International Journal of Soft Computing and Engineering
ISSN : 2231 - 2307 Website: www.ijsce.org Volume-3 Issue-1, March 2013 Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Ltd.
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G INN www.ijsce.org Exploring Innovation Editor In Chief Dr. Shiv K Sahu Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT) Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Dr. Shachi Sahu Ph.D. (Chemistry), M.Sc. (Organic Chemistry) Additional Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Vice Editor In Chief Dr. Vahid Nourani Professor, Faculty of Civil Engineering, University of Tabriz, Iran
Prof.(Dr.) Anuranjan Misra Professor & Head, Computer Science & Engineering and Information Technology & Engineering, Noida International University, Noida (U.P.), India
Chief Advisory Board Prof. (Dr.) Hamid Saremi Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran
Dr. Uma Shanker Professor & Head, Department of Mathematics, CEC, Bilaspur(C.G.), India
Dr. Rama Shanker Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea
Dr. Vinita Kumari Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., India
Dr. Kapil Kumar Bansal Head (Research and Publication), SRM University, Gaziabad (U.P.), India
Dr. Deepak Garg Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India, Senior Member of IEEE, Secretary of IEEE Computer Society (Delhi Section), Life Member of Computer Society of India (CSI), Indian Society of Technical Education (ISTE), Indian Science Congress Association Kolkata.
Dr. Vijay Anant Athavale Director of SVS Group of Institutions, Mawana, Meerut (U.P.) India/ U.P. Technical University, India
Dr. T.C. Manjunath Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. Kosta Yogeshwar Prasad Director, Technical Campus, Marwadi Education Foundation’s Group of Institutions, Rajkot-Morbi Highway, Gauridad, Rajkot, Gujarat, India
Dr. Dinesh Varshney Director of College Development Counceling, Devi Ahilya University, Indore (M.P.), Professor, School of Physics, Devi Ahilya University, Indore (M.P.), and Regional Director, Madhya Pradesh Bhoj (Open) University, Indore (M.P.), India
Dr. P. Dananjayan Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry,India
Dr. Sadhana Vishwakarma Associate Professor, Department of Engineering Chemistry, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Kamal Mehta Associate Professor, Deptment of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. CheeFai Tan Faculty of Mechanical Engineering, University Technical, Malaysia Melaka, Malaysia
Dr. Suresh Babu Perli Professor& Head, Department of Electrical and Electronic Engineering, Narasaraopeta Engineering College, Guntur, A.P., India
Dr. Binod Kumar Associate Professor, Schhool of Engineering and Computer Technology, Faculty of Integrative Sciences and Technology, Quest International University, Ipoh, Perak, Malaysia
Dr. Chiladze George Professor, Faculty of Law, Akhaltsikhe State University, Tbilisi University, Georgia
Dr. Kavita Khare Professor, Department of Electronics & Communication Engineering., MANIT, Bhopal (M.P.), INDIA
Dr. C. Saravanan Associate Professor (System Manager) & Head, Computer Center, NIT, Durgapur, W.B. India
Dr. S. Saravanan Professor, Department of Electrical and Electronics Engineering, Muthayamal Engineering College, Resipuram, Tamilnadu, India
Dr. Amit Kumar Garg Professor & Head, Department of Electronics and Communication Engineering, Maharishi Markandeshwar University, Mulllana, Ambala (Haryana), India
Dr. T.C.Manjunath Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. P. Dananjayan Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry, India
Dr. Kamal K Mehta Associate Professor, Department of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. Rajiv Srivastava Director, Department of Computer Science & Engineering, Sagar Institute of Research & Technology, Bhopal (M.P.), India
Dr. Chakunta Venkata Guru Rao Professor, Department of Computer Science & Engineering, SR Engineering College, Ananthasagar, Warangal, Andhra Pradesh, India
Dr. Anuranjan Misra Professor, Department of Computer Science & Engineering, Bhagwant Institute of Technology, NH-24, Jindal Nagar, Ghaziabad, India
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. Saber Mohamed Abd-Allah Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Yue Yang Road, Shanghai, China
Dr. Himani Sharma Professor & Dean, Department of Electronics & Communication Engineering, MLR Institute of Technology, Laxman Reddy Avenue, Dundigal, Hyderabad, India
Dr. Sahab Singh Associate Professor, Department of Management Studies, Dronacharya Group of Institutions, Knowledge Park-III, Greater Noida, India
Dr. Umesh Kumar Principal: Govt Women Poly, Ranchi, India
Dr. Syed Zaheer Hasan Scientist-G Petroleum Research Wing, Gujarat Energy Research and Management Institute, Energy Building, Pandit Deendayal Petroleum University Campus, Raisan, Gandhinagar-382007, Gujarat, India.
Dr. Jaswant Singh Bhomrah Director, Department of Profit Oriented Technique, 1 – B Crystal Gold, Vijalpore Road, Navsari 396445, Gujarat. India
Technical Advisory Board Dr. Mohd. Husain Director, MG Institute of Management & Technology, Banthara, Lucknow (U.P.), India Dr. T. Jayanthy Principal, Panimalar Institute of Technology, Chennai (TN), India
Dr. Umesh A.S. Director, Technocrats Institute of Technology & Science, Bhopal(M.P.), India
Dr. B. Kanagasabapathi Infosys Labs, Infosys Limited, Center for Advance Modeling and Simulation, Infosys Labs, Infosys Limited, Electronics City, Bangalore, India
Dr. C.B. Gupta Professor, Department of Mathematics, Birla Institute of Technology & Sciences, Pilani (Rajasthan), India
Dr. Sunandan Bhunia Associate Professor & Head,, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Jaydeb Bhaumik Associate Professor, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Rajesh Das Associate Professor, School of Applied Sciences, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Mrutyunjaya Panda Professor & Head, Department of EEE, Gandhi Institute for Technological Development, Bhubaneswar, Odisha, India
Dr. Mohd. Nazri Ismail Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia
Dr. Haw Su Cheng Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia, 63100 Cyberjaya
Dr. Hossein Rajabalipour Cheshmehgaz Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia (UTM) 81310, Skudai, Malaysia
Dr. Sudhinder Singh Chowhan Associate Professor, Institute of Management and Computer Science, NIMS University, Jaipur (Rajasthan), India
Dr. Neeta Sharma Professor & Head, Department of Communication Skils, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Ashish Rastogi Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Santosh Kumar Nanda Professor, Department of Computer Science and Engineering, Eastern Academy of Science and Technology (EAST), Khurda (Orisa), India
Dr. Hai Shanker Hota Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Sunil Kumar Singla Professor, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala (Punjab), India
Dr. A. K. Verma Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India
Dr. Durgesh Mishra Chairman, IEEE Computer Society Chapter Bombay Section, Chairman IEEE MP Subsection, Professor & Dean (R&D), Acropolis Institute of Technology, Indore (M.P.), India
Dr. Xiaoguang Yue Associate Professor, College of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China
Dr. Veronica Mc Gowan Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman China Dr. Mohd. Ali Hussain Professor, Department of Computer Science and Engineering, Sri Sai Madhavi Institute of Science & Technology, Rajahmundry (A.P.), India
Dr. Mohd. Nazri Ismail Professor, System and Networking Department, Jalan Sultan Ismail, Kaula Lumpur, MALAYSIA
Dr. Sunil Mishra Associate Professor, Department of Communication Skills (English), Dronacharya College of Engineering, Farrukhnagar, Gurgaon (Haryana), India
Dr. Labib Francis Gergis Rofaiel Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology, Mansoura City, Egypt
Dr. Pavol Tanuska Associate Professor, Department of Applied Informetics, Automation, and Mathematics, Trnava, Slovakia
Dr. VS Giridhar Akula Professor, Avanthi's Research & Technological Academy, Gunthapally, Hyderabad, Andhra Pradesh, India
Dr. S. Satyanarayana Associate Professor, Department of Computer Science and Engineering, KL University, Guntur, Andhra Pradesh, India
Dr. Bhupendra Kumar Sharma Associate Professor, Department of Mathematics, KL University, BITS, Pilani, India
Dr. Praveen Agarwal Associate Professor& Head, Department of Mathematics, Anand International College of Engineering, Jaipur (Rajasthan), India
Dr. Manoj Kumar Professor, Department of Mathematics, Rashtriya Kishan Post Graduate Degree, College, Shamli, Prabudh Nagar, (U.P.), India
Dr. Shaikh Abdul Hannan Associate Professor, Department of Computer Science, Vivekanand Arts Sardar Dalipsing Arts and Science College, Aurangabad (Maharashtra), India
Dr. K.M. Pandey Professor, Department of Mechanical Engineering,National Institute of Technology, Silchar, India
Prof. Pranav Parashar Technical Advisor, International Journal of Soft Computing and Engineering (IJSCE), Bhopal (M.P.), India
Dr. Biswajit Chakraborty MECON Limited, Research and Development Division (A Govt. of India Enterprise), Ranchi-834002, Jharkhand, India
Dr. D.V. Ashoka Professor & Head, Department of Information Science & Engineering, SJB Institute of Technology, Kengeri, Bangalore, India
Dr. Sasidhar Babu Suvanam Professor & Academic Cordinator, Department of Computer Science & Engineering, Sree Narayana Gurukulam College of Engineering, Kadayiuruppu, Kolenchery, Kerala, India
Dr. C. Venkatesh Professor & Dean, Faculty of Engineering, EBET Group of Institutions, Kangayam, Erode, Caimbatore (Tamil Nadu), India
Dr. Nilay Khare Assoc. Professor & Head, Department of Computer Science, MANIT, Bhopal (M.P.), India
Dr. Sandra De Iaco Professor, Dip.to Di Scienze Dell’Economia-Sez. Matematico-Statistica, Italy
Dr. Yaduvir Singh Associate Professor, Department of Computer Science & Engineering, Ideal Institute of Technology, Govindpuram Ghaziabad, Lucknow (U.P.), India
Dr. Angela Amphawan Head of Optical Technology, School of Computing, School Of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia Dr. Ashwini Kumar Arya Associate Professor, Department of Electronics & Communication Engineering, Faculty of Engineering and Technology,Graphic Era University, Dehradun (U.K.), India
