 205–223. http://doi.org/10.3923/rjasci.2017.205.223 Authors: Giftson Solomon J, D Janis Bibiyana Impact of Foreign Direct Investment of Indian Economy in Epoch of Global Value Chain with Paper Title: Reference to Industrialists in Tirunelveli District Abstract: A foreign direct investment (FDI) is an investment in the form of controlling ownership in a business in one country by an entity based in another country. It is thus distinguished from a foreign portfolio investment by a notion of direct control. Foreign direct investment (FDI) is an investment made by a firm or individual in one country into business interests located in other country. Generally, Foreign direct investment (FDI) takes place when an investor establishes foreign business operations or acquires foreign business assets, including establishing ownership or controlling interest in a foreign company.Foreign direct investment (FDI) in India is a major monetary source for economic development in India. Foreign companies invest directly in fast growing private Indian businesses to take benefits of cheaper wages and changing business environment of India. Foreign Direct Investment (FDI) gives both positive and negative impacts on Indian economy in epoch of global value chain. The global value chain (GVC) describes the people and activities involved in the production of a good or service and its supply, distribution, and post-sale activities (also known as the supply chain) when 109. activities must be coordinated across geographies. A supply chain is the network of all the individuals, organizations, resources, activities and technology involved in the creation and sale of a product from the delivery of source materials from the supplier to the manufacturer, through to its eventual delivery to the end 635-637 user. International production, trade and investments are increasingly organized within so-called global value chains (GVCs) where the different stages of the production process are located across different countries. Industrialists are having different thoughts on impacts of Foreign Direct Investment (FDI) on Indian economy.

Keyword: Foreign direct investment (FDI), Global value chain (GVC), Supply chain, Industrialists, Indian economy. References: 1. www.thehindubusinessline.com 2. www.businessstandard.com 3. www.ibef.org 4. www.makeinindia.com 5. www.corporatefinanceinstitute.com 6. www.investopedia.com Shegelman Ilia Romanovich, Vasilev Aleksey Sergeevich, Galaktionov Oleg Nikolaevich, Kuznetsov Authors: Alexey Vladimirovich, Sukhanov Yury Vladimirovich Bulding a Knowledge Base for Developing New Technical Solitions for the Development of Forest Paper Title: Roads Network Abstract: Currently, the transportation component in the cost of production in Russia is high and exceeds 40% in the logging industry. Among the most important trends in the development of forest transport in the country is a continuous increase in the share of timber hauling by forest hauling vehicles and an increase in the distance of timber transportation by truck-hauler trucks. At the same time, one of the main reasons hindering the development of timber industry complexes in the northern regions of Russia is the low degree of provision of forest infrastructure for transportation of business and energy wood. Therefore, considerable attention should be paid to improving the processes of forest road transport by solving the problems of developing a network of forest roads. A significant development of the network of forest roads is necessary to increase the economic accessibility of forests for clear and selective logging, thinning, and reforestation. It is also necessary to increase 110. the economic efficiency of the operation of timber-carrying trucks during forest removal, to increase the level of development of the calculated cutting area, to increase the level of forest fire safety of forests, to prevent and 638-646 extinguish forest fires. This led to the formation of a knowledge base for improving forest road transport processes by developing new technical solutions for the development of a network of forest roads. The formation of a knowledge base was made on the basis of an extended scientific, technical and patent search. Based on the knowledge base, recommendations for the development of a network of forest roads have been developed; new technologies have been proposed for involving local rocks in the processing of crushed stone for the construction of rocks, as well as the construction of temporary forest roads using logging waste.

Keyword: timber road transport, knowledge base, timber hauling, forest roads, timber industry enterprises, road foundation, patent, road covering, road construction. References: 1. Fan, Y., Weisberg, P. & Nowak, R. (2014). Spatio-temporal analysis of remotely-sensed forest mortality associated with road de- icing salts. The Science of the Total Environment. Vol. 472. 929-938. 2. Silva, F., Luciano José Minette, L. J., de Souza, A. P., de Moraes, A., C. & Schettino S. (2016). Classification of forest roads and determination of route using geographic information system. Revista Árvore. Vol. 40. No 2. http://dx.doi.org/10.1590/0100- 67622016000200015. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-67622016000200329 3. Sosa, А., Kevin, McDonnell K. & Ger Devlin G. (2015). Analysing Performance Characteristics of Biomass Haulage in Ireland for Bioenergy Markets with GPS, GIS and Fuel Diagnostic Tools. Retrieved from https://www.mdpi.com/1996- 1073/8/10/12004/htm 4. Tinker, D. B., Resor, C. A. C., Beauvais, G. P., Kipfmueller, K. F., Fernandes, Ch. I. & Baker, W. L. (1998). Watershed analysis of forest fragmentation by clearcuts and roads in a wyoming forest. Landscape Ecology. Vol. 13. No 3. 149-165. 5. Vasilev, A. S., Shegelman, I. R., Aminov, V. N., Kameneva, E. E. & Shchukin P. O. (2016). Philosophy of Technical Equipment Improvement as Exemplified by a Jaw Crusher. Indian Journal of Science & Technology. Vol. 9 (46). Retrieved from http://www.indjst.org/index.php/indjst/article/view/107536v 6. Weintraub, A., Church, R. L., Murray, A. T. & Guignard, M. (2000). Forest management models and combinatorial algorithms: analysis of state of the art. Sessions, J. A. Annals of Operations Research, no 96. 271–285. 7. Alyab’ev, V.I., Ilyin, B.A., Kuvaldin, B.I. & Grehov, G.V. (1990). Forest land transport. Moscow: Lesnaya promyshlennost'. 8. Afonichev, D.N. (2005). Improving the theory of calculation and design parameters of precast coatings for timber roads. Voronezh. 9. Afonichev, D.N. & Zanin, A.A. (2009). Comprehensive assessment of the impact of rolling stock on the road structure in the computer-aided design system, taking into account the characteristics of forest transport. Modelirovaniye sistem i protsessov, no 3-4. 23-28. 10. Afonichev, D.N., Morkovin, V.A. & Goptarev, S.M. (2018). Optimization of the integrated process of hauling timber from logging sites. Lesotekhnicheskiy zhurnal. Vol.8.No 2(30). 132-141. 11. Arutyunyan, A. Yu., Skrypnikov, A. V., Kozlov, V. G. & Skvortsova, T. V. (2016). Automated design of the forest road. Automation. Sovremennyye tekhnologii, no 6. 38-41. 12. Gerasimov, Y., Senko, S. & Karjalainen, T. (2013). Prospects of forest road infrastructure development in northwest Russia with proven Nordic solutions. Scandinavian Journal of Forest Research. Vol. 28. No 8. 758-774. 13. Batrudinov, A.N., Sangadzhiev, M.M., Erdniev, O.V. & Ledzhinov, V.S. (2016). Investigation of the physico-mechanical properties of local building materials to strengthen the shoulders (Lower Volga Region). Geologiya, geografiya i global'naya energiya, no 2(61). 14-29. 14. Baranov, A.N., Kisilev, A.E. & Burshina, M.P. (23.05.18). Patent of the Russian Federation No. 2654930 “Method of construction of a technological logging road section”. 15. Baranov, A.N. & Plyaskin, A.V. (20.01.2015). Patent of the Russian Federation No. 2539473 “Road clothes “Method of construction of a technological logging road section”. 16. Baranov, A.N. & Chumakov, V.F. (10.02.2013). The patent of the Russian Federation № 2539473 "Method of construction of a road bed". 17. Baranov, A.N., Chumakov, V.F. & Yasinskiy, R.A. Baranov, A.N. & Chumakov, V.F. (20.08.2012). Patent of the Russian Federation No. 2539473 “Method of construction of a technological logging road section”. 18. Bikbau, M.Ya., Miroshnikov, A.I. & Levin, B.A. (27.10.2009). Patent of the Russian Federation No. 2371537 "Method of road construction on weak and frozen soils and precast coating for its implementation." 19. Bolshakov, B.M. (1998). Central Scientific Research and Design and Design Institute of Mechanization and Energy of Forest Industry (CSRDIMEFI) and scientific and technical progress in the timber industry Khimki. CSRDIMEFI. 20. Burmistrova, O. N., Plastinina, E. V. & Voronina, M. A. (2012). Justification of design schemes and mathematical models of non-rigid pavements, reinforced with geosynthetic materials. Vestnik Povolzhskogo GTU. No. 1 (15). 45-51. 21. Weinstein, E. V., Salikhov, M. G., Weinstein, V. M., Nekhoroshkov, P. A. (2012). Investigation of changes in the vertical displacements from the load of logging trucks in the design of road pavement and the road bed by the finite element method. Sovremennyye problemy nauki i obrazovaniya, no 6. 22. Weiss, K.E. & Nikolaev, G.B. (2012). Features of the construction of forest roads in difficult engineering and geological conditions in the North of the European part of Russia. In the collection: Oriented fundamental and applied research is the basis for the modernization and innovative development of the architectural, construction and road-transport complexes of Russia. 56- 66. 23. Hacisalihoğlu, S., Gümüş, S., Kezik, U. & Karadağ, H. (2019). Impact of Forest Road Construction on Topsoil Erosion and Hydro-Physical Soil Properties in a Semi-Arid Mountainous Ecosystem in Turkey. Polish Journal of Environmental Atudits, no 28(1). 113–121. 24. Veyukov, E.V. & Gilyova, Yu.A. (2014). Economic efficiency of the implementation of anti-icing crushed stone-mastic asphalt concrete. Proceedings of the Volga State Technological University. Series: Technological. No 2. 228-230. 25. Veyukov, E.V. & Shigapov, R.R. (2017). Installation for determining the forces of adhesion of ice with the surfaces of the roads' pavements. Modernization and scientific research in the transport complex. Vol. 1. 192-196. 26. Voronin, A.V. (2012). Experience in the formation of models, methods and algorithms for integrated planning and management of material flows in multi-level geographically distributed transport and production systems. Inzhenernyy vestnik Dona, no 2 (20). 456-459. 27. Goptarev, S.M. & Morkovin, V.A. (2013). Justification of the volume of construction of temporary forest roads. Voronezhskiy nauchno-tekhnicheskiy Vestnik, no 4 (6). 76-83. 28. Gorbachevsky, V.A. (1984). Wood removal technology and logging efficiency. Promyshlennyy transport, no 1. 20-23. 29. Ilyin, B.A. (1986). Traction and operational calculations in the design of forest roads. Leningrad: LTA. 30. Kamusin, A.A., Kondrashova, E.V., Levushkin, D.M. & Burmistrov, V.A. (2014). Resource support of the process of construction, repair and maintenance of forest road sections. Forestry Bulletin, no 2(101).21-27. 31. Kamusin, A.A. & Levushkin, D.M. (2011). Investigation of the working capacity of the working layer of surface treatment of forest roads based on traditional and modified bitumen. Forestry Bulletin, no 5. 70-74. 32. Kotlov, V. G., Salikhov, M. G., Veiukov, E. V., Zheleznova, T. V. & Weinstein, E. V. (2013). On the use of crushed stone-mastic asphalt concrete to cover the streets of asphalt granulate cold milling. Vestnik Volgogradskogo gosudarstvennogo arkhitekturno- stroitel'nogo universiteta. Seriya: Stroitel'stvo i arkhitektura, no31-2 (50). 441-444. 33. Kruchinin, I. N. (2016). Justification of the use of stone materials in the construction of foundations and coatings of forest roads. Lesotekhnicheskiy zhurnal. Vol. 6. No 2 (22). 84-90. 34. Heilman, Jr., Strittholt, J. & Slosser, N. (2002). Forest fragmentation of the conterminous United States: assessing forest intactness through road density and spatial characteristics. Bioscience. Vol. 52. No 5. 411-422. 35. Kruchinin, I.N. & Sushkov, S.I. (2016). Improving the transport and operational qualities of gravel bases and coatings of forest roads. Stroitel'nyye i dorozhnyye mashiny, no 6. 36-38. 36. Kruchinin, I. N. (2014). Assessment of the impact of timber transport machines on the foundations and the coverage of forest roads. Transport. Transportnyye sooruzheniya. Ekologiya, no 4. 40-48. 37. Kuvaldin, B.I. & Skrypnik, V.I. (1976). Calculations on the computer modes of movement of timber-back trucks. Izvestiya vuzov: Lesnoy zhurnal, no 6. 60-65. 38. Kuryanov, V. K. & Afonichev, D. N. (2007). Car roads. Voronezh. 284. 39. Kuryanov, V. K., Afonichev, D. N., Burmistrova, O. N. & Skrypnikov A. V. (2002). Improving the convenience and safety of the movement of timber trucks on curves of small radius. Vestnik Tsentral'no-Chernozemnogo regional'nogo otdeleniya nauk o lese. Vol. 4. No 1. 178-187. 40. Kuryanov, V. K., Skrypnikov, A. V., Kondrashova E. V. & Morkovin V. A. (2014). The model of traffic flow on forest roads. Izvestiya vysshikh uchebnykh zavedeniy «Lesnoy zhurnal». No 2. 61-67. 41. Lifantev, V.I., Salikhov, M.G. & Yezhova, S.V. (20.10.2018). Patent of the Russian Federation No. 2336387 "Method of compacting concrete with aggregates from local road-building materials". 42. Malyanova L. I. & Salikhov M. G. (2013). Study of the effect of the modified additive on some properties of asphalt concrete with limestone crushing screenings for covering forest roads. Vestnik Povolzhskogo gosudarstvennogo tekhnologicheskogo universiteta. Seriya: Les. Ekologiya. Prirodopol'zovaniye, no 1 (17). 64-71. 43. Moiseev, V.I. (2013). Increase of the transport and operational level of pavements of forest roads with use of a rubber crumb. Krasnoyarsk. 44. Naskovets, M. T., Drachilovsky, A. I. & Dini, M. N. (2015). Interaction of forest road embankments containing reinforcing layers with peat bases. Vestnik Sibirskoy gosudarstvennoy avtomobil'no-dorozhnoy akademii, no 6 (46). 71-76. 45. Holzleitner, F., Kanzian, C. & Stampfer, K. (2011). Analyzing time and fuel consumption in road transport of round wood with an onboard manager. European Journal of Forest Research, Vol.130. No 2.293-301. 46. Nemtsov, V.P. & Shestakov, B.A. (1982). Operation of road transport in a timber company. Moscow: Lesnaya promyshlennost'. 47. Prokopets A.S., Sergeev, A.S., Yushkov, B.S. & Sushkov, S.I. (2016). Formation of transverse cracks in asphalt concrete pavements of logging roads arranged on slopes. Al'ternativnyye istochniki energii v transportno-tekhnologicheskom komplekse: problemy i perspektivy ratsional'nogo ispol'zovaniya. Vol. 3. No 3 (6). 380-386. 48. Raschektaev, V. A., Kruchinin, I. N. & Chudinov, S. A. (10.12.2014). The patent of the Russian Federation No. 148339 "Road coverage". 49. Rodin, S. A. & Degtev, V. T. (04/20/2015). Patent of the Russian Federation No. 2459899 "Method of decompression of forest roads." 50. Salikhov, M. G., Weinstein, V. M. & Veyukov, E. V. (2017). New organic concretes and features of their production and use technologies. Vestnik Povolzhskogo gosudarstvennogo tekhnologicheskogo universiteta. Seriya: Materialy. Konstruktsii. Tekhnologii. No 2. 38-43. 51. Smirnov, M. Yu., Skrypnikov, A. V., Kondrashova, E. V., Dorokhin, S. V. & Skvortsova, T.V. (2014). Methods, models, algorithms for managing the process of construction, repair and maintenance of forest roads in conditions of limited resources. International Journal of Applied and Fundamental Research, no 6. 126-128. 52. Storodubtseva, T.N., Chernikov, E. A., Tomilin, A. I. & Aksomitny, A. A. (2014). Calculation of slabs of temporary forest roads from polymer sand composite materials (PPKM). Aktual'nyye napravleniya nauchnykh issledovaniy XXI veka: teoriya i praktika. Vol. 2. No 2-1 (7-1). 489-493. 53. Sushkov, S. I., Burmistrova, O. N. & Burmistrov D. V. (2017). Improving the performance of forest roads. Voronezh. 163. 54. Sushkov, S.I., Burmistrova, O.N. & Pilnik, Yu.N. (2015). Principles of solving management problems in multi-level transportation and production systems of the forest complex. Fundamental'nyye issledovaniya, no 11-2. 317-321. 55. Sushkov, S.I., Knyazev, A.V. & Vostrikov, D.S. (2018a). On the use of geosynthetic materials in the construction of forest roads. No 1(23).15-21. 56. Kameneva, E. T., Aminov, V. N., Shegelman, I. R., Vasilev, A. S. & Shchukin, P. O. (2016). Specifics of Studying Crushability of Construction Rocks. Indian Journal of Science & Technology. Volume 9, Issue 46. Retrieved from http://www.indjst.org/index.php/indjst/article/view/107540 57. Tyurin, V.I. (2011). Questions of the use of geosynthetic materials in road construction in the design of forest roads. Dorogi. Innovatsii v stroitel'stve. No 7. 22-27. 58. Umarov, M. M., Skrypnikov, A. V., Chernyshova, E. V. & Mikova, E. Yu. (2018). The use of digital terrain models for tracing forest roads. Lesnoy zhurnal, no 2. 58–69. 59. Chernikov, E. A., Zobov, S. Yu. (2014). Technological principles for the manufacture of blocks of the track covering of temporary logging roads from wood fiber composite materials (WFCM). Voronezhskiy nauchno-tekhnicheskiy Vestnik, no 4 (10). 88-91. 60. Chernyshova, E. V., Skrypnikov, A. V., Samtsov, V. V. & Abasov, M. A. (2019). Logging highways in the transport network of a timber enterprise. Lesnoy zhurnal, no 2. 95–101. 61. Shegelman, I. R. (2013). Formation of end-to-end technologies of forest industry: scientific and practical aspects. Global'nyy nauchnyy potentsial, no 8 (29). 119-122. 62. Shegelman, I. R., Skrypnik, V. I. & Kuznetsov, A. V. (04/20/2013). Patent of the Russian Federation №2479200 "Method of creating a whisker coating in areas with low bearing capacity of soils." 63. Shegelman, I. R., Schukin, P. O. & Petukhov, R. A. (2011). Resource approach to the development of a regional network of forest roads. Perspektivy nauki, no 11(26). 88-191. 64. Shegelman, I. R., Vasiliev, A. S., Schukin, P. O., Aminov, V. N. & Kameneva, E. E. (12.10.2017). Patent of the Russian Federation № 2633396 "Method of crushing lumpy rock in a jaw crusher." 65. Shegelman, I. R., Vasiliev, A. S., Shchukin, P. O., Aminov, V. N. & Kameneva, E. E. (July 01, 2015). Patent of the Russian Federation № 158121 "Jaw crusher". 66. Shirnin, Yu. A., Shirnin, A. Yu., Lebedeva, N. Yu. & Fedorova, I. Ya. (08.20.2013). Patent of the Russian Federation №2489844 "Method for the development of forest areas routes of oil and gas pipelines and transmission lines." 67. Saibara, K., Nishigaki, S., Matsuda, F. & Kubota, S. (2014). Contrivances to assist forest machine operator on forest road with steep slope. Proceedings of the 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC). 458-465. 68. Stefan, Yu. V., Bondarev, B. A. & Yankovsky, L. V. (2016). The use of cubic molten slag rubble for the construction and repair of main forest roads. Remont. Vosstanovleniye. Modernizatsiya, no 10. 11-16. 69. Ganjali, M., & Teimourpour, B. (2016). Identify Valuable Customers of Taavon Insurance in Field of Life Insurance with Data Mining Approach. UCT Journal of Research in Science, Engineering and Technology, 4(1), 1-10. 70. Ngirwa, C. C., & Ally, M. (2018). An ICT Based Solution for Pesticides Authenticity Verification: A Case of Tanzania. Journal of Information Systems Engineering & Management, 3(4), 27. 71. Singh, P., Teoh, S. H., Cheong, T. H., Md Rasid, N. S., Kor, L. K., & Md Nasir, N. A. (2018). The Use of Problem-Solving Heuristics Approach in Enhancing STEM Students Development of Mathematical Thinking. International Electronic Journal of Mathematics Education, 13(3), 289-303. https://doi.org/10.12973/iejme/3921 72. Sessions, J. A. (1987). Heuristic algorithm for the solution of the variable and fixed cost transportation problem. Symposium on System Analysis in Forest Resources. Univ. of Georgia, Athens. 324-336. 73. Shegelman, I. R., Vasiliev, A. S. & Shchukin, P. O. (2018a). Particularities of Ensuring Food Security in the Conditions of the North of Russia. Astra Salvensis, no 6. 941-949. Authors: Rashed Alneyadi, Mohammed Nusari, Ali Ameen, Amiya Bhaumik Impact of Organizational Justice (Distributive Justice, Procedural Justice, and Interactional Justice) Paper Title: 111. on Job Satisfaction Abstract: Perceptions of organizational justice constitute an important heuristic in organizational decision- making, as research relates it to job satisfaction, turnover, leadership, organizational citizenship, organizational 647-652 commitment, trust, customer satisfaction, job performance, employee theft, role breadth, alienation, and leader- member exchange. The public sector in UAE is the focus of this paper. Applying the concept of organizational justice (distributive justice, procedural justice, interactional justice) to examine the effect of it on employees’ satisfaction. The data was collected from 452 officers from 7 sectors in the ministry of interior in UAE and analysed using structural equation modelling via SmartPLS 3.0. There were three main results: first, distributive justice has a positive impact on job satisfaction; second, procedural justice is significantly predicting job satisfaction; third, interactional justice has a significant impact on job satisfaction. The proposed model explained 33.7% of the variance in job satisfaction. Theoretical and practical implications are also provided.

Keyword: Organizational justice; distributive justice; procedural justice; interactional justice; job satisfaction. References: 1. O. Isaac, Z. Abdullah, T. Ramayah & M. Mutahar Ahmed, (2017). Examining the Relationship between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. 2. O. Isaac, Z. Abdullah, T. Ramayah, A. M. Mutahar & I. Alrajawy, (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), pp. 205–223. 3. O. Isaac, Z. Abdullah, T. Ramayah, & A. M. Mutahar, (2017). Internet usage, user satisfaction, task-technology fit, and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), pp. 210–241. 4. R. V Krejcie & D. W. Morgan, (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 5. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 6. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 7. Wolfe, S. E., Rojek, J., Manjarrez, V. M., Jr., & Rojek, A. (2018). Why does organizational justice matter? Uncertainty management among law enforcement officers. Journal of Criminal Justice, 54, 20-29. 8. Middelkamp-Hup MA, Pathak MA, Parrado C, Goukassian D, Rius-Diaz F, Mihm MC, et al. Oral Polypodium leucotomos extract decreases ultraviolet-induced damage of human skin. J Am Acad Dermatol. 2004; 51, pp. 910–8. 9. M. Abdulrab, A. R. Zumrah, Q. Almaamari, A. N. Al-Tahitah, O. Isaac, & A. Ameen, (2018). The Role of Psychological Empowerment as a Mediating Variable between Perceived Organizational Support and Organizational Citizenship Behaviour in Malaysian Higher Education Institutions. International Journal of Management and Human Science (IJMHS) Vol. 2. 10. Palaiologos, Anastasios & Papazekos, Panagiotis & Panayotopoulou, Leda. (2011). Organizational justice and employee satisfaction in performance appraisal. Journal of European Industrial Training. 35. 826-840. Ahmed Hamoud Al-Shibami, Nayef Alateibi, Mohammed Nusari, Ali Ameen, Gamal S. A. Khalifa, Authors: Amiya Bhaumik Impact of Organizational Culture on Transformational Leadership and Organizational Paper Title: Performance Abstract: This study employs structural equations modeling via PLS to analyze the 392 valid questionnaires in order to assess the proposed model that is based on the transformational leadership characteristics to identify its effect on the performance of organizations, besides assessing the moderating role of organizational culture in the government sector in the United Arab Emirates. The main independent construct is transformational leadership as a second-order construct of idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. The dependent construct covers organizational performance in terms of learning & growth and internal process. Whereas power distance representing the organizational culture as a moderating variable. The study will describe the relations among the various constructs. Our work has improved our insight into the importance of transformational leadership and organizational culture. Results indicated that the independent variable significantly predicted performance, in addition to power distance having a significant moderating role between transformational leadership and internal process, but not between transformational leadership and learning & growth. The proposed model explained 40.8% of the variance in learning & growth and 29.8% in internal process.

112. Keyword: Transformational leadership; organizational culture; power distance; organizational performance; UAE. 653-664 References: 1. Gavrea, L. Ilies & R. Stegerean (2011). Determinants of organizational performance: The case of Romania. Management & Marketing, 6(2), pp. 285–300. 2. P. J. Richard, T. Devinney, G. Yip & G. Johnson, (2009). Measuring Organizational Performance: Towards Methodological Best Practice. Journal of Management Vol. 35. https://doi.org/10.1177/0149206308330560 3. R. S. Kaplan & D. P. Norton (2005). The Balanced Scorecard: Measures That Drive Performance. Harvard Business Review, (July-August). 4. S. Alkhateri, A. E. Abuelhassan, G. S. A. Khalifa, M. Nusari & A. Ameen, (2018). The Impact of perceived supervisor support on employees turnover intention : The Mediating role of job satisfaction and affective organizational commitment. International Business Management, 12(7), pp. 477–492. http://doi.org/10.3923/ibm.2018.477.492 5. Ameen, H. Almari & O. Isaac, (2019). Determining Underlying Factors that Influence Online Social Network Usage Among Public Sector Employees in the UAE. In Fathey M. Faisal Saeed, Nadhmi Gazem (Ed.), Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing (Recent Tre, Vol. 843, pp. 945–954). Springer Nature Switzerland AG: Springer International Publishing. http://doi.org/10.1007/978-3-319-99007-1 6. Ameen & K. Ahmad, (2011). The Role of Finance Information Systems in anti financial corruptions: A theoretical review. In 11 International Conference on Research and Innovation in Information Systems (ICRIIS’11 (pp. 267–272). Ieee. http://doi.org/10.1109/ICRIIS.2011.6125725 7. Ameen & K. Ahmad, (2012). Towards Harnessing Financial Information Systems in Reducing Corruption : A Review of Strategies. Australian Journal of Basic and Applied Sciences, 6(8), pp. 500–509. 8. Ameen & K. Ahmad, (2013). A Conceptual Framework of Financial Information Systems to reduce corruption. Journal of Theoretical and Applied Information Technology, 54(1), pp. 59–72. 9. C. Lee, J. O. Yoon & I. Lee, (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), pp. 1320–1329. http://doi.org/10.1016/j.compedu.2009.06.014 10. O. Isaac, Z. Abdullah, T. Ramayah & M. Mutahar Ahmed, (2017). Examining the Relationship Between Overall Quality, User Satisfaction and Internet Usage: An Integrated Individual, Technological, Organizational and Social Perspective. Asian Journal of Information Technology, 16(1), pp. 100–124. http://doi.org/10.3923/ajit.2017.100.124 11. O. Isaac, Z. Abdullah, T. Ramayah & A. M. Mutahar, (2017). Internet usage , user satisfaction , task-technology fit , and performance impact among public sector employees in Yemen. The International Journal of Information and Learning Technology, 34(3), pp. 210–241. http://doi.org/10.1108/IJILT-11-2016-0051 12. O. Isaac, Z. Abdullah, T. Ramayah, A. M. Mutahar & I. Alrajawy, (2017). Towards a Better Understanding of Internet Technology Usage by Yemeni Employees in the Public Sector: An Extension of the Task-Technology Fit (TTF) Model. Research Journal of Applied Sciences, 12(2), pp. 205–223. http://doi.org/10.3923/rjasci.2017.205.223 13. L. A. Hayduk & L. Littvay (2012). Should researchers use single indicators , best indicators , or multiple indicators in structural equation models ? BMC Medical Research Methodology, 12(1), pp. 1–17. https://doi.org/10.1186/1471-2288-12-159 14. G. Tabachnick & L. S. Fidell, (2007). Using Multivariate Statistics. PsycCRITIQUES, 28, pp. 980. http://doi.org/10.1037/022267 15. R. V Krejcie & D. W. Morgan, (1970). Determining sample size for research activities. Educational and Psychological Measurement, 38, pp. 607–610. 16. M. Ringle, S. Wende, & J.-M. Becker, (2015). SmartPLS 3. Bonningstedt: SmartPLS. 17. J. C. Anderson & D. W. Gerbing, (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), pp. 411–423. http://doi.org/10.1037/0033-2909.103.3.411 18. R. E. Schumacker & R. G. Lomax, (2004). A Beginner’s Guide to Structural Equation Modeling. New York: Lawrence Erlbaum. 19. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. New Jersey. 20. J. F. J. Hair, G. T. M. Hult, C. Ringle & Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 46 Long Range Planning 328 (2014). London: Thousand Oaks: SAGE. http://doi.org/10.1016/j.lrp.2013.01.002 21. V. R. Kannana & K. C. Tan, (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega: The International Journal of Management Science, 33(2), pp. 153–162. 22. E. Werts, R. L. Linn & K. G. Jöreskog, (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), pp. 25–33. 23. R. B. Kline, (2010). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press. 24. Gefen, D. Straub & M.-C. Boudreau, (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), pp. 1–79. 25. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. 26. W. W. Chin, (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), pp. 7–16. 27. Z. Awang, (2014). Structural Equation Modeling Using AMOS. Shah Alam.Malaysia: University Teknologi MARA Publication Center. 28. J. Cohen, (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Editio). LawreAssociatesnce Erlbaum. Authors: Irina B. Kostina, Yuliya P. Gladkikh, Maxim A. Velichko, Lyudmila V. Krasovskaya, Olga N. Satler Assessment of Ecological Consciousness Formation among Adolescent Girls in the Learning Process Paper Title: by Means of Specialized Computer Systems Abstract: The article discusses the results of empirical research in the framework of ascertaining experiment, the purpose of which was to assess the level of environmental consciousness formation of the secondary school adolescent girls. The results analysis was carried out on the intensity levels of subjective relations, such as: perceptive-affective, cognitive and behavioral. To diagnose each component the technique of "Naturafil" was used, which helped to identify the nature of development level of ecological consciousness. Information processing within the framework of the expected results evaluation criterion was carried out on the basis of mathematical statistics methods included in the data analysis package of MS Excel software application. Significant differences in the studied parameters between the groups were revealed by the determination coefficient.