Dr. Yash Pal Singh Professor, Department of Electronics & Communication Engg, Director, KLS Institute Of Engg.& Technology, Director, KLSIET, Chandok, Bijnor, (U.P.), India
Dr. Ashish Jain Associate Professor, Department of Computer Science & Engineering, Accurate Institute of Management & Technology, Gr. Noida (U.P.), India
Dr. Abhay Saxena Associate Professor&Head, Department. of Computer Science, Dev Sanskriti University, Haridwar, Uttrakhand, India
Dr. Judy. M.V Associate Professor, Head of the Department CS &IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Brahmasthanam, Edapally, Cochin, Kerala, India
Dr. Sangkyun Kim Professor, Department of Industrial Engineering, Kangwon National University, Hyoja 2 dong, Chunche0nsi, Gangwondo, Korea
Dr. Sanjay M. Gulhane Professor, Department of Electronics & Telecommunication Engineering, Jawaharlal Darda Institute of Engineering & Technology, Yavatmal, Maharastra, India
Dr. K.K. Thyagharajan Principal & Professor, Department of Informational Technology, RMK College of Engineering & Technology, RSM Nagar, Thiruyallur, Tamil Nadu, India
Dr. P. Subashini Asso. Professor, Department of Computer Science, Coimbatore, India
Dr. G. Srinivasrao Professor, Department of Mechanical Engineering, RVR & JC, College of Engineering, Chowdavaram, Guntur, India
Dr. Rajesh Verma Professor, Department of Computer Science & Engg. and Deptt. of Information Technology, Kurukshetra Institute of Technology & Management, Bhor Sadian, Pehowa, Kurukshetra (Haryana), India
Dr. Pawan Kumar Shukla Associate Professor, Satya College of Engineering & Technology, Haryana, India
Dr. U C Srivastava Associate Professor, Department of Applied Physics, Amity Institute of Applied Sciences, Amity University, Noida, India
Dr. Reena Dadhich Prof.& Head, Department of Computer Science and Informatics, MBS MArg, Near Kabir Circle, University of Kota, Rajasthan, India
Dr. Aashis.S.Roy Department of Materials Engineering, Indian Institute of Science, Bangalore Karnataka, India
Dr. Sudhir Nigam Professor Department of Civil Engineering, Principal, Lakshmi Narain College of Technology and Science, Raisen, Road, Bhopal, (M.P.), India
Dr. S.Senthilkumar Doctorate, Department of Center for Advanced Image and Information Technology, Division of Computer Science and Engineering, Graduate School of Electronics and Information Engineering, Chon Buk National University Deok Jin-Dong, Jeonju, Chon Buk, 561- 756, South Korea Tamilnadu, India
Dr. Gufran Ahmad Ansari Associate Professor, Department of Information Technology, College of Computer, Qassim University, Al-Qassim, Kingdom of Saudi Arabia (KSA)
Dr. R.Navaneethakrishnan Associate Professor, Department of MCA, Bharathiyar College of Engg & Tech, Karaikal Puducherry, India
Dr. Hossein Rajabalipour Cheshmejgaz Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi Skudai, Malaysia
Dr. Veronica McGowan Associate Professor, Department of Computer and Business Information Systems, Delaware Valley College, Doylestown, PA, Allman China
Dr. Sanjay Sharma Associate Professor, Department of Mathematics, Bhilai Institute of Technology, Durg, Chhattisgarh, India
Dr. Taghreed Hashim Al-Noor Professor, Department of Chemistry, Ibn-Al-Haitham Education for pure Science College, University of Baghdad, Iraq
Dr. Madhumita Dash Professor, Department of Electronics & Telecommunication, Orissa Engineering College , Bhubaneswar,Odisha, India
Dr. Anita Sagadevan Ethiraj Associate Professor, Department of Centre for Nanotechnology Research (CNR), School of Electronics Engineering (Sense), Vellore Institute of Technology (VIT) University, Tamilnadu, India
Dr. Sibasis Acharya Project Consultant, Department of Metallurgy & Mineral Processing, Midas Tech International, 30 Mukin Street, Jindalee-4074, Queensland, Australia
Dr. Neelam Ruhil Professor, Department of Electronics & Computer Engineering, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Faizullah Mahar Professor, Department of Electrical Engineering, Balochistan University of Engineering and Technology, Pakistan
Dr. K. Selvaraju Head, PG & Research, Department of Physics, Kandaswami Kandars College (Govt. Aided), Velur (PO), Namakkal DT. Tamil Nadu, India
Dr. M. K. Bhanarkar Associate Professor, Department of Electronics, Shivaji University, Kolhapur, Maharashtra, India
Dr. Sanjay Hari Sawant Professor, Department of Mechanical Engineering, Dr. J. J. Magdum College of Engineering, Jaysingpur, India
Dr. Arindam Ghosal Professor, Department of Mechanical Engineering, Dronacharya Group of Institutions, B-27, Part-III, Knowledge Park,Greater Noida, India
Dr. M. Chithirai Pon Selvan Associate Professor, Department of Mechanical Engineering, School of Engineering & Information Technology, Amity University, Dubai, UAE
Dr. S. Sambhu Prasad Professor & Principal, Department of Mechanical Engineering, Pragati College of Engineering, Andhra Pradesh, India.
Dr. Muhammad Attique Khan Shahid Professor of Physics & Chairman, Department of Physics, Advisor (SAAP) at Government Post Graduate College of Science, Faisalabad.
Dr. Kuldeep Pareta Professor & Head, Department of Remote Sensing/GIS & NRM, B-30 Kailash Colony, New Delhi 110 048, India
Dr. Th. Kiranbala Devi Associate Professor, Department of Civil Engineering, Manipur Institute of Technology, Takyelpat, Imphal, Manipur, India
Dr. Nirmala Mungamuru Associate Professor, Department of Computing, School of Engineering, Adama Science and Technology University, Ethiopia
Dr. Srilalitha Girija Kumari Sagi Associate Professor, Department of Management, Gandhi Institute of Technology and Management, India
Dr. Vishnu Narayan Mishra Associate Professor, Department of Mathematics, Sardar Vallabhbhai National Institute of Technology, Ichchhanath Mahadev Dumas Road, Surat (Gujarat), India
Dr. Yash Pal Singh Director/Principal, Somany (P.G.) Institute of Technology & Management, Garhi Bolni Road , Rewari Haryana, India.
Dr. Sripada Rama Sree Vice Principal, Associate Professor, Department of Computer Science and Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh. India.
Dr. Rustom Mamlook Associate Professor, Department of Electrical and Computer Engineering, Dhofar University, Salalah, Oman. Middle East.
Dr. Ramzi Raphael Ibraheem Al Barwari Assistant Professor, Department of Mechanical Engineering, College of Engineering, Salahaddin University – Hawler (SUH) Erbil – Kurdistan, Erbil Iraq.
Dr. Kapil Chandra Agarwal H.O.D. & Professor, Department of Applied Sciences & Humanities, Radha Govind Engineering College, U. P. Technical University, Jai Bheem Nagar, Meerut, (U.P). India.
Dr. Anil Kumar Tripathy Associate Professor, Department of Environmental Science & Engineering, Ghanashyama Hemalata Institute of Technology and Management, Puri Odisha, India.
Managing Editor Mr. Jitendra Kumar Sen International Journal of Soft Computing and Engineering (IJSCE)
Editorial Board Dr. Soni Changlani Professor, Department of Electronics & Communication, Lakshmi Narain College of Technology & Science, Bhopal (.M.P.), India
Dr. M .M. Manyuchi Professor, Department Chemical and Process Systems Engineering, Lecturer-Harare Institute of Technology, Zimbabwe
Dr. John Kaiser S. Calautit Professor, Department Civil Engineering, School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, United Kingdom
Dr. Audai Hussein Al-Abbas Deputy Head, Department AL-Musaib Technical College/ Foundation of Technical Education/Babylon, Iraq
Dr. Şeref Doğuşcan Akbaş Professor, Department Civil Engineering, Şehit Muhtar Mah. Öğüt Sok. No:2/37 Beyoğlu Istanbul, Turkey
Dr. H S Behera Associate Professor, Department Computer Science & Engineering, Veer Surendra Sai University of Technology (VSSUT) A Unitary Technical University Established by the Government of Odisha, India
Dr. Rajeev Tiwari Associate Professor, Department Computer Science & Engineering, University of Petroleum & Energy Studies (UPES), Bidholi, Uttrakhand, India
Dr. Piyush Kumar Shukla Assoc. Professor, Department of Computer Science and Engineering, University Institute of Technology, RGPV, Bhopal (M.P.), India
Dr. Piyush Lotia Assoc.Professor, Department of Electronics and Instrumentation, Shankaracharya College of Engineering and Technology, Bhilai (C.G.), India
Dr. Asha Rai Assoc. Professor, Department of Communication Skils, Technocrat Institute of Technology, Bhopal (M.P.), India
Dr. Vahid Nourani Assoc. Professor, Department of Civil Engineering, University of Minnesota, USA
Dr. Hung-Wei Wu Assoc. Professor, Department of Computer and Communication, Kun Shan University, Taiwan
Dr. Vuda Sreenivasarao Associate Professor, Department of Computr And Information Technology, Defence University College, Debrezeit Ethiopia, India
Dr. Sanjay Bhargava Assoc. Professor, Department of Computer Science, Banasthali University, Jaipur, India
Dr. Sanjoy Deb Assoc. Professor, Department of ECE, BIT Sathy, Sathyamangalam, Tamilnadu, India
Dr. Papita Das (Saha) Assoc. Professor, Department of Biotechnology, National Institute of Technology, Duragpur, India
Dr. Waail Mahmod Lafta Al-waely Assoc. Professor, Department of Mechatronics Engineering, Al-Mustafa University College – Plastain Street near AL-SAAKKRA square- Baghdad - Iraq
Dr. P. P. Satya Paul Kumar Assoc. Professor, Department of Physical Education & Sports Sciences, University College of Physical Education & Sports Sciences, Guntur
Dr. Sohrab Mirsaeidi Associate Professor, Department of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia
Dr. Ehsan Noroozinejad Farsangi Associate Professor, Department of Civil Engineering, International Institute of Earthquake Engineering and Seismology (IIEES) Farmanieh, Tehran - Iran
Dr. Omed Ghareb Abdullah Associate Professor, Department of Physics, School of Science, University of Sulaimani, Iraq Dr. Khaled Eskaf Associate Professor, Department of Computer Engineering, College of Computing and Information Technology, Alexandria, Egypt
Dr. Nitin W. Ingole Associate Professor & Head, Department of Civil Engineering, Prof Ram Meghe Institute of Technology and Research, Badnera Amravati
Dr. P. K. Gupta Associate Professor, Department of Computer Science and Engineering, Jaypee University of Information Technology, P.O. Dumehar Bani, Solan, India
Dr. P.Ganesh Kumar Associate Professor, Department of Electronics & Communication, Sri Krishna College of Engineering and Technology, Linyi Top Network Co Ltd Linyi , Shandong Provience, China
Dr. Santhosh K V Associate Professor, Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal, Karnataka, India