Keyword: ecology, ecological consciousness, ecological worldview, ecological education. References: 1. Lavigine, I.V. 2013. Gender peculiarities of ecological consciousness. Psychology in economy and management. 2, 136-141. 2. Kostina, I.B. 2006. Social and ecological stability of personality. Philosophy over barriers: planetary thinking and globalization of the XXI century. 1 (2), 101-105. 113. 3. Korunova, V.O., 2017. The Role of ecological culture and ecological consciousness in the formation of human relations with the environment. Management of socio-economic systems. 215-217. 4. Chuikova, L. Yu. 2012. Ecological thinking and ecological worldview as a product of ecological education at school: Analysis of 665-668 scientific concepts and interpretations. Astrakhan Bulletin of ecological education. 1 (19), 46 – 68. 5. . Derjabo, S.D., Jasvin, V.A. 1996. Ecological pedagogy and psychology. Rostov - on - Don: Publishing house “Phoenix”. 480. 6. Markova, M.N. 2011. The role of environmental education and training in the formation of environmental thinking. Bulletin of the Volga region Institute of management. 2, 199 – 203. 7. . Dvoynev, V., Starostina, O. 2007. Ecological consciousness of the student: the relevance of the study. Higher education in Russia. 5, 134–136. 8. Soto, C., Gosling, S., Oliver, J., Potter, J. 2011. Age Differences in Personality Traits From 10 to 65: Big Five Domains and faces in a Large Cross-Sectional Sample. Journal of Personality and Social Psychology. 100(2), 330-348, doi: 10.1037/a0021717 9. Jackson, J., Bogg, T. 2009. Not all Conscientiousness Scales Change Alike: A Multimethod, Multisample Study of Age Differences in the Facets of Conscientiousness. Journal of Personality and Social Psychology. 96 (2), 446-459, doi: 10.1037/a0014156 10. Polyansky, D.V. 2006. Ecological educationalism and the concept of advanced education. Bulletin of the Baltic Federal University. I. Kant. Series: Humanities and social Sciences. 12, 32-40. 11. Panov, V.I. 2014. Ecopsychology: Paradigmal search. Moscow; Saint-Petersburg.: Psychological institute of the RAE: Nestor- Istoriya. 3(1), 215-218. 12. Prozersky, V. 2013. Ecological esthetics on the edge of millennium: choice of conceptual path. Vestnik of Saint Petersburg University. Philosophy and Conflict Studies. 3, 22-28. 13. Saydali, S., & Parvin, H. (2015). Prediction and Diagnosis of Down Syndrome Disease by using the CHAID Algorithm. UCT Journal of Research in Science, Engineering and Technology, 3(4), 31-34. 14. Coelho, P., Zúquete, A., & Gomes, H. (2018). Federation of Attribute Providers for User Self-Sovereign Identity. Journal of Information Systems Engineering & Management, 3(4), 32. 15. Afriyani, D., Sa’dijah, C., Subanji, S., & Muksar, M. (2018). Characteristics of Students’ Mathematical Understanding in Solving Multiple Representation Task based on Solo Taxonomy. International Electronic Journal of Mathematics Education, 13(3), 281- 287. https://doi.org/10.12973/iejme/3920 Authors: S. Aravindan, S. Prasad

Paper Title: FDI Contribution to the Maritime Industry in India Abstract: In today`s economy FDI (Foreign Direct Investment) is indispensable element for economic growth of rapidly developing countries like India. The FDI in addition to providing sources of technology and best practices from the developed nations also can helps the investing companies to take benefits of cheap wages, tax benefits and other facilities from the invested countries. With respect to the shipping and ports, India allows 100% FDI and also facilitates ten years tax free for companies which develop port or container terminal, maintenance and its operations. In fact Indian government has eased the FDI in port sector through automatic route in which a foreign company doesn`t require prior approval from the central government or RBI. The automatic route is in fact now allowable in sectors and business activities. The companies can invest in shipbuilding, ship repair, ship recycling etc. This paper explains the infrastructure and economic contributions of the ports and shipping before and after the introduction FDI in these sectors. The paper describes how the FDI impacted the technological growth in the local scenario, socio economic growth of the regions , industries 114. alongside the ports like economic zones / free zones , popularity of Indian port infrastructures in the global shipping market which will attract bigger vessels and more port calls, transshipments etc. 669-672

Keyword: FDI, RBI. References: 1. India Surging Ahead 2019–Economic Diplomacy and States Division, Ministry of External Affairs. 2. UNCTAD World Investment Report 2019 3. India’s Recent Inward Foreign Direct Investment An Assessment - K.S. Chalapati Rao & Biswajit Dhar 2018 4. www.dipp.gov.in 5. www.isid.org.in 6. www.fifp.gov.in 7. www.rbi.org.in 8. http://www.ceicdata.com 9. http://fdi.finance.com 10. www.toanewdawn.blogspot.com 11. https://www.ukibc.com Authors: Gauri Agrawal, Alok Agrawal, Anuj Kumar Agarwal, Piyush Kumar Tripathi A Mathematical Model to Examination the Behavior of Two Competing Biological Species under the Paper Title: Effect of a Toxicant Abstract: It is well known that the toxicants present in the environment affect the growth of any biological population living in that habitat. It also affects the carrying capacity of the environment with respect to that biological population. In this paper we are considering two logistically growing biological populations competing for a common resource under the effect of a toxicant and we’ve assumed that the first population discharges toxicant which is harmful to the second population only. Since, condition of the population and their habitat are limited therefore, keeping the above in the mind, here we’ve proposed a mathematical model to study the behaviour of the two competing population and observed that one species dies away as the time lapses due to the effect of the toxicants. It has been shown further that under certain conditions both the competing species can coexist in a long run.

Keyword: competing populations, toxicants, growth rate, carrying capacity,. References: 115. 1. Agarwal, A. K., Khan, A. W., &Agrawal, A. K. (2016). The effect of an external toxicant on a biological species in case of deformity: a model. Modeling Earth Systems and Environment, 2(3), 148. 2. Agrawal, A. K., Dubey, B., Sinha, P., &Shukla, J. B. (2000). Effects of two or more toxicants on a biological species: A non 673-677 linear mathematical model and its analysis. Mathematical Analysis and Applications, A. P Dwivedi (editor), Narosa Publishing House, New Delhi, 93-109. 3. Deluna, J. T. & Hallam. T. G. (1987): Effect of toxicants on population: a qualitative approach IV: Resource–consumer–toxicant models. Ecol Model., 35, 249–273. 4. Dubey, B. & Hussain, J. (2000): A model for the allelopathic effect on two competing species. Ecologicl Modelling, 129(2-3), 195-207. 5. Dubey, B., Shukla, J. B., Sharma, S., Agarwal, A. K., & Sinha, P. (2010): A mathematical model for chemical defense mechanism of two competing species. Nonlinear Analysis: Real World Applications, 11(2), 1143-1158. 6. Kumar, A., Agrawal, A. K., Hasan, A. & Misra, A. K. (2016): Modeling the effect of toxicant on the deformity in a subclass of a biological species. Modeling Earth Systems and Environment, 2(1), 40. 7. La Salle, J. & Lefschetz, S. (2012): Stability by Liapunov's Direct Method with Applications by Joseph L Salle and Solomon Lefschetz (Vol. 4). Elsevier. 8. Shukla, J. B. & Agrawal, A. K. (1999): Some mathematical models in ecotoxicology: Effects of toxicants on biological species. Sadhana, 24(1-2), 25-40. 9. Shukla, J. B., Agrawal, A. K., Dubey, B. & Sinha, P. (2001): Existence and survival of two competing species in a polluted environment: a mathematical model. Journal of Biological Systems, 9(2), 89-103. 10. Shukla, J. B. & Dubey, B. (1996): Simultaneous effect of two toxicants on biological species: a mathematical model. Journal of Biological Systems, 4(1), 109-130.

116. Authors: Soumys Shetty, Janet Jyothi D Souza Paper Title: An Empirical Examination of the CAPM on BSE SENSEX Stocks Abstract: Investment plays a significant role in the modern economy. The investor understands the importance of investment in wealth creation. But real causing problem for investor is prediction of risk to have assured return in each company shares. It has understood that minimizing the systematic risk is always difficult than unsystematic risk. If we look in to the earlier study done by many researchers, we find that CAPM model would be right technique to know the risk and return relationship in any stock. With the point of view of significance and reliability of CAPM model, we have used CAPM techniques to conclude the results. The first model developed by William Sharpe and other scholars supporting to this model has been used to test the results. This study investigates the validity of CAPM on BSE 30 companies from BSE website. The study considered closing price of 30 companies of BSE stock market from January 2009 to December 2018.

Keyword: Investment, BSE Stock, Closing price, wealth creation, CAPM model . References: 1. Alam, M. R. (2015). Application of application of capital asset pricing model empirical evidences from chittagong stock exchange. The cost and management, 43(3), 38-44. 2. Ansari, V. A. (2000). Capital asset pricing model: should we stop using it? Vikalpa, 25(1), 55-64. 3. Bajpaia, S., & Sharmab, A. K. ( 2015 ). An empirical testing of capital asset pricing model in India. Procedia - social and behavioral sciences 189, 259 – 265. 4. Banz, R. W. (1981). The relationship between return and market value of common stocks. Journal Of Financial Economics(9), 3- 18. 5. Barber, B. M., & lyon, J. D. (1997). Firm size, book-to-market ratio, and security returns: a holdout sample of financial firms. The Journal of Finance, 52(2), 875-883. 6. Baura, S. K., Raghunathan, V., & Varma, J. R. (1994). Research on the indian capital market:a review. Vikalpa, 19(1), 15-31. 7. Bondt, W. F., & Thaler, R. (1984). Does the stock market overreact? The Journal of Finance, 40(3), 793-805. 8. Breeden, D. T. (1979). An intertemporal asset pricing model with stochastic consumption and investment opportunities. Journal of Financial Economics(7), 265-296. 9. Campbell, J. Y. (1996, april). Understanding risk and return. The Journal of political Economy, 104(2), 298-345. 10. Chan, l. K., & Lakonishok, J. (1993). Are the reports of beta's deatth premature? Portfolio management, 51-62. 11. Chan, l. K., Jegadeesh, N., & Lakonishok, j. (1995). Evaluating the performance of value versus glamour stocks the impact of selection bias. Journal of Financial Economics(38), 269-296. 12. Chaudhary, P. (2016). Testing of capm in Indian context. Business analyst, 37(1), 1-18. 13. Daniel, K., & Titman, S. (1996). Evidence on the characteristics of cross sectional variation in stock returns. National bureau of economic research, 1-38. 14. Davis, J. L. (1994). The cross-section of realized stock returns: the pre-compustat evidence. The Journal of Finance, 5, 1579- 1593. 15. Dybvig, P. H., & Jr, J. E. (1982). Mean-variance theory in complete markets. The Journal of Business, 55(2), 233-251. 16. Elshqirat, M. K., & Sharifzadeh, M. M. (2018). Testing a multi -factor capital asset pricing model in the jordanian stock market. International business research, 11(9), 13-22. 678-685 17. Eugene, F. F., & James, D. M. (1973). “risk, return and equilibrium: empirical tests. Journal of political economy, 81(3),may- june. 18. Fama, E. F. (1991). Efficient capital markets: ii. The Journal of finance, 46(5), 1575-1617. 19. Fama, E. F., & french, k. R. (2015). A five-factor asset pricing model. Journal of financial economics116,, 1-22. 20. Fama, E. F., & Macbeth, J. D. (1973). Risk,return and equilibrium :empirical tets. Journal of politicaleconomy, 81(3), 607-636. 21. Fischer Black, ,. M. (1972). The capital asset pricing model: some empirical tests ,in studies in the theory of capital markets,ed.by m.c. Praeger publishers, new york. 22. French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of financial economics(33), 3-56. 23. Heaton, J., & Lucas, D. (2000). Portfolio choice and asset prices: the importance of entrepreneurial risk. The Journal of finance, lv(3), 1163-1198. 24. Iwaki, H. (2018). An equilibrium asset pricing model under the dual theory of the smooth ambiguity model. Journal of mathematical finance, 8, 497-515. 25. Jaggannathan, R., & , W. Z. (1996). The conditional capm and the cross return of expected returns. The Journal of finance, 51(1), 3-53. 26. Jegadeesh, N., & Titman, S (1993). Returns to buying winners and selling losers:implications for losers stock market efficiency. The joijknal of finance, 48(1), 65-91. 27. Karakoc, B. (2016). A validity analysis of capital asset pricing model (capm) in istanbul stock exchange. Journal of social sciences, 4(1), 45-56. 28. Karp, A., & vuuren, G. V. (2017). The capital asset pricing model and fama french three factor model in an emerging market environment. International business & economics research, 16(3), 231-256. 29. Lakonishok, ,. J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. The Journal of finance, 49(5), 1541-1578. 30. Lakonishok, J., & shapiro, a. C. (1986). Systematic risk, total risk and size as determinants of stock market returns. Journal of banking and finance(10), 115-132. 31. Levy, H. (2010). The capm is alive and well: a review and synthesis. European financial management,, 16(1), 43-71. 32. Lewellen J and, N. S. (2006). The conditional capm does not explain asset pricing anamolies. Journal of financial ecnomics, 82(2), 53-60. 33. Markowitz, H. (1952). Portfolio selection. The Journal of finance, 7(1), 77-91. 34. Merton, R. C. (1985). On the current state of the stock market rationality hypothesis. 1-49. 35. Modigliani, F., & pogue1, G. A. (1973). An introduction to risk and return concepts and evidence. 36. Reddy, ,. M., & Durga, S. (2015). Testing the validity of capm in indian stock markets. International Journal of multidisciplinary research and development ;, 2(2): , 56-60. 37. Reinganum, M. R. (1982). A direct test of roll's conjecture on the firm size effect. The Journal of Finance, xxxvi(1). 38. Ritter, J. R., & Chopra, N. (1989). Portfolio rebalancing and the turn-of-the-year effect. 44(1), 149-166. 39. Roll, R. (1977). A critique of the asset pricing theory’s tests. Journal of financial economics(4), 129-176. 40. Sharpe, W. F. (1964). Capital asset prices: a theory of market equilibrium under conditions of risk. The Journal Of Finance, 19(3), 425-442. 41. Sharpe, W. F. (1964). Capital asset prices: a theory of market equilibrium under conditions of risk. Journal of finance 19(3), 425- 442. 42. Sreenu, N. (2018). An empirical test of capital asset-pricing model and three-factor model of fama in indian stock exchange. Management and labour studies, 43(4), 1-14. 43. Stambaugh, R. F. (1982). On the exclusion of assets from tests of the two parameter model a sensitivity analysis. Journal of financial economics(10), 237-268. 44. Yu, Y. J. (2012). The asset pricing system. Modern economy, 3, 473-480. Authors: M.Gurupandi, S.Eswaran

Paper Title: Foreign Direct Investment on Agricultural Industry in India Abstract: Agriculture is the primary source of livelihood for about 58 per cent of India’s population. Gross Value Added by agriculture, forestry and fishing is estimated at Rs 18.53 trillion (US$ 271.00 billion) in FY18. According to the Department for Promotion of Industry and Internal Trade (DPIIT), the Indian food processing industry has cumulatively attracted Foreign Direct Investment (FDI) equity inflow of about USD 9.08 billion between April 2000 and March 2019. The agriculture sector in Asian country is anticipated to come up with higher momentum within the next few years thanks to accrued investments in agricultural infrastructure like irrigation facilities, deposit and cold storage. What is more, the growing use of genetically changed crops can probably improve the yield for Indian farmers. India is anticipated to be self-sustaining in pulses within the returning few years because of conjunctive efforts of scientists to urge early-maturing types of pulses and therefore the increase in minimum support value. FDI works as a way of integration developing countries into the world market place and increasing the capital accessible for investment, so resulting in inflated economic process required to cut back financial condition and lift living standards. India is expected to achieve the ambitious goal of doubling farm income by 2022. This study main objective is analyzing Indian agricultural manufacturing and allied industries are qualified for the future expansion of agriculture sector through its modernization of agro based machineries industries. This study centered solely the chances of the allied industries (R& D, equipments, and machineries up gradation.

Keyword: FDI, Agriculture, Investments, Agro Products, Warehousing. 117. References: 1. Sunil Kumari and Preeti Devi (2016) “Foreign Direct Investment on Indian Agriculture” p-ISSN: 2394-1545; e-ISSN: 2394-1553; 686-694 Volume 3, Issue 7; July-September, 2016, pp. 748-752. 2. Epaphra, M (2017) “Analysis of Foreign Direct Investment, Agricultural Sector and Economic Growth in Tanzania” ISSN Online: 2152-7261 ISSN Print: 2152-7245 3. Dadson Awunyo-Vitor and Ruby Adjoa Sackey (2018) “Agricultural sector foreign direct investment and economic growth in Ghana” 4. Adekunle and E Oludayo (2018) Foreign Direct Investment Inflow and Agricultural Sector Productivity In Nigeria IOSR Journal of Economics and Finance (IOSR-JEF) e- ISSN: 2321-5933, p-ISSN: 2321-5925. Volume 9, Issue 4 Ver. PP 12-19. 5. Munisamy Gopinath (2010) “Foreign direct investment and wages: a cross-country analysis” https://doi.org/10.1080/0963819032000132067. 6. Tanay Kumar Nandi and Ritankar Sahu (2007) “Foreign direct investment in India with special focus on retail trade” 7. Sumei Tang and E. A. Selvanathan (2008) “Foreign Direct Investment, Domestic Investment and Economic Growth in China: A Time Series Analysis” 8. https://www.imarcgroup.com/farm-agricultural-equipments-industry-india 9. https://community.data.gov.in/fdi-equity-inflows-in-agricultural-machinery-sector-from-2000-01-to-2016-17/ 10. https://www.ripublication.com/gjfm16/gjfmv8n2_02.pdf 11. https://pib.gov.in/newsite/PrintRelease.aspx?relid=191212 12. https://business.mapsofindia.com/fdi-india/sectors/agriculture-services.html 13. https://www.indianmirror.com/indian-industries/agricultural.html 14. https://www.imarcgroup.com/farm-agricultural-equipments-industry-india 15. https://www.google.com/search?q=factors+and+challenges+in+the+Indian+agricultural+equipments+market&rlz=1C1CHZL_enI N779IN779&oq=factors+and+challenges+in+the+Indian+agricultural+equipments+market&aqs=chrome..69i57.3303j0j8&sourc eid=chrome&ie=UTF-8 16. https://shodhganga.inflibnet.ac.in/bitstream/10603/96165/6/06_chapter1.pdf 17. https://www.quora.com/What-are-competition-issues-in-the-agricultural-sector-in-India 18. https://www.thehindubusinessline.com/economy/foreign-direct-investment-up-28-in-april-june-2019/article29340468.ece Authors: S. Josephin Arulmozhi, K. Praveenkumar, G. Vinayagamoorthi

Paper Title: Medical Tourism in India Abstract: In the recent era medical tourism has certain significance place in the tourism industry, In India now famous for low cost medical service with high quality medical treatment. The countries where medical tourism is being actively promoted include Greece, South Africa, Jordan, India, Malaysia, Philippines and Singapore. Recently, Indian healthcare sector shows huge advancements in fields such as technology, infrastructure, and manpower, catapulting India as one of the preferred medical destinations in the world and invariably paving path to an entirely new sector, the medical tourism industry. The medical tourism in India will 118. touch the $8 billion mark by the end of 2020, the influx of the population that experiences a saving of close to 50 to 70 percent on medical tourism industry. Cost effectiveness is a major factor in India, because a patient can undergo any type of treatment at an extremely affordable cost without compromising the quality and other 695-698 reason is of course the availability of medical visa without any hassle. The Indian government predicts that, India $17-billion-a-year healthcare industry could grow 13 per cent in each of the next six years, boosted by medical tourism, which industry watchers say is growing at 30 per cent annually. This study has been focused by the fully by secondary data, which are collected from the Indian tourism department, and also it analyze the growth percentage in Past years, it will be more helpful to medical service providers. Mainly this study’s objective was examining the foreign exchange earning option through medical tourism and analysis of annual growth of foreign tourist in India. It proves that the annual growth an efficiency of handling capacity of Indian medical the medical industry.

Keyword: Foreign direct investment (FDI), Global value chain (GVC), Supply chain, Industrialists, Indian economy. References: 1. Wan Normila Mohamada (2012) “The Moderating Effect of Medical Travel Facilitators in Medical Tourism” Science Direct Procedia - Social and Behavioral Sciences Volume 65, 3 December 2012, Pages 358-363 2. NTK Naik and B. Suresh Lal (2013) “Economic Analysis Of Indian Medical Tourism(International Healthcare Destination)” IJBMEIT Vol.5,No.2,Julu-December 2013: 259-277 3. K.R.Shanmugam (2013) “Medical tourism in India: Progress, opportunities and challenges” MONOGRAPH 26/2013 MADRAS SCHOOL OF ECONOMICS Gandhi Mandapam Road Chennai 600 025 India March 2013 4. Anu Rail (2014) “Forecasting the Demand for Medical Tourism in India” IOSR Journal Of Humanities And Social Science (IOSR-JHSS) Volume 19, Issue 11, Ver. I (Nov. 2014), PP 22-30 e-ISSN: 2279-0837, p-ISSN: 2279-0845. 5. Binoy TA (2017) “Dynamics of medical tourism in India-A microscopic analysis” Asia Pacific Journal of Research Vol: I. Issue LVIII, December 2017 Authors: A. Muthusamy, G. Kalpana

Paper Title: The Influence of FDI with GDP its Impact of FDI in Civil Aviation Sector in India Abstract: The Civil Aviation Sector in India includes Airports, Scheduled and Non-Scheduled, Domestic Passenger Airlines Helicopter Services, Ground Handling Services, Maintenance and Repair Organizations, Flying Training Institutes and Technical Training Institutions. The government has issued the National Civil Aviation Policy on 2016. The Civil Aviation Sector currently contributes $72 billion to Gross Domestic Product. The National Civil Aviation Policy covers the policy areas such as Regional Connectivity, Safety, Air Transport Operation, 5/20 requirement for International Operations, Bilateral Traffic Rights, Fiscal Support, Maintenance, Repair and Overhaul, Air Cargo, Aeronautical ‘Make In India’. The Central Government announces that the foreign airlines now will be allowed to invest in domestic airlines up to 49 percent. The researcher has to study the impact of FDI Inflows in Aviation Sector in India and Annual Growth Rate of FDI Inflows in Aviation Sector in India. FDI is necessary for all stakeholders and partners to work together to maximize the benefits of air transport, and to support the sustainable growth of aviation by connecting more people and more places. 119. Aviation has continued to expand. It has weathered crises and confirmed long-term resilience, becoming a crucial means of transport. Historically, air transport has doubled in size every 15 years and has grown earlier 699-704 than most other industries. The researcher has used Statistical Tools such as, Trend Analysis, Descriptive Analysis, and Regression. The present study covers period of ten years taking from 2009-10 to 2018-19. The research paper concludes the positive growth and positive impact of FDI in Aviation Sector.

Keyword: FDI,. References: 1. Veena Tewari Nandi, (2013) FDI in Aviation: Retrospection in the Indian Economy, Business and Information 2013, Bali, July 7- 9 2. Syed Azhar & K.N. Marimuthu, (2018), An overview of Foreign Direct Investment in India, International Journal of Multidisciplinary management studies, Vol, 2, Issue 1, January 2012, ISSN: 22498834 3. Anil Duggal, (2017), Foreign Direct Investment in India, Journal of Internet Banking and Commerce, December 2017, Vol: 22, No: 3. 4. Computed from Department for Promotion of Industry and Internal Trade: Date: July 2019 5. The World Bank Data, Date: July 2019 Authors: Tran Ngoc Tu , Nguyen Thi Hai Ha, Do Duc Luu

Paper Title: Prediction of Ship Motions and Added Resistance in Head Waves Base on Linera Strip Theory Abstract: Prediction of ship motions and added resistance is an importance step in the ship design phases and considerable researches are related to this subject. It plays a unique role in main seakeeping characteristics such as maximum ship speed in sea waves, voluntary and involuntary speed reduction due to wave forces and added resistance as well as ship safety and ship routing, which affect transportation time, fuel consumption and total cost. The effects of environmental condition on calculation results is analyzed by performing some calculation with different wave parameter of JONSWAP spectra. The calculation results for the DTMB vessel are examined by the comparisons with experimental data carried out at Ship Design and Research Centre's towing tank in Poland, and show good agreement, which demonstrates the ability of the present method to assess 120. seakeeping characteristics at the initial ship design phases. The calculation is performed by using the commercial software MAXSURF. 705-709 Keyword: ship motion, Strip theory, added ship resistance, pitch motion, heave motion. References: 1. G. O. Young, “Synthetic structure of industrial plastics (Book style with 1. Newman, J.N. Panel methods in marine hydrodynamics. in Proc. Conf. Eleventh Australasian Fluid Mechanics-1992. 1992. 2. Kring, D.C., Time domain ship motions by a three-dimensional Rankine panel method. 1994, Massachusetts Institute of Technology. 3. Kim, K.-H. and Y. Kim, Numerical study on added resistance of ships by using a time-domain Rankine panel method. Ocean Engineering, 2011. 38(13): p.1357-1367. 4. Journée, J., Quick strip theory calculations in ship design. Newcastle upon Tyne: sn, 1992. 5. BASO, S., et al., New Strip Theory Approach to Ship Motions Prediction. 6. Journée, J.M. and W. Massie, Offshore hydrodynamics. Delft University of Technology, 2001. 4: p. 38. 7. MAXSURF Motions Program & User Manual, Bentley Systems, Incorporated, 2016. 8. MAXSURF Motions Program & User Manual 2016 Bentley Systems, Incorporated. 9. Chrismianto, D. and D.-J. Kim, Parametric bulbous bow design using the cubic Bezier curve and curve-plane intersection method for the minimization of ship resistance in CFD. Journal of Marine Science and Technology, 2014. 19(4): p. 479-492. 10. Seakeeping test report for DTMB vessel. CTO, Poland 2017. 11. Naderi R. Solving a nonlinear Singular Cauchy Problem of Euler- Poisson-Darboux Equation through Homotopy Perturbation Method. Medbiotech Journal. 2019;03(02):29-34. 12. Mirabbasi, D., parvin, M., & javid, H. (2015). A Comparison of Several Approaches to Load Frequency Control of Multi Area Hydro-Thermal System. UCT Journal of Research in Science, Engineering and Technology, 3(4), 24-30. 13. Mnunguli, J. P., & Kisangiri, M. (2018). Evidence based Practices for Drug Abuse Information Management and Awareness Approaches. Journal of Information Systems Engineering & Management, 3(4), 31. 14. Osman, S., Che Yang, C. N. A., Abu, M. S., Ismail, N., Jambari, H., & Kumar, J. A. (2018). Enhancing Students’ Mathematical Problem-Solving Skills through Bar Model Visualisation Technique. International Electronic Journal of Mathematics Education, 13(3), 273-279. https://doi.org/10.12973/iejme/3919 Authors: Gamal H. El Saeed , Neveen B. Abdelmageed , Peter Riad, M. Komy The Rates of Changining Confined Aquifer Hydraulic Parmeters under Dynamic Conditions, Area Paper Title: Three in Darb El Arbeain, South Western Desert, Egypt Abstract: Darb El-Arbeain area lies between long. 29o 00/ and 31o 00/ E and lat. 22o 00/ and 24o 30/ N. In this study the changing rates of the hydraulic parameters are investigated through different pumping rates using the three dimensional finite difference flow model (MODFLOW 2005) to simulate the flow system. The initial aquifer hydraulic parameters are; The average hydraulic gradient is 0.00259, the initial transmissivity value is 1075 m2/day, average hydraulic conductivity is 6.5 M/ day, and average flow rate in the aquifer =0.01683 m/day. Under different pumping rates a general trend is introduced to the rates of changing different hydraulic parameters, and the governing equations.