Dr. Subhendu Kumar Pani Assoc. Professor, Department of Computer Science and Engineering, Orissa Engineering College, India
Dr. Syed Asif Ali Professor/ Chairman, Department of Computer Science, SMI University, Karachi, Pakistan
Dr. Vilas Warudkar Assoc. Professor, Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, India
Dr. S. Chandra Mohan Reddy Associate Professor & Head, Department of Electronics & Communication Engineering, JNTUA College of Engineering (Autonomous), Cuddapah, Andhra Pradesh, India
Dr. V. Chittaranjan Das Associate Professor, Department of Mechanical Engineering, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India
Dr. Jamal Fathi Abu Hasna Associate Professor, Department of Electrical & Electronics and Computer Engineering, Near East University, TRNC, Turkey
Dr. S. Deivanayaki Associate Professor, Department of Physics, Sri Ramakrishna Engineering College, Tamil Nadu, India
Dr. Nirvesh S. Mehta Professor, Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, South Gujarat, India
Dr. A.Vijaya Bhasakar Reddy Associate Professor, Research Scientist, Department of Chemistry, Sri Venkateswara University, Andhra Pradesh, India
Dr. C. Jaya Subba Reddy Associate Professor, Department of Mathematics, Sri Venkateswara University Tirupathi Andhra Pradesh, India
Dr. TOFAN Cezarina Adina Associate Professor, Department of Sciences Engineering, Spiru Haret University, Arges, Romania
Dr. Balbir Singh Associate Professor, Department of Health Studies, Human Development Area, Administrative Staff College of India, Bella Vista, Andhra Pradesh, India
Dr. D. RAJU Associate Professor, Department of Mathematics, Vidya Jyothi Institute of Technology (VJIT), Aziz Nagar Gate, Hyderabad, India
Dr. Salim Y. Amdani Associate Professor & Head, Department of Computer Science Engineering, B. N. College of Engineering, PUSAD, (M.S.), India
Dr. K. Kiran Kumar Associate Professor, Department of Information Technology, Bapatla Engineering College, Andhra Pradesh, India
Dr. Md. Abdullah Al Humayun Associate Professor, Department of Electrical Systems Engineering, University Malaysia Perlis, Malaysia Dr. Vellore Vasu Teaching Assistant, Department of Mathematics, S.V.University Tirupati, Andhra Pradesh, India
Dr. Naveen K. Mehta Associate Professor & Head, Department of Communication Skills, Mahakal Institute of Technology, Ujjain, India
Dr. Gujar Anant kumar Jotiram Associate Professor, Department of Mechanical Engineering, Ashokrao Mane Group of Institutions, Vathar, Maharashtra, India
Dr. Pratibhamoy Das Scientist, Department of Mathematics, IMU Berlin Einstein Foundation Fellow Technical University of Berlin, Germany
Dr. Messaouda AZZOUZI Associate Professor, Department of Sciences & Technology, University of Djelfa, Algeria
Dr. Vandana Swarnkar Associate Professor, Department of Chemistry, Jiwaji University Gwalior, India
Dr. Arvind K. Sharma Associate Professor, Department of Computer Science Engineering, University of Kota, Kabir Circle, Rajasthan, India
Dr. R. Balu Associate Professor, Department of Computr Applications, Bharathiar University, Tamilnadu, India
Dr. S. Suriyanarayanan Associate Professor, Department of Water and Health, Jagadguru Sri Shivarathreeswara University, Karnataka, India
Dr. Dinesh Kumar Associate Professor, Department of Mathematics, Pratap University, Jaipur, Rajasthan, India
Dr. Sandeep N Associate Professor, Department of Mathematics, Vellore Institute of Technology, Tamil Nadu, India
Dr. Dharmpal Singh Associate Professor, Department of Computer Science Engineering, JIS College of Engineering, West Bengal, India Dr. Farshad Zahedi Associate Professor, Department of Mechanical Engineering, University of Texas at Arlington, Tehran, Iran
Dr. Atishey Mittal Associate Professor, Department of Mechanical Engineering, SRM University NCR Campus Meerut Delhi Road Modinagar, Aligarh, India
Dr. Hussein Togun Associate Professor, Department of Mechanical Engineering, University of Thiqar, Iraq
Dr. Shrikaant Kulkarni Associate Professor, Department of Senior faculty V.I.T., Pune (M.S.), India
Dr. Mukesh Negi Project Manager, Department of Computer Science & IT, Mukesh Negi, Project Manager, Noida, India
Dr. Sachin Madhavrao Kanawade Associate Professor, Department Chemical Engineering, Pravara Rural Education Society’s,Sir Visvesvaraya Institute of Technology, Nashik, India
Dr. Ganesh S Sable Professor, Department of Electronics and Telecommunication, Maharashtra Institute of Technology Satara Parisar, Aurangabad, Maharashtra, India
Dr. T.V. Rajini Kanth Professor, Department of Computer Science Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India
Dr. Anuj Kumar Gupta Associate Professor, Department of Computer Science & Engineering, RIMT Institute of Engineering & Technology, NH-1, Mandi Godindgarh, Punjab, India
Dr. Hasan Ashrafi- Rizi Associate Professor, Medical Library and Information Science Department of Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
Dr. Golam Kibria Associate Professor, Department of Mechanical Engineering, Aliah University, Kolkata, India
Dr. Mohammad Jannati Professor, Department of Energy Conversion, UTM-PROTON Future Drive Laboratory, Faculty of Electrical Enginering, Universit Teknologi Malaysia,
Dr. Mohammed Saber Mohammed Gad Professor, Department of Mechanical Engineering, National Research Centre- El Behoos Street, El Dokki, Giza, Cairo, Egypt,
Dr. V. Balaji Professor, Department of EEE, Sapthagiri College of Engineering Periyanahalli,(P.O) Palacode (Taluk) Dharmapuri,
Dr. Naveen Beri Associate Professor, Department of Mechanical Engineering, Beant College of Engg. & Tech., Gurdaspur - 143 521, Punjab, India
Dr. Abdel-Baset H. Mekky Associate Professor, Department of Physics, Buraydah Colleges Al Qassim / Saudi Arabia
Dr. T. Abdul Razak Associate Professor, Department of Computer Science Jamal Mohamed College (Autonomous), Tiruchirappalli – 620 020 India
Dr. Preeti Singh Bahadur Associate Professor, Department of Applied Physics Amity University, Greater Noida (U.P.) India
Dr. Ramadan Elaiess Associate Professor, Department of Information Studies, Faculty of Arts University of Benghazi, Libya
Dr. R . Emmaniel Professor & Head, Department of Business Administration ST, ANN, College of Engineering & Technology Vetapaliem. Po, Chirala, Prakasam. DT, AP. India
Dr. C. Phani Ramesh Director cum Associate Professor, Department of Computer Science Engineering, PRIST University, Manamai, Chennai Campus, India
Dr. Rachna Goswami Associate Professor, Department of Faculty in Bio-Science, Rajiv Gandhi University of Knowledge Technologies (RGUKT) District- Krishna, Andhra Pradesh, India
Dr. Sudhakar Singh Assoc. Prof. & Head, Department of Physics and Computer Science, Sardar Patel College of Technology, Balaghat (M.P.), India
Dr. Xiaolin Qin Associate Professor & Assistant Director of Laboratory for Automated Reasoning and Programming, Chengdu Institute of Computer Applications, Chinese Academy of Sciences, China
Dr. Maddila Lakshmi Chaitanya Assoc. Prof. Department of Mechanical, Pragati Engineering College 1-378, ADB Road, Surampalem, Near Peddapuram, East Godavari District, A.P., India
Dr. Jyoti Anand Assistant Professor, Department of Mathematics, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Nasser Fegh-hi Farahmand Assoc. Professor, Department of Industrial Management, College of Management, Economy and Accounting, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Dr. Ravindra Jilte Assist. Prof. & Head, Department of Mechanical Engineering, VCET Vasai, University of Mumbai , Thane, Maharshtra 401202, India
Dr. Sarita Gajbhiye Meshram Research Scholar, Department of Water Resources Development & Management Indian Institute of Technology, Roorkee, India
Dr. G. Komarasamy Associate Professor, Senior Grade, Department of Computer Science & Engineering, Bannari Amman Institute of Technology, Sathyamangalam,Tamil Nadu, India
Dr. P. Raman Professor, Department of Management Studies, Panimalar Engineering College Chennai, India
Dr. M. Anto Bennet Professor, Department of Electronics & Communication Engineering, Veltech Engineering College, Chennai, India
Dr. P. Keerthika Associate Professor, Department of Computer Science & Engineering, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Kumar Behera Associate Professor, Department of Education, Sidho-Kanho-Birsha University, Ranchi Road, P.O. Sainik School, Dist-Purulia, West Bengal, India
Dr. P. Suresh Associate Professor, Department of Information Technology, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Shivajirao Lomte Associate Professor, Department of Computer Science and Information Technology, Radhai Mahavidyalaya, N-2 J sector, opp. Aurangabad Gymkhana, Jalna Road Aurangabad, India
Dr. Altaf Ali Siyal Professor, Department of Land and Water Management, Sindh Agriculture University Tandojam, Pakistan
Dr. Mohammad Valipour Associate Professor, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
Dr. Prakash H. Patil Professor and Head, Department of Electronics and Tele Communication, Indira College of Engineering and Management Pune, India
Dr. Smolarek Małgorzata Associate Professor, Department of Institute of Management and Economics, High School of Humanitas in Sosnowiec, Wyższa Szkoła Humanitas Instytut Zarządzania i Ekonomii ul. Kilińskiego Sosnowiec Poland, India S. Volume-3 Issue-1, March 2013, ISSN: 2231-2307 (Online) Page No Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. No.
Authors: Manoj Kumar Jain, Ravi Khatwal Paper Title: High Performance Simulator Analyzing the Efficient Cache Memory Simulation Behavior Abstract: High performance is the major concern in the area of VLSI Design. Cache memory consumes the half of total power in various systems. Thus, the architecture behavior of the cache governs both high performance and low power consumption. Simulator simulates cache memory design in various formats with help of various simulators like simple scalar, Xilinx etc. This paper explores the issue and consideration involved in designing efficient cache memory and we have discussed the cache memory simulation behavior on various simulators. Memory design concept is becoming dominant; memory level parallism is one of the critical issues concerning its performance. We have to propose high performance cache simulation behavior for performance improvement for future mobile processors design and customize mobile devices.
Keywords: Application Specific Instruction Processors, Memory design, Simple scalar simulator, Xilinx, Micro wind, Top spice 8 Simulator etc.