Keyword: Darb El-Arbeain, hydraulic parameters, hydraulic conductivity. References: 1. Ahmed Hassan, Gamal Elsaeed, Mohamed Nagaty, Eman Abdelghani. (2015). Groundwater Flow Modelling in A Nubian Sandstone Aquifer, South Western Desert, Egypt. 2. Abdel-Lattif. A.and Mohamed El Kashouty. (2009). Statical investigation of the groundwater system in Darb El Arbeain, south western desert, Egypt. 3. A.M. S Gejam P. H.S. Riad, M.A. Gad, K.A. Rashed and N.A. Hasan. (2016). impact of Pumping Rate on Seawater Intrusion in Jefara Plain, Libya. 4. Ambroggi, R. (1966). Water under the Sahara: Scientific American, v 214, no 5. 5. Rocha, T., Martins, J., Branco, F., and Gonçalves, R. (2017). Evaluating Youtube Platform Usability by People with Intellectual 121. Disabilities (A User Experience Case Study Performed in a Six-Month Period). Journal of Information Systems Engineering & Management, 2(1), 5. https://doi.org/10.20897/jisem.201705 6. Continental Oil Company (CONOCO, 1989). Geologic map of Egypt, scale 1; 50000. 710-715 7. Development and Application of a Groundwater/ Surface-Water Flow Model using MODFLOW-NWT for the Upper Fox River Basin, South eastern Wisconsin. (2012). 8. Karimova, B., Ongarbayeva, A., Sebepova, R., Aubakirova, A., & Mirzabekova, M. (2018). Synergetic approach in trilingua education of the Republic of Kazakhstan. Opción, 34(85), 327-343. 9. El Gammal, N. 2004. Hydrogeological studies in Darb ElArbaein area, south Egypt. Master science, Geology Department, Cairo university. 10. El Kashouty, M. A. & Abdel-Lattif A. (2010) Groundwater management in the Darb El Arbaein, South western desert, Egypt. International Journal of Water Resources and Environmental Engineering Vol.1 (5). 11. Mardani, M., Lavasani, S. M., & Omidvari, M. (2014). An investigation into DOW and MOND indices with fuzzy logic based on fire and explosion risk assessment in Iran oil refinery, UCT Journal of Research in Science, Engineering and Technology, 2(3): 126-137. 12. El Sabri, M. & Shedid A. (2014) Impact of Wells’s Design on Their Productivity in Selected Areas in the Western Desert, Egypt. Egy. J. Pure & Appl. Sci. (2014); 52(1):37-46. 13. Fathy, R., El Nagaty, M., Atef, A. and El Gammal, N. (2002).Contribution of the hydrogeological and hydrochemical charateteristics of Nubian sandstone aquifer in Darb ElArbaein, south western Desert, Egypt. Al Azhar Bull Sciv13 no2; 69-100. 14. General Survey of Egypt (EGMSA), (1987). Geophysical investigation of the Egyptians transitional sandstone project; Report to groundwater research Institute, Egypt. 15. German Water Group, (1977), Hydrogeological study of groundwater resources in the Kufra area: German Water Engineering, GB, Vol. 5. 16. Journal of American Science (2013); 9 (6). 17. Twentieth International Water Technology Conference, IWTC20 Hurghada, 18-20 May (2017). 18. Issawi, B., (1971), Geology of Darb EL- Arbian, Western Desert, Egypt: Ann. G.S.E., Cairo. 19. International Journal of Geosciences Vol.3 No.5(2012), Article ID:24988,13 pages. 20. Sustainable Groundwater Management Policy Directives June (2016), Mexico City, Mexico. Authors: Morteza Yavari, Fazlollah Karimi Ghotbabadi, Mohammad Rezaei afkham Examining and Organizing the Spatial Development Pattern of Shiraz City using Shannon Entropy Paper Title: and Heldren Models Abstract: Today, physical growth and spatial development without urban plans are inevitable due to population growth and increasing migration, which in some cities has caused the city sprawl and disrupt the city 122. and degrade its environment. Therefore, it recognizes the spatial and physical development of the city as well as presents a pattern It is considered as one of the most important issues facing urban planners for the future of metropolitan cities, in order to guide it towards sustainable urban development. A model that identifies the 716-721 directions of physical extension of the city, land use, physical form, and spatial distribution of activities in order to minimize damage to agricultural and environmental land around the city. Shiraz city has experienced five different structure along its life.the existence of different structures in Shiraz caused the observation of multiple patterns of development in it. Accordingly, the purpose of this research is to identify, analyze and organize the spatial development pattern of the city of Shiraz. The research methodology is applied based on its nature, descriptive-analytical, and in terms of its purpose. The data and information needed to conduct the research was collected through library studies and field operations, and then the obtained data were analyzed based on Shannon and Heldren entropy models. Surveying the results of this work shows that in the period of 1385-95, 59% of its growth has been due to population growth and the remaining 41%, due to horizontal and sprawl growth, which has resulted in decrease in grass population concentration and increase in gross capitation of town land. So, in order to prevent inefficient use of urban lands and reduce the costs of creating infrastructure and facilities and urban amenities and achieving sustainable urban development, the proposed model for physical development of the city of Shiraz is a compact city model, which, given the existing capacities and potentials, It can be used in the city.

Keyword: physical development, urban growth pattern, Shannon entropy, Heldren model, Shiraz. References: 1. Abdollahzadeh Fard, AS (2004). Investigating the Directions and Factors Affecting the Physical Development of Shiraz during 1921-2003 and Modeling the Development Paths to Horizon 2021 Using Geographic Information System, Master of Urban Planning. Shiraz university. Page 149. 2. Anselin, L. (1995). space stat version 1.80 users; Guide, university of Illinois, urbanachampaign, II. 3. Athari, K. (2000). "Towards the Effectiveness of Government Interference in the Urban Land Market". Journal of Housing Economics. 30 (4): 41-34. 4. Audirac, I. shermyen A.H, smith M.T. (1990). Ideal urban from and visions of the good life, Journal of American planning Association, 56(2): 470- 480 5. Beck, Roy kolankiewiez, Leon & camarota, steven A,(2003),outsmarting smart grow th,populationgrowth, Immigration, and the problem of sprawl growth,Imigration studies,washington 6. cheng, J. (2003). Modelling spatial and Temporal urban growth, UPLA, Enschede, N1, ITC:203 7. Ebrahim Zadeh Asmin, h. Ebrahimzadeh, A. and Habibi, M. (2010). "An Analysis of the Physical Extension and Spiral Growth Factors of Tabas City after the Earthquake Using the Heldren Entropy Model". Journal of Geography and Development. 19 (4): 46-25. 8. Ebrahimzadeh, AS and Rafiei, Q (2009). "An Analysis of the Physical-Spatial Pattern of Marvdasht City Using Shannon and Heldren Entropy Models and Presenting the Desirable Future Extension Pattern". Journal of Human Geography Research. 69 (2): 138-123. 9. ghadami MH and Yusefiani P. (2014). An Analysis of Spatial Structure Changes in Esfahan City by Avoiding Air Pollution. Urban Planning Studies Quarterly. 10. Habibi K. Behzadfari M. Meshkinini A. Alizadeh AH and Mottaki. (2011). Assessing the Impacts of Urban Development on the Destruction and Quality Improvement of the Space of the Old Iranian City Iranian-Islamic Studies Quarterly. 11. Hekmatya, H, and Mousavi, m. (2006). Model application in geography with emphasis on urban and regional planning. first volume. Modern Science Publications. Page 372. 12. Hess,G.R. (2001). Just what is sprawl Anyway? www4.ncsu.Edu/~grhess 13. Iran Statistical Center, Results of the General Census of Housing Population of Fars Province, 1986-2016. 14. johanson, E.A.J. (1998). the organization of spage in development press,countries. Cambridge, Harvard university. 15. Majedi, h. (1999). "Land is the main issue of urban development". Abadi Journal. 33 (2): 14-3 16. merlin,p. (2000). methods Quantitative and spase urban publisher, university of paris. 17. Mirbagheri, B and Mutkan, AS. (2009). "Quantitative Assessment of Urban Land Development Concentration Using Ripley, s K Function in GIS (Case Study: Islamshahr, Robat Karim and Nasimshahr)". Geographical Research, 69 (2): 66-51. 18. Mohammadzadeh, R. (2007). "Environmental Impact Assessment of Accelerated Physical Development of Cities with Emphasis on Tehran and Tabriz Cities". Journal of Geography and Regional Development. 9 (2): 112-93. 19. Naghsh e Jahan Pars Consulting Engineers. (1989). Justification Report of Shiraz Civil Development Plan. 20. Pour Mohammadi, M. Jamali, F and Asghari Zamani, A. (2008). "Evaluation of Spatial-Physical Spatial Development of Zanjan with Emphasis on Zanjan Urban Land Use Change". Journal of Geographical Research. 63 (1): 46-29. 21. Shahr o khane consulting engineers. (2007). Overview of Shiraz Detailed Plan. first volume. 22. wu,f. (2000).A parameter isedd urban cellular model combining spontaneous and self organising growth, Geocomputation: Innovation in GIS 7. p.A.A.D. Martin london, Taylor & francis. london 24(2): pp. 73-85. Authors: R. Vijayalakshmi, V. Palanisingh, G. Lingavel, T. R. Gurumoorthy

Paper Title: Factors Determining in Foreign Direct Investment (FDI) in India Abstract: Foreign direct investment (FDI) has become an integral part of national development strategies for almost all the nations globally. The study global popularity and positive output in augmenting of domestic capital, productivity and employment; has made it an indispensable tool for initiating economic growth for countries. The FDI in India has contributed effectively to the overall growth of the economy in the recent times. The government adopted a New Economic Policy which promoted the policy of LPG (Liberalization, Privatization and Globalization). This has resulted in promoting more foreign direct investment into the country. The purpose of this study is to investigate the factors determining the foreign direct investment in India. This study also examines foreign direct investment in India. The main objectives of the study factors determining in 123. foreign direct investment in India. The data mainly based on secondary data. The collected data were analysed by using trend analysis and growth rate of top ten sectors in India. This study also found that FDI in India has 722-729 contributed effectively to the overall growth of the economy in the recent times. Thus, India can grow without FDI and in fact developed without or with very little FDI. Developing countries like India need substantial foreign inflows to achieve the required investment to accelerate economic growth and development.

Keyword: Foreign Direct Investment, Economic Growth, Foreign Direct Investment Sectors, Economic Policy, Developing Countries. References: 1. https://www.mbarendezvous.com/general-awareness/why-fdi-is-needed-in-india/ 2. http://www.studiofynn.com/journal/points-view-fdi-emerging-markets. 3. Otuo Serebour & Christopher Gbettey et.al (2019) “Country-level corporate governance and Foreign Direct Investment in Africa”, Corporate Governance: The International Journal of Business in Society, ISSN: 1472-0701, DOI: https://doi.org/10.1108/CG-07-2018-0259. 4. Justice Gameli Djokoto & Francis Yao Srofenyoh et.al (2014) in her study entitled “Domestic and foreign direct investment in Ghanaian agriculture”, Agricultural Finance Review, Vol. 74 No. 3, pp. 427-440, https://doi.org/10.1108/AFR-09-2013-0035. 5. Laura Alfaro (2017). 'Multinational Activity in Emerging Markets: How and When Does Foreign Direct Investment Promote Growth?', Geography, Location, and Strategy (Advances in Strategic Management, Volume 36. Emerald Publishing Limited, pp. 429-462. DOI: https://doi.org/10.1108/S0742-332220170000036012. 6. Steven Globerman (2017) "A new era for foreign direct investment?", Multinational Business Review, Vol. 25 No. 1, pp. 5-10, DOI: https://doi.org/10.1108/MBR-12-2016-0047. 7. Michael Asiamah, Daniel Ofori and Jacob Afful (2019) "Analysis of the determinants of foreign direct investment in Ghana", Journal of Asian Business and Economic Studies, Vol. 26 No. 1, pp. 56-75, DOI : https://doi.org/10.1108/JABES-08-2018-0057. 8. http://www. ministry of commerce & industry. 9. Sapna Hooda (2011) “A Study of FDI and Indian Economy”. Authors: V. Sureshbabu, R. Vinitha

Paper Title: FDI and Make in India Abstract: Foreign Direct Investment (FDI) is viewed as a source of economic development, modernization, employment, and income growth for emerging economies like India. It acts as a significant catalyst and as the lifeblood of economic development by way of up-gradation of technology, managerial skills, capabilities, etc., The main advantage of FDI is that it supplements the available domestic capital without adding to the national debt. A steady and continuous inflow of foreign investments helps in boosting our Balance of Payments situations and strengthening the value of Indian currency against global currencies. India has liberalized its FDI regimes and pursued several other policies to make India an attractive destination for FDI. Government of India has taken strenuous efforts and initiatives in recent years like dispensing the need of getting approvals at various stages from the Government /other regulatory bodies and relaxing FDI norms across various sectors such as Defence, Public Sector Undertaking Oil refineries, Telecom sector, Stock exchanges, etc., Major initiative in this regard is the "Make in India" launched by the Prime Minister Shri. Narendra Modi in September 2014. Make in India is a powerful, galvanizing call and an invitation to potential investors around the world to transform India into a global design and manufacturing hub. Tackling the problems of unemployment by creation of new jobs, advancement of employability skills and fostering innovation are the major objectives of this initiative. Series of reforms launched by the Government of India to liberalize its foreign investment norms has enabled our country to be one of the world’s fastest-growing economies and a top market for foreign direct investments globally. This paper attempts to analyze the FDI in various sectors and the impact of Make in India scheme on FDI. 124.

Keyword: FDI, Economic Development, Make in India, Manufacturing hub. 730-733 References: 1. https://www.ibef.org/economy/foreign-direct-investment.aspx 2. https://www.ibef.org/pages/37752 3. http://www.makeinindia.com/documents/10281/0/Consolidated+FDI+Policy+2017.pdf 4. https://www.toppr.com/guides/commercial-knowledge/government-policies-for-business-growth/fdi-in-india/ 5. https://dipp.gov.in/sites/default/files/ru497_0.pdf 6. https://www.rbi.org.in/scripts/bs_viewcontent.aspx?Id=2513 7. https://factly.in/in-the-last-19-years-more-than-50-of-the-fdi-was-routed-through-mauritius-singapore/ 8. https://nexia.com/insights/global-insight/make-in-india-campaign-boosts-fdi-inflows/ 9. http://pib.nic.in/newsite/PrintRelease.aspx?relid=138079 10. https://www.opindia.com/2019/04/how-make-in-india-initiative-is-accelerating-fdi-investment-in-india-and-helping-india- emerge-as-the-fastest-growing-economy/ 11. https://www.businesstoday.in/current/corporate/fdi-flows-to-india-grew-6-in-2018-to-42-billion-world-investment-report- 2019/story/355635.html 12. https://www.moneycontrol.com/news/business/economy/budget-2019-govt-proposes-fdi-norm-relaxation-in-media-aviation- insurance-single-brand-retail-4173261.html 13. https://www.investindia.gov.in/why-india 14. https://www.investindia.gov.in/foreign-direct-investment 15. http://madaan.com/fdiapprovals.html 16. https://economictimes.indiatimes.com/news/economy/finance/india-received-highest-ever-fdi-worth-usd-64-37-billion-in- fy19/articleshow/70454327.cms 17. https://www.ijsr.net/archive/v6i3/ART20171742.pdf 18. http://www.indianjournals.com/ijor.aspx?target=ijor:zijmr&volume=8&issue=9&article=039 Authors: S.R. Bakasov, A.E. Prorokov, Yu.N. Matveev, V.N. Bogatikov, B.V. Palux

Paper Title: Technological Safety and the Production System Abstract: Implementation of disease detection systems and technology safety management in the states is intended. The technique of defining the security center based on the linear programming problem solving and 125. two-level system decision-making on technology safety assurance is presented. In the first level the safety center is defined, in the second level the process stability problem in the field of safe operation is solved. 734-736

Keyword: state assessment, safety of technologies, area of safety, center of safety, linear programming, preparation and decision-making. References: 1. Bogatikov V.N. Construction of discrete models of chemical-technological systems. Theory and Practice / Bogatikov V.N, Palyukh B.V. // Apatity: ed. Kola Science Center, 1995. - 164 p. 2. Alekseev V.V. Applications of the method of separation of states to management of technological safety on the basis of the safety index / Alekseev V.V., Bogatikov V.N., Palyukh B.V., Prorokov A.E. // - Tver: TSTU, 2009. - 368 p. 3. Zade L. The concept of a linguistic variable and its application to the adoption of approximate solutions .- M .: World, 1976.-167 p. 4. Melikhov A. N. The situation-dependent advising systems with a fuzzy logic / Melikhov A. N., Bernstein L. S., Korovin S.Ya.//M.: Science, 1990. – 272 pages. 5. 5.An Alternative Approach for Solving Bi-Level Programming Problems 6. Rashmi Birla, Vijay K. Agarwal, Idrees A. Khan, Vishnu Narayan Mishra 7. American Journal of Operations Research Vol.7 No.3. Full-Text HTML XML Pub. Date: May 27, 2017 8. Akimzhanov, T., Suleymenova, S., Altynbekkyzy, A., Zinkevich, T., Edressov, S., & Dosanova, M. (2018). Ensuring the principle of zero tolerance to antisocial manifestations: The important condition of the constitutional state creation. Opción, 34(85), 500-521. 9. 7. Smrcka, L., and Camska, D. (2016). Receivables Management and Possible Use of Information Technologies. Journal of Information Systems Engineering & Management, 1(3), pp. 167-176. https://doi.org/10.20897/lectito.201632 Authors: Raju Sarkar, Abhirup Dikshit, Hemanta Hazarika, Koji Yamada, Krishna Subba

Paper Title: Probabilistic Rainfall Thresholds for Landslide Occurrences in Bhutan Abstract: Several works have been conducted all across the globe determining rainfall thresholds in context of intensity-duration thresholds. Such results provide results in terms of occurrence or non-occurrence of landslides. This paper determines probabilities for various rainfall parameters causing landslides using a Bayesian approach along Phuentsholing Thimphu Highway in Chukha Dzongkhag of Bhutan. For Bhutan Himalayas, probabilistic rainfall thresholds for landslide initiation has not yet been attempted. The probabilities determined can be used for early warning systems considering it is a major trade route with India.

Keyword: Probabilistic Thresholds, Chukha Dzongkhag, Bhutan. References: 1. Abdulhameed, A. A., Al-Hamdi, K. E., & Mathkoor, M. A. (2018). Clinical Evaluation of Efficacy and Safety of Combined Topical Timolol and Oral Propranolol in Children with Infantile Hemangioma. Journal of Clinical and Experimental Investigations, 9(1), 1-8. 2. Aleotti, P. 2004. “A warning system for rainfall-induced shallow failures”. Eng Geol 73:247–265. 3. Baum, R.L., W.Z. Savage, J.W. Godt. 2002. “TRIGRS – a FORTRAN program for transient rainfall infiltration and grid-based regional slope stability analysis”, US Geological Survey Open-File Report 2002-424. 4. Berti, M., M. L. V. Martina, S. Franceschini, S. Pignone, A. Simoni, M. Pizziolo. 2012. “Probabilistic rainfall thresholds for 126. landslide occurrence using a Bayesian approach”. J. Geophys. Res. 117: F04006. doi:10.1029/2012JF002367. 5. Caine, N. 1980. “The rainfall intensity–duration control of shallow landslides and debris flows”. Geogr Ann A 62: 23–27. 6. Cannon, S.H., and J.E. Gartner. 2005. “Wildfire-related debris flow from a hazards perspective”. In: Debris flow hazards and 737-742 related phenomena, edited by Jakob M., and Hungr O, 363-385. Berlin: Springer. 7. Capparelli, G., and P. Versace. 2011. “FLaIR and SUSHI: two mathematical models for early warning of landslides induced by rainfall”. Landslides 8: 67. doi: 10.1007/s10346-010-0228-6. 8. Chen, H.X., and L.M. Zhang. 2014. “A physically-based distributed cell model for predicting regional rainfall-induced shallow slope failures”. Engineering Geology 8: 67-79. doi: 10.1016/j.enggeo.2014.04.011. 9. Crosta, G.B., and P. Frattini. 2001. “Rainfall thresholds for triggering soil slips and debris flow”. In Mediterranean storms, edited by Mugnai A., Guzzetti F., Roth G. Siena, 463-487. Proc. of the 2nd EGS Plinius Conf. on Mediterranean Storms. Siena, Italy. 10. De Luca, D.L., and P. Versace. 2017. “A comprehensive framework for empirical modeling of landslides induced by rainfall: The Generalized FLaIR Model (GFM)”. Landslides 14: 1009. doi: 10.1007/s10346-016-0768-5. 11. Dikshit, A., and D.N. Satyam. 2018. “Estimation of rainfall thresholds for landslide occurrences in Kalimpong, India”. Innov. Infrastruct. Solut 3: 24. doi: 10.1007/s41062-018-0132-9. 12. Dikshit, A., and N. Satyam. 2017. “Rainfall Thresholds for Landslide Occurrence in Kalimpong using Bayesian Approach” Indian Geotechnical Conference. 13. Do, H., and K. Yin. 2018. “Rainfall Threshold Analysis and Bayesian Probability Method for Landslide Initiation Based on Landslides and Rainfall Events in the Past”. Open Journal of Geology 8: 674-696. doi: 10.4236/ojg.2018.87040. 14. Dunning, S.A., N.J. Rosser, D.N. Petley, C.R. Massey. 2006. “Formation and failure of the Tsatichhu landslide dam, Bhutan”. Landslides 3: 107. doi:10.1007/s10346-005-0032-x. 15. Dunning, S., C. Massey, N. Rosser. 2009. “Structural and geomorphological features of landslides in the Bhutan Himalaya derived from terrestrial laser scanning”. Geomorphology 103:17-29. 16. Gansser, A. 1983. Geology of the Bhutan Himalaya. Basel, Switzerland: Birkhaüser Verlag. 17. González, A., and E. Caetano. 2017. “Probabilistic Rainfall Thresholds for Landslide Episodes in the Sierra Norte De Puebla, Mexico”. Natural Resources 8: 254-267. doi: 10.4236/nr.2017.83014 Authors: Krishnaveer Singh, Aruna Dhamija Macroeconomic Factors as a Predictor of Stock Market: Empirical Evidences from India, U.S. and Paper Title: U.K. Abstract: The study investigated the impact of Macroeconomic variables such as: Gross Domestic Product (GDP), The Index of Industrial Production (IIP), Consumer Price Index (CPI), Foreign-exchange reserves (also called forex reserves or FX reserves), International Crude Price (CP) on selected stock market, namely Indian 127. Stock Market (S&P BSE SENSEX (BSE 30) index, S&P CNX Nifty index (NIFTY 50), London Stock Exchange (Financial Times Stock Exchange 100 Index (FTSE 100) and New York Stock Exchange Dow Jones Industrial Average (Dow 30). The data sets of all variables have been considered from April, 2001 to March, 743-751 2018 on a monthly basis. The study reveals long run relationship among the variables and the results of Granger Causality test reveals unidirectional, bilateral relation (Feedback) and exogeneity (Independence) among the variables.

Keyword: FDI, RBI. References: 1. Mehrara, M. (n.d.). The Relationship between Stock Market and Macroeconomic Variables: a Case Study for Iran. Iranian Economic Review, Vol.10. No.17, Fall 2006, 138-148. 2. Anayochukwu,O.B.TheImpact of Stock Market Returns on Foreign Portfolio Investment in Nigeria.Journal of Business and Management(IOSRJBM),2(4),10-19 3. Asai, M.and Shiba,T.(1995)‘The Japanese stock market and the macro economy: an empirical investigation’, Financial Engineering and the Japanese market, Vol. 2 pp259-267. 4. Ahuja, H. L. (n.d.). Macroeconomics: theory and policy (17th Rev. ed.). New Delhi, India: S. Chand and Company Ltd. 5. Mishra, C. (n.d.). mpact of Macro Economic Variables on the Stock Price Index: An Empirical Study on Indian Stock Market after Post Liberalization period. LAP LAMBERT Academic Publishing. 6. Amadi,S.N.,Onyema,J.I.,&Odubo,T.D.(2002).Macroeconomic Variables and Stock Prices.A Multivariate Analysis. Africa Journal of Development Studies, 2(1), 159-164. 7. Dwivedi, D. N. (2007). Macroeconomics Theory and Policy. Tata McGraw-Hill Publishimg Company Limited. 8. OLOWE, R. A. (n.d.). The relationship between stock prices and macroeconomic factors in the Nigerian Stock Market. African review of money finance and banking – 2007. 9. Abugri, B. A. (2008). Empirical Relationship between Macroeconomic Volatility and Stock Return: Evidence from Latin American Markets, International Review of Financial Analysis, 17: 396-410. 10. Ahmed,S.(2008).Aggregate Economic Variables and Stock Market in India,International Research Journal of FinanceandEconomics,14:14-64. 11. Aisyah, A.R., Noor,Z.M.S.,& Fauziah,H.T.(2009). Macroeconomic determinants of Malaysian stock market. African Journal of Business Management,3(3), 095-106. 12. Alam, M.M.,& Uddin,M.G.S.(2009).Relationship between interest rate and stock price: empirical evidence from developed and developing countries. International journal of business and management,4(3), P43. 13. Adjasi,C.K.(2009).Macroeconomic uncertainty and conditional stock-price volatility in frontier African markets: Evidence from Ghana. Journal of Risk Finance,the10(4),333-349. 14. Antonios A.(2010)‘Stock market and economic growth: an empirical analysis for Germany’, Business and Economics Journal, Vol. 2010: BEJ-1. 15. Ali,I.,Rehman,K.U.,Yilmaz,A.K.,Khan,M.A.,&Afzal,H.(2010).Causal relationship between macro-economic indicators and stock exchange prices in Pakistan. African Journal of BusinessManagement,4(3), 312-319. 16. Asaolu,T.O.,& Ogunmuyiwa,M.S.(2011).An Econometric Analysis of the Impact of Macroeconomic Variables on Stock Market Movement in Nigeria.Asian Journal of BusinessManagement,3(1). 17. Adaramola, A.O.(2011).The Impact of Macroeconomic Indicators on Stock Prices in Nigeria. DevelopingCountryStudies,1(2),1- 14 18. Aduda,J.,Masila,J.M.,&Onsongo,E.N.(2012).The Determinants of Stock Market Development: The Case for the Nairobi Stock Exchange. International Journal of Humanities and SocialScience,2(9),2221-0989. 19. Asma,A.R.,Naseem,M.A.,Sultana,N.(2013)Impact of Macroeconomic Variables on Stock Market Index (ACase of Pakistan) www.elixirpublishers.com International journal. Fin. Mgmt. 57(2013) 14104 20. Alam,N.(2013).Macroeconomic Variables ,Firm Characteristics and Stock Returns during Good and Bad Times: Evidence from SEA .Asian Journal of Finance&Accounting,5(2), 159-182. 21. Abdullah,A.M.,Saiti,B.,&Masih,A.M.M.(2014).Causality between Stock Market Index and Macroeconomic Variables: A Case Study for Malaysia. Munich Personal RePEc Archive Paper No.56987.Onlineathttp://mpra.ub.uni-muenchen.de/56987/ 22. Al-Majali,A.A.,&Al-Assaf,G.I.(2014).Long-run and short-run relationship between stock market index and main macroeconomic variables performance in Jordan. EuropeanScientificJournal,10 (10). 23. Banik, N. (2015). The Indian Economy A Macroeconomic Perspective. SAGE Publication India Pvt Ltd. 24. Banik, N. (2015). The Indian Economy A Macroeconomic Perspective. SAGE Publication India Pvt Ltd Authors: Chabi Gupta, Rachna Saxena

Paper Title: Behavioural Finance and Investment Preference in Private Equity Indian Companies Abstract: At first glance, it may be easy to see many deficiencies in the efficient market theory, created in the 1970s by Eugene Fama. Eugene Fama never imagined that his efficient market would be 100% efficient all the time. Of course, it's impossible for the market to attain full efficiency all the time, as it takes time for stock prices to respond to new information released into the investment community. The efficient hypothesis, however, does not give a strict definition of how much time prices need to revert to fair value. Moreover, under an efficient market, random events are entirely acceptable but will always be ironed out as prices revert to the norm. It is important to ask, however, whether EMH undermines itself in its allowance for random occurrences or environmental eventualities. There is no doubt that such eventualities must be considered under market efficiency but, by definition, true efficiency accounts for those factors immediately. In other words, prices should respond nearly instantaneously with the release of new information that can be expected to affect a 128. stock's investment characteristics. So, if the EMH allows for inefficiencies, it may have to admit that absolute market efficiency is impossible 752-757 The study tries to elucidate the very factor that is “Cognitive psychology: the study of how people (including investors) think, reason, and make decisions”. They may not be always rational. Individuals do not always act shrewdly when it comes to making financial decisions and that there are various mental errors that influence them while making decisions. The sample size of the study is 60 employees of private equity companies. The sampling technique used is simple random sampling. Primary data has been used in the study, which was collected through a structured questionnaire based on behavioral finance techniques and investment preference. Various statistical tools were used to analyze the data like Descriptive Statistics, t-Test Statistical Tool, Correlation Tool and Percentage Analysis. The study tried to explain the irrational decisions taken by the investors during the time of taking financial portfolio decisions. Through the study, it is discerned that private equity employees are aware about the various possibilities in investments and it is found that there exist a relationship between behavioral finance and investment preference among employees of private equity companies. Using the principles of behavioral finance and investment preference the study tried to delve the psychological concept of “individual attachment style”, especially with reference to employees of private equity companies and the wide range of investment avenues and their investment preference procedure.

Keyword: Behavioral Finance, Investment Preferences, Cognitive Biases, Individual Decision Making, Rational Investor References: 1. Shleifer, Andrei. 2000. Inefficient Markets: An introduction to Behavioral Finance. New York: Oxford University Press. 2. Sinha, Anand.2012. Changing Contours of Global Crisis – Impact on Indian Economy. < http://rbi.org.in/scripts/BS_SpeechesView.aspx?Id=678> . Retrieved: April 2012 Sons. 3. Selden, G. C., 1965. Psychology of the Stock Market 4. Shefrin, Hersh (Editor), 2001. Behavioral Finance 5. Shefrin, Hersh, 2000. Beyond Greed and Fear : Understanding Behavioral Finance and the Psychology of Investing. 6. Shiller, Robert J., 2000, 2006. Irrational Exuberance. 7. Nofsinger, John R., 2001. Investment Madness : How Psychology Affects Your Investing--and What to Do About It, 8. Nofsinger, John R.2001. Investment madness: how psychology affects your investing – and what to do about it. USA: Pearson Education 9. Nunnally, C. J. 1976. Psychometric Theory, New York: McGraw Hill. 10. O’Hagan, Anthony.,Buck, Caitlin E., Daneshkhah, Alireza., Eiser, J Richard.,Garthwaithe, Paul H., Jenkinson, David J,. Oakley, Jeremy E., and Rakow, Tim.2006.Uncertain Judgements: Eliciting Experts’ Probabilities. USA: John Wiley & Sons. 11. Odean, Terrance. 1998. Volume, Volatility, Price, and Profit When All Traders Are Above Average. The Journal of Finance 53(6) : 1887 – 1934 12. Oeberst, A.; Goeckenjan, I. (2016). "When being wise after the event results in injustice: Evidence for hindsight bias in judges' negligence assessments". Psychology, Public Policy, And Law. 22 (3): 271–279. doi:10.1037/law0000091 13. Oehler, Andreas., Rummer, Marco., and Wendt, Stefan. 2008. Portfolio Selection of German Investors: On the Causes of Home- biased Investment Decisions. The Journal of Behavioral Finance 9: 149 – 162. 14. Parikh, Parag. 2011. Value Investing and Behavioral Finance. New Delhi : Tata Mcgraw Hill. 15. Payne, J. W., 1976, Task Complexity and Contingent Processing in Decision Making: An Informational Search and Protocol Analysis, Organizational Behavior and Human Performance 16, 366-387. 16. Payne, J. W., 2005, It is Whether You Win Or Lose: The Importance of the overall Probabilities of Winning Or Losing in Risky Choice, Journal of Risk and Uncertainty 30, 5-19. 17. Payne, J. W., J. R. Bettman, and D. A. Schkade, 1999, Measuring Constructed Preferences: Towards a Building Code, Journal of Risk and Uncertainty 19, 243-270. 18. Payne, J.W., Bettman, J. R. and E. J Johnson, 1992, Behavioral decision research: A constructive processing perspective, Annual Review of Psychology 43, 87–131. 19. Payne, J.W., Bettman, J. R. and E. J. Johnson, 1993, The adaptive decision maker, Cambridge University Press. 20. Liang, H., Yang, C., Zhang, R., & Cai, C. (2017). Bounded rationality, anchoring-and-adjustment sentiment, and asset pricing. The North American Journal of Economics and Finance, 40, 85-102. 21. Baker, H. K., Filbeck, G., & Ricciardi, V. (2017). How Behavioural Biases Affect Finance Professionals. 22. Chang, C. C., Chao, C. H., & Yeh, J. H. (2016). The role of buy-side anchoring bias: Evidence from the real estate market. Pacific-Basin Finance Journal, 38, 34-58. 23. Gupta, Chabi. "Payment Banks and Demonetization", International Journal of Technical Research and Science, IJTRS-V1-I9-002, December 2016 24. Jones, P.and Roelofsma P. (2000) The potential for social contextual and group bias in team decision-making: biases, conditions and psychological mechanisms. Ergonomics, vol. 43, no. 8, pp. 1129-1152. 25. Kahneman, D. and Klein, G. (2010) Strategic decisions: When can you trust your gut? McKinsey Quarterly. http://www.mckinsey.com/insights/strategy/strategic_decisions_when_can_you_trust_your_gut (2013-10-27) Authors: Vikram Sandhu, Heena Atwal

Paper Title: Goods and Services Tax: Issues and Challenges in India Abstract: Number of indirect taxes is under one umbrella which simplifies taxation system for service and commodity businesses. GST can convey various advantages to economy as an indirect tax. The paper focuses on advantages to Indian economy, and various problems, issues and challenges in front of GST. These advantages include effect on GDP ratio, competitive advantages, price and consumption benefits and others. Present GST rates, exempted products from GST, issues and challenges are also discussed in this paper in which some problems such as lack of growth, complexity, filing charges, multiple returns are included.

Keyword: GST, Advantages of GST, GST Rates, problems, Issues and challenges in implementation process of GST.

129. References: 1. Abda, S.(2017)Research paper on effects of goods and services tax on indian economy. International education and research journal, 3(5), 584–585. 758-760 2. B, MitraPriya. (2017). GST- A Game Changer, International Journal of Management Research and Social Science (IJMRSS), vol. 4(1), pp. 10-12. 3. Dani, S., (2016). A Research Paper on an Impact of Goods and Service Tax (GST) on Indian Economy. Business and Economics Journal, Bus Eco J 7: 264. doi: 10.4172/2151-6219.1000264. 4. Kapil Kapoor (2017). GST New Tax Regime: Issues and Challenges. International journal of recent scientific research, vol. 8(4), pp. 16786- 16790. 5. Kawle ,S, P. and Aher, L.,Y.(2017). GST: An economic overview: Challenges and Impact ahead. International Research Journal of Engineering and Technology, Volume: 04 Issue: 04, pp. 2760-2763. 6. Lourdunathan F and Xavier P (2016). A study on implementation of goods and services tax (GST) in India; Prospectus and challenges, International Journal of Applied Research, vol. 3(1), pp. 626-629. 7. Nayyar, A. and Singh, I. (2017). A Comprehensive Analysis of Goods and Services Tax (GST) in India. Indian Journal of Finance, DOI: 10.17010/ijf/2018/v12i2/121377. 8. Rupa, R.(2017).Gst in india: an overview. international education and research journal, https://www.researchgate.net/publication/315331885. 9. Shefali Dani (2016). a RESEARCH PAPER ON AN IMPACT OF GOODS AND SERVICE TAX ON INDIAN ECONOMY. BUSINESS and economics journal, vol. 7 (4). DOI: 10.4172/2151-6219.1000264. 10. Yadav,S., S. and Shankar, R. (2018). "Goods and service tax (GST): how and why", Journal of Advances in Management Research, Vol. 15 Issue: 1, pp.2-3. 11. http://www.gstcouncil.gov.in/ 12. http://www.gstindia.com/ 13. http://www.gstindia.com/basics-of-gst-implementation-in-india/ 14. https://en.wikipedia.org/wiki/Goods_and_Services_Tax_(India) Authors: Sukhaji G. Naik

Paper Title: Domestic and Foreign Tourists Arrivals in Goa: Growth Examiation Abstract: An attempt is made in this paper, to examine growth trend of domestic and foreign tourists arrivals, month wise tourist arrivals, nation wise foreign tourists arrivals, foreign tourists arrivals, foreign tourists arrive by flights and the growth of hotels, no. of rooms and no. of beds. The required data is collected from the reports of tourists statistics, Department of tourism, Govt. of Goa. Further, the data collected for 30 years is divided into two sub periods namely sub period I (1988-89 to 2002-03) and sub period II (2003-04 to 2017-18) and a comparative growth of domestic and foreign tourists arrivals is studied. A chain index statistical tool is employed to compute yearwise growth trend. The study reveals that the foreign tourists recorded more fluctuation in the growth as compared to the growth trend of domestic tourists. Country wise arrivals of tourists 130. shows that Russia has registered the highest tourists arrivals followed by UK and Ukrain. The yearwise growth of tourists arrivals shows a marginal variation during the study period.Keyword: 761-768 References: 1. Datt, Gaurav and Mahajan, Ashwani (2016), Datt and sundharams Indian economy, S. Chand and company Pvt. Ltd, New Delhi 2. Gupta, S C (2014), Fundamentals of statistics, Himalaya publishing house, Mumbai. 3. Kothari, C R and Garg, Gaurav (2014), Research methodology: Methods and techniques, New Age international (P) Ltd. Publishers, New Delhi 4. Bhatt, Harish (2006), Hospitality and tourism management, Crescent Publishing Corporation, New Delhi 5. Bhatia, A K (2009), Tourism development: Principles and Practice, Sterling Publishers Private Ltd, New Delhi 6. Economy Survey Report 2017-18 7. http://www.uou.ac.in/sites/default/files/slm/BTTM-503.pdf 8. Tourist statistics (2002), Department of Tourism, Govt. of Goa, Panaji – Goa Authors: Sukhvinder Singh Bamber Implementation of Improved Synchronization in Inter Process Communication using Threads for Paper Title: Microkernel and Distributed Operating Systems Abstract: Interprocess Communication (IPC) is used by the cooperating processes for communication and synchronization. With the advent of Distributed Systems and Microkernel Operating systems, IPC has been used for designing the system for cooperation. This raised the requirements for improving the communication and synchronization for the better performance of the system. Here, a mechanism of synchronization between the processes to reduce the waiting time of process using POSIX (Portable Operating System Interface) threads has been proposed to perform and synchronize the given task. 131.

Keyword: IPC, Microkernel Operating System, Distributed Operating System, POSIX. 769-771 References: 1. “Advanced Linux Programming”, Mark Mitchell, Jeffrey Oldham and Alex Samel C-5(95). 2. “Operating System Concepts 7th Edition”, Silberchatz, Galvin and Gagne C-3(94). 3. “How to make multiprocessor computer that correctly executes multiprocess programs”, IEEE Transaction on Computers, Lemport, Leslie (Sep, 1979), C-28(9). 4. Thread (Cmputing) – www.wikipedia.org 5. Pthread (Win-32): Level of standard Conformance 2006-12-22, 2010. 6. POSIX_Thread – www.wikipedia.org. Authors: Mallikharjuna Lingam K, VSK Reddy

Paper Title: Retrieval of Video Contents based on Deep Parameter Analysis using Machine Learning Abstract: In the recent past, video content-based communication hasincreases with a significant consumption of space and time complexity.The introduction of the data is exceedingly improved in video information as the video information incorporates visual and sound data. The mix of these two kinds of information for a single data portrayal is exceedingly compelling as the broad media substance can make an 132. ever-increasing number of effects on the human cerebrum. Thus, most of the substance for training or business or restorative area are video-based substances. This development in video information have impacted a 772-779 significant number of the professional to fabricate and populate video content library for their use. Hence, retrieval of the accurate video data is the prime task for all video content management frameworks. A good number of researches are been carried out in the field of video retrieval using various methods. Most of the parallel research outcomes have focused on content retrieval based on object classification for the video frames and further matching the object information with other video contents based on the similar information. This method is highly criticised and continuously improving as the method solely relies on fundamental object detection and classification using the preliminary characteristics. These characteristics are primarily depending on shape or colour or area of the objects and cannot be accurate for detection of similarities. Hence, this work proposes, a novel method for similarity-based retrieval of video contents using deep characteristics. The work majorly focuses on extraction of moving objects, static objects separation, motion vector analysis of the moving objects and the traditional parameters as area from the video contents and further perform matching for retrieval or extraction of the video data. The proposed novel algorithm for content retrieval demonstrates 98% accuracy with 90% reduction in time complexity.

Keyword: Object Separation, Regeneration of regions, moving objects detection, frame of reference stabilization, frame rate calibration References: 1. Ekermo, V. Norell, "Reducing the need for manual cleaning maintenance of digital surveillance cameras—A conceptual study", 2013. 2. Y. M. E. Candes, X. Li, J. Wright, "Robust principal component analysis", J. ACM, vol. 58, no. 3, pp. 11-20, 2011. 3. Lu, J. Feng, Y. Chen, W. Liu, Z. Lin, S. Yan, "Tensor robust principal component analysis: Exact recovery of corrupted low-rank tensors via convex optimization", Proc. IEEE Conf. Comput. Vision Pattern Recognit., pp. 5249-5257, 2016. 4. X. Liu, G. Zhao, J. Yao, C. Qi, "Background subtraction based on low-rank and structured sparse decomposition", IEEE Trans. Image Process., vol. 24, no. 8, pp. 2502-2514, Aug. 2015. 5. X. Zhou, C. Yang, W. Yu, "Moving object detection by detecting contiguous outliers in the low-rank representation", IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 3, pp. 597-610, Mar. 2013. 6. X. Zhang, C. Zhu, S. Wang, Y. Liu, M. Ye, "A Bayesian approach to camouflaged moving object detection", IEEE Trans. Circuits Syst. Video Technol., vol. 27, no. 9, pp. 2001-2013, Sep. 2017. 7. O. Oreifej, X. Li, M. Shah, "Simultaneous video stabilization and moving object detection in turbulence", IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 2, pp. 450-462, Feb. 2013. 8. W. Cao et al., "Total variation regularized tensor RPCA for background subtraction from compressive measurements", IEEE Trans. Image Process., vol. 25, no. 9, pp. 4075-4090, Sep. 2016. 9. X. Cao, L. Yang, X. Guo, "Total variation regularized RPCA for irregularly moving object detection under dynamic background", IEEE Trans. Cybern., vol. 46, no. 4, pp. 1014-1027, Apr. 2016. 10. Yong, D. Meng, W. Zuo, L. Zhang, "Robust online matrix factorization for dynamic background subtraction", IEEE Trans. Pattern Anal. Mach. Intell., vol. 40, no. 7, pp. 1726-1740, Jul. 2018. 11. L. Li, P. Wang, Q. Hu, S. Cai, "Efficient background modeling based on sparse representation and outlier iterative removal", IEEE Trans. Circuits Syst. Video Technol., vol. 26, no. 2, pp. 278-289, Feb. 2016. Authors: Bakanova A., Letov N.E., Kaibassova D., Kuzmin K.S., Loginov K.V., Shikov A.N. The use of Ontologies in the Development of a Mobile E-Learning Application in the Process of Staff Paper Title: Adaptation Abstract: The article discusses the method of using ontologies for developing a mobile application of the corporate e-learning system in the process of adaptation of companies’ new employees. The problems of shortening the period of adaptation of newly recruited employees force companies to look for effective methods of personnel management, their training and development. Well-known publications and the best developments in the field of mobile devices in corporate training systems, which allow to determine the vector of development of corporate training systems from e-learning to mobile learning, were considered. The widespread use of mobile devices makes the process of learning and adaptation of employees flexible, convenient, which leads to reduction of the time for employees to join the company's business processes. The problems of motivation and staff engagement in the process of early adaptation remain, but they are solved in the course of our other studies. The original method is use of ontologies when building individual learning paths in the process of adaptation of employees. The article examines the main approaches to the presentation and analysis of employees’ competencies based on ontologies when building modern corporate systems of adaptation and personnel training. An original approach to creating mobile applications is proposed, which reduces the time for adaptation and training of new employees.

133. Keyword: ontologies, corporate knowledge, competencies, competence management, corporate knowledge base, corporate training, mobile application, staff adaptation. 780-789 References: 1. Kobtseva M.I. The use of modern innovative technologies in the management of labor adaptation of staff // "Economy and Society" 2017.- №2 (33). C. 22. 2. V. Campbell, W. Hirsh Talent Management System: A Four Step Approach URL:https://www.employment- studies.co.uk/system/files/resources/files/502.pdf 3. M. Smatana and P. Butka Extraction of Keyphrases from Single Document Based on Hierarchical Concepts (SAMI 2016, IEEE 14th International Symposium on Applied Machine Intelligence and Informatics, January 21-23, 2016, Herl’any, Slovakia, p.93- 98). 4. Tarus, John K.; Niu, Zhendong; Mustafa, Ghulam Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning / ARTIFICIAL INTELLIGENCE REVIEW Т. 50 / 1. pp. 21-48. https://link.springer.com/article/10.1007%2Fs10462-017-9539-5 5. Berniukevicius, Andrius On application of semantic web technologies to personalise learning / 12th International Technology, Education and Development Conference Valencia, SPAIN, MAR 05-07, 2018, INTED Proceedings pp.4281-4288. 6. Abech, Marcia; da Costa, Cristiano Andre; Victoria Barbosa, Jorge Luis. A model for learning objects adaptation in light of mobile and context-aware computing / PERSONAL AND UBIQUITOUS COMPUTING Т. 20 № 2 .SI p. 167-184. 7. Ingavelez-Guerra, P., Robles-Bykbaev, V., Oton, S., Vera-Rea, P., Galan-Men, J., Ulloa-Amaya, M., Hilera, J.R. A proposal based on knowledge modeling and ontologies to support the accessibility evaluation process of learning objects(Conference Paper) / Congreso Argentino de Ciencias de la Informatica y Desarrollos de Investigacion, CACIDI 201819 December 2018, № 85843552018 Congreso Argentino de Ciencias de la Informatica y Desarrollos de Investigacion, CACIDI 2018; Buenos Aires; Argentina; 28 November 2018 до 30 November 2018; CFP18H47-ART. 8. Abech, M., da Costa, C.A., Barbosa, J.L.V., Rigo, S.J., da Rosa Righi, R. 3rd International Conference on Advances in New Technologies, Interactive Interfaces and Communicability, ADNTIIC 2012: Design, E-Commerce, E-Learning, E-Health, E- Tourism, Web 2.0 and Web 3.02012, 12p3rd International Conference on Advances in New Technologies, Interactive Interfaces and Communicability: Design, E-Commerce, E-Learning, E-Health, E-Tourism, Web 2.0 and Web 3.0, ADNTIIC 2012; Huerta Grande, Cordoba; Argentina; 3 December 2012 до 5 December 2012. 9. Duran, E.B., Alvarez, M.M., Unzaga, S.I. Generic model of a multi-agent system to assist ubiquitous learning / Procedia - Social and Behavioral Sciences Volume 28, 2011, Pages 963-967World Conference on Educational Technology Researches, WCETR- 2011; Nicosia/Kyrenia; Cyprus; 5 July 2011 до 9 July 2011. 10. Ercan, T. Benefits of semantic approach in the learning environment / Procedia - Social and Behavioral Sciences 28 (2011) 963 – 967. 11. Aeiad, E., Meziane, F. An adaptable and personalised E-learning system applied to computer science Programmes design / Education and Information Technologies Volume 24, Issue 2, 16 March 2019, p/ 1485-1509. 12. Huang, Q., Huang, C., Huang, J., Fujita, H. Adaptive resource prefetching with spatial–temporal and topic information for educational cloud storage systems / Knowledge-Based Systems 2019. 13. Bouihi, B., Bahaj, M. An ontology-based architecture for context recommendation system in E-learning and mobile-learning applications Proceedings of 2017 International Conference on Electrical and Information Technologies, ICEIT 2017, p. 1-6. 14. Bouihi, B., Bahaj, M. A Semantic Web Architecture for Context Recommendation System in E-learning Applications / Lecture Notes in Networks and Systems 37, p. 67-73. 15. Saleh, M., Salama, R.M. Recommendations for building adaptive cognition-based e-Learning / International Journal of Advanced Computer Science and Applications Volume 9, Issue 8, 2018, P. 385-393. 16. Tarus, J.K., Niu, Z., Yousif, A. A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining / Future Generation Computer Systems 72, с. 37-48. 17. Bakanova A., Nikitina L.N., Shikov P.A., Shikov U.A., Shikov A.N. Recommended system of personalized corporate e-learning based on ontologies / MATEC Web of Conferences, Vol. 193, 05074, (2018). 18. Chunaev A.V., Shikov A.N. The method of personalized corporate e-learning based on personal traits of employees / Procedia Computer Science Vol. 136, 2018, Pages 511-521. 19. Bakanova A., Chunaev A.V., Loginov K.V., Okulov S.A., Shikov A.N. / Mobile technologies as innovations in corporate e- learning systems // Scientific journal "labor Economics» -2018. Tom 5. № 2. doi: 10.18334/et.5.2.39096. 20. Bakanova A., Chunaev A.V., Loginov K.V., Okulov S.A., Shikov A.N. The concept of personalized e-learning with the use of mobile applications based on ontologies / Ponte - 2018, Vol. 74, No. 1|SI, pp. 61-70. 21. Rahideh M, Mazloum SZ. Combination System Optimization of Solar Collector/ Photovoltaic with Genetic Algorithms. Medbiotech Journal. 2019;03(02):58-64. 22. Kashisaz S, Mobarak E. The Effects of Private Education Institutes in Providing Modern Financial Knowledge in Developing Countries. Journal of Humanities Insights. 2018;02(04):172-8. 23. Kheirabadi MA, Mirzaei Z. Descriptive valuation pattern in education and training system: a mixed study. Journal of Humanities Insights. 2019;3(01):7-12. 24. Eslami R, Ahmadi S. Investigating the Role of Educational Media on Secondary School Students’ Learning Process Improvement in Jahrom City. Journal of Humanities Insights. 2019;3(01):13-6. 25. Mirrashid N, RakhtAla SM. Fuel Cell Systems and Developments in Control Abilities. Medbiotech Journal. 2019;03(02):41-6. 26. Vajravelu, K. (2018). Innovative Strategies for Learning and Teaching of Large Differential Equations Classes. International Electronic Journal of Mathematics Education, 13(2), 91-95. https://doi.org/10.12973/iejme/2699 27. Kurmanali, A., Suiyerkul, B., Aitmukhametova, K., Turumbetova, Z., & Smanova, B. (2018). Analysis of the proverbs related to the lexemes" tongue/language". Opción, 34(85-2), 97-115. 28. Ganjali, M., & Teimourpour, B. (2016). Identify Valuable Customers of Taavon Insurance in Field of Life Insurance with Data Mining Approach. UCT Journal of Research in Science, Engineering and Technology, 4(1), 1-10. 29. Fujo, M. H., & Dida, M. A. (2019). Centralized Admission System for Advanced Level Private Schools: Case of Kilimanjaro Region, Tanzania. Journal of Information Systems Engineering & Management, 4(1). Lee Enn Hooi, Mohammad Rahim Kamaluddin, Norruzeyati Che Mohd Nasir, Hilwa Abdullah @ Authors: Mohd Nor, Noremy Md Akhir Exploring the Psychometric Properties of Mandarin-Translated Zuckerman Kuhlman Personality Paper Title: Questionnaire among Chinese High School Students in Malaysia Abstract: The Zuckerman Kuhlman Personality Questionnaire (ZKPQ-50-CC) is widely used tool to measure personality traits among the test takers and has been translated in various languages. However, based on the literatures related to personality, it is apparent that there is no Mandarin translated ZKPQ is available to measure personality traits among Chinese population based on the Alternative Five Factor Model. Therefore, the aim of this study is to validate and explore the psychometric properties of the Mandarin-translated version of the Zuckerman Kuhlman Personality Questionnaire. A cross-sectional study was designed involving 250 Malaysian Chinese High school students, aged thirteen to eighteen. Forward-backward translations were performed followed by the factor analysis and reliability testing. The five factors structure was assessed and the factor loadings are similar with the Malay version of ZKPQ. This Mandarin translated ZKPQ comprised of 38 items with the factor loadings ranged from 0.41 to 0.79. The reliability values also showed that Mandarin translated ZKPQ is reliable. As such, the Mandarin translated ZKPQ was found to be valid and reliable to use among 134. Mandarin speaking population for the purpose of personality testing and screening.

790-794 Keyword: Mandarin language, personality tool, psychometric properties, reliability, validation, Zuckerman-Kuhlman Personality Questionnaire

References: 1. B. Muhammad Amin, K. Mohammad Rahim, & M.S. Geshina Ayu. (2014). A trend analysis of violent crimes in Malaysia. Health and the Environment Journal. 5, 41-56. 2. W. Mischel, Introductory to Personality (6th ed). Florida: Harcourt Brace College Pub, 1999. 3. M. Goma-i-Freixanet, & S.V. Ventura (2008). Spanish normative data of the Zuckerman-Kuhlman Personality Questionnaire in a general population sample. Psicotherna. 20 (2), 324-330. 4. M. Zuckerman, “Zuckerman-Kuhlman personality questionnaire (ZKPQ): An alternative five-factorial model,” in Big five assessments B. de Raad & M. Perugini, Eds. Ashland, OH, US: Hogrefe & Huber Publishers, 2002, pp.376-392. 5. J. A. Gray, The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system. New York: Oxford University Press, 1982. 6. A. Aluja, J. Rossier, L.F. Garcia, A. Angleitner, M. Kuhlman & M. Zuckerman. (2006). A cross-cultural shortened form of the ZKPQ (ZKPQ-50-cc) adapted to English, French, German, and Spanish languages. Personality and Individual Differences, 41, 619-628. 7. K. Mohammad Rahim, M. S. Nadiah Syariani, O. Azizah, I. Khaidzir, M. S. Geshina Ayu. (2014). Associations between personality traits and aggression among Malay adult male inmates in Malaysia, ASEAN Journal of Psychiatry. 15, 176-185. 8. M. S. Geshina Ayu, K. Mohammad Rahim, M. S. Nadiah Syariani, O. Azizah, I. Khaidzir. (2015). Linking psychological traits with criminal behavior: A Review. ASEAN Journal of Psychiatry. 16, 135-147. 9. K. Mohammad Rahim, M. S. Nadiah Syariani, M. S. Geshina Ayu. (2013). A Validity Study of Malay Translated Zuckerman- Kuhlman Personality Questionnaire Cross-Cultural 50 Items (ZKPQ-50-CC). Health and the Environment Journal. 4(2), 37-52. 10. T. K. Dharmalingam, K. Mohammad Rahim & S. K. Hassan (2016). Factorial validation and psychometric properties of establishment of Malay version critical care family need inventory. The International Medical Journal of Malaysia, 15 (1), 51-60. 11. L. R. Gay, G. E. Mills, & P. W. Airasian, Educational Research: Competencies for Analysis and Applications. USA: Pearson Education Limited, 2014. 12. A. Field, Discovering statistics using SPSS (3rd ed.). SAGE: Publication Ltd, London, 2009. 13. P. Allen, K, Bennet, & B. Heritage, SPSS Statistics Version 22: A Practical Guide. Australia: Cengage Learning Australia PtyLimited, 2014. 14. D. George & P. Mallery, SPSS for Windows Step by Step: A Simple Guide and Reference. 11.0 update. (4th ed.). Boston: Allyn & Bacon, 2003. 15. George, D. & Mallery, P. (2003). SPSS for Windows Step by Step: A Simple Guide and Reference. 11.0 update. (4th ed.). Boston: Allyn & Bacon. Authors: B. Pullarao, S. Srinivasan Energy Storage with Inclusion of Power Stability Improvement with Advanced Controls Based on Paper Title: VLSI Abstract: Multi rate strategy is fundamental for systems with different data and yield taking a gander at rates. Late advances in negligible figuring and correspondence applications deals low power and rapid VLSI DSP structures. This Paper presents Multi rate modules used for binding to offer sign overseeing in remote correspondence structure. Distinctive arranging made for the structure of low multifaceted nature, bit parallel Multiple Constant Multiplications improvement which principles the unusualness of DSP systems. In any case, basic hindrances of present approaches are either outrageously extravagant or not profitable enough. On the other hand, MCM and digit-consecutive snake offer elective low multifaceted nature plans, since digit-dynamic structure consolidate less space and are free of the data word length. Distinctive Constant Multiplications is capable way to deal with oversee decrease the proportion of enlargement and subtraction in poly stage channel execution. This Multi rate structure believing is purposeful and real to various issues. In this paper, thought has given to the MCM and digit dynamic structure with moving and including technique that offers elective low multifaceted nature in exercises. This paper what's more pivoted around Multi rate Signal Processing Modules using Voltage and Technology scaling. Lessening of intensity use is giant for VLSI system and moreover it ends up one of the most fundamental game-plan parameter.