References: 1. M. K. Jain, M. Balakrishnan and A Kumar, “Integrated on-chip storage evaluation in ASIP synthesis ”, VLSI Design, 2005. 18th International Conference ,2005, pp.274 - 279. 2. P. R. Panda, N.D. Dutt and A. Nicoulau, “Data Memory Organization and Optimization In Application Specific Systems”,IEEE design & Tests of Computers, May-June 2001, pp. 56-68. 3. M. Martin, “Low power SRAM circuit design”, IEEE design and test of 1. computer pg.115-122, 1999. 4. K.. Itoh, “Embedded Memories: Progress and a look in to the future “, IEEE Circuits and Systems Society, IEEE Computer Society pg.10-13, Jan -Feb, 2011, Japan. 1-6 5. Z. Ge,“Memory Hierarchy Hardware –Software Co-design in Embedded systems”, IT lab, Singapore journal. 2004. 6. X. Wang, “A Combined Optimization Method for Tuning Two-level hierarchy considering Energy consumption”, EURASIP Journal on Embedded system, 21 Sept, 2010. 7. S. Simon Wong and A. El. Gamal, “The prospect of 3-D IC”, IEEE Design and test computer, June, 2009.pp..445-447. 8. S. Mama kakis,“Custom Design of Multi- Level Dynamic Memory management Subsystem for Embedded systems”, IEEE Society ,April-2004 pp. 170-175. 9. J. Liu and H. Sun, “3- DRAM Design And Application to 3-D Multicore System”, IEEE design and test ,2009. pp.36-48 10. F .Hamzaoglu, Y.Wang, P.,Kolar, U.Bhattacharya and K Zhang., "Bit Cell Optimizations and Circuit Techniques for Nanoscale SRAM Design", IEEE Design and Test of Computers, vol. 28, 2011, pp. 22-31. 11. E. Jeannot, R. Namyst, and J. Roman (Eds.), “FELI: HW/SW Support for On-Chip Distributed Shared Memory in Multicores”, Euro-Par 2011, LNCS 6852, Part I, 2011, pp. 280–292. 12. V. K. Singhal, B. Singh,“ Comparative Study Of Power Reduction Techniques For Static Random Access Memory” ,International Journal of VLSI and Signal Processing Applications, Vol. 1, Issue 2 , May 2011,pp.80-88. 13. S Petit.J. Sahuquillo, P Lopez, J. Duato, and A Valero, “Design, Performance and Energy Consumption of e-DRAM SRAM Macrocells for Data Caches”, IEEE computer society, 29 July 2011. 14. www.simplescalar.com. 15. S., Singh, N Arora,M. Suthar and N. Gupta, “Low power efficient SRAM cell structure at different technology”, International journal of VLSI & signal processing Application, Vol.2, 1Feb 2012, pp.41-46. 16. K., Dhanumjaya, M., Sudha, M., MN.Giri Prasad,And K. Padmaraju, “Cell stability analysis of conventional 6 T Dynamic 8T SRAM cell in 45 nm technology”, International journal of VLSI design & communication system (VLSICS), Vol.3, No.2, April-2012. 17. A.Jhansi Rani, V.G. Santhi Swaroop, “Designing and analysis of 8bit SRAM cell with Low subthres hold Leakage Power”, International Journal of Modern Engineering Research(IJMER) ,Vol. 2,Issue .3, May-June 2012, pp.733-741. 18. www.xilinx.com/homepage/. Authors: V. Siva Rama Prasad, P. Anantha Reddy, M.Ganeshwar Rao Paper Title: On a r - GCD-Sum Function Over r-Regular Integers Modulo nr Abstract: Introducing an r-gcd-sum function over r-regular integers modulo (studied by the authors [10] earlier), we obtain an asymptotic formula for its summatory function. The case of our result gives the formula established by László Tóth [8].
Keywords: regular integers modulo -gcd of two positive integers, -residue system, reduced -residue system, unitary divisor of an integer, Dirichlet divisor problem, Riemann Hypothesis. 2010 Mathematics Subject Classification: Primary: 11A25, Secondary: 11N37
References: 2. 1. . Bordellès, A note on the average order of the gcd-sum function, J. Integer Sequences, 10 (2007), Art. 07.3.3 2. E. cohen, Arithmetical functions associated with the unitary divisors of an integer, Math. Zeit. , 74(1960), 66-80 7-11 3. L.E. Dickson, History of Theory of numbers, Volume I, Carnegie Institution of Washington, 1919; reprinted Chelsea Publishing Company, New York, 1952 4. G.H. Hardy, The average order of the arithmetical functions and , Proc., London Math. Soc., 15(2), (1916), 192-213 5. M.N. Huxley, Exponential sums and Lattice points III, Proc. London Math. Soc., 87 (2003), 591-609 6. V.L. Klee, A generalization of Euler's function, Amer. Math. Monthly, 55 (1948), 358-359 7. László Tóth, Regular integers (mod n), Annales Univ. Sci. Budapest. Sect. Comp., 29 (2008), 263-275 8. László Tóth, A gcd-sum function over regular integers modulo n, J. Integer Sequences, Vol.12 (2009), Article 09.2.5 9. Paul J. McCarthy, Introduction to Arithmetical functions, Springer-Verlag, New York, 1986 10. V. Siva Rama Prasad, P. Anantha Reddy, and M. Ganeshar Rao, r-Regular Integers Modulo J. Andra Pradesh Society of Math. Sci. (Accepted) 11. V. Siva Rama Prasad, P. Anantha Reddy, and M. Ganeshar Rao, On the r-gcd-sum function (communicated). 12. D. Suryanarayana and V. Siva Rama Prasad, The number of k-free and k-ary divisors of m which are prime to n, J. Reine Angew. Math. 264 (1973), 56-75 Authors: Anindya Sundar Das, Banibrata Bag, Akinchan Das, Ardhendu Sekhar Patra Paper Title: A Novel Radio over Fiber System for Long Haul Single-Mode-Fiber Transmission Abstract: We have proposed and demonstrated a novel architecture of a radio over fiber (RoF) system in this paper. In this downlink system, the base band data signals are carried by the optical millimeter-wave generated at the central station and converted to the electrical RF signal by a converter at the base station before we distribute them through antenna. Here we generate and transmit the optical millimeter-wave by using external modulation technique and carrier suppression method. The performance is investigated by the good eye diagram and the significantly low BER at different lengths of the single mode fiber (SMF).
Keywords: RoF system, Optical carrier suppression, Long haul transmission, Bit error rate, Q-factor.
References: 3. 1. A.Naser, A.Mohamed, A.Rashed, M. Tabour and S.Hanafy “ Radio over fiber communication systems over multimode polymer optical fibers for short transmission distances under modulation technique”, International Journal of Science and Technology, vol. 1, no. 2, August, 2011, pp. 60-68. 12-15 2. R.P.Braun, G.Grosskopf, D.Rohde, “Optical millimeter-wave generation and transmission technologies for mobile technologies for mobile communications, an overview”, in: Proceedings of Microwave Systems Conference, May 1995, IEEE NTC ’9517-19, pp.239. 3. J.Yu, Z.Jia, L.Xu, L.Chen, T.Wang, and G.Chang, “DWDM optical millimeter wave generation for radio over fiber using an optical phase modulator and an optical interleaver”, IEEE photonics technology letters, vol.18, no.13, 2006, pp. 1418-1420 4. G.Qi, J.Yao, K.Wu, X. Zhang and R. Kasyap ,“Phase-noise analysis of optically generated millimeter wave signals with external modulation technique”, Jounal of Lightwave Technology, vol. 24, no. 12, Dec. 2006, pp.4861-4875. 5. J.M.Fuster, J. Marti, J.L. Corral, V. Polo and F.Ramos, “Generalized Study of Dispersion-Induced Power Penalty Mitigation Techniques in Millimeter-Wave Fiber-Optic Links”. Journal of Lightwave Technology, vol. 18, no. 7, July 2000, pp.933-940. 6. G.Smith, D. Novak and Z. Ahmed, “Overcoming chromatic-dispersion effects in fiber-wireless systems incorporating external modulators”, IEEE transactions on microwave theory and techniques, vol.45, no.8, August 1997, pp.1410-1415. 7. A.O. Aladeloba, A.J. Phillips, M.S. Woolfson, “Improved bit error rate evaluation for optically pre-amplified free-space optical communication systems in turbulent atmosphere”, IET Optoelectronics, July 2011, pp. 26-33. 8. G.Keiser, Optical Fiber Communication, Tata McGraw-Hill., 2010, pp. 269–274. 9. G.P.Agrawal, Fiber-Optic Communication System, John Wiley & sons, inc., publication, 2002, pp. 159-166 Authors: N V Uma Reddy, M V Chaitanya Kumar Paper Title: InGaAs/GaAs HEMT for High Frequency Applications Abstract: In the modern VLSI especially for high speed devices, where the conventional MOSFET technology is reaching its limitations due to various short channel effects and velocity saturation effects etc, hetero-junction FETs have shown great promise for high speed devices. Novel HEMT device using heterojunctions made of InGaAs and InAlAs on a GaAs substrate is designed and modeled using TCAD software. Highly doped deep source-drain implants are proposed for the design. The device simulations have demonstrated its utility towards high frequency applications in GHz range.
Keywords: HEMT, InGaAs,InAlAs 4. References: 16-20 1. D. H. Kim and J. A. Del Alamo, “30 nm E-mode InAs PHEMTs for THz and future logic applications,” in IEDM Tech. Dig., Dec. 2008, pp. 719–722. 2. Ghandhi, S.K. “VLSI Fabrication Principles- Silicon and Gallium Arsenide”, Second Edition, John Wiley & Sons, New York (1994). 3. Leuther, R. Weber, M. Dammann, M. Schlechtweg, M. Mikulla, M. Walther, and G. Weimann, “Metamorphic 50 nm InAs-channel HEMT” in Proc. 17th Int. Conf. IPRM, May 2005, pp. 129–132. 4. William Liu. “Fundamentals of III-V Devices”. John Wiley & Sons, 1999. 5. Kennedy D.P (1975). “The potential and electric field at the metallurgical boundary of an abrupt p-n semiconductor junction”. IEEE Trans. Electr. Dev. 22, 988-994. 6. W, Liu “Fundamentals of III-V devices”, John Wiley & Sons, New York (1999). 7. “ http://www.cleanroom.byu.edu/EW_ternary.phtml” 8. Adachi, S (1985, Aug) “GaAs, AlAs, and AlxGa1-xAs: Material parameters for use in research and device applications.” J Appl Phys 58, R1-R29 Authors: K.Chakraborty, R. R. Mukherjee, S.Mukherjee Paper Title: Tuning Of PID Controller Of Inverted Pendulum Using Genetic Algorithm Abstract: This paper presents different types of mathematical modelling of Inverted Pendulum and also a Proportional-Intregal-Derative (PID) controller is designed for its stabilization. After desiging of PID controller some reference stable system has been selected and then different types of error has been optimized (minimized) by using Genetic algorithms. The proposed system extends classical inverted pendulum by incorporating two moving masses. Also a tuning mechanism is done by genetic algorithm for optimizing different gains of controller parameter. Also here different performance indeces are calculated in MATLAB environment. This paper addresses 5. to demonstrate the capability of genetic algorithm’s to solve complex and constraint optimization problems via utilizing GA’s as a general purpose optimizing tool to solve different control system design problems. 21-24
Keywords: Inverted pendulum,Mathematical modelling,swing up control ,PID controller,Tuning,Genetic Algorithm,Performance Indeces,Error minimization.
References: 1. Elmer P. Dadias, Patrick S. Fererandez, and David J,”Genetic Algorithm on Line Controller For The Flexible Inverted Pendulum Problem”, Journal Of Advanced Computational Intelligence and Intelligent Informatics 2. R. Murillo Garcia1, F. Wornle1, B. G. Stewart1 and D. K. Harrison1, “Real-Time Remote Network Control of an Inverted Pendulum using ST-RTL”, 32nd ASEE/IEEE Frontiers in Education Conference November 6 - 9, 2002, Boston, MA. 3. DONGIL CHOI and Jun-Ho Oh “Human-friendly Motion Control of a Wheeled Inverted Pendulum by Reduced-order Disturbance Observer” 2008 IEEE International Conference on Robotics and Automation Pasadena, CA, USA, May 19-23, 2008. 4. W. Wang, “Adaptive fuzzy sliding mode control for inverted pendulum,” in Proceedings of the Second Symposium International Computer Science and Computational Technology(ISCSCT ’09) uangshan, P. R. China, 26-28, Dec. pp. 231-234, 2009. 5. Berenji HR. A reinforcement learning-based architecture for fuzzy logic control. International Journal of Approximate Reasoning 1992;6(1):267–92. 6. I. H. Zadeh and S. Mobayen, “ PSO-based controller for balancing rotary inverted pendulum, ” J. AppliedSci., vol. 16, pp. 2907-2912 2008. Authors: S.Manikandan Paper Title: High Performance Optimization of Low Power Multi -Threshold Voltage Using Level Converters Abstract: Applying multiple supply voltages (multi- VDD) is an effective technique for reducing the power consumption without reducing speed in an integrated circuit (IC). In order to transfer signals among the circuits operating at different supply voltages specialized voltage level converters are required. Two new multi threshold voltage (multi-VTH) level converters are proposed in this paper. The proposed level converters are compared with the level converters in [7], for operation at different supply voltages. When the level converters are individually optimized for minimum power consumption and propagation delay, the proposed level converters offers significant power saving and speed is enhanced as compared to the level converter in [7] of same technology.
Keywords: High-performance, multiple supply voltages, multiple threshold voltages, power efficiency, voltage level converters
References: 6. 1. V. Kursun and E. G. Friedma , Multi-Voltage CMOS Circuit Design.New York: Wiley, 2006. 2. K. Usami et al., “Automated low-power technique exploiting multiple Supply voltages applied to a media processor,” IEEE J. Solid- State Circuits, 25-29 3. Y. Taur and T. H. Ning , Fundamentals of Modern VLSI Devices. Cambridge, MA: Cambridge University Press, 1998. 4. S. H. Kulkarni and D. Sylvester, “High performance level conversion for dual VDD design,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 12, no. 9, pp. 926–936, Sep. 2004. 5. Srivastava , and D. Sylvester, “Minimizing total power by Simultaneous Vdd/Vth Assignment,” in Proc. IEEE Des. Autom.Jan.2003, pp. 400–403. 6. S. H. Kulkarni, A. N. Srivastava, and D. Sylvester, “A new algorithm For improved VDD assignment in low power dual VDD systems,” in Proc. IEEE Int. Symp. Low Power Electron. Des. Aug. 2004, pp. 200–205. 7. F. Ishihara, F. Sheikh, and B. Nikolic´, “Level conversion for Dualsupply systems,”IEEE Trans.Very Large Scale Integr. (VLSI) Syst., vol. 12, no. 2, pp. 185–195, Feb. 2004.S 8. V. Kursun, R. M. Secareanu, and E. G. Friedman, “CMOS voltage Interface circuit for low power systems,” in Proc. IEEE Int. Symp. Circuits Syst., May 2002, vol. 3, pp. 667–670. 9. M. Takahashi et al., “A 60-mW MPEG4 video codec using clustered Voltage scaling with variable supply-voltage scheme,” IEEE J. Solid-State Circuits, vol. 33, no. 11, pp. 1772–1780, Nov. 1998. 10. M. Hamada et al., “A top-down lowpower design technique using Clustered Voltage scaling with variable supply-voltage scheme,” in Proc.IEEE Custom Integr. Circuits Conf., May 1998, pp. 495–498. 11. D. E. Lackey et al., “Managing power and performance for system-on-chip designs using voltage islands,” in Proc. IEEE/ACM Int. Conf. Comput.Aided Des., Nov. 2002, pp. 195–202. Authors: Er. Farhad Aslam, Er. Birendra Kumar Yadav, Ram Sharan Choudhary, Gopal Kumar Choudhary A Comparative Analysis of Controllers Controlling Uncertainty in the Form of 2nd Order Load, Paper Title: Affecting the Robust Position Control of DC Motor Abstract: All the industrial process applications require robust position control of DC motor. The aim of this paper is to design a robust position control of DC motor by selecting different controllers like P, PI, PID and their tuning methods. The model of a DC motor is considered as a third order system with incorporating uncertainty. This paper compares the different kinds of tuning methods of parameter for PID controller. One is the controller design by Zeigler and Nichols method, second is the auto tuning of the controller in basic design mode and third is in the extended design mode. It was found that the proposed PID parameters adjustment in the basic and extended design mode is far better than the P, PI and Zeigler and Nichols method. The proposed method could be applied to the higher order system also.
Keywords: Basic mode, DC motor, PID tuning, robust position control. 7. References: 30-33 1. Steven T.Karris, ‘Introduction to Simulink with Engineering Applications’, Orchard Publications,www.orchardpublications.com 2. Tan Kiong Howe, May 2003, Thesis, B.E (Hons.), ‘Evaluation of the transient response of a DC motor using MATLAB/SIMULINK’, University of Queensland. 3. Math Works, 2001, Introduction to MATLAB, the Math Works, Inc. 4. O. Dwyer, .PI And PID Controller Tuning Rules for Time Delay Process: ASummary. Part 1: PI Controller Tuning Rules, Proceedings of Irish Signals and Systems Conference, June1999 5. Raghavan S. Digital control for speed and position of a DC motor. MS Thesis,Texas A&M University, Kingsville, 2005. 6. M. Chow and A. Menozzi, “on the comparison of emerging and conventional techniques for DC motor control,” Proc. IECON, pp. 1008- 1013, 1992. 7. SimPowerSystems for use with Simulink, users guide, Math Works Inc., Natick, MA, 2002. 8. S. Li and R. Challoo, Restructuring electric machinery course with an integrative approach and computer-assisted teaching methodology, IEEE Trans Educ. 49 (2006), 16_28. 9. J. J. D’Azzo and C. H. Houpis, Linear control system analysis and design, McGraw-Hill, New York, 1995. 10. S. J. Chapman, Electric machinery fundamentals, 3rd ed., WCB/McGraw-Hill, New York, 1998. Authors: Medhat H. A. Awadalla, Kareem Ezz El-Deen 8. Paper Title: Real-Time Software Profiler for Embedded Systems Abstract: Embedded systems are a mixture of software running on a microprocessor and application-specific hardware. There are many co-design methodologies that are used to design embedded systems. One of them is Hardware/Software co-design methodology which requires an appropriate profiler to detect the software portions that contribute to a large percentage of program execution and cause performance bottleneck. Detecting these software portions improves the system efficiency where these portions are either reprogrammed to eliminate the performance bottleneck or moved to the hardware domain gaining the advantages of this domain. There are profiling tools used to profile software programs such as GNU Gprof profiler. GNU Gprof integrates an extra code with the software program to be profiled causing inaccurate results and a significant execution time overhead. To address these issues, this paper proposes a software profiler called AddressTracer that is accurately able to evaluate performance matrices of any specific software portion. A set of benchmarks, Dijkstra, Secure Hash Algorithm, and Bitcount are profiled using AddressTracer, Airwolf and GNU software profiling tool (Gprof), for a quantitative comparison. The achieved results show that AddressTracer gives accurate profiling results compared to Gprof and Airwolf profilers. AddressTracer provides up to 50.15% improvement in accuracy of profiling software compared to Gprof and 6.89% compared to Airwolf. Furthermore, AddressTracer is a non-intrusive profiler which does not cause any performance overhead.
Keywords: Embedded Systems, FPGA, profiling tools, Hardware/Software co-design.
References: 1. Sungpack H., Tayo O., Jared C., Nathan G., Kozyrakis C., Olukotun K. “ A case of system-level hardware/software co-design and co- verification of a commodity multi-processor system with custom hardware. Proceedings of the 10th International Conference on Hardware/Software Co-design and System Synthesis, pp. 513-520, 2012. 2. Patrick Schaumont . A Practical Introduction to Hardware/Software Codesign. 2nd Edition., xxii+480p, ISBN:978-1-4614-3736-9, December 2012 3. Miller, F. Vahid, T. Givargis. Application-Specific Codesign Platform Generation for Digital Mockups in Cyber-Physical Systems 34-41 IEEE Electronic System Level Synthesis Conf. (ESLsyn), pp 1-6, June 2011. 4. Patrick R. Schaumont. A Practical Introduction to Hardware/Software Codesign. ISBN: 978-1-4419-5999-7 (Print) 978-1-4419-6000-9, 2010. 5. Bhattacharya, A. Konar, S. Das, C. Grosan, and A. Abraham, “Hardware Software Partitioning Problem in Embedded System Design Using Particle Swarm Optimization Algorithm”. Proceedings of the 2008 International Conference on Complex, Intelligent and Software Intensive Systems, 2008. 6. Jason G. Tong and Mohammed A. S., “Profiling Tools for FPGA-Based Embedded Systems: Survey and Quantitative Comparison”, journal of computers, Vol. 3, No. 6, 2008. 7. R. Lysecky, S. Cotterell, and F. Vahid, “A Fast On-Chip Profiler Memory”, in Proc. of the 39th Conference on Design Automation, pp. 28–33, June 2002. 8. Fenlason J. and Stallman R., GNU Gprof, accessed 2008. Available Online: http://gnu.huihoo.org/gprof- 2.9.1/html_chapter/gprof_toc.html. 9. Gordon-Ross A. and Vahid F., “Frequent Loop Detection Using Efficient Non-Intrusive On-Chip Hardware”, in Proc. of the 2003 International Conference on Compilers, Architecture and Synthesis for Embedded Systems, San Jose, California, USA, pp. 117–124, 2003. 10. Shannon L. and Chow P., “Maximizing System Performance: Using Reconfigurability to Monitor System Communications”, in Proc. of the 2004 International Conference on Field Programmable Technology (ICFPT), the University of Queensland, Brisbane, Australia, pp. 231–238, 2004. 11. Xilinx Incorporated, “Connecting Customized IP to the MicroBlaze Soft Processor Using the Fast Simplex Channel (FSL) Link”, 2004. 12. Xilinx Incorporated, “Embedded System Tools Reference Manual”, v7.0 January 8, 2007. 13. Jason G. Tong and Mohammed A. S., “Profiling Tools for FPGA-Based Embedded Systems: Survey and Quantitative Comparison”, journal of computers, Vol. 3, No. 6, 2008. 14. Xilinx Incorporated, “Spartan-3E Starter Kit Board User Guide”, V1.0, 9, 2006. 15. Dhaval N. Vyas, “FPGA-Based Hardware Accelerator Design for Performance Improvement of a System-on-a-Chip Application”, Master of Science in Electrical Engineering in the Thomas J. Watson School of Engineering and Applied Sciences Binghamton University State University of New York 2005. 16. Xilinx Incorporated, “Embedded System Tools Reference Manual”, v7.0 January 8, 2007. 17. Altera Corporation, “Nios Development Board Reference Manual, Stratix Professional Edition”, 2004. Authors: A.S.Syed Fiaz, N.Devi, S.Aarthi Paper Title: Bug Tracking and Reporting System Abstract: This is the world of information. The ever-growing field Information Technology has its many advanced notable features which made it what it was now today. In this world, the information has to be processed, clearly distributed and must be efficiently reachable to the end users intended for that. Otherwise we know it lead to disastrous situations. The other coin of the same phase is it is absolutely necessary to know any bugs that are hither-to faced by the end users. The project “Bug Tracking and Reporting System” aims to provide the solution for that. The Bug Tracker can be made from any two types. The first one being the system side, the other being the services side. Our project deals with the second one. The paper is wholly dedicated to tracking the bugs that are hither-by arise. The administrator maintains the master details regarding to the bugs id , bugs type, bugs description, 9. bugs severity, bugs status, user details. The administrator too has the authority to update the master details of severity level , status level, etc, modules of the paper. The administrator adds the users and assign them 42-45 responsibility of completing the paper. Finally on analyzing the paper assigned to the particular user, the administrator can track the bugs, and it is automatically added to the tables containing the bugs , by order of severity and status.The administrator can know the information in tact the various paper’s assigned to various users, their bug tracking status, their description etc in the form of reports from time to time. The paper wholly uses the secure way of tracking the system by implementing and incorporating the Server side scripting. The administrator can now add the project modules, project descriptions etc. He too adds the severity level, its status etc.The whole beauty of the paper is its high-level and user-friendly interface which mean that is the well based Bug Tracker which helps in tracking the whole system by providing the efficient reporting system. The Bug Tracker can be further by analyzed and further relevant and quick decisions can be taken.