Keyword: VLSI, DSP, TSMC, multiply constant multiplication (MCM) References: 1. “Battery power for your residential solar electric system,” Technical Report, National Renewable Energy Laboratory, 2002. 2. “Electrical energy storage,” Technical Report, International Electrochemical Commission, http://www.iec.ch/whitepaper/pdf/iecWP-energystorageLR-en.pdf, 2011. 3. P. R. Abel, Y.-M. Lin, H. Celio, A. Heller, and C. B. Mullins, “Improving the stability of nanostructured silicon thin film lithium- ion battery anodes through their controlled oxidation,” ACS Nano, vol. 6, no. 3, pp. 2506–2516, 2012. 4. P. R. Abel, Y.-M. Lin, H. Celio, A. Heller, and C. B. Mullins, “Improving the stability of nanostructured silicon thin film lithium- 135. ion battery anodes through their controlled oxidation,” ACS Nano, vol. 6, no. 3, pp. 2506–2516, 2012. 5. H. Akagi and H. Sato, “Control and performance of a doubly-fed induction machine intended for a flywheel energy storage system,” IEEE Transactions on Power Electronics, vol. 17, no. 1, pp. 109–116, 2002. 795-800 6. A. Allegre, A. Bouscayrol, and R. Trigui, “Influence of control strategies on battery/supercapacitor hybrid energy storage systems for traction applications,” in Proceedings of the Vehicle Power and Propulsion Conference (VPPC), pp. 213–220, 2009. 7. F. Altaf, L. Johannesson, and B. Egardt, “Performance evaluation of multilevel converter based cell balancer with reciprocating air flow,” in Proceedings of the Vehicle Power and Propulsion Conference (VPPC), pp. 706–713, 2012 8. S. M. Amin and B. F. Wollenberg, “Toward a smart grid: power delivery for the 21st century,” IEEE Power and Energy Magazine, vol. 3, no. 5, pp. 34–41, 2005. 9. T. B. Atwater, P. J. Cygan, and F. C. Leung, “Man portable power needs of the 21st century: I. applications for the dismounted soldier. ii. enhanced capabilities through the use of hybrid power sources,” Journal of Power Sources, vol. 91, no. 1, pp. 27–36, 2000. 10. L. Barote, R. Weissbach, R. Teodorescu, C. Marinescu, and M. Cirstea, “Stand-alone wind system with vanadium redox battery energy storage,” in Proceedings of the International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), pp. 407–412, 2008. 11. Y. Barsukov, “Battery cell balancing: What to balance and how,” Technical Report, Texas Instruments, 2009. 12. S. Bashash, S. J. Moura, J. C. Forman, and H. K. Fathy, “Plug-in hybrid electric vehicle charge pattern optimization for energy cost and battery longevity,” Journal of Power Sources, vol. 196, no. 1, pp. 541–549, 2011. 13. F. Belhachemi, S. Ra¨el, and B. Davat, “A physical based model of power electric double-layer supercapacitors,” in Proceedings of the Industry Applications Conference, vol. 5, pp. 3069–3076, 2000. 14. J. L. Bernal-Agustn and R. Dufo-L´opez, “Simulation and optimization of stand-alone hybrid renewable energy systems,” Renewable and Sustainable Energy Reviews, vol. 13, no. 8, pp. 2111–2118, 2009. 15. P. Bhatnagar and R. Nema, “Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications,” Renewable and Sustainable Energy Reviews, vol. 23, pp. 224–241, 2013. 16. A. Bilodeau and K. Agbossou, “Control analysis of renewable energy system with hydrogen storage for residential applications,” Journal of Power Sources, vol. 162, no. 2, pp. 757–764, 2006. 17. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2004. 18. D. Bresser, E. Paillard, M. Copley, P. Bishop, M. Winter, and S. Passerini, “The importance of “going nano” for high power battery materials,” Journal of Power Sources, vol. 219, pp. 217–222, 2012. 19. D. A. Brownson, D. K. Kampouris, and C. E. Banks, “An overview of graphene in energy production and storage applications,” Journal of Power Sources, vol. 196, no. 11, pp. 4873–4885, 2011. 20. S. Brutti, J. Hassoun, B. Scrosati, C.-Y. Lin, H. Wu, and H.-W. Hsieh, “A high power Sn–C/C–LiFePO4 lithium ion battery,” Journal of Power Sources, vol. 217, pp. 72–76, 2012. 21. S. Buller, E. Karden, D. Kok, and R. De Doncker, “Modeling the dynamic behavior of supercapacitors using impedance spectroscopy,” in Proceedings of the Industry Applications Conference, vol. 4, pp. 2500–2504, 2001. 22. S. Buller, M. Thele, R. De Doncker, and E. Karden, “Impedance-based simulation models of supercapacitors and li-ion batteries for power electronic applications,” IEEE Transactions on Industry Applications, vol. 41, no. 3, pp. 742–747, 2005. 23. S. Caron and G. Kesidis, “Incentive-based energy consumption scheduling algorithms for the smart grid,” in Proceedings of the Smart Grid Communications (SmartGridComm) Conference, pp. 391–396, 2010. 24. P. Carter, J. Baxter, T. Newill, and T. Erekson, “An ultracapacitor-powered race car update,” in Proceeding of the Electrical Insulation Conference and Electrical Manufacturing Expo, pp. 267–274, 2005. 25. S. Chakraborty, M. Lukasiewycz, C. Buckl, S. Fahmy, N. Chang, S. Park, Y. Kim, P. Leteinturier, and H. Adlkofer, “Embedded systems and software challenges in electric vehicles,” in Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE), pp. 424–429, 2012. 26. N. Chang and M. Pedram, “Hybrid electrical energy storage systems,” Tutorial at International Symposium on Quality Electronics Design (ISQED), 2011. 27. N. Chang, J. Seo, D. Shin, and Y. Kim, “Room-temperature fuel cells and their integration into portable and embedded systems,” in Proceedings of the Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 69–74, 2010. 28. P. Chanhom, S. Sirisukprasert, and N. Hatti, “DC-link voltage optimization for SOC balancing control of a battery energy storage system based on a 7-level cascaded PWM converter,” in Proceedings of the International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 1–4, 2012. 29. C. Chen, B. Das, and D. J. Cook, “Energy prediction based on resident’s activity,” in Proceedings of the International Workshop on Knowledge Discovery from Sensor Data (SensorKDD), 2010. 30. C.-Y. Chen and P. H. Chou, “DuraCap: a supercapacitor-based, powerbootstrapping, maximum power point tracking energy- harvesting system,” in Proceedings of the International Symposium on Low-Power Electronics and Design (ISLPED), pp. 313– 318, 2010. 31. H. Chen, T. N. Cong, W. Yang, C. Tan, Y. Li, and Y. Ding, “Progress in electrical energy storage system: A critical review,” Progress in Natural Science, vol. 19, no. 3, pp. 291–312, 2009. 32. Q. Cheng, J. Tang, J. Ma, H. Zhang, N. Shinya, and L.-C. Qin, “Graphene and carbon nanotube composite electrodes for supercapacitors with ultrahigh energy density,” Physical Chemistry Chemical Physics, vol. 13, no. 39, pp. 17615–17624, 2011. 33. Q. Cheng, J. Tang, J. Ma, H. Zhang, N. Shinya, and L.-C. Qin, “Graphene and nanostructured MnO2 composite electrodes for supercapacitors,” Carbon, vol. 49, no. 9, pp. 2917–2925, 2011. 34. Y. Cheng, V. Joeri, and P. Lataire, “Research and test platform for hybrid electric vehicle with the super capacitor based energy storage,” in Proceedings of the European Conference on Power Electronics and Applications, pp. 1–10, 2007. 35. S. Chiang, K. Chang, and C. Yen, “Residential photovoltaic energy storage system,” IEEE Transactions on Industrial Electronics, vol. 45, no. 3, pp. 358–394, 1998. 36. Y. Choi, N. Chang, and T. Kim, “DC–DC converter-aware power management for low-power embedded systems,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 26, no. 8, pp. 1367–1381, 2007. 37. M. Chowdhury, M. Haque, M. Aktarujjaman, M. Negnevitsky, and A. Gargoom, “Grid integration impacts and energy storage systems for wind energy applications — a review,” in Proceedings of the Power and Energy Society General Meeting, pp. 1–8, 2011. 38. Consolidated Edison Company of New York, Inc. 2012, “Service classification no. 1 — residential and religious,” 39. A. Czerwi´nski, S. Obrbowski, and Z. Rogulski, “New high-energy lead-acid battery with reticulated vitreous carbon as a carrier and current collector,” Journal of Power Sources, vol. 198, pp. 378–382, 2012. 40. K. Darcovich, N. Gupta, I. Davidson, and T. Caroni, “Residential electrical power storage scenario simulations with a large-scale lithium ion battery,” Journal of Applied Electrochemistry, vol. 40, pp. 749–755, 2010. 41. J. P. Deane, B. P. O. Gallach´ ´ oir, and E. McKeogh, “Techno-economic review of existing and new pumped hydro energy storage plant,” Renewable and Sustainable Energy Reviews, vol. 14, no. 4, pp. 1293–1302, 2010. 42. K. Divya and J. Østergaard, “Battery energy storage technology for power systems — an overview,” Electric Power Systems Research, vol. 79, no. 4, pp. 511–520, 2009. 43. D. Doerffel and S. A. Sharkh, “A critical review of using the peukert equation for determining the remaining capacity of lead- acid and lithium-ion batteries,” Journal of Power Sources, vol. 155, no. 2, pp. 395–400, 2006. 44. R. Dougal, S. Liu, and R. White, “Power and life extension of batteryultracapacitor hybrids,” IEEE Transactions on Components and Packaging Technologies, vol. 25, no. 1, pp. 120–131, 2002. 45. M. Einhorn, W. Roessler, and J. Fleig, “Improved performance of serially connected li-ion batteries with active cell balancing in electric vehicles,” IEEE Transactions on Vehicular Technology, vol. 60, no. 6, pp. 2448–2457, 2011. 46. O. Ekren and B. Y. Ekren, “Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing,” Applied Energy, vol. 87, no. 2, pp. 592–598, 2010. 47. O. Ekren, B. Y. Ekren, and B. Ozerdem, “Break-even analysis and size optimization of a PV/wind hybrid energy conversion system with battery storage — a case study,” Applied Energy, vol. 86, no. 78, pp. 1043–1054, 2009. 48. T. Esram and P. Chapman, “Comparison of photovoltaic array maximum power point tracking techniques,” IEEE Transactions on Energy Conversion, vol. 22, no. 2, pp. 439–449, 2007. 49. A. Evans, V. Strezov, and T. J. Evans, “Assessment of utility energy storage options for increased renewable energy penetration,” Renewable and Sustainable Energy Reviews, vol. 16, no. 6, pp. 4141–4147, 2012. 50. C. Fabjan, J. Garche, B. Harrer, L. Jrissen, C. Kolbeck, F. Philippi, G. Tomazic, and F. Wagner, “The vanadium redox-battery: An efficient storage unit for photovoltaic systems,” Electrochimica Acta, vol. 47, no. 5, pp. 825–831, 2001. Authors: A. Lajwanti Naidu, Manohar Sajnani, Zeenat Zaidi Tangible and Intangible Attributes for the Development of Convention Tourism - An Economic Paper Title: Proposition Abstract: The present working paper documents the results of a pilot study on the Economic Impacts of Development of Convention Tourism in Hyderabad. Gaining impetus from various stakeholders of the tourism industry, the research employs the importance - performance model. The assessment is done under two heads: tangibles and intangibles, to examine whether the city of Hyderabad does live up to its reputation of being the 136. “Convention Capital of India” attracting, in particular, leading industry giants to participate in congresses and conventions. The main study would endeavor to provide a sustainable business model to supplement the efforts of Government of Andhra Pradesh. 801-808

Keyword: Convention Tourism, Economic Proposition, Importance Performance Model. References: 1. Braun, B. M., & Rungeling, B. (1992). The relative economic impact of convention and tourist visitors on a regional economy: a case study. International Journal of Hospitality Management, 11(1), 65-71. 2. Kim, S. S., Chon, K., & Chung, K. Y. (2003). Convention industry in South Korea: an economic impact analysis. Tourism Management, 24(5), 533-541. 3. Braun, B. M. (1992). The economic contribution of conventions: The case of Orlando, Florida. Journal of Travel Research, 30(3), 32-37. 4. Yoo, J. J. E., & Weber, K. (2005). Progress in convention tourism research. Journal of Hospitality & Tourism Research, 29(2), 194-222. 5. Dwyer, L., Mellor, R., Mistilis, N., & Mules, T. (2000). A framework for assessing “tangible” and “intangible” impacts of events and conventions. Event management, 6(3), 175-189. 6. Mackellar, J. (2007, January). Conventions, festivals, and tourism: Exploring the network that binds. In Journal of Convention & Event Tourism (Vol. 8, No. 2, pp. 45-56). Taylor & Francis Group 7. McCartney, G. (2008, November). The CAT (casino tourism) and the MICE (meetings, incentives, conventions, exhibitions): Key development considerations for the convention and exhibition industry in Macao. In Journal of Convention & Event Tourism (Vol. 9, No. 4, pp. 293-308). Taylor & Francis Group. 8. Weber, K. (2001). Meeting planners’ use and evaluation of convention and visitor bureaus. Tourism Management, 22(6), 599- 606. 9. J. E., & Chon, K. (2008). Factors affecting convention participation decision-making: Developing a measurement scale. Journal of Travel Research. 10. Weber, K., & Roehl, W. S. (2001, August). Service quality issues for convention and visitor bureaus. In Journal of Convention & Exhibition Management (Vol. 3, No. 1, pp. 1-19). Taylor & Francis Group. 11. Mair, J., & Jago, L. (2010). The development of a conceptual model of greening in the business events tourism sector. Journal of Sustainable Tourism, 18(1), 77-94. 12. Lee, M. J., & Back, K. J. (2007). Effects of destination image on meeting participation intentions: Empirical findings from a professional association and its annual convention. The Service Industries Journal, 27(1), 59-73. 13. Yoo, J. J. E., & Zhao, X. (2010). Revisiting determinants of convention participation decision making. Journal of Travel & Tourism Marketing, 27(2), 179-192. 14. Breiter, D., & Milman, A. (2006). Attendees’ needs and service priorities in a large convention center: Application of the importance–performance theory.Tourism Management, 27(6), 1364-1370. 15. Go, F., & Zhang, W. (1997). Applying importance-performance analysis to Beijing as an international meeting destination. Journal of Travel Research,35(4), 42-49. 16. Ennew, C. T., Reed, G. V., & Binks, M. R. (1993). Importance-performance analysis and the measurement of service quality. European journal of marketing, 27(2), 59-70. 17. Zhang, H. Q., Leung, V., & Qu, H. (2007). A refined model of factors affecting convention participation decision- making. Tourism Management, 28(4), 1123-1127. 18. Sivakoti Reddy, M. (2019). Impact of RSERVQUAL on customer satisfaction: A comparative analysis between traditional and multi-channel retailing. International Journal of Recent Technology and Engineering. 8(1), pp. 2917-2920. 19. Sivakoti Reddy, M., Venkateswarlu, N.(2019). Customer relationship management practices and their impact over customer purchase decisions: A study on the selected private sector banks housing finance schemes. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1720-1728. 20. Sivakoti Reddy, M., Murali Krishna, S.M.(2019). Influential role of retail service quality in food and grocery retailing: A comparative study between traditional and multi-channel retailing. International Journal of Management and Business Research. 9(2), pp. 68-73. 21. Sivakoti Reddy, M., Naga Bhaskar, M., Nagabhushan, A. (2016). Saga of silicon plate: An empirical analysis on the impact of socio economic factors of farmers on inception of solar plants. International Journal of Control Theory and Applications. 9(29), pp. 257-266. 22. Manukonda et al. (2019). What Motivates Students To Attend Guest Lectures?. The International Journal of Learning in Higher Education. Volume 26, Issue 1. 23-34. 23. Hymavathi, C.H., Koneru, K.(2019). Investors perception towards Indian commodity market: An empirical analysis with reference to Amaravathi region of Andhra Pradesh. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1708-1714. 24. Neelima, J., Koneru, K.(2019). Assessing the role of organizational culture in determining the employee performance - empirical evidence from Indian pharmaceutical sector. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1701-1707. 25. Kishan Varma, M.S., Koneru, K., Yedukondalu, D.(2019). Affect of worksite wellness interventions towards occupational stress. International Journal of Recent Technology and Engineering. 8(1), pp. 2874-2879. 26. Hymavathi, C., Koneru, K. (2019). Role of perceived risk in mutual funds selection behavior: An analysis among the selected mutual fund investors. International Journal of Engineering and Advanced Technology. 8(4), pp. 1913-1920. 27. Suhasini, T., Koneru, K. (2019). Employee engagement through HRD practices on employee satisfaction and employee loyalty: An empirical evidence from Indian IT industry. International Journal of Engineering and Advanced Technology. 8(4), pp. 1788-1794. 28. Suhasini, T. Koneru, K. (2018). A study on employee engagement driving factors and their impact over employee satisfaction - An empirical evidence from Indian it industry. International Journal of Mechanical Engineering and Technology. 9(4), pp. 725-732. 29. Hymavathi, C.H., Koneru, K.(2018). Investors' awareness towards commodities market with reference to GUNTUR city, Andhra Pradesh. International Journal of Engineering and Technology(UAE). 7(2), pp. 1104-1106 Authors: Pratibha Rai, Om Jee Gupta Measuring the Mediating Effect of Utilitarian Motive in the Relationship of Product Quality, Paper Title: Product Price with Consumer Purchase Intention Abstract: Retail business has always been an attractive business for marketers. In recent years, many research works were being carried out in the retail industry. Most of this research work was being carried out in the developed cities of India but none of the researchers has focused on smaller states or new cities of India. This research work was undertaken in the state of Chhattisgarh (Raipur, Bilaspur and Durg). The researcher has used 137. one dependent variable (consumer purchase intention), three independent variables (product quality, product price and utilitarian motive, and one mediating variable (utilitarian motive). The researcher has used descriptive research design to undertake this work. Convenience sampling method was chosen to collect the primary data 809-816 for the study. The researcher has collected data from 470 respondents, whereas 153 responses were found to be unsuitable for the study. They were found to be unengaged responses, where respondents have ticked on the answers without reading the questions. After eliminating these questionnaires, the researcher is left with 317 responses. Then the researcher has used confirmatory factor analysis (CFA) to check the validity and reliability of the constructs. Thereafter, the researcher has used structural equation modeling to test the hypothesis.

The finding of the study revealed that utilitarian motive significantly mediates the relationship of product quality with consumer purchase intention and product price with consumer purchase intention. At last, the researcher has drawn a managerial implication from this study and has also suggested future areas of researches for the upcoming scholars.

Keyword: Consumer Purchase Intention, Product Quality, Product Price, Organized Retail, Utilitarian Motive, Indian Retail Market. References: 1. Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of consumer research, 20(4), 644-656. 2. Chi, H. K., Yeh, H. R., & Huang, M. W. (2009). The Influences of advertising endorser, brand image, brand equity, price promotion on purchase intention: The mediating effect of advertising endorser. The Journal of Global Business Management, 5(1), 224-233. 3. Engardio, P., Roberts, D., &Bremner, B. (2004). The China price. Business Week. New York, 4. Ghosh, A. (1990). Retail management. Chi cago: Drydden press. 5. Jin, B., & Kim, J. O. (2003). A typology of Korean discount shoppers: shopping motives, store attributes, and outcomes.International Journal of Service Industry Management. 14(4). 396-419. 6. Keller,K. L. (2008). Strategic Brand Management. Building, Measuring, and Managing Brand Equity. 3 Ed., New Jersey. Pearson Education International. 7. Khraim, H. S. (2011). The Influence of Brand Loyalty on Cosmetics Buying Behavior of UAE Female Consumers.International Journal of Marketing Studies, 3(2), 123-133. 8. Kotler P. & Armstrong, G. (2010). Principles of Marketing. New Jersey: Pearson Prentice Hall. 9. Lee, AbdouIllia, &Assion Lawson- Body. (2010). Perceived price fairness of dynamic pricing. Journal of Industrial Management & Data Systems, 111, 531- 550. 10. Sarwar, A. A. M., Azam, S. F., Haque, A. K. M., Sleman, G., &Nikhashemi, S. R. (2013). Customer’s perception towards buying Chinese products: An empirical investigation in Malaysia.World Applied Sciences Journal, 2(2), 152-160. 11. Shah, H., Aziz, A., Jaffari, A. R., Waris, S., Ejaz, W., Fatima, M., &Sherazi., K. (2012). The Impact of Brands on Consumer Purchase Intentions. Asian Journal of Business Management, 4(2). 105-110. 12. Tsiotsou, R., (2006). The role of perceived product quality and overall satisfaction on purchase intention, International journal of consumer studies, 30(2), 207-217. 13. Yavas, U., &Babakus, E. (2009). Modeling patronage behavior: Atri-partite conceptualization. Journal of Consumer Marketing, 26(7), 516-526. 14. Zeeshan, Z. (2013). The impact of mobile service attributes on males’ and females’ purchase decision.Management & Marketing Challenges for the Knowledge Society, 8(4), 669-682. 15. Sivakoti Reddy, M. (2019). Impact of RSERVQUAL on customer satisfaction: A comparative analysis between traditional and multi-channel retailing. International Journal of Recent Technology and Engineering. 8(1), pp. 2917-2920. 16. Sivakoti Reddy, M., Venkateswarlu, N.(2019). Customer relationship management practices and their impact over customer purchase decisions: A study on the selected private sector banks housing finance schemes. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1720-1728. 17. Sivakoti Reddy, M., Murali Krishna, S.M.(2019). Influential role of retail service quality in food and grocery retailing: A comparative study between traditional and multi-channel retailing. International Journal of Management and Business Research. 9(2), pp. 68-73. 18. Sivakoti Reddy, M., Naga Bhaskar, M., Nagabhushan, A. (2016). Saga of silicon plate: An empirical analysis on the impact of socio economic factors of farmers on inception of solar plants. International Journal of Control Theory and Applications. 9(29), pp. 257-266. 19. Manukonda et al. (2019). What Motivates Students To Attend Guest Lectures?. The International Journal of Learning in Higher Education. Volume 26, Issue 1. 23-34. 20. Hymavathi, C.H., Koneru, K.(2019). Investors perception towards Indian commodity market: An empirical analysis with reference to Amaravathi region of Andhra Pradesh. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1708-1714. 21. Neelima, J., Koneru, K.(2019). Assessing the role of organizational culture in determining the employee performance - empirical evidence from Indian pharmaceutical sector. International Journal of Innovative Technology and Exploring Engineering. 8(7), pp. 1701-1707. 22. KishanVarma, M.S., Koneru, K., Yedukondalu, D.(2019). Affect of worksite wellness interventions towards occupational stress. International Journal of Recent Technology and Engineering. 8(1), pp. 2874-2879. 23. Hymavathi, C., Koneru, K. (2019). Role of perceived risk in mutual funds selection behavior: An analysis among the selected mutual fund investors. International Journal of Engineering and Advanced Technology. 8(4), pp. 1913-1920. 24. Suhasini, T., Koneru, K. (2019). Employee engagement through HRD practices on employee satisfaction and employee loyalty: An empirical evidence from Indian IT industry. International Journal of Engineering and Advanced Technology. 8(4), pp. 1788-1794. 25. Suhasini, T. Koneru, K. (2018). A study on employee engagement driving factors and their impact over employee satisfaction - An empirical evidence from Indian it industry. International Journal of Mechanical Engineering and Technology. 9(4), pp. 725-732. 26. Hymavathi, C.H., Koneru, K.(2018). Investors' awareness towards commodities market with reference to GUNTUR city, Andhra Pradesh. International Journal of Engineering and Technology(UAE). 7(2), pp. 1104-1106. Authors: N. Naveen, S. Suresh, P. Karunakar Reddy

Paper Title: An Entropy based Model for Examination of Social Media Data Mining for Marketing Intelligence Abstract: Social Websites Provides Platform for to Deliver Customer Opinion in the form of comments. It is also Highly Impossible to get the huge comments throughout the World; in this Paper we proposed the 138. Concept of Customer Review and Ranking of the Product in the Marketing for this us used an Algorithm of re- ranking technique. Entropy Based Model supports for review and also used for reviews along with ranking Our 817-820 algorithm Gives Better results comparing with the Other Existed Algorithms .The Output results gives the Better Marketing Intelligence Strategy that will supports customer to select good in the Marketing. And also supports for Blocking Website in the Marketing Who are not providing customer not satisfied Product in the Market. Keyword: Social Media, Data Mining, Ranking, Search strategy.

References: 1. V. Hatzivassiloglou and K. R. McKeown. Predicting the semantic orientation of adjectives. In Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, pages 174–181, Morristown, NJ, USA, 1997. Association for Computational Linguistics. 2. S.-M. Kim, P. Pantel, T. Chklovski, and M. Pennacchiotti. Automatically assessing review helpfulness. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pages 423–430, Sydney, Australia, July 2006. Association for Computational Linguistics. 3. L. L. Nan Hu and J. J. Zhang. Do online reviews affect product sales? the role of reviewer characteristics and temporal effects. Information Technology and Management, 2008. [4] B. Pang, L. Lee, and S. Vaithyanathan. Thumbs up?: sentiment classification using machine learning techniques. In EMNLP ’02: Proceedings of the ACL-02 conference on Empirical methods in natural language processing, pages 79–86, Morristown, NJ, USA, 2002. Association for Computational Linguistics. 4. D.-H. Park, J. Lee, and I. Han. The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. Int. J. Electron. Commerce, 11(4):125–148, 2007.[6] C. E. Shannon. A mathematical theory of communication. SIGMOBILE Mob. Comput. Commun. Rev., 5(1):3–55,2001. 5. P. Turney. Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. 6. I. Weimer, Markus; Gurevych. Predicting the perceived quality of web forum posts. Proceedings of the Conference on Recent Advances in Natural Language Processing (RANLP), 2007. 7. M.Weimer, I. Gurevych, and M.M¨uhlh¨auser. Automatically assessing the post quality in online discussions on software. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions, pages 125–128, Prague, Czech Republic, June 2007. Association for Computational Linguistics. 8. Y. Yang and J. O. Pedersen. A comparative study on feature selection in text categorization. In Proceedings of the Fourteenth International Conference on Machine Learning, pages 412–420, San Francisco, CA, USA, 1997. Morgan Kaufmann Publishers Inc. 9. H. Yu and V. Hatzivassiloglou. Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the 2003 conference on Empirical methods in natural language processing, pages 129– 136, Morristown, NJ, USA, 2003. Associationfor Computational Linguistics. Authors: P Venkat Reddy, Sudarson Jena, V Kamakshi Prasa

Paper Title: An Efficient Exchanged Hyper Cube for Parallel and Distributed Network Abstract: Enormously parallel distribution memory designs are accepting and expanding regard to satisfy the expanding need on processing power. Numerous topologies have been projected for interconnecting the processors of distributed computing systems. The hypercube topology has attracted significant consideration because of a significant number of attractive properties. The engaging properties of the hypercube topology, for example, vertex and edge balance, recursive structure, logarithmic diameter, maximally fault-tolerance, simple routing and broadcasting, and the capacity to recreate other interconnection systems with least overhead have made it a brilliant possibility for some parallel processing applications. Numerous varieties of the hypercube topology have been accounted for the literature, mostly to add the computational power of the hypercube. One of the gorgeous versions of the hypercube was introduced for the improvement of the presented Exchanged hypercube. An Exchanged hypercube has the equivalent structural complexities of the hypercube. It protects the gorgeous properties of the hypercube and diameter the communication time by dropping the diameter by a factor of two. This paper presents the fundamental communication and some of the essential operations normally required in parallel computing on the Exchanged hypercube interconnection networks.

Keyword: interconnecting network, routing protocol, Hypercube, exchanged hypercube. References: 1. J. Al-Sadi, K. Day, and M. Ould-Khaoua, "Unsafety Vectors: A New Fault-Tolerant Routing for Binary n-Cubes," Journal of 139. Systems Architecture, vol. 47, no. 9, pp-783-793, 2002. 2. G. Chiu and K. Chon, "Efficient Fault-Tolerant Multicast Scheme for Hypercube Multicomputers," IEEE Transactions on Parallel and Distributed Systems, vol. 9, no. 10, pp. 952-962, 1998. 821-829 3. K. Day and A. Al-Ayyoub, "The Cross Product of Interconnection Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 2, pp. 109-118, 1997. 4. R. Klasing, "Improved Compressions of CubeConnected Cycles Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 19, no. 8, pp. 803-812, 1998. 5. T. Leighton, Introduction to Parallel Algorithms and Architectures: Arrays, Trees, and Hypercubes, Morgan Kaufmann, 1992. 6. M. Quinn, Parallel Computing: Theory and Practice, McGraw Hill, 1994. 7. Y. Saad and M. Schultz, "Topological Properties of the Hypercube," IEEE Transactions on Computers, vol. C-37, no. 7, pp. 867- 872, 1988. 8. V. Sharma and E. Varvarigos, "Circuit Switching with Input Queuing: An Analysis for the dDimensional Wraparound Mesh and the Hypercube," IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 4, pp. 349-366, 1997. 9. L. Bhuyan and D. Agrawal, "Generalized Hypercube and Hyperbus Structures for a Computer Network," IEEE Transactions on Computers, vol. C-33, no. 4, pp. 323-333, 1984. 10. F. Preparata and J. Vuillemin, "The Cube-Connected Cycles: A Versatile Network for Parallel Computation," Communications of the ACM, vol. 24, no. 5, pp. 3000-309, 1981. 11. El-Amaway and S. Latifi, "Properties and Performance of Folded Hypercubes," IEEE Transactions on Parallel and Distributed Systems, vol. 2, no. 1, pp. 31-42, 19991. 12. Youssef and B. Narahari, "The BanyanHypercube Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 1, no. 2, pp. 160-169, 1990. 13. S. Zheng, B. Cong, and S. Bettayeb, "The StarHypercube Hybrid Interconnection Networks," Proceedings of the ISCA International Conference on Computer Application in Design, Simulation, and Analysis, pp. 98-101, 1993. 14. E. Abuelrub, "Parallel Computation on Twisted Hypercubes," Al-Manarah Journal, vol. 5, no. 1, pp. 1-10, 2002. 15. E. Abuelrub, "Embedding Quad Trees into Twisted Hypercubes," Proceedings of the 2nd IASTED International Conference on Parallel and Distributed Systems, pp. 155-160, 1998. 16. E. Abuelrub and S. Bettayeb, "Embedding Rings into Faulty Twisted Hypercubes," Computers and Artificial Intelligence, vol. 16, no. 4, pp. 425-441, 1997. 17. K. Efe, "The Crossed Cube Architecture for Parallel Computation," IEEE Transactions on Parallel and Distributed Systems, vol. 3, no. 5, pp. 513-524, 1992. 18. W. Huang, J. Tan, C. Hung, and L. Hsu, "FaultTolerant Hamiltonicity of Twisted Cubes," Journal of Parallel and Distributed Computing, vol. 62, pp. 591-604, 2002. 19. P. Kulasinghe and S. Bettayeb, "Embedding Binary Trees into Crossed Cubes," IEEE Transactions on Computers, vol. 44, no. 7, pp. 923-929, 1995. 20. P. Kulasinghe and S. Bettayeb, "The MultiplyTwisted Hypercube with 5 or more Dimensions is not Edge-Transitive," Information Processing Letters, vol. 53, pp. 33-36, 1995. 21. Awwad and J. Al-Sadi, "On the Routing of the OTIS-Cube Network in the presence of Faults," The International Arab Journal of Information Technology, vol. 2, no. 1, pp. 17-23, January 2005. 22. Decayeux and D. Seme, "3D Hexagonal Network: Modeling, Topological Properties, Addressing Schemes, and Optimal Routing Algorithm," IEEE Transactions on Parallel and Distributed Systems, vol. 16, no. 9, pp. 875-884, September 2005. 23. J. Fu and G Chen, "Hamiltonicity of the Hierarchical Cubic Network," Theory of Computer Systems, vol. 35, pp. 59-79, 2002. 24. R. Lander abd M. Fischer, "Parallel Prefix Computation," Journal of the ACM, vol. 27, pp. 831- 838, 1980 Authors: Ch. Srigiri, K. V. Lalitha, T V Prasad, S. Krishna Vamsi

Paper Title: Industry Fire Safety System using Embedded Technology with Internet of Things Abstract: This paper keeps tabs to the security also security of the article of clothing plant disappointments and outrage on his/her staff need getting to be a most amazing issue currently a times. Those articles of clothing plant workers face a considerable measure about issues and broken crazy of chimney a standout amongst them beyond any doubt. Those depositors aren’t demonstrating to whatever enthusiasm toward this segment and fact that this division may be getting toner. In this examine a chimney identification system may be propounded and conjointly gives data of the area influenced. Here we utilized ARM7 which are inserted with diverse sorts from the sensors. We give acceptable connect verification system to Abstain from cautioning. The system could right away send a SMS of the admin. Those admin will verify or deny the data. If those admin verify softening out about fire At that point system could immediately raise an alert and SMS will a chance to be sent of the close-by blaze unit.

Keyword: Fire safety, ARM7, ESP8266, sensors, authentication, GSM. References: 1. Sowah, Robert, et al. "Design and implementation of a fire detection and control system for automobiles using fuzzy logic." 140. Industry Applications Society Annual Meeting, 2016 IEEE. IEEE, 2016. 2. Nalajala, Paparao, et al. "Working Women Hand Held Safety Self Defense System Using IoT." (2017): 2051-2059. 830-833 3. Chen, Thou-Ho, et al. "The smoke detection for early fire-alarming system base on video processing." Intelligent Information Hiding and Multimedia Signal Processing, 2006. IIH-MSP'06. International Conference on. IEEE, 2006. 4. Fuzi, Mohd Faris Mohd, et al. "HOME FADS: A dedicated fire alert detection system using ZigBee wireless network." Control and System Graduate Research Colloquium (ICSGRC), 2014 IEEE 5th. IEEE, 2014. 5. Kwon, Oh-Hyun, Sung-Min Cho, and Sun-Myung Hwang. "Design and implementation of fire detection system." Advanced Software Engineering and Its Applications, 2008. ASEA 2008. IEEE, 2008. 6. Islam, Taoufikul, Hafiz Abdur Rahman, and Minhaz Ahmed Syrus. "Fire detection system with indoor localization using ZigBee based wireless sensor network." Informatics, Electronics & Vision (ICIEV), 2015 International Conference on. IEEE, 2015. 7. Paparao Nalajala, S Bhagya Lakshmi,”A Secured IoT Based Advanced Health Care System for Medical Field using Sensor Network”, international journal of engineering &Technlogoy , Vol. 7, Issue 2.20, (2018): 105-108. 8. Dong, Wen-hui, et al. "Design of wireless automatic fire alarm system." Procedia Engineering 135 (2016): 413-417. 9. Sun, Xiao-qian, and Ming-chun Luo. "Fire risk assessment for super high-rise buildings." Procedia engineering 71 (2014): 492- 501. 10. Godavarthi, Bhavana, Paparao Nalajala, and Vasavi Ganapuram. "Design and implementation of vehicle navigation system in urban environments using internet of things (IoT)." IOP Conference Series: Materials Science and Engineering. Vol. 225. No. 1. IOP Publishing, 2017. 11. Yu, Liyang, Neng Wang, and Xiaoqiao Meng. "Real-time forest fire detection with wireless sensor networks." Wireless Communications, Networking and Mobile Computing, 2005. Proceedings. 2005 International Conference on. Vol. 2. IEEE, 2005. Authors: Sasmita Nayak, Neeraj Kumar, B. Choudhury Selection of Commercial Robots with Anticipated Cost and Design Specifications using Regression Paper Title: Models Abstract: The selection of robots used for industry purpose is a crucial practice where various parameters have to be considered during appropriate selection process. The decision strategy of robot selection has a potential research direction to justify the necessity of industrial needs. We have compared three different mathematical models and selected the best method for choosing the industrial robot to provide a complete 141. selection framework to the present article. Principal Component Regression (PCR), Partial Least Square Regression (PLSR) and Linear Regression using Feed Forward Neural Network (FNN) are the three mathematical models used to correlate input with output parameters. During the testing procedure, eleven 834-839 numbers of distinct parameters are considered to estimate the best possible rank selection. The strata or rank of the robot is approximated by utilizing the proposed algorithm. However, the most approved rank has met the desired genuinity for a targeted application. In addition to the mathematical methodologies applied here, the performance characteristics for selecting the robot is examined by assessment of statistical errors namely Mean Square Error (MSE), Root Mean Square Error (RMSE), and R-Squared Error (RSE).

Keyword: Robot selection, PLSR, FNN, PCR, Selection Framework, Robot parameters. References: 1. R.P. Paul, and Shimon Y. Nof, “Work Methods Measurement: A Comparison Between Robot and Human Task Performance”,Taylor&Francis,IFPR, Volume:17, Issue:3, Pages:277-303, 1979. 2. V.P. Agrawal and V.Kohli, S. Gupta, “Computer-Aided Robot Selection: the Multiple-Attribute Decision Making an Approach”,International Journal of Production Research, Volume:29, Issue:8, Pages: 1629-1644, 1991. 3. ŞenimÖzgürler, Ali F. Güneri,BahadırGülsün, OnurYılmaz,“Robot Selection for a Flexible Manufacturing System with AHP and TOPSISMethod”, 15th International Research Conference on TMT-2011, Prague, Czech-Republic, 2011. 4. M.Z. Rehman, N.M. Nawi, “The Effect of Adaptive Momentum in Improving Accuracy of Gradient Descent Backpropagation Algorithm on Classification Problems”, Springer-Verlag, Volume:179, Pages: 380-390, 2011. 5. G.H. Liang, and M.J. Wang, “A Fuzzy Multicriteria Decision-Making Approach for Robot Selection”,Robotics, and Computer-Aided Manufacturing, Volume:10, Pages: 267-274, 1993. 6. M. Vukobratovic, “Scientific Fundamentals of Industrial Robots1: Dynamics of Manipulator Robots Theory and Applications”,Springer-Verlag Publication, New York, 1982. 7. M. Khouja, “The Use of Data Envelopment Analysis for Technology Selection”, Computer Industrial Eng., Volume:28, Pages: 123- 132, 1995. 8. T.C. Chu, and Y.C. Lin, “A Fuzzy-TOPSIS Method for Robot Selection”,International Journal of Advanced Manufacturing Technology, Volume:21, Pages: 284-290, 2003. 9. C. Parkan, M.L. Wu, “Decision-Making and Performance Measurement Models with Applications to Robot Selection”,Computer Industrial. Eng., Volume:36, Issue:3, Pages: 503-523, 1999. 10. R.V. Rao, K.K. Padmanabhan, “Selection, Identification and Comparison of Industrial Robots Using Digraph andMatrix Methods”,Elsevier, Robotics, and Computer Integrated Manufacturing, Volume:22, Issue:4, Pages: 373-383, 2006. 11. SuprakashMondal, S.Chakraborty, “A Solution to Robot Selection Problems Using Data Envelopment Analysis”, International Journal of Ind. Eng. Computations, Volume:4, Issue:3, Pages:355-372, 2013. 12. Varun K. Nagaraja,Wael Abd-Almageed, "Feature Selection using Partial Least Squares regression and optimal experiment design", International Joint Conference on Neural Networks (IJCNN), Pages:1-8, 2015. 13. Chu TC, Lin YC, "A fuzzy TOPSIS method for robot selection", International Journal of Advanced Manufacturing Technology, Volume 21, pages: 284–290, 2003. 14. Nicole Kr¨amer, Masashi Sugiyama, The Degrees of Freedom of Partial Least Squares Regression, Journal of the American Statistical Association, Page: 1-23, 2011. 15. B. Efron, The Estimation of Prediction Error: Covariance Penalties and Cross-Validation. Journal of the American Statistical Association, 99(467):619–633, 2004. 16. I. Frank, and J. Friedman, A Statistical View of Some Chemometrics Regression Tools. Technometrics, 35(2):109–135, 1993. 17. Carsten Neumann, Michael Förster, Birgit Kleinschmit, SibylleItzerott, Utilizing a PLSR-Based Band-Selection Procedure for Spectral Feature Characterization of Floristic Gradients, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume: 9, Issue: 9, Pages:3982 - 3996, Sept. 2016. 18. Nayak S., Choudhury B.B., Lenka S.K. Gradient Descent with Momentum Based Backpropagation Neural Network for Selection of Industrial Robot. In: Satapathy S., Das S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 1. Smart Innovation, Systems and Technologies, vol 50. Springer, 2016. Authors: Saravanan.K, Senthil Kumar Balakrishnan

Paper Title: Key Factors & Features Influencing Selection of Open Source Functional Test Automation Tools Abstract: Software Testing is an integral part of high quality software development process. To enhance quality, IT Companies are spending huge amount of money, labor and time on testing efforts. Test Automation tools help speed up testing effort, improve quality and also reduce cost in the long run. Currently, a combination of Open Source and Commercial Test Automation tools are employed to perform Functional Testing activities. With wide adoption of tools like Selenium, Open Source Functional Test Automation tools are accepted as a viable alternative for Commercial Tools. Professionals involved in the selection and purchase of a new Test Automation Tool or replace an existing tool are reviewing and analyzing various factors and features that drive them to select a particular tool. Research Reports, Tool Adoption Trends in Industry and Comparative review of various Test Automation Tools are some of the sources for them to guide their tool selection decision. As Open Source tools are accepted as viable alternative to Commercial tools and are highly economical, an empirical assessment focusing on the factors and features influencing the selection of these Open Source Functional Test 142. Automation tools is attempted. This research aims in identifying the key factors and features that influence the selection of these tools by surveying IT Companies located in India who have already adopted these tools. 840-843 Keyword: Open Source Test Automation Tools, Selenium, Software Test Automation. References: 1. Glenford J.Myers, The Art of Software Testing, Second Edition, 2004 2. Rex Black, Critical Testing Processes, 2004 3. Allah Bachayo Brohi, Pinial Khan Butt, Shaobo Zhang, Software quality Assurance: Tools and Techniques, 2019 4. Ramli, Ramona & Ismail, Roslan & Ahmad, Abdul, Evaluating and selecting software testing tools: a case study, 2014 5. Harsh Bajaj, Choosing the right automation tool and framework is critical to project Success, 2018 6. Joachim Herschmann, Thomas E. Murphy, “Magic Quadrant for Software Test Automation”, 27 November 2018 - ID G00347980 7. Joachim Herschmann, Thomas E. Murphy, “Magic Quadrant for Software Test Automation”, 20 November 2017 ID: G00320337 8. Dimensional research. Testing trends in 2017: A Survey of software Professionals, January 2017 9. Diego Lo Giudice with Christopher Mines and Sara Sjoblom, “The Forrester WaveTM: Modern Application Functional Test Automation Tools, Q4 2016”, December 5, 2016 10. Dhanavandan S, Application of garret ranking Technique: Practical approach, International Journal of Library and Information Studies, Vol. 6(3) Jul-Sep, 2016 Authors: Sibu C. Chithran, K.S.Chandrasekar 143. Paper Title: Development of Performance Evaluation Model for Public Sector Industrial Organizations in Kerala Abstract: The performance of public sector industrial organizations always occupies in the front page of newspapers and headlines among mass media. The public sector industrial organizations in Kerala, in fact, suffer from various problems all the time. The aim of the study was to examine the systems of performance evaluation existing in the various public sector industrial organizations under manufacturing sector in Kerala and to identify the relevant criteria for establishing an objective performance evaluation system and to develop a model for proper evaluation. An attempt was also made to highlight the real problems with a view to suggest remedial measures. To achieve the objectives an extensive in-depth literature review as well as an elaborate field survey were carried out. For the investigation in the field, 18 industrial organizations from among 42 existing public sector industrial organizations in Kerala under manufacturing sector were selected and with the help of a set of structured questionnaires/interview schedules, the required data for the purpose were collected through personal interviews and discussions with the concerned managing directors/chief executives and department heads of the organizations. The data collected were analyzed scientifically using appropriate statistical tolls and interpreted. The findings thus obtained were made along with the respective recommendations.

Keyword: Performance Evaluation, Public Sector Industrial Organizations, Manufacturing Sector, Corporate Management, Model Development References: 1. “A Review of Public Enterprises in Kerala”, Bureau of Public Enterprises, Government of Kerala, 1995-2004. 2. Altman Edward, “Corporate Bankruptcy Prediction and its Implications for Commercial Loan Evaluation”, The Journal of Commercial Bank Lending, December 1970. 3. Altman Edward, “Financial Ratios, Discriminant Analysis and Prediction of Corporate Bankruptcy”, The Journal of Finance, Vol. 23, September 1970. 4. Beaver, H, “Financial Ratios as Predictors of Failure”, Empirical Research in Accounting – Selected Studies 1996, Institute of 844-854 Professional Accounting, January 1967. 5. Blum Marc, “The Failing Company Doctrine”, Unpublished PhD Dissertation, Columbia University, 1969. 6. “Britannica Ready Reference Encyclopaedia”, (Set of 10 Volumes), Encyclopaedia Britannica (India) Private Limited, 1999. 7. Edminister Robert, “Financial Ratios and Credit Scoring for Small Business Loans”, The Journal of Commercial Bank Lending, September 1971. 8. Edminister Robert, “Financial Ratios as Discriminant Predictors of Small Business Failure”, Unpublished PhD Dissertation, The Ohio State University, 1970. 9. Ewert David, “Trade Credit Management: Selection of Accounts Receivables using Statistical Model”, Unpublished PhD Dissertation, Stanford University, 1968. 10. Finnerty John D, “Corporate Financial Analysis”, McGraw-Hill International Editions, Singapore, 1986. 11. Hickman W.B, “Corporate Bond Quality and Investor Experience”, Princeton University Press, Princeton, 1958. 12. Johnson Craig G, “Ratio Analysis and the Prediction of Firm Failure”, The Journal of Finance, December 1970. 13. Marwin C, “Financing Small Corporations, New York”, Bureau of Economic Research, 1942. 14. May O. George, “Truth in Accounting”, University of Pennsylvania Press, Philadelphia. 15. Robert Morris Associates (RMA), Annual Statement Studies, Philadelphia: 1958-66. 16. Sapru R.K, “Management of Public Sector Enterprises in India”, (Set of 2 Volumes), Ashish Publishing House, 1987. 17. Smith R.F & Wincar A.H, “Changes in the Financial Structure of Unsuccessful Corporations”, University of Illinois, Bureau of Business Research, 1935. 18. Srinivasan R, “Strategic Management: The Indian Context”, Prentice-Hall of India Private Limited, 2002. 19. Trivedi P & Gopal V, “MOU and Other Performance Improvement Systems – A Comparison”, Public Enterprise ICP, Ljubljana, 1990. 20. Trivedi P & Vithal H.P, “Menu of Financial Indicator used in MOUs: An Exercise in Clarification”, Working Paper Series, Indian Institute of Management, Kolkata, 1992 21. Trivedi Prajapati (Ed), “Memorandum of Understanding – An Approach to Improving Public Enterprise Performance”, International Management Publishers, New Delhi, 1990. 22. Zeppou M & Sotiraku T, “The STAIR Model: A Comprehensive Approach for Managing and Measuring Government Performance in the Post-Modern Era”, International Journal of Public Sector Management, Vol: 6, No: 4, 2003. Authors: Inbalatha.K, Palaniswamy K.M

Paper Title: Intellectual Green Corridor for Crisis Wellbeing Transference Abstract: Traffic is a major concern for most of the metropolitan cities of the world. The design proposes a notion for Traffic Control System which is more imaginativethan currently existing schemes.The system automatically affords a distinctive lane in which entirely the red signal indication will be turned spontaneously to green intended for the ambulance. Subsequently this assists the ambulance instantly in reaching its destination within stint.In accumulation to the Traffic Control Scheme, wellbeing specialist care Scheme displays the patient long-suffering state of affairs resembling heartbeat, blood pressure. This system comprises of dedicated intellectual smart ambulance with GPS, GSM and smart mobile solicitation beside with Internet of Things 144. (IoT).The patient’s state of affairs will be directed to the medical wingover cloud.The information of the patient is sent to the hospital via GSM module and blood bank gets information only if the condition is chosen as serious. The projected effort stays targeted to plan and progress an operative traffic control scheme for smart 855-859 ambulance. The outcomes of the recommended traffic control model transports upright decline of time by clearing the traffic very fast and protect the patient’s lifespan at the most primitive.

Keyword: Blood pressure, Internet of Things, Metropolitan, Smart Ambulance References: 1. Wenwen Kang et.al, “Traffic Signal Coordination for Emergency Vehicles”, 2014 IEEE 17th International Conference on Intelligent Transport Systems (ITSC) October 2014, Qingdao China. 2. S. Pradeep Kumar et.al, “Call Ambulance Smart Elderly Monitoring System with Nearest Ambulance Detection using Android and Bluetooth”, 2016 IEEE Second International Conference on Science and Technology Engineering and Management. 3. G.Beri and P.Ganjare“Intelligent ambulance with traffic control” 3rd National Conference on Advancements in Communication, Computing and Electronic Technology[ACCET-2016] held at M.E.S. College of Engineering, Pune 11-12, February 2016. 4. Rajeshwari S et.al, “Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance and Stolen Vehicle Detection”,2014 IEEE Sensors Journals. 5. OmkarUdawantet.al,“Smart Ambulance System using IoT”, International Conference on Big Data, IoT and Data Science (BID)Vishwakarma Institute of Technology, Pune, Dec 2017 6. Liang Qi et.al, “A Two-level Traffic Light Control Strategy for Preventing Incident-Based Urban Traffic Congestion”,2016 IEEE transactions on Intelligent Transport Systems. 7. Abdullahi Chowdhury et.al,“Priority Based and Secured Traffic Management System for Emergency Vehicle using IoT”, Faculty of Science and Technology Federation University Australia 2015. 8. SabeenJavaid et.al, “Smart Traffic Management System using Internet of Things”, 2018 20th International Conference on Advanced Communication Technology (ICACT). 9. HoomanSamani et.al, “Robotic Automated External of the Defibrillator Ambulance for Emergency Medical Service in Smart Cities”,2015 IEEE Access Journal. 10. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "A Dynamic MooM Dataset Processing Under TelMED Protocol Design for QoS Improvisation of Telemedicine Environment." Journal of medical systems 43, no. 8 (2019): 257. 11. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "An Optimized RTSRV Machine Learning Algorithm for Biomedical Signal Transmission and Regeneration for Telemedicine Environment." Procedia Computer Science 152 (2019): 140- 149. 12. Patil, Kiran Kumari, and Syed Thouheed Ahmed. "Digital telemammography services for rural India, software components and design protocol." In 2014 International Conference on Advances in Electronics Computers and Communications, pp. 1-5. IEEE, 2014. 13. Thouheed, Syed, S. Ahmed, M. Sandhya, and S. Shankar. "ICT’s Role in Building and Understanding Indian Telemedicine Environment: A Study." In Information and Communication Technology for Competitive Strategies. Lecture Notes in Networks and Systems, vol 40. Springer Singapore, 2019. Authors: Sreedhar Kumar S, Syed Thouheed Ahmed, Nisha Bai, Vınutha B A Type of Supervised Text Classification System for Unstructured Text Comments using Probability Paper Title: Theory Technique Abstract: In this paper, an improved sentimental text analysis system called Probability Based Text Classifier (PBTC) is presented. It aims to train the existing unstructured text command set and to classify the sampled text command belongs into positive or negative polarity based on probability theory and supervised concepts. It consists of three stages pre-processed, training and classification. In the first stage, the proposed (PBTC) system identifies the relevant and irrelevant words in the unstructured text command set based on pre- determined text pattern model. In the second stage it identifies two dissimilar classes over the preprocessed text command set based on predetermined text pattern model and simple probability theory concepts. Next stage, the PBTC identifies the sample test text command without class label belong on which class based on Naive Bayer scheme and trained existing text command set. Experimental result shows that the proposed (PBTC) system is well suitable to train the unstructured text command set and classify the new text command belongs into positive or negative polarity with higher accuracy

Keyword: Classifier; Probability Based Text Classifier; Unstructured Text Command; Text Pattern; Supervised; Sentimental Analysis. References: 1. Hobbs Jerry R, Walker Donald E, Amsler Robert A, “ Natural Language Access to Structured Text,” Proceeding of the 9th conference on computational linguistics (COLING’82), PP. 127-132, 1982. 2. https://en.wikipedia.org/wiki/Sentiment_analysis 3. Jayasanka, Sachira & Madhushani, Thilina & R. Marcus, E & A. A. U. Aberathne, I & Premaratne, Saminda. “Sentiment 145. Analysis for Social Media”, Information Technology Research Symposium, Volume: 4, 2013. 4. Krishnamoorthy R, Sreedhar Kumar S, “An improved agglomerative clustering algorithm for outlier detection ”, Applied Mathematics and Information Science, vol. 10, no. 3, pp. 1141-1154, 2016. 860-866 5. Sreedhar Kumar S, Madheswaran M, Vinutha B A, Manjunatha Singh H, Charan K V, “A brief survey of unsupervised agglomerative hierarchical clustering schemes,” International Journal of Engineering & Technology (UAE), vol. 8, no. 1, pp. 29- 37, 2019. 6. Ismail, Heba M., Saad Harous and Boumediene Belkhouche. “A Comparative Analysis of Machine Learning Classifiers for Twitter Sentiment Analysis”, Research in Computer Science, vol. 110, pp. 71-83, 2016 7. Mehra R, Bedi M K, Singh G, Arora R, Bala T and Saxena S, "Sentimental analysis using fuzzy and naive bayes", International Conference on Computing Methodologies and Communication (ICCMC), Erode, pp. 945-950, 2017. 8. Ranganathan, Jaishree & S. Irudayaraj, Allen & Tzacheva, Angelina. “Action Rules for Sentiment Analysis on Twitter Data Using Spark”, IEEE International Conference on Data Mining Workshops (ICDMW), 2017, DOI: 10.1109/ICDMW.2017.14. 9. Trupthi M, Pabboju S, Narasimha G ,“Sentiment analysis on twitter using streaming API”, IEEE 7th International Advance Computing Conference (IACC), 2017. 10. Ragupathy R, Lakshmana Phaneendra Maguluri, “ Comparative analysis of machine learning algorithm on social media test,” vol. 7, no. 2.8, pp. 284-290, 2018. 11. Akshi Kumar, Teeja Mary Sebastian, “Sentiment Analysis on Twitter”, International Journal of Computer Science Issues, vol. 9, no. 4, pp 372-378, 2012 12. Nakov, P., Ritter, A., Rosenthal, S., Sebastiani, F. and Stoyanov, V, “SemEval-2016 task 4: Sentiment analysis in Twitter”, In Proceedings of the 10th international workshop on semantic evaluation (semeval-2016) ,pp. 1-18, 2016. 13. Gautam, Geetika & Yadav, Divakar, “Sentiment Analysis of Twitter Data Using Machine Learning Approaches and Semantic Analysis”, 7th International Conference on Contemporary Computing, 10.1109/IC3.2014.6897213. 14. Abdeljalil Elouardighi, Mohcine Maghfour, Hafdalla Hammia, Fatima-zahra Aazi. “A machine Learning approach for sentiment analysis in the standard or dialectal Arabic Facebook comments”, 3rd international conference on Cloud Technologies and Applications (CloudTech), 2016. 15. Apoorv Agarwal, Boyi Xie, Ilia Vovsha, Owen Rambow, Rebecca Passonneau, “Sentiment analysis of twitter data”. Proceedings of the Workshop on Language in Social Media (LSM 2011), pp. 30–38, 23rd June 2011. 16. Vishal.A.Kharde, Prof. Sheetal.Sonawane, “Sentiment analysis of twitter data: a survey of techniques”, International Journal of Computer Applications , pp 5-15, DOI:10.5120/ijca2016908625, April 2016. 17. Tang D, Wei F, Yang N, Zhou M, Liu T, Qin B. “Learning sentiment-specific word embedding for twitter sentiment classification”, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, pp. 1555–1565, 25th June 2014. 18. M. S. Neethu and R. Rajasree, "Sentiment analysis in twitter using machine learning techniques," Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), Tiruchengode, pp. 1-5, 2013. 19. Grabber D., Zanier M., Fliedl G., Fuchs M, “Classification of Customer Reviews based on Sentiment Analysis”, Information and Communication Technologies in Tourism , pp 460-470, 2012. 20. Abbasi, Ahmed, Ammar Hassan and Milan Dhar. “Benchmarking Twitter Sentiment Analysis Tools.” Language Resources and Evaluation Conference, 2014. 21. Ranganathan, Jaishree & S. Irudayaraj, Allen & Tzacheva, Angelina., “Action Rules for Sentiment Analysis on Twitter Data Using Spark”, IEEE International Conference on Data Mining Workshops (ICDMW), pp 51-60, 2017. DOI: 10.1109/ICDMW.2017.14. 22. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "A Dynamic MooM Dataset Processing Under TelMED Protocol Design for QoS Improvisation of Telemedicine Environment." Journal of medical systems 43, no. 8 (2019): 257. 23. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "An Optimized RTSRV Machine Learning Algorithm for Biomedical Signal Transmission and Regeneration for Telemedicine Environment." Procedia Computer Science 152 (2019): 140- 149. 24. Patil, Kiran Kumari, and Syed Thouheed Ahmed. "Digital telemammography services for rural India, software components and design protocol." In 2014 International Conference on Advances in Electronics Computers and Communications, pp. 1-5. IEEE, 2014. 25. Thouheed, Syed, S. Ahmed, M. Sandhya, and S. Shankar. "ICT’s Role in Building and Understanding Indian Telemedicine Environment: A Study." In Information and Communication Technology for Competitive Strategies. Lecture Notes in Networks and Systems, vol 40. Springer Singapore, 2019. Authors: J Subba Raju, Basavaraju S

Paper Title: Structural Parameters and Working Range Estimation of Excavator Backhoe Mechanism Abstract: Earthmoving machines like excavators and loaders characteristics such as productivity, weight, reliability depend on their backhoe mechanism. For that, the backhoe mechanism has to deliver the desired working range, digging forces and stability which are dependent on structural parameters like components length and joint angles. This paper describes the method of developing a backhoe mechanism for the desired working range which constitutes cutting heights and reaches by using structural parameters. This requires to develop forward kinematical model by considering the backhoe mechanism as a mechanical manipulator. A computer algorithm was developed, that uses the forward kinematic model, to estimate the working range. Also, a relationship is established between joint angles and cylinder lengths. Results of Virtual prototype, modeled and simulated in MSC ADAMS along with the testing results of BEML designed Physical prototype were used to validate the working range and structural parameters. This research provides a solid foundation for analyzing the effect of structural parameters on digging forces and stability.