Keywords: Bug Tracker, Scripting, Severity.
References: 1. Bill Evjen, Thiru Thangarathinam, Bill Hatfield, ‘Professional ASP.NET 1.1 2. Dave Mercer, ‘ASP.NET – A Beginners Guide’, O’Reilly Publications 3. http://en.wikipedia.org/wiki/Bug_tracking_system 4. Jonathan Corbet (May 14, 2008). "Distributed bug tracking". LWN.net .http://lwn.net/Articles/281849/ 5. Joey Hess (6 April 2007). "Integrated issue tracking with Ikiwiki". LinuxWorld.com. http://www.linuxworld.com/news/2007/040607- integrated-issue-tracking-ikiwiki.html. Retrieved 7 January 2009. 6. Kevin Loney, George Koch(2003), ‘Ms-Access –The Complete Reference’, Tata Mc-GrawHill Publishing Company Limited. Authors: Sunita, O.S Khanna, Amandeep Kaur Improvement in End-to-End delay and Energy Consumption using Routing Algorithms in Wireless Paper Title: Sensor Network Abstract: The popularity of Wireless Sensor Networks has increased tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. In wireless sensor network one of the main problems is related to energy issue because every node is operated by battery. In wireless sensor networks, sensors consume energy both in sensing data and in transmitting the sensed data to a base station. The power consumption for transmitting data is an exponential function of the distance from the sensor to the base station, while the power consumption for sensing data is determined by the type of sensor as well as the routing protocol. The problem in this paper is to increase the life time of the sensor networks. To have large network life time all nodes need to minimize their energy consumption. Node is composed of small battery so that the energy associated with this node is very less. So replacing and refilling of battery is not possible which is very costly. Hence some techniques are applied through which the energy associated with each node can be conserved. This paper proposes two algorithms, to minimize the energy consumption and end-to-end delay. Using both algorithm, there is improvement in energy consumption and end-to-end delay
Keywords: Wireless Sensor Networks, Energy Consumption, Multi-path Routing, Lifetime of wireless sensor network, end- to-end delay.
10. References: 1. W. Heinzelman, J. Kulik and H. Balakrishnan, “Adaptive Protocols for Information Dissemination in Wireless Sensor Networks”, Proc. 5th ACM/IEEE Mobicom Conference (MobiCom '99), 1999, pp. 174-85. 46-51 2. Praveen Kaushik ; Jyoti Singhai, “Energy Efficient Routing Algorithm for Maximizing the Minimum Lifetime of Wireless Sensor Network: A Review” , International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) , vol.2 , 2011. 3. Vijay Raghunathan, Curt Schurgers, Sung Park, and Mani B. Srivasta, “Energy-Aware Wireless Microsensor Networks” , IEEE Conference on SIGNAL PROCESSING MAGAZINE, 2002, pp. 1053-5888. 4. Mehdi Golsorkhtabar, Farzad Kavaini Nia, Mehdi Hosseinzadeh, Ynes Vejdanparast , “The Novel Energy Adaptive Protocol for Heterogeneous Wireless Sensor Networks”, IEEE , 2010. 5. S. Lindsey and C. Raghavendra, “PEGASIS: Power-efficient Gathering in Sensor Information Systems”, IEEE Aerospace Conference Proceedings, vol. 3, 2002, pp. 1125-1130. 6. Ossama Younis and Sonia Fahmy, “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks”, IEEE Transactions on Mobile Computing, vol.3 no.4, 2004, pp.366-379. 7. Zhao Cheng, Mark Perillo and Wendi B. Heinzelman, “General network lifetime and cost models for evaluating sensor network deployment strategies”, IEEE Transactions on mobile computing, vol. 7, 2008. 8. Stanislava Soro and Wendi B. Heinzelman, “Cluster head election techniques for coverage preservation in wireless sensor networks”, Journal of Ad Hoc Networks 7, 2009, pp. 955–972. 9. Ye XiaoGuo, Lv KangMeng, Wang RuChuan and Sun LiJuan, “Adaptive Load-Balanced Routing Algorithm” , IEEE International Conference on Digital Manufacturing & Automation, 2011. 10. Sandip Kumar Chaurasiya, Tumpa Pal and Sipra Das Bit, “An Enhanced Energy-Efficient Protocol with Static Clustering for WSN”, International Conference on Information Networking (ICOIN), 2011. 11. B. Chen, K. Jamieson, H. Balakrishnan and R. Morris, “SPAN: an energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks", Wireless Networks, vol. 8, 2002, pp. 481-494. 12. O. Younis and S. Fahmy, “An experimental study of routing and data aggregation in sensor networks”, Proceedings of the 2nd IEEE International Conference on Mobile Ad-hoc and Sensor Systems MASS, 2005. Authors: R.Subramanian, K.Thanushkodi Paper Title: An Efficient Firefly Algorithm to Solve Economic Dispatch Problems Abstract: The Economic Dispatch(ED) problems are the major consideration in electric power generation systems in order to reduce the fuel cost their by reducing the total cost for the generation of electric power. This paper presents an Efficient and Reliable Firefly Algorithm (FA), for solving ED Problem. The main objective is to minimize the total fuel cost of the generating units having quadratic cost characteristics subjected to limits on generator true power output & transmission losses. The FA is a stochastic Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of the FA to ED for 11. different Test Case system. ED is applied and compared its solution quality and computation efficiency to Simulated Annealing (SA), Genetic algorithm (GA), Differential Evolution (DE), Particle swarm optimization 52-55 (PSO), Artificial Bee Colony optimization (ABC), and Biogeography-Based Optimization (BBO) optimization techniques. The simulation results show that the proposed algorithm outperforms previous optimization methods.
Keywords: Artificial Bee Colony optimization, Biogeography-Based Optimization, Economic dispatch, Firefly Algorithm, Genetic algorithm, and Particle swarm optimization.
References: 1. Wood, A. J. and Wollenberg, B. F., Power Generation, Operation, and Control, 1996, Wiley,New York, 2nd ed. 2. A. Bakirtzis, P. N. Biskas, C. E. Zoumas, and V. Petridis, Optimal Power Flow By Enhanced Genetic Algorithm, IEEE Transactions on power Systems, Vol.17, No.2, pp.229-236, May 2002. 3. D. C. Walters and G. B. Sheble, Genetic Algorithm Solution of Economic Dispatch with Valve Point Loading, IEEE Transactions on Power Systems,Vol. 8, No.3,pp.1325–1332, Aug. 1993. 4. P. H. Chen and H.C. Chang, Large-Scale Economic Dispatch by Genetic Algorithm, IEEE Transactions on Power Systems, Vol. 10, No.4,pp. 1919–1926, Nov. 1995. 5. A. H. Mantawy, Y. L. Abdel-Magid and S. Z. Selim, Integrating Genetic Algorithm, Tabu search, and Simulated Annealing for the Unit Commitment Problem, IEEE Transactions on Power Systems, Vol. 14, pp. 829-836, August 1999. 6. D. Simon, “Biogeography-based optimization,” IEEE Trans. Evol. Comput., vol. 12, no. 6, pp.702–713, Dec. 2008 7. G. B. Sheble and K. Brittig, Refined genetic algorithm- economic dispatch example, IEEE Trans. Power Systems, Vol.10, pp.117-124, Feb.1995. 8. B. K. Panigrahi, V. R. Pandi. “Bacterial foraging optimization: Nelder-Mead hybrid algorithmfor economic load dispatch.” IET Gener. Transm, Distrib. Vol. 2, No. 4. Pp.556-565, 2008. 9. K. S. Kumar, V. Tamilselvan, N. Murali, R. Rajaram, N. S. Sundaram, and T. Jayabarathi, “Economic load dispatch with 10. emission constraints using various PSO algorithms,” WSEAS Transactions on Power Systems, vol. 3, no. 9, pp. 598–607, 2008. 11. X. S. Yang, “Firefly algorithm, Levy flights and global optimization,” in Research and Development in Intelligent Systems XXVI, pp. 209–218, Springer, London, UK, 2010 12. Dervis Karaboga and Bahriye Basturk, ‘Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems,’ Springer-Verlag, IFSA 2007, LNAI 4529, pp. 789–798. 13. X.-S. Yang, S. S. Sadat Hosseini, and A. H. Gandomi, "Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect," Applied Soft Computing, vol. 12, pp. 1180-1186,2012. 14. X. S. Yang, “Firefly algorithms for multimodal optimization,” in Proceedings of the Stochastic Algorithms: Foundations and Applications (SAGA ’09), vol. 5792 of Lecture Notes in Computing Sciences, pp. 178–178, Springer, Sapporo, Japan, October 2009. 15. R. Storn and K. Price, Differential Evolution—A Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces,International Computer Science Institute,, Berkeley, CA, 1995, Tech. Rep. TR-95–012. 16. Nayak, S.K.; Krishnanand, K.R.; Panigrahi, B.K.; Rout, P.K. -Application of Artificial Bee Colony to economic load dispatch problem with ramp rate limit and prohibited operating zones,IEEE word congress on Nature and Biologically inspired computing (NaBIC)-2009, pp- 1237 – 1242 . 17. A. Bakirtzis, V. Petridis, and S. Kazarlis, Genetic Algorithm Solution to the Economic Dispatch Problem, Proceedings. Inst. Elect. Eng. –Generation, Transmission Distribution, Vol. 141, No. 4, pp. 377–382, July 1994. 18. C. A. Roa–Sepulveda and B. J. Pavez–Lazo, A solution to the optimal power flow using simulated annealing, IEEE Porto Power Tech Conference, 10-13 th September,Porto, Portugal. 19. E. Zitzler, M. Laumanns, and S. Bleuler, “A Tutorial on Evolutionary Multi-objective Optimization,” Swiss Federal Institute of Technology _ETH_ Zurich, Computer Engineering and Networks Laboratory _TIK_, Zurich, Switzerland. Authors: Amera Ismail Melhum, Lamya abd allateef Omar, Sozan Abdulla Mahmood Paper Title: Short Term Load Forecasting using Artificial Neural Network Abstract: Load forecasting helps an electric utility to make important decisions including decisions on purchasing and generating electric power, load switching, and infrastructure development. Load forecasts are extremely important for developing country like Iraq, financial institutions, and other participants in electric energy generation, transmission, distribution must be studied and took a good attention. This work analyzes and discusses a comprehensive approach for Short Term Load Forecasting (STLF) using artificial neural network. Proposed architectures were trained and tested using previous two years actual load data obtained from Duhok ELC. Control in Iraq. In this study, four ANN models are implemented and validated with reasonable accuracy on real electric load generation output data. The first and second model are to predict values of one ahead day and seven days, while the third and fourth models are also to predict values of next and seven days, concerning the amount of period of disconnected time. A forecasting performance measure such as the absolute mean error AME has been presented for each model.
Keywords: Load forecasting, artificial neural network, back propagation 12. References: 1. Laiq Khan, Kamran Javed, Sidra Mumtaz,”ANN Based Short Term Load Forecasting Paradigms for WAPDA Pakistan”,Australian 56-58 Journal of Basic and Applied Sciences, 2010. pp 932-947. 2. Papalexopoulos, A.D., Hesterberg, T.C., “A regression based approach to short-term ystem load forecasting”, Proceedings of PICA conference ,1989,pp414-423. 3. Hill, T., OConnor, M., Remus, W., “Neural Networks Models for Time Series Forecasts”, Management Sciences,(1996) 1082-1092. 4. Huang, H., Hwang, R.,Hsieh, J.” A new artificial intelligent peak power load forecaster based on non-fixed neural networks”, Electr. Power Energy Sys., 2002, pp 245-250 5. Irisarri, G.D., Widergren, S.E. Yehsakul, P.D,” Online load forecasting for energy control center application, IEEE Transactions on Power Apparatus and Systems,PAS 101 ,1971, pp 900-911 6. Sanjib Mishra, "Short Term Load Forecasting Using Computational Intelligence methods", Masters thesis, National Institute of Technology Rourkela,2008. 7. G.A. Adepoju, S.O.A. Ogunjuyigbe, K.O. Alawode, “ Application of Neural Network to Load Forecasting in Nigerian Electrical Power System “,The Pacific Journal of Science and Technology” Volume 8. Number 1. May 2007 . 8. Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang,”Forecasting Using Support Vector Regression Machines”, A Study on Guangdong Province of China 1985-2008”,World Academy of Science, Engineering and Technology 71, 2010. 9. A.A. Rasool, A.A. Fttah, I.B.Sadik ,”Short Term Load Forecasting for Erbil Distribution System Using ANN and Wavelet Transform”,International Journal of Computer and Electrical Engineering, Vol. 1, No. 3, August 2009 10. Al-Shareef, A.J., E.A. Muhammad and E. Al-Judaibi, "One Hour Ahead Load Forecasting Using Artificial Neural Network for the Western Area of Saudi Arabia", International Journal of Electrical Systems Science and Engineering, 2009 , pp 219-224. Authors: H. I. Abdel-Gawad, Mohamed Osman, Nasser S. Elazab Paper Title: Exact Solutions of Time Dependent Korteweg-de Vries Equation by The Extended Unified Method 13. Abstract: Recently the unified method for finding traveling wave solutions of nonlinear evolution equations was proposed by the first author. It was shown that, this method unifies all the methods being used to find these 59-63 solutions. In this paper, we extend this method to find a class of formal exact solutions to Korteweg-de Vries equation with time dependent coefficients. A new class of multiple-soliton or wave trains is obtained.
Keywords: Exact solution, Extended unified method, Korteweg-de Vries equation, Variable coefficients
References: 1. P. J. Olivier, Application Of Lie Groups To Differential Equations. GTM, Vol. 107 ( Berlin, Springer ) (1986). 2. J. Weiss, M. Tabor, G. Carenville, J. Math. Phys., 24, 522 (1983). 3. R. Conte, Phys. Lett. A., 134, 100-104 (1988). 4. B. Y. Gou and Z. X. Chen, J. Phys. A Math. Gen. , 24, 645-650 (1991). 5. H.I. Abdel-Gawad , J. Statis. Phys., 97, 395-407 (1999). 6. C. Rogers and W. F. Shadwick, Backlund Transformations ( Academic, New york) (1982). 7. K. M. Tamizhmani and M. Lakshamanan, J. Phys. A, Math. Gen. , 16 , 3773 (1983). 8. Y. Xie, J. Phys. A Math. Gen., 37 5229 (2004). 9. C. Rogers and Szereszewski, J. Phys. A Math. Theor. 42, 40-4015 (2009). 10. E. Fan, and H. Zhang, Phys. Lett. A, 245, 389-392 (1999). 11. E. Fan, Phys. Lett. A, 265, 353-257 (2000). 12. E. Fan, Phys. Lett. A, 294, 26-29 (2002). 13. L. Yang, Z. Zhu, and Y. Wang, Phys. Lett A, 260, 55-59 (1999). 14. E. M. H. Moussa, R. M. El-Shikh, Phys. Lett. A, 372, 1429-1431 (2008). 15. M. L. Wang, and Y. B. zhou Phys. Lett. A 318, 84 (2003). 16. M. L. Wang, and X. Z. Li, Phys. Lett. A, 343, 48 (2005). 17. G. L. Cai, Q. C. Wang and J. J. Huang, Int. J. Nonl. Sci.2, 122-128 (2006). 18. N. A. Kurdashov, Phys. Lett. A, 147, 287 (1990). 19. M. Wang, J. Zhang, and X. Li, Phys. Lett. A,372, 417 (2008). 20. H. I. Abdel-Gawad, J. Stat. Phys, 147, 506-518 (2012). 21. Nirmala, N.; Vedan, M. J.; Baby, B. V., J. Math. Phys, 27, Issue 11, 2640-2643 (1986). Authors: G. Satheesh, T. Bramhananda Reddy, CH. Sai Babu SVPWM Based DTC of OEWIM Drive Fed With Four Level Inverter with Asymmetrical DC Link Paper Title: Voltages Abstract: A new approach for a fixed switching frequency direct torque control (DTC) of an open end winding induction motor configuration using four level inverter is proposed. The four level SVPWM voltages are generated by using two conventional two level inverters which are fed with the unequal dc link voltages at a ratio of 2:1. A decoupled algorithm for the two inverters feeding the open end winding induction motor is proposed. However, the proposed DTC scheme does not require the sector information of the estimated fundamental stator voltage vector and its relative position with respect to the stator flux vector. With the proposed method simulation clearly demonstrate simple numerical calculations and results in a better dynamic manner.
Keywords: Decoupled SVPWM Algorithm, Dual inverters, DTC, Four level SVPWM, Multi level Inverters, OEWIM, Unequal DC links, Zero sequence voltages.
References: 1. G Joohn-Sheok Kim and Seung-Ki Sul, “A novel voltage modulation technique of the space vector PWM”, in Conf. Rec. IPEC’95, Yokohama, Japan, 1995, pp. 742-747. 2. E. G. Shivakumar, K.Gopakumar, S.K. Sinha, Andre Pittet, V.T. Ranganathan, “Space Vector Control of Dual Inverter Fed Open-end Winding Induction Motor Drive”, EPE Journal, Vol.12, No.1, pp.9 –18 (2002). 3. H.Stemmler, P. Guggenbach," Configurations of High-Power Voltage Source Inverter Drives", Proc. EPE Conf.,pp.7 – 14, (1993). 4. M. R. Baiju , K. Gopakumar, K. K. Mohapatra , V. T.Somasekhar, L. Umanand, “Five-level inverter voltage space phasor generation 14. for an open-end winding induction motor drive”, IEE Proc. on Electric Power Applications, Vol.150, No.5, pp. 531-538, (2003). 5. M. R. Baiju , K. Gopakumar, K.K. Mohapatra, V. T.Somasekhar L. Umanand, “A high resolution multilevel voltage space phasor generation for an open-end winding induction motor drive”, EPE Journal, Vol.13, No.4, pp. 29-37, (2003). 64-68 6. B. Venugopal Reddy, V.T.Somasekhar, Y. Kalyan, “Decoupled Space-Vector PWM strategies for a Four-Level Asymmetrical Open- End Winding Induction Motor Drive With waveform Symmetries” IEEE TRANS on INDUSTRIAL ELECTRONICS, VOL. 58, NO. 11, NOVEMBER 2011 pp. 5130 – 5141. 7. G.Satheesh, T. Bramhananda Reddy and Ch. SaiBabu, “Novel SVPWM Algorithm for Open end Winding Induction Motor Drive Using the Concept of Imaginary switching Times” IJAST, Vol. 2, No.4,2011, pp 44- 92. 8. Arbind Kumar, B.G. Fernandes and K. Chatterjee, “Direct Torque Control of Open-end Winding Induction Motor Drive Using the Concept of Imaginary Switching Times for Marine Propulsion Systems”, IEEE, pp. 1504-1509. 9. S. Srinivas and V.T. Somasekhar, “Space-vector-based PWM switching strategies for a three-level dual-inverter-fed open-end winding induction motor drive and their comparative evaluation” IEEE Trans, IET Electr. Power Appl., 2008, 2, (1), pp. 19–31. 10. G. Buja, D. Casadei, and G. Serra, “Direct stator flux and torque control of an induction motor: theoretical analysis and experimental results,” in Proc. 24th Annu. Conf. IEEE Ind. Electron. Soc., Aachen, Germany, Sep. 31, 1998, vol. 1, pp. T50–T64. 11. J. Quan and J.Holtz, “Sensorless vector control of induction motors at very low speed using a nonlinear inverter model and parameter identification,” IEEE Trans. Ind. Appl., vol. 38, no. 4, pp. 1087–1095, Aug. 2002. 12. Arhind Kurnar, BG Fernandes, K Chatterjee. "Simplified Hybrid SVM Based Direct Torque Control of Thee Phase Induction Motor," National conference on CClS 2W. Goa (India) Vol.l, pp 137-142.2004. 13. Arbind Kumar, BG Fernandes, K Chatterjee, “DTC of Open-End Winding Induction Motor Drive Using Space Vector Modulation With Reduced Switching Frequency,” IEEE-PESC, 2004, pp 1214-1219. 14. Arbind Kumar, BG Fernandes, K Chatterjee, “Direct Torque Control of Three Phase Induction Motor Using SVPWM With-out Sector and Angle Determination”, EPE-PEMC 2004, Paper No. A-71121 15. G.Satheesh, T. Bramhananda Reddy and Ch. Sai Babu, “DTC of Open End Winding Induction Motor fed by Two Space-Vector- Modulated Inverters”, IEEE-INDICON, 2011. 16. G.satheesh, T. Bramhananda reddy and CH. Sai babu.” Space-vector based pwm switching strategy for a four-level dual inverter fed open-end winding induction motor drive”, ICAESM -2012, India, pp: 111- 115. Authors: S.Rajkumar, V.Narayani Clustered Evaluation of Implementing Fuzziness and Uncertainty in Deception Detection with the Paper Title: Randomness Bridge for the Teenager Communication System 15. Abstract: In the recent era of computer electronic communication we are currently facing the critical impact of Deception which plays its vital role in the mode of affecting efficient information sharing system. Identifying 69-76 Deception in any mode of communication is a tedious process without using the proper tool for detecting those vulnerabilities. This paper deals with the efficient tools of Deception detection in which combined application implementation is our main focus rather than with its individuality. We propose a research model which comprises Fuzzy logic, Uncertainty and Randomization. This paper deals with an experiment which implements the scenario of mixture application with its revealed results. We also discuss the combined approach rather than with its individual performance.