Keyword: Earthmoving machine, Backhoe mechanism, Structural parameters, Working range. References: 1. P. K. Vähä and M. J. Skibniewski, “Dynamic Model of Excavator,” Journal of Aerospace Engineering, vol. 6, no. 2, pp. 148– 158, 1993. 2. J. Koivo, “Kinematics of Excavators (Backhoes) for Transferring Surface Material,” Journal of Aerospace Engineering, vol. 7, no. 1, pp. 17–32, 1994. 3. J. Koivo, M. Thoma, E. Kocaoglan, and J. Andrade-Cetto, “Modeling and Control of Excavator Dynamics during Digging 146. Operation,” Journal of Aerospace Engineering, vol. 9, no. 1, pp. 10–18, 1996. 4. F. Hofstra, A. J. M. V. Hemmen, S. Miedema, and J. V. Hulsteyn, “Describing the position of backhoe dredge buckets,” 2000. 5. S. Rao and P. Bhatti, “Probabilistic approach to manipulator kinematics and dynamics,” Reliability Engineering & System Safety, 867-872 vol. 72, no. 1, pp. 47–58, 2001. 6. S. Frimpong and Y. Li, “Virtual prototype simulation of hydraulic shovel kinematics for spatial characterization in surface mining operations,” International Journal of Surface Mining, Reclamation and Environment, vol. 19, no. 4, pp. 238–250, 2005. 7. N. Demirel and S. Frimpong, “Dragline dynamic modelling for efficient excavation,” International Journal of Mining, Reclamation and Environment, vol. 23, no. 1, pp. 4–20, 2009. 8. J. Xu and H.-S. Yoon, “A Review on Mechanical and Hydraulic System Modeling of Excavator Manipulator System,” Journal of Construction Engineering, vol. 2016, pp. 1–11, 2016. 9. H. Yu, Y. Liu, and M. S. Hasan, “Review of modelling and remote control for excavators,” International Journal of Advanced Mechatronic Systems, vol. 2, no. 1/2, p. 68, 2010. 10. C. Xiao and G. Zhang, “Dynamic Simulation Analysis of Working Device for Hydraulic Excavator Based on ADAMS,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 14, no. 3A, p. 194, 2016. 11. Y. Li and W. Y. Liu, “Spatial Kinematics Modeling and Simulation of Wheel Loader,” Journal of Modeling, Simulation, Identification, and Control, vol. 1, no. 2, pp. 78–88, Feb. 2013. 12. Y. Li, S.-S. Chang, and W. Liu, “Spatial kinematics and virtual prototype modeling of Bucyrus shovel,” The International Journal of Advanced Manufacturing Technology, vol. 69, no. 5-8, pp. 1917–1925, 2013. 26. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "A Dynamic MooM Dataset Processing Under TelMED Protocol Design for QoS Improvisation of Telemedicine Environment." Journal of medical systems 43, no. 8 (2019): 257. 27. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "An Optimized RTSRV Machine Learning Algorithm for Biomedical Signal Transmission and Regeneration for Telemedicine Environment." Procedia Computer Science 152 (2019): 140- 149. 28. Patil, Kiran Kumari, and Syed Thouheed Ahmed. "Digital telemammography services for rural India, software components and design protocol." In 2014 International Conference on Advances in Electronics Computers and Communications, pp. 1-5. IEEE, 2014. 29. Thouheed, Syed, S. Ahmed, M. Sandhya, and S. Shankar. "ICT’s Role in Building and Understanding Indian Telemedicine Environment: A Study." In Information and Communication Technology for Competitive Strategies. Lecture Notes in Networks and Systems, vol 40. Springer Singapore, 2019. Authors: Pawan Kumar Tanwar, Ajay Khunteta, Vishal Goar 147. Paper Title: Applying Multi Property Tree for Multi Keyword Rank Searching and Dynamic Update in Cloud Abstract: Various types of data structures are used for keyword searching like binary tee, KBB tree, inverted tree, inverted index, Multi Property Tree (MPT). These data structures are used for searching keywords in cloud space after getting instructions from data user. On the basis of MPT data structure the authors have introduced a search scheme called MPTsearch algorithm. Experiments show that the proposed scheme performs better than linear search. It also achieves lower time consumption and computing overhead for queries and trapdoor formation. Moreover this scheme not only fulfills the searching part but also plays vital role in dynamic update (insertion and deletion) of data provided by the data owner.

Keyword: Multi Property Tree, MPTsearch algorithm, dynamic update. References: 70. Perrig, D. Wagner and D. X. Song ‘‘Practical techniques for searches on encrypted data,’’ In the Proc. of ieee sympo. for Sec. and Priva., Berkeley, USA, May 2000, pp. 44-55. 71. W. Jonker, Hartel P. and R. Brinkman, “Conjunctive wildcard search over encrypted data,” In the proceedings of workshop for secure data management, Seattle, USA, 2011, pp. 114-27. 72. R. Ostrovsky, S. Kamara, J. Garay and R. Curtmola, “Searchable symmetric ncryption: Improved definitions and efficient constructions,” Jou. of Comp. Sec., volume 19, number 5, pp. 895-934, Jan. 2011. 73. G. Persiano, R. Ostrovsky, G. Di Crescenzo and D. Boneh, “Public key encryption with keyword search”, in Proceedings of euro crypt, Switzerland, 2004, pp. 506-22. 74. Waters, Shi E. and E. Shen, “Predicate privacy in encryption systems”, in Th. of Crypt., San Francisco, USA, Springer, 2009, pp. 457- 73. 75. B. Waters and D. Boneh, “Conjunctive subset and range queries on encrypted data,” In the Proceedings of Theory crypt. Conference, The Netherlands, 2007, pp. 535-54. 76. F. Monrose, Kamara S. and L. Ballard, “Achieving efficient conjunctive keyword searches over encrypted data,” in the proceedings of International Conference for Info. and Comm. Sec., China, 2005, pp. 414-26. 77. P. J. Lee, D. J. Park and K. Kim, “Public key encryption with conjunctive field keyword search,” in Proceedings of Int. workshop of Info. Sec. Application, South Korea, 2004, pp. 73-86. 78. P. J. Lee and Y. H. Hwang, “Public key encryption with conjunctive keyword search and its extension to a multi- user system,” In Proc. 873-875 of Int. Conf. of Pairing Based Crypt., Tokyo, Japan, 2007, pp. 2-22. 79. J. Chen, L. Zhu and C. Liu, “Efficient searchable symmetric encryption for storing multiple source data on cloud,” in the proceedings of IEEE trust com / Big Data SE/ISPA, FINLAND, August 2015, pp. 451-58. 80. S. Zhou, J. Wu, Lin Y., Xiao S. and W. Zhang, “Privacy preserving ranked multi keyword search for multiple data owners in cloud computing,” ieee Transaction for Computing, volume 65, number. 5, pp. 1566-77, May 2016. 81. Waters, Sahai A. & J. Katz, “Predicate encryption supporting disjunctions, polynomial equations, and inner products,” In proceedings of International Conference, Theory Application Cryptography Tech., Turkey, 2008, pp. 146-62. 82. B. Waters, Staddon J. & P. Golle, “Secure conjunctive keyword search over encrypted data,” In the proceedings of International Conference, Application of Crypt. and Network Sec., Heidelberg, Germany, 2004, pp. 31-45. 83. W. Lou, K. Ren, M. Li, C. Wang and N. Cao, “Privacy-preserving multi-keyword ranked search over encrypted cloud data” in Proceedings of ieee infocom, shanghai, China, Apr. 2011, pp. 829-37. 84. Q. Wang, X. Sun, X. Wang and Z. Xia, “A secure and dynamic multi keyword ranked search scheme over encrypted cloud data,” Ieee Transaction for Para. Distr. Sys., volume 27, Number 2, pp. 340-52, Jan. 2016. 85. Roeder, Papamanthou C. & S. Kamara, “Dynamic searchable symmetric encrypt.”, in proceedings of ACM Conf. for Comp. and Communication System, Raleigh,USA, 2012, pp. 965-76. 86. Papamanthou and Kamara S., “Parallel and dynamic searchable symmetric encryption,” in proceedings of Int. Conf. for Fin. Crypt. & Data Sec., 2013, pp. 258-74. 87. Liu X. F., Quan H. Y., Y. Q. Zhang and L. L. Zhang ‘‘Efficient conjunctive keyword search over encrypted medical records,” (Chinese), J. Software, vol. 27, no. 6, pp. 1577-91, June 2016 88. W. Sun et al., “Privacy preserving multi-keyword text search in the cloud supporting similarity-based ranking,” in proceed. of ASIACCS, Hangzhou, China, 2013, pp. 71–82 89. Y. T. Hou, W. Lou, H. Li and W. Sun, “Privacy preserving keyword search over encrypted data in cloud computing,” in secure cloud computing, USA: Springer-Verlag, 2014, pp. 189–212 90. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Design of new multi keyword ranked search scheme and validation for cloud computing,” in proc. of AICTC - 16, Aug. 12 &13, 2016, Bikaner, India 91. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Performance evaluation of multi keyword ranked search schema 92. called BDMRS-CM & EDMRS-BM in cloud computing”, An Int. Journal of Engg. Sci., Issue July 2017, Vol. 24 pp 42-51 93. Tanwar Pawan Kumar, Goar Vishal, Khunteta Ajay, “Design and Analysis of Search Algorithm with B-tree and Commutative key RSA for dynamic Updation in Cloud Computing”, IJCAR (Int. Journal of Current Adv. Research) Vol 7, Issue 7(H), pp 14414-418, July 2018 Authors: D. Sowmya, R. Praveen Sam, K. Govardhan Reddy

Paper Title: Smart Water Dripping System for Agriculture/ Farming Abstract: The main work uses an ARDUINO microcontroller that is programmed to obtain the input signal of varying moisture condition of the soil through the sensing association. Soil sensor is done by way of usage of an op-amp as a comparator which acts as an interface among the sensing arrangement and the microcontroller. Once the controller receives this sign, it generates an output that drives a relay for running the water pump. An LCD show is also interfaced to the microcontroller to show repute of the soil, temperature, PH, WIFI and water pump. 148. Water shortage has been massive trouble for agriculture. This proposed concept is beneficial to the farmers to irrigate the farms successfully the usage of an electronic irrigation gadget based totally on soil temperature, 876-881 moisture and pH. Respective sensors are used to locate the soil water content material stage and based on this, and microcontroller drives the servo motor and pump. Irrigation fame is up to date to the database the use of PC. This method works utilizing putting in sensors within the subject to monitor the soil temperature, moisture and kind of soil, which transmits the data to the microcontroller for estimation of the correct amount of water as according to the requirements. The accumulated data is updated sometimes to the server and may be accessed through an Android app. The next watering of plant life may be managed the usage of the aforementioned app. Depending upon the form of soil and crop, the fertilizers are recommended by means of applying Naïve Bayes set of rules at the database. The estimated quantity of rain is predicted using weather forecasting using Web scraper, and the plants are watered for this reason, i.e., is a heavy rainfall is predicted then the device will routinely reduce the water supplied to the plants.

Keyword: ARDUINO LCD show PH, WIFI References: 1. V. B. Shinde and S. S. Wandre, “Solar photovoltaic water pumping system for irrigation: A review”, African Journal of Agricultural Research, Vol. 10, pp. 2267-2273, 2015. DOI -10.5897/AJAR2015.9879 2. Mohanlal Kolhe, J. C. Joshi and D. P. Kothari, “Performance Analysis of a Directly Coupled Photovoltaic Water-Pumping System”, IEEE Trans. on energy conversion, Vol. 19, pp. 613-618, 2004. DOI - 10.1109/TEC.2004.82703. 3. Nafisa Binte Yousuf, Khosru M. Salim, Rafid Haider, Md. Rajin Alam and Fatima Binte Zia, “Development of a Three Phase Induction Motor Controller for Solar Powered Water Pump”, 2nd International Conference on the Developments in Renewable Energy Technology (ICDRET), Jan. 2012. 4. J. V. Mapurunga Caracas, G. De Carvalho Farias, L. F. Moreira Teixeira and L. A. De Souza Ribeiro, “Implementation of a HighEfficiency, High-Lifetime, and Low-Cost Converter for an Autonomous Photovoltaic Water Pumping System”, IEEE Trans. on industry applications, Vol. 50, pp. 631-641, 2014. DOI - 10.1109/TIA.2013.2271214 5. R. Krishnan, “Electric Motor Drives: Analysis, Modeling and Control”, Prentice Hall Inc., New Jersey, 2001. 6. Rajan Kumar and Bhim Singh, “Solar PV Array Fed Cuk Converter-VSI Controlled BLDC Motor Drive for Water Pumping”, IEEE Power India International Conference (PIICON), Dec. 2014. DOI - 10.1109/POWERI.2014.7117669 7. Rajan Kumar and Bhim Singh, "Buck-Boost Converter Fed BLDC Motor Drive for Solar PV Array-Based Water Pumping", IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Dec. 2014 DOI - 10.1109/PEDES.2014.7042001 8. Henry Shu-Hung Chung, K. K. Tse, S. Y. Ron Hui, C. M. Mok and M. T. Ho, “A Novel Maximum Power Point Tracking Technique for Solar Panels Using a SEPIC or Cuk Converter”, IEEE Trans. on Power Electronics, Vol. 18, pp. 717-724, 2003. DOI - 10.1109/TPEL.2003.810841 9. Z. Hamidon, P. D. Abd. Aziz and N. H. Mohd Yunus, "Photovoltaic array modelling with P&O MPPT algorithm in MATLAB", International Conference on Statistics in Science, Business, and Engineering (ICSSBE), Sept. 2012. DOI - 10.1109/ICSSBE.2012.6396616 10. https://greenpeacechallenge.jovoto.com/ideas/32221 11. Muhammad H. Rashid, "Electric Renewable Energy Systems", Academic Press Inc, November 2015. 12. https://www.arduino.cc/en/Guide/Introduction Authors: Gajanan P. Mudholkar, Ram D. Kolhe

Paper Title: Marketing Strategies Adopted by Private Coaching Classes in Marathwada Region Abstract: In Today’s world everyone wants to excel in his /her life .To reach this goal of excellence one needs access to quality education. However, the present education system or schools of the country were unable to cater to the needs of the aspiring students so they were compelled to look for other alternative avenues and here come to the picture the private coaching classes and their importance in shaping the future of students. In the modern era, educational institutes have gone under various reforms. Also, there has been huge growth in this sector. Growth in India is especially due to growing need of importance and awareness of education. India is a developing country. Today we can see various private educational institutes providing various courses at various levels. And, it still has many untapped opportunities. Also, the aspiring students have become more aware and there have been development of private educational brands apart from government universities. In order to capitalise on the prevailing conditions and to make their presence felt the coaching institutes were adopting various methods and strategies and the current research is dedicated to analyse these Methods and strategies. The Indian education system is divided into two major segments core and non-core. While, the core group has schools and higher education, the non-core consists of pre-schools, vocational training and coaching classes. Increased college perseverance and completion, One such effort which is the focus of our paper has been the use of mentors and coaches to facilitate student persistence and completion. The education seekers have started 149. prioritizing their needs and wants. Hence, it has become important for educational institutes to be updated according to student and industry needs in order to prepare Industry Ready Professionals The purpose of the 882-886 study is to analyze students needs and attitude towards educational institutes. Since, fulfilling student’s needs is one of the major factors for private universities, in order to generate value education in society. Researcher wants to carry research on “Marketing Strategies Adopted by Private Coaching Classes in Nanded and Latur districts.”

Keyword: Marketing strategies, Coaching Classes, marketing of educational Institutes, E-Marketing, and Marketing Mix. References: 1. Keller P., & Fox K. (1995); Strategic Marketing for Educational Institutions (2nd ed.), Englewood Cliffs, N.J.: Prentice-Hall. 2. Al-Fattal, A. (2010); Understanding Student Choice of University and Marketing Strategies in Syrian Private Higher Education. Thesis: Doctor of Philosophy, School of Education, UK: University of Leeds. 3. Smith, P. R.& Taylor, J. (2004).Marketing Communications an Integrated Approach (4th Ed). London, UK: Kogan Page Limited. 4. Masterson, R. & Pickton, D. (2010); Marketing: An Introduction. London, UK: SAGE Publication. 5. Lovelock, C & Wright, L. (2010); Principles of Services Marketing and Management. New York, USA: Pearson Education, Inc. 6. Mukerjee, K. (2007); Customers Relationship Management: A Strategic Approach to Marketing. New Dehli, India: Prentice Hall. 7. Gibbs, P., & Knapp, M. (2002) ; Marketing Higher and Further Education: an Educator's Guide to Promoting Courses, Departments and Institutions. London: Kogan Page. 8. Wright, R. (1999); Marketing: Origins, Concepts and Environment. London: Business press . 9. http://notesdesk.com/notes/marketing/the-marketing-mix-4-ps-of-marketing/(25-01-2012 at 4:00 pm)

150. Authors: Ravikumar. J.S, Syed Mohammad Ghouse, T. Narayana Reddy Online Customer Comments and their Impact on Consumer Buying Behavior: Using Social Paper Title: Cognitive Theory to Understand Consumer Expectations and Media Influences Abstract: Many opportunities, with the help of web-based technologies, are provided to word-of-mouth communication. The method of communication of customers and sharing the product details with others is transformed by the immense utilisation of electronic commerce shopping communities. Until recently, the area of e-commerce shopping communities where buyers participate has been underexplored in the field of academic research. The online reviews provided by the customers exert a high impact on customers’ buying decisions while shopping on e-commerce websites and thus provides significance to the concept of word of mouth. The growing amount of literature covering various domains that emphasizes customers’ reviews online can be considered as a justification of this concept. The factors that affect continual intention of buying online and the extent, reciprocity and reputation of vendor creativity affect consumer expectations. This study provides a brief insight into online customer reviews and their impact on consumer buying behavior by using social cognitive theory. A conceptual framework showcasing the various factors affecting the perceptions and attitudes of consumers in the context of online reviews will be provided in the paper. This study is the first to apply social cognitive theory on online customer reviews and to study their impact on consumer expectations.

Keyword: Customer reviews, customer behavior, social cognitive theory, customer expectations. References: 1. Adjei, M., Noble, C. and Noble, S. (2010), “The influence of C2C communications in online brand communities on customer purchase behavior”, Journal of the Academy of Marketing Science, Vol. 38 No. 5, pp. 634-653. 2. Alalwan, A., Rana, N., Algharabat, R. and Tarhini, A. (2016a). A Systematic Review of Extant Literature in Social Media in the Marketing Perspective. The 15th IFIP Conference on e-Business, e-Services and e-Society on Social Media: The Good, the Bad, and the Ugly, Swansea, UK. 3. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. 4. Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299. 5. Bansal, H., and Voyer, P. Word-of-mouth processes within a services purchase decision context. Journal of Service Research, 3, 2, 2000, 166–178. 6. Bolton, R. N., Parasuraman, A., Hoefnagels, A., Migchels, N., Kabadayi, S., Gruber, T., ...& Solnet, D. (2013). 7. Understanding Generation Y and their use of social media: a review and research agenda. Journal of service management, 24(3), 245-267. 8. Case, T., Burns, O. M., and Dick, G. N. ìDrivers of on-line purchasing among U.S. university students.î Proceedings of the 7th Americas Conference on Information Systems, 2001, pp. 873-878. 9. Centola, D. The spread of behavior in an online social network experiment. Science, 329, 2010, 1194–1197. 10. Chen, Y., Wang, Q., & Xie, J. (2010). Online social interactions: A natural experiment on word of mouth versus observational learning. Available at SSRN 1501843. 11. Chen, Y.B., Wang, Q., & Xie, J.H. (2011). Online social interactions: A natural experiment on word of mouth versus 887-892 observational learning. Journal of Marketing Research, 48(2), 238–254. 12. Cheung, C.M.K., & Lee, M.K.O. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218–225. 13. Coulter, K.S., Roggeveen, A., 2012. ‘‘Like it or not” Consumer responses to word-of-mouth communication in on-line social networks. Manage. Res. Rev. 35 (9), 878–899. 14. Cui, G., Lui, H. K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39-58. 15. Demangeot, C. and Broderick, A.J. (2006), “Exploring the experiential intensity of online shopping environments”, Qualitative Market Research: An International Journal, Vol. 9 No. 4, pp. 325-351. 16. Drews, W., & Schemer, C. (2010). eTourism for all? Online travel planning of disabled people. Information and Communication Technologies in Tourism 2010, 507-518. 17. Einwiller, S. The significance of reputation and brand in creating trust between an online vendor and its customers. In 18. O. Petrovic, M. Fallenböck, and C. Kittl (eds.), Trust in the Network Economy, Springer-Verlag, Heidelberg, Germany, 2003, 113–127. 19. Ekelund, R., Mixon, F., and Ressler, R. Advertising and information: an empirical study of search, experience and credence goods. Journal of Economic Studies, 22, 2, 1995, 33–43. 20. Flavián, C. and Guinalíu, M. (2005), “The influence of virtual communities on distribution strategies in the internet”, International Journal of Retail & Distribution Management, Vol. 33 No. 6, pp. 405-425. 21. Gao, Q., & Feng, C. (2016). Branding with social media: User gratifications, usage patterns, and brand message content strategies. Computers in Human Behavior, 63, 868-890. 22. Huang, J. and Chen, Y. (2006), “Herding in online product choice”, Psychology and Marketing, Vol. 23 No. 5, pp. 413-28. 23. Jarvenpaa, S. L., Tractinsky, N., and Vitale, M. ìConsumer trust in an Internet store,î Information Technology and Management (1), 2000, pp. 45-71 24. Jarvenpaa, S. L., Tractinsky, N., and Vitale, M. ìConsumer trust in an Internet store, Information Technology and Management (1), 2000, pp. 45ñ71 25. Lee, J., Kim, S., and Ham, C. D. (2016). A Double-Edged Sword? Predicting Consumers’ Attitudes Toward and Sharing Intention of Native Advertising on Social Media. American Behavioral Scientist, 0002764216660137. 26. Lee, J., Park, D. and Han, I. (2008), “The effect of negative online consumer reviews on product attitude: an information processing view”, Electronic Commerce Research and Applications, Vol. 7 Nos 3, special section: New Research from the 2006 International, pp. 341-52. 27. Leeflang, P.S., Verhoef, P.C., Dahlström, P., Freundt, T., 2014. Challenges and solutions for marketing in a digital era. Eur. Manage. J. 32 (1), 1–12. 28. Li, N., & Zhang, P. (2002). Consumer online shopping attitudes and behavior: An assessment of research. AMCIS 2002 Proceedings, 74. 29. Liang, T., and Lai, H. ìElectronic store design and consumer choice: an empirical study,î Proceedings of the 33rd Hawaii International Conference on System Sciences, 2000. 30. Libert, B., & Spector, J. (2007). We are smarter than me: How to unleash the power of crowds in your business. Upper Saddle River, NJ: Pearson Prentice Hall. Authors: Natalia P. Nikonova 151. Paper Title: Development of Personal Social Activity: Formation of Students 'Political Culture Abstract: The problems of the formation of a political culture based on the development of a person’s social activity, its translation into a socio-political one, which is a factor in the formation of students' political culture, are examined. The article is based on a study whose purpose is a comprehensive scientific and theoretical analysis of the political culture of modern students; revealing the features of its formation. The authors argue that political culture is a set of regulations and values that determine the participation of people in the political life of society, the formation of political culture, citizenship among young people is inextricably linked with the process of political socialization, which lays the foundation for basic knowledge, judgments and ideas of the individual about politics, power, the state.

Keyword: Social activity, social activity, socio-political activity, culture, political culture, personality, values, norms, factors, conditions. 893-897 References: 1. Almond, G. (1997). Political science: the history of discipline. Policy. Political Studies, (6), 174-183. 2. Carmine, A.S. (2004). Culturology: Textbook. 5th ed. SPb .: Publishing house "Doe, 928. 3. Cohn, I.S. (1989). Psychology of early youth: book. for teacher / Igor Semenovich Kon. M .: Education, 254. 4. Duranov, M.E., & Shvachko, E.V. (2014). Theory and methodology of sociocultural education and personality development. Moscow: Humanity. ed. Center VLADOS. 5. Herder, I. G., & Mikhailova, A. V. (1977). Ideas for the philosophy of the history of mankind Text. In Monuments of historical thought / Acad. sciences of the USSR. M .: Science (p. 116). 6. Khaikin, V. L. (2000). Activity (characteristics and development). M .: Mosk. psychol. social in here. 7. Kvasha, A. (2015). Legal Power and Huge Suspension: Comparative Analysis of Categories. State control and self-determination, (1), 3-12. 8. Malik, E. N. (2009). Mass media as an institution of political socialization of youth in modern Russia. 9. Melnikov, A.V. (2014). Political participation of youth: actual problems of identifying value preferences. Central Russian Bulletin of Social Sciences, (3 (33)). Authors: Hamdan ALMATRUSHI, Mohammed NUSARI, Ali Ameen, Amiya Bhaumik Examining the Accessibility, Support, Benefits of Training in Road and Transport Authority: The Paper Title: Case of Service Quality in UAE Abstract: This study investigates the relationships between three training dimensions and affective organizational commitments, as well as service quality within UAE public sectors. In the current study, the relation between the access, support, and benefits of training are assessed by implementing affective organizational commitment as their mediating . The study was conducted using survey research design with 540 participants of UAE licenced units. Analysis of the confirmatory parameters were conducted to demonstrate the quality services of the three licenced units of the training scales and hypothesis testing were conducted. The 152. study findings showed that all the dimensions of the training directly and indirectly positively affected service quality of UAE public sectors. In addition to that, the three-training dimension have also a positive effect on affective organizational commitments. Further affective organizational commitment positively affected service 898-909 quality.

Keyword: Access, support, and benefits of training, affective organizational commitment, service quality, public sectors, UAE. References: 1. C. Fornell & D. F. Larcker, (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), pp. 39–50. Authors: Natalia V. Kamenez

Paper Title: Factors of Actualization of the Resource of Social and Political Participation of Youth Abstract: The continuity of social, political, economic, sociocultural transformations is becoming a hallmark of modern society. The high speed of the changes and the crises with which they are associated create the risk of individual and group social maladaptation. In this article, the authors consider features that analyze and systematize the factors of actualizing the resource of political participation of youth, the criteria for systematizing factors: the external and internal environment, fixed, situational. They are not only interconnected, but also interdependent. Factors related to external ones influence the formation of internal ones (in a stable, economically developed society, in which the basic material needs of people are satisfied, the first place is satisfaction of social and prestigious needs, and especially in political participation); with a certain set of internal 153. factors, situational factors are formed (in the absence of political interest in a young person, even the most professionally prepared propaganda and motivational technologies will not give the desired effect). 910-914

Keyword: youth, system of factors, political participation, political involvement, political system, socialization. References: 1. Reutov EV Political mobilization of youth as a technology to minimize social outsider / Belgorod region: past, present. The future: materials regional. scientific and practical conf. Belgorod, 2016.S. 110-117. 2. Interest in politics: monitoring // Publishing mode: http://bd.fom.ru/report/map/proiects/dominant/dom0625/domt0625 l / tb062507. - System requirements: IBM PC; Internet Explorer 3. Ryabukhina Yu.N. The system of factors of youth political participation // South Russian Journal of Social Sciences. 2012. No3. URL: https://cyberleninka.ru/article/n/sistema-faktorov-politicheskogo-uchastiya-molodyozhi (accessed: 01.10.2019). 4. Gayfullin A.Yu., Rybalko N.V. Diagnostics of the development of political activity of youth // VEGU Bulletin. 2011. No 6 (56). 5. Sociology of Youth: Textbook / Ed. prof. V.T. Lisovsky. — St. Petersburg: Publishing House of St. Petersburg University, 1996. 460 p. 6. 6. Kon I.S. Sociology of youth. In the book: A Brief Dictionary of Sociology M., 1988. 7. Belikova E. A. Political participation of youth: analysis of the problems of political activity / E. A. Belikova // Central Russian Bulletin of Social Sciences. 2014. No1 (31). URL: https://cyberleninka.ru/article/n/politicheskoe-uchastie-molodezhi-analiz- problem-politicheskoy-aktivnosti (accessed September 29, 2019) 8. Kopaeva E. V., Kotova K. A., Lisova S. Yu. Political activity of students: problems and trends / E. V. Kopaeva, K. A. Kotova, S. Yu. Lisova // Manuscript. 2017. No. 6-1 (80). URL: https://cyberleninka.ru/article/n/politicheskaya-aktivnost-studencheskoy- molodezhi-problemy-i-tendentsii (accessed: 09/28/2019). 9. Arshinova E.V., Bilan M.A., Gorbatova M.M., Rassokhina I.Yu. VALUE ASPECTS OF ELECTORAL BEHAVIOR OF STUDENT YOUTH / E.V. Arshinova, M.A. Bilan, M.M. Gorbatova, I.Yu. Rassokhina // Vocational education in Russia and abroad. 2019.No 1 (33). URL: https://cyberleninka.ru/article/n/tsennostnye-aspekty-elektoralnogo-povedeniya-studencheskoy- molodezhi (accessed date: 09/28/2019). 10. Karpenko O.M. , Lamanov I.A. Youth in the modern political process in Russia, M. 2006. –C. 52-53. Authors: Kalavathy. K. S, Swapna. H. R

Paper Title: An Assessment of Service Quality Dimensions Conducted at Oyo Hotel, Bangalore Abstract: OYO, an online hotel booking service organization is getting popularity all over India for their innovative and technology based services. Customers are becoming tech-savvy and are increasingly using Internet for booking hotels online. It is important to know the factors that are determining the consumer’s changing behavior. The purpose of the paper is to understand the factors influencing customer’s decision to book OYO rooms. An exploratory study using purposive sampling method was carried out. Chi-Square analysis revealed that customer demographics, specifically age, education and occupation play a significant role on customer usage frequency. The study aids in giving an additional insight to understand consumer behavior in online hotel booking services and to understand the need for assessment of service quality to deliver the expected service.

Keyword: Customer Satisfaction, Service Quality, Service Dimension. References: 1. Agarwal A, Kumar G (2016), “Identify The Need for Developing a New Service Quality Model in Today’s Scenario: A Review of Service Quality Models”, Arabian J Bus Managerial Review, Volume 6, pp193. 2. Alauddin, Syed, Masrurul, Islam and Musharof (2019), ‘Investigating the Relationship between Service Quality, Customer Satisfaction and Customer Loyalty in Hotel Industry: Bangladesh Perspective’, Global Journal of Management and Business Research: A Administration and Management Volume 19 Issue 1 Version 1.0 3. Anckar B. and Walden P., (2002), “Self-booking of high and low complexity travel products: exploratory findings”, Journal of 154. Information Technology and Tourism, Volume 4, Issue 1, 151-165. 4. Arrunada Benito (June 2000), “Audit Quality: Attributes, Private Safeguards and the Role of Regulation”, The European Accounting Review, 9(2), 205-224. 915-920 5. Beldona S., Nusair K. and Demicco F., (2009). “Online travel purchase behavior of generational cohorts: A longitudinal study”, Journal of Hospitality Marketing and Management, Volume 18,Issue 1,406-420. 6. Dr. Namrata Maheshwari, Dr. Jesu A. Kundailaraj, (2018), ‘Determining The Factors Affecting Customers Satisfaction In Oyo Rooms’, Journal of Emerging Technologies and Innovative Research (JETIR), February 2018, Volume 5, Issue 2. 7. Dr. Ramesh Kumar Chaturvedi (2017), ‘Mapping Service Quality in Hospitality Industry: A Case through SERVQUAL’, A & V Publications. 8. Kothari C.R (1990), ‘Research Methodology Methods and techniques’, Second edition. 9. Kotler P (2002), ‘Marketing management’, New Jersey: Pearson Education 10. Nguyen Thi Thanh Xuan (2017), ‘A Review of Customer Loyalty Models in Hotel Services and Research Model in Vietnam’, International Journal of Management Research & Review, Vol: 3 Issue: 1 11. Parasuraman, Zeithame and Berry, (1988), “SERVQUAL: A Multiple- Item Scale for Measuring Consumer perceptions of Service Quality”, Journal of Retailing, Volume 64, Issue-1. 12. Patricia Dodu Silvia, (2008), “The internet, threat or tool for travel agencies?” , Annals of the University of Oradea, Economic Science Series, Volume 17, Issue 2 13. Rosen Cheryl, Wilde Candee, (November 13, 2000), “Travel agents haven’t proven they can beat the internet threat- up in the air”, Information Week, Gale-British Council Library 14. S Akhila and C Manikandan (2018), ‘A study on growing trends of online hotel booking’, International Journal of Commerce and Management, Volume 4; Issue 3; Page No. 09-15. 15. Sharma Deependra, (August 2016),"Enhancing customer experience using technological innovations", Worldwide Hospitality and Tourism Themes, Vol. 8 Issue 4, 469 - 480 16. Starkov, M; Safer M.M. (2010) Top Ten Internet Marketing Resolutions. Hospitality e-Business Strategies (HeBS), http://www.hospitalityebusiness.com/ articles.php, downloaded: February 15th 2010. 17. Valarie A. Zeithaml (2010), ‘Service Marketing’, McGraw Hill Education, Seventh edition. 18. https:/oyorooms.com 19. https://marketingmix.co.uk/promotion Authors: Anurag Singh

Paper Title: E-Word of Mouth: Strengthening the Strategic Tool of Digital Marketing Abstract: Electronic Word of Mouth (e-WoM), has developed into one of the most dominant source of 155. information in recent years, in all the fields of product and service industry, with the arrival of web based platforms. It is being widely used in all the areas to seek the information and facilitate communication, particularly in marketing. As more and more customer are adapting to this technological changes, e-WoM is 921-926 getting a crucial role in shaping consumer behaviour. The e-WOM, due to high impact on the behaviour of consumer, has been a vital concept used by researchers in recent times. But the related literature remains heterogeneous in spite of the rising number of studies, which might impact the comprehensive understanding of e-Word of Mouth in long term. In the backdrop of the problem, this chapter systematically reviews of the concepts, through available but splintered literature on e-WoM. The chapter ends with the stories of successful companies, applied e-WoM in past with managerial implications.

Keyword: e-Word of Mouth, Strategy, Social Media, Stories, Strengthen. References: 1. Abubakar, A. M., & Ilkan, M. (2016). Impact of online WOM on destination trust and intention to travel: A medical tourism perspective. Journal of Destination Marketing & Management, 5(3), 192-201. 2. Aciar, S., Zhang, D., Simoff, S., & Debenham, J. (2007). Informed recommender: Basing recommendations on consumer product reviews. IEEE Intelligent systems, 22(3). 3. ACNielson. (2007) Trust in Advertising: A Global Nielsen Consumer Report, October. 4. Ayeh, J. K. (2015). Travellers’ acceptance of consumer-generated media: An integrated model of technology acceptance and source credibility theories. Computers in Human Behavior, 48, 173-180. 5. Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the association for information systems, 8(4), 3. 6. Beer Jay (2019) Influencer Marketing Platforms, Retrieved on 09/02/2019 from https://influencermarketinghub.com/influencer- marketing-what-why-how-to-guide/ 7. Breazeale, M. (2009). Word of mouse-An assessment of electronic word-of-mouth research. International Journal of Market Research, 51(3), 1-19. 8. Brown, C., Burgess, F., & Braithwaite, V. A. (2007). Heritable and experiential effects on boldness in a tropical poeciliid. Behavioral Ecology and Sociobiology, 62(2), 237-243. 9. Cacioppo, J. T., & Petty, R. E. (1984). The elaboration likelihood model of persuasion. ACR North American Advances. 10. Cantallops, A. S., & Salvi, F. (2014). New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management, 36, 41-51. 11. Charlie C, (2019), Wix Review 2019: 7 Crucial Things to Know, retrieved on 13/02/2019 from https://www.websitebuilderexpert.com/website-builders/wix/wix-review/ 12. Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470. 13. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345-354. 14. Daugherty, T., & Hoffman, E. (2014). eWOM and the importance of capturing consumer attention within social media. Journal of Marketing Communications, 20(1-2), 82-102. 15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. 16. Dellarocas C, (2003) The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, Vol. 49, No. 10, pp. 1407–1424.. 17. Dougherty Jim, (2015) 9 Word-of-Mouth Campaigns That Rocked, retrieved on 13/02/2019 from https://www.cision.com/us/2015/03/9-word-of-mouth-campaigns-that-rocked/ 18. Duhan Punita, & Singh Anurag, (2013a), Social Media : A Paradigm Shift in Integrated Marketing Communication, Integral Review , 6(2), pp 1-12 19. Duhan Punita, & Singh Anurag, (2013b), Impact of Usefulness, Ease of Use, Enjoyment, Attitude and Subjective Norms on Behavioural Intensions and Adoption of Virtual Communities: An Empirical Study, Journal of IMS Group, 2 (1), pp 1-10 20. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. 21. Gómez-Suárez, A., Nelson, D. J., & Nolan, S. P. (2017). Quantifying and understanding the steric properties of N-heterocyclic carbenes. Chemical Communications, 53(18), 2650-2660. 22. Hennig-Thurau, T., Gwinner, K.P., Walsh, G. and Gremler, D.D. (2004), Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet?, Journal of Interactive Marketing, Vol. 18 No. 1, pp. 38-52. 23. Henning-Thurau, T. (2004). Motive des lesens von kundenartikulationen im internet: theoretische und empirische analyse. In Konsumentenverhalten im Internet (pp. 171-193). Gabler Verlag. 24. Hull P, (2013), Don't Get Lazy About Your Client Relationships, retrived on 13/02/2019 from https://www.forbes.com/sites/patrickhull/2013/12/06/tools-for-entrepreneurs-to-retain-clients/#7090b5502443 25. Ians, (2017), Nargis Fakhri clicks 'Pink Selfie' to support breast cancer awareness, retrieved on 13/02/2019 from https://www.indiatvnews.com/entertainment/bollywood/nargis-fakhri-pink-selfie-to-support-breast-cancer-awarness-17744.html 26. Jhagadia, (2014), Abbott to develop nutrition products suited to Indian tastes, retrieved on 13/02/2019 from https://www.thehindubusinessline.com/companies/Abbott-to-develop-nutrition-products-suited-to-Indian- tastes/article20888339.ece 27. Katz, E., Haas, H., & Gurevitch, M. (1973). On the use of the mass media for important things. American Sociological Review, 38(2), 164-181 28. Kim, E. E. K., Mattila, A. S., & Baloglu, S. (2011). Effects of gender and expertise on consumers’ motivation to read online hotel reviews. Cornell Hospitality Quarterly, 52(4), 399-406. 29. Kristen M, (2019), How to Create and Host a Webinar: The Ultimate Start-to-Finish Guide (+ Expert Advice), retrieved on 13/02/2019 from https://learn.g2crowd.com/how-to-create-and-host-a-webinar 30. Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism management, 29(3), 458-468. 31. Martin B and Simone H, (2012), Political Change in the Middle East: An Attempt to Analyze the “Arab Spring”, retrieved on 13/02/2019 from https://www.giga-hamburg.de/system/files/publications/wp203_beck-hueser.pdf 32. Mayfield A (2008). A commander Strategy for Social Media retrieved on 13/02/2019 from www.dtic.mil/dtc/tr/fulltext/u2/a535374. 33. McMillen Jacob, (2016), Word-of-Mouth Marketing: Building a Strategy That Really Works, retrieved on 13/02/2019 from https://www.yotpo.com/blog/word-of-mouth-marketing/ 34. Mishra Yog, Singh Anurag (2018), “Exploring the Determinants of e-WoM influence: An Empirical Study on Tourist visiting Varanasi” Management Today, 8, (3), pp 266-273 35. Mishra Yog, Singh Anurag, (2017) Role of E word of Mouth in M Commerce Age: An Exploration, International Journal of Marketing & Financial Management, 5 (3), pp 65-76 36. Reza Jalilvand, M., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention: An empirical study in the automobile industry in Iran. Marketing Intelligence & Planning, 30(4), 460-476. 37. Shu, M., & Scott, N. (2014). Influence of social media on Chinese students’ choice of an overseas study destination: An information adoption model perspective. Journal of Travel & Tourism Marketing, 31(2), 286-302. 38. Singh Anurag , (2014), CSR communication through Social Media: A Strategy for Brand Building and Market Growth, Review of Professional Management, Vol 12, No.1, pp 82-89 39. Singh R, (2014), PediaSure bets on young & smart moms to take on the big boys, retrieved on 13/02/2019 from //economictimes.indiatimes.com/articleshow/38022192.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign= cppst 40. Sotiriadis, M. D., & Van Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: the use of twitter by tourists. Electronic Commerce Research, 13(1), 103-124. 41. Sugita Katyal, (2018), Netflix looks at the bigger picture in India, retrieved on 13/02/2019 from https://www.fortuneindia.com/opinion/netflix-looks-at-the-bigger-picture-in-india/102120 42. Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1), 47-65. 43. Thorson, K. S., & Rodgers, S. (2006). Relationships between blogs as eWOM and interactivity, perceived interactivity, and parasocial interaction. Journal of Interactive Advertising, 6(2), 5-44. 44. Zephoria Digital Marketing, 2018, The Top 20 Valuable Facebook Statistics – Updated January 2019, retrieved on 13/02/2019 from https://zephoria.com/top-15-valuable-facebook-statistics/ Authors: M.R. Dileep, K.S.Chandrasekar

Paper Title: A Perspective Research on Information Systems in Tourism Sector in Kerala Abstract: Tourism, a multi-dimensional and multi-faceted activity with diverse social, cultural, economic and ecological impacts, got evolved as one of the largest and most significant economic sectors in the world. The lure of tourism as an engine of economic growth and diversification has been urging each and every country in the world to develop and promote it in the most possible manner (Dileep, 2018). As per the current projections, tourism is tend to grow further and it will remain as one of the most vibrant, growing and economically useful activities in the world having wide social and cultural ramifications in the years to come as well. Being an amalgam of industries, this sector includes a diverse range of industries like, intermediaries; transportation; accommodation; entertainment and recreation; shopping; hospitality; and infrastructure. Complex linkages and interrelationships exist among the various individual sectors of the tourism industry. The post second world war era has witnessed tremendous growth of tourism and in the same era has recorded the evolution and growth of information and communication technology as well. Information Technology has become one of the most fundamental and vital components of the successful businesses and organizations and is a major facilitator. In the growth of tourism as a major social phenomenon in the 21st century, Information and communication technology (ICT) too had played significant roles. Indeed, the relationship between tourism and ICT was symbiotic as well, since the latter sector got many opportunities for the application of it in the tourism sector, like in the air transportation which was a pioneer in developing transaction systems for handling the cumbersome booking data in the 1950s and 60s. Information systems for the core of ICT applications in businesses and organisations. Tourism Sector too has been using different types of information systems intensively in the international scenario. Kerala, one of the late entrants in the international tourism, has turned to be successful international tourist destinations within a few decades of time. The number of tourism arrivals has been registering consistent growth and the industry got expanded exponentially in Kerala. To compete globally, tourism of anywhere requires a variety of information systems. Kerala tourism industry is also not an exception to this. In this context, a study on the current usage of information systems in the tourism sector in Kerala seems inevitable. The study has to focus upon the types of information systems used by the tourism industry in Kerala, efficiency as well as 156. the impacts of the usage of such information systems by the industry, comparing the scenario with the international standards and also to discuss about the future to suggest suitable solutions to look ahead to have more competence by the Kerala tourism. 927-934

Keyword: Information and communication technology (ICT). References: 1. Bardi A James, 2003, Hotel Front Office Management, IIIrd Edition, John Wiley, New Jersey, 421. 2. Boyd and Butler, (1996), Seeing the forests through the trees; using GIS to identify potential ecotourim sites in Northern Ontarion, In L.C.Harrison and W Husband (eds), practicing responsible tourism:International case Studies in Tourism planning, Policy and Development. 3. J.Wiley and Sons, New York, Pp 404-421. 4. BuhalisDimitrios, (1996), I T as strategic tool for tourism and hospitality management in the new millennium, Tourism Review,2,Pp 34-36. 5. Christo doulakis, et.al, (2004), Minotaurus; Distributed Multimedia Tourism Infromation Systems (PDF version in Internet), Multimedia Systems Institute of Crete (MUSIC), Technical University of Crete, Greece. 6. Cooper Chris, Fletcher John, Gilbert David and Swanhill Stephen, (1993), Tourism-principles and Practices, Pitman with EL/BS, London. 7. Dileep M R., 2018. Tourism: Concept, Theory and Practise, IK International, New Delhi 8. Dileep, M.R., 2011, Information Systems in Tourism, Excel Books,: New Delhi 9. FarsariYianna, [email protected], Research scholar, University of Surrey, UK in collaboration with FORTH,Greece, Published in Internet, accessed on 23/08/04. 10. Inkpen Gary, 1998, Information Technology for travel and Tourism, Addion Wesley Longman Limited, Esex, England. 11. Jaiswal M and Mital M (2004), management Information System, Oxford University Press, new Delhi. 12. Kim BH, Singh AJ, and Huh C, 2005, Information technology Practices and performance Impacts-A Case of Korean Hotel Industry, Journal of Hospitality and Tourism, 3, 1-20. 13. Koontz Harold and Weirich Heinz, 1990, Essentials of Management, 5th edition, Tata McGrawHill, New Delhi. 14. Laudon K and Laudon J, (2004), Management Information System-Managing the digital Firm, 8thedition,Prentice Hall, India:08. 15. Maedchea Alexander, Staab Stephen, (2004), Applying Semantic Web Technologies for Tourism Infromation Systems, (PDF,Internet),Research Center for Information technology, University of Karlsruhe, WIM, Germany 16. McAdam,D.(1999), The value and cope of GIS in Tourism management, Journal of Sustainable Tourism, 7(1), 77-98. 17. O’Brien, (1998), Management Information Systems-A managerial perspective, Galgotia, New Delhi:06. 18. Poon A, 1993, tourism, technology and competitive strategies, CABI, Oxford. 19. Ran Dejan, DjordeviSlobodanka, Kajan, Stoimenovleonid, To VCladimir, (2004), Some applications of the Multimedia GIS in Tourism, (PDF,Internet), Faculty of Engineering, University of Ni, Yugoslavia. 20. Ritchie JBR, Ritchie JR, (2002), Framework for an industry-supported destination marketing information system, Tourism management, 23, Pp439-454. 21. Schafer,J.B, Konstan J, Riedl.J, (2001), E-Commerce ,Recommender Applications, Journal of data mining and knowledge discovery, 5, 115-53. 22. Scheldon P, Wober K and Fesenmalec D (Eds), (2001), Information and Communication technologies in tourism, Springer Verlag, Vienna. 23. Senn A James, 1989, Analysis and Design of Information Systems, McGraw Hill international Edition, Singapore. 24. Sheldon J Pauline, 2003, Tourism Information Technology, CABI publishing, Oxon, UK. 25. Stair Ralph and Reynolds George, 2001, Principles of Information System, Thomson Learning, Singapore 26. Stair Ralph and Reynolds George, 2001, Principles of Information System, Thomson Learning, Singapore:04. 27. Turban, Rainer and Potter,2002, Introduction to Information Technology, John Wiley and Sons, Singapore. 28. Van Hoof, HB, Collins GR, Combrink TE and Verbeteen MJ, 1995, Technology needs and perceptions: Assessment of the US lodging industry, Cornell Hotel and Administration, 36 (5), 64-69. 29. Wall Geoffrey, (2000), Geographic Information System, In JafarJafari (Chief Editor),Encyclopedia of Tourism, Routledge, London. 30. WerthnerHannes, Klein Stefan, 1999, Information Technology and Tourism-a challenging relationship, Springer Wien, New York. 31. Whitten, Bentley and Dittman, 2002, Systems Analysis and Design, Galgotia, New Delhi. 32. [Williams P W, Paul J and Hainsworth, (1996), Keeping track of what really counts: Tourism resource inventory system in British Columbia, Canada, In L.C.Harrison and W Husband (eds), practicing responsible tourism:International case Studies in Tourism planning, Policy and Development, J.Wiley and Sons, New York, Pp 404-421. 33. Wise Stephen, (2002), GIS basics, Taylor & Francis, London. 34. Wober W Karl,(2003), Information supply in tourism management by marketing decision support systems, Tourism management, 24, Pp 241-255. 35. WTOBC, (2001), eBusiness for Tourism: Practical guidelines for destinations and businesses, World Tourism Organisation, Madrid. 36. www.tourmis.com, the official website of Tour MIS, Austria, data accessed on 16/6/04. 37. Yianna Farsari, (2004), GIS Based support for sustainable tourism planning and policy making (Internet, PDF), University of Surrey and FORTH, Greece. Authors: DivyaSrinath, Shashishankar A, Ravindra R, Mohiyuddin C S Compressive Strength of Concrete with Construction and Demolition Waste and m-SAND using Paper Title: Additives Abstract: Construction and Demolition wastes(C&D wastes) are generated in all cities of the world due to rapid urbanization. Disposing C & D waste these days is a costly affair, and raises environmental issues. Hence an attempt is made to reuse the demolished concrete as a partial replacement of natural coarse aggregates. Also due to ban of sand mining by local authorities, the cost of natural fine aggregate is very high and itself becoming a scarce material. Hence crushed stone aggregates called manufactured sand (m sand) is used, totally replacing natural fine aggregates. This concept is found to be cost effective, minimizes disposal of C & D wastes, and leads towards Green Building Concepts. Compression test on M40 concrete cubes of size 150mmx150mmx150mm are conducted at end of 7 days and 28days. Mix design for M40 concrete is made in accordance to IS: 10262-2019 with water cement ratio of 0.45 using 53 Grade Ordinary Portland cement. Superplasticizer (LIQUIFIX) is used to enhance workability. Nano Silica (NS)(1.5% by weight of cement),Wollastonite powder(WP)(10%by weight of cement) and Basalt fibres(BF)(1% by weight of cement) are added as additives. It is observed, that compressive strength of 7 days and 28 days cured samples is 25% more with the addition of all three additives compared to samples without additives. Hence the loss of compressive strength obtained by using demolished concrete as aggregates and m sand in concrete is regained with the addition of additives.

Keyword: Construction & Demolition waste, Concrete, m Sand, Nano Silica, Basalt fibres, Wollastonite 157. powder. References: 1. Forood Torabian Isfahani, Elena Redaelli, Federica Lollini, Weiwen Li,and Luca Bertolini,"Effects of Nanosilica on Compressive 935-937 Strength and Durability Properties of Concrete with Different Water to Binder Ratios", Advances in Materials Science and Engineering Volume 2016, Article ID 8453567, 16 pages http://dx.doi.org/10.1155/2016/8453567. 2. Rutuja Mininath Sarade, Suraj Ramesh Shinde, Rohan Kantilal Wayase, Namdev Bapu Rajguru, Dr. P. D. Nemade," Effect of Nano Silica on Compressive Strength of Concrete", IJSRD - International Journal for Scientific Research & Development| Vol. 5, Issue 04, 2017 | ISSN (online): 2321-0613 . 3. Renu Mathur, A K Misra and Pankaj Goel, "Influence of wollastonite on mechanical properties of concrete", Journal of Scientific & Industrial Research,Vol. 66, December 2007, pp. 1029-1034. 4. Kandula Mohankrishna Reddy& K. V. S. Gopala Krishna Sastry, "Strength properties of concrete using wollastonite-flyash and wollastonite-silica fume", International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development (IJCSEIERD) ISSN(P): 2249-6866; ISSN(E): 2249-7978 Vol. 6, Issue 5, Oct 2016, pages 1-12. 5. Tehmina Ayub, Nasir Shafiq, and M. Fadhil Nuruddin,"Effect of Chopped Basalt Fibers on the Mechanical Properties and Microstructure of High Performance Fiber Reinforced Concrete", Hindawi Publishing Corporation, Advances in Materials Science and Engineering Volume 2014, Article ID 587686, 14 pages 6. Nayan Rathod,, Mukund Gonbare,, Mallikarjun Pujari,,"Basalt Fiber Reinforced Concrete",International Journal of Science and Research (IJSR),2013 ISSN (Online): 2319-7064. 7. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "A Dynamic MooM Dataset Processing Under TelMED Protocol Design for QoS Improvisation of Telemedicine Environment." Journal of medical systems 43, no. 8 (2019): 257. 8. Ahmed, Syed Thouheed, M. Sandhya, and Sharmila Sankar. "An Optimized RTSRV Machine Learning Algorithm for Biomedical Signal Transmission and Regeneration for Telemedicine Environment." Procedia Computer Science 152 (2019): 140- 149. 9. Patil, Kiran Kumari, and Syed Thouheed Ahmed. "Digital telemammography services for rural India, software components and design protocol." In 2014 International Conference on Advances in Electronics Computers and Communications, pp. 1-5. IEEE, 2014. 10. Thouheed, Syed, S. Ahmed, M. Sandhya, and S. Shankar. "ICT’s Role in Building and Understanding Indian Telemedicine Environment: A Study." In Information and Communication Technology for Competitive Strategies. Lecture Notes in Networks and Systems, vol 40. Springer Singapore, 2019. Authors: Dipankar Mohan

Paper Title: Changing Status of the Ahom Priestly Class Abstract: Human society is the result of a continuous transformation process. In this transformation process religion plays a significant role. In every society customs, beliefs, behaviour, traditions are mostly connected with the religion. So in every society religion and religious traditions became the identity of a society. In case of Assam every tribes had their own priestly class to do priesthood. Similarly the Ahoms had their own priestly class to do priesthood. In this article an attempt has been made to assess the condition of the Ahom priestly class i.e. the Mohan, the Deodhai and the Bailungs.

Keyword: tradition, customs, priestly class, priesthood, religion. 158. References: 1. H.K., Barpujari (ed.), The Comprehensive History of Assam, Vol-III, Publication Board of Assam, Guwahati, 2007, p.254. 938-941 2. P., Gogoi, Tai Ahom Religion and Customs, Publication Board of Assam, Guwahati, 1976, p.35. 3. B.K., Gohain, The Ahoms and Their Traditions, Vol-I, Omsons Publications, New Delhi, 2011, p.102 4. ibid. 5. ibid., p.103. 6. Interview with Gyanendra Phukan. 7. Interview with Manuranjan Phuakn. 8. B.K., Gohain, The Ahoms and Their Traditions, Vol-I, Omsons Publications, New Delhi, 2011, p.104. 9. Interview with Tileshwar Mohan. 10. Lakshminandan, Bora (Ed.), Tai Pandit Tengai Mohung Aru Mohan Deodhai Bailunghokol, Bakata Parijat, 2015, p.30. 11. B.K Gohain, op.cit., p.104. 12. Lakshminandan, Bora (Ed.), op.cit., p.30. 13. Interview with Gyananedra Phukan. 14. Lakshminandan, Bora (ed.), op.cit., p.30.