Keywords: Deception, Detection, Uncertainty, Fuzzy logic, Randomness
References: 1. Steve Woznaik, Kevin D.Mitnick, William L.Simon, The art of Deception: controlling the human element of security, Wiley 1st Edition, 2002. 2. Zuckerman, DePaul, Rosenthal, Verbal and Nonverbal Communication of Deception, In L Berkowitz (Ed) 2003. 3. Burgeon, J.K., Qin, T. “The Dynamic Nature of Deceptive Verbal Communication”, Journal of Language and Social Psychology, Vol25 (1), 1-22, 2006. 4. Bond,c.,F. “A world of lies: the global deception research team”, Journal of Cross-culture Psychology, Vol.37 (1), 60-74, 2006. 5. David P. McCabe†, ‡, Alan D. Castel*, Matthew G. Rhodes*, “The Influence of fMRI Lie Detection Evidence on Juror Decision Making”, Behavioural Sciences and the Law Behave. Sci. Law 29, 566–577, 2011. 6. Bruce Luber, Carl Fisher, Paul S. Appelbaum, Marcus Ploesser, Sarah H. Lisanby, “Non-Invasive Brain Stimulation in the Detection of Deception: Scientific Challenges and Ethical Consequences” Behavioural Sciences and the Law Behave. Sci. Law 27, 191–208, 2009. 7. http://en.wikipedia.org/wiki/Fuzzy_logic 8. Von Altrock, Constantin (1995). Fuzzy logic and NeuroFuzzy applications explained. Upper Saddle River, NJ: Prentice Hall PTR. ISBN 0-13-368465-2. 9. Arabacioglu, B. C. (2010). "Using fuzzy inference system for architectural space analysis". Applied Soft Computing 10 (3): 926–937. 10. Biacino, L.; Gerla, G. (2002). "Fuzzy logic, continuity and effectiveness". Archive for Mathematical Logic 41 (7): 643–667. doi:10.1007/s001530100128. ISSN 0933-5846. 11. Cox, Earl (1994). The fuzzy systems handbook: a practitioner's guide to building, using, maintaining fuzzy systems. Boston: AP Professional. ISBN 0-12-194270-8. 12. Gerla, Giangiacomo (2006). "Effectiveness and Multivalued Logics". Journal of Symbolic Logic 71 (1): doi: 10.2178/jsl/1140641166. ISSN 0022-4812. Authors: Kiran Kumar Kommineni, Adimulam Yesu Babu Paper Title: An Approach for the Assessment of the Information Security and Its Measures Abstract: The information security management standard requires enterprises to undertake regular reviews of the effectiveness of their information security management system. According to ISO, the effectiveness of the implemented information security controls to verify that the security requirements, according to the business objectives, have been met. This paper focuses on the identification of a set of assessment measures that could be used in assessing information security readiness according to the recommended security controls of the information security management standard. This paper presents the suitable security measures that could be used as an input to an analytical model for numerically assessing enterprise information security.
Keywords: Information Security; Risk management; Assessment; Measures; ISO.
References: 1. Chunlin Liu., Chong-Kuan Tan., Yea-Saen Fang., Tat-Seng Lok “The Security Risk Assessment Methodology” Procedia Engineering, Volume 43, 2012, pp 600–609. 2. Serap Atay & Marcelo Masera “Challenges for the security analysis of Next Generation Networks” Information Security Technical Report, Vol.16, Issue 1, 2011, pp 3–11 3. Rok Bojanc., Borka Jerman-Blažič “An economic modelling approach to information security risk management” International Journal of Information Management, Volume 28, Issue 5, October 2008, pp 413–422 16. 4. Azzam Mourad., Marc-André Laverdière., Mourad Debbabi “An aspect-oriented approach for the systematic security hardening of code” Computers & Security, Volume 27, Issues 3–4, May–June 2008, pp 101–114 77-80 5. Chi-Chun Lo., Wan-Jia Chen “A hybrid information security risk assessment procedure considering interdependences between controls” Expert Systems with Applications, Volume 39, Issue 1, January 2012, pp 247–257 6. Sanjay Goel., InduShobha N. Chengalur-Smith “Metrics for characterizing the form of security policies” The Journal of Strategic Information Systems, Volume 19, Issue 4, December 2010, pp 281–295 7. Daniel Mellado., Eduardo Fernández-Medina., Mario Piattini “A common criteria based security requirements engineering process for the development of secure information systems” Computer Standards & Interfaces, Volume 29, Issue 2, February 2007, pp 244–253 8. Shaun Posthumus., Rossouw von Solms “A framework for the governance of information security” Computers & Security, Volume 23, Issue 8, December 2004, pp 638–646 9. Michael, W., William, H, B., Detmar Straub “Security lapses and the omission of information security measures: A threat control model and empirical test” Computers in Human Behavior, Volume 24, Issue 6, 17 Sept 2008, pp 2799–2816 10. Chung-Hung Tsai., Cheng-Wu Chen “An earthquake disaster management mechanism based on risk assessment information for the tourism industry-a case study from the island of Taiwan” Tourism Management, Volume 31, Issue 4, August 2010, pp 470–481 11. Xingzhi Wang., Zheng Yan., Li Li “A grid computing based approach for the power system dynamic security assessment” Computers & Electrical Engineering, Volume 36, Issue 3, May 2010, pp 553–564 12. Ray Bernard “Information Lifecycle Security Risk Assessment: A tool for closing security” Computers & Security, Volume 26, Issue 1, February 2007, pp 26–30 13. Rogério de Paula., Xianghua Ding., Paul Dourish., Kari Nies., Ben Pillet., Roberto Silva Filho “In the eye of the beholder: A visualization-based approach to information system security” International Journal of Human-Computer Studies, Volume 63, Issues 1–2, July 2005, pp 5–24 14. Karin P. Badenhorst., Jan H.P. Eloff “TOPM: a formal approach to the optimization of information technology risk management” Computers & Security, Volume 13, Issue 5, 1994, pp 411–435 Authors: Deepak B. Nagare, Kishor L. More, Nitin S. Tanwar, S.S.Kulkarni Paper Title: Multi-Agent Secure Dynamic Carpooling 17. Abstract: Carpooling (also known as car-sharing, ride-sharing and lift sharing), is the sharing of car journeys so that more than one person travels in a single car [5]. Carpooling consists of sharing one’s personal vehicles with 81-85 one or several passengers in which the related passengers shares the related costs but also help to reduce the traffic as well as pollution. One major issue in carpooling is the prior agreement between the car owner and the ride seekers. Dynamic carpooling uses an IT system to remove this limitation and provide ways to react to events such as a traffic jam as well as improving the quality of life benefits of participating people. But it requires accessing potentially sensitive information such as the real time users’ position or their identity. So there must be an efficient security mechanism should be implemented to protect data exchanged to provide the service but also to increase the users’ confidence in the tool. This paper mostly focuses on the security services allowing both the mutual authentication of the users and of the application components with the system.Traffic congestion and the associated pressure in car parking, that results from increased number of cars on the road ,it require the study of innovative measures to reduce the number of cars traveling every day to the main areas in the city, specifically single occupant vehicles.
Keywords: CarOwner, Ride Seeker, Mobile Authentication, Multi-Agent System, Dynamic Carpooling.
References: 1. C´edric Bonhomme, G´erald Arnould and Djamel Khadraoui Public Research Centre Henri Tudor 29 Avenue John F. Kennedy, L-1855, Luxembourg [email protected]"Dynamic Carpooling Mobility Services based on Secure Multi-Agent Platform". 2. Blerim Ciciy?, Athina Markopoulouy, Enrique Frías-Martínez?, Nikolaos Laoutaris? UC Irviney, Telefonica Research(Spain)? {bcici, athina}@uci.edu, {efm, nikos}@tid.es . Quantifying the Potential of Ride-Sharing using Call Description Records. 3. Deepak B. Nagare, Kishor L. More, Nitin S. Tanwar, S.S.Kulkarni, Kalyan C. Gunda, “Dynamic Carpooling Application Development on Android Platform”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume- 2, Issue-3, February 2013 4. The true cost of a car over its lifetime:http://www.doughroller.net/smart-spending/true-cost-of-a-car-over-its-lifetime. 5. Arpita Dixit, Shweta Bora, Sonali Chemate, Nikita Kolpekwar,Real-Time Carpooling System for Android Platform, International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 6, December 2012. 6. George Dimitrakopoulos, Panagiotis Demestichas and Vera Koutra,”Intelligent Management Functionality for Improving Transportation Efficiency by Means of the Car Pooling Concept”,IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 13, NO. 2, JUNE 2012 7. Marc Oliphant & Andrew Amey,"Dynamic Ridesharing:Carpooling Meets the Information Age",MIT “Real-Time” Rideshare Current Research: Andrew Amey [email protected],Future MIT Research & Collaboration: John Attanucci [email protected]. 8. Gérald Arnould, Djamel Khadraoui,Marcelo Armendáriz, Juan C. Burguillo, Ana Peleteiro,"A Transport Based Clearing System for Dynamic Carpooling Business Services",2011 11th International Conference on ITS Telecommunications. 9. Daniel Graziotin,"Dycapo: On the creation of an open-source Server and a Protocol for Dynamic Carpooling",Free University of Bolzano. 10. G. Arnould, D. Khadraoui, M. Armend´ariz, J. C. Burguillo, and A. Peleteiro, “Mobile and vehicular communication optimization and simulation in the context of a dynamic carpooling subsystem,” in Int. J. Signal and Imaging Systems Engineering, vol. 1, no. 3/4, 2011. 11. Shangyao Yan, Chun-Ying Chen, and Yu-Fang Lin, “A Model with a Heuristic Algorithm for Solving the Long-Term Many-to-Many Carpooling Problem”,IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,VOL. 12, NO. 4, DECEMBER 2011 Authors: Muzhir Shaban Al-Ani, Abdulrahman Dira Khalaf Paper Title: Image Information Retrieval Using Wavelet and Curvelet Transform Abstract: The rapid growth of multimedia data applications via Internet becomes a big challenge over the world. This research is concentrated on the implementation of an accurate and fast algorithm that retrieves image information based on vector space model. The big challenge of information retrieval is a semantic gap, which is the difference between the human perception of a concept and how it can be represented using a machine- level language. This paper aims to design an information retrieval system based on hybrid algorithm through two stages; first one is training and the second one is testing. This algorithm based on extracted features using Wavelet and Curvelet decomposition and the statistic parameters such as mean, standard deviation and energy of signals. The system is tested over 1000 images which are divided into 10 categories, each category has 100 images. The tested results of system are compared between system based on Wavelet and system based on Histogram. Performance measures are implemented applying two metrics called precision and recall. The results of training phase show that the elapsed time of system based on hybrid Algorithm is greater than the elapsed time based on DWT or Histogram. The Average Retrieving Time (ART) for system based on hybrid algorithm is less than ART based on Wavelet and Histogram.
18. Keywords: Information Retrieval, Multimedia Information Retrieval, Discrete Wavelet Transform, Curvelet Transform, Vector Space Model, Feature Extraction. 86-90
References: 1. M. S. Lew, "Principles of Visual Information Retrieval," London: Springer-Verlag limited, 2001. 2. R. Barbara, "Latent Semantic Indexing: An Overview," INFOSYS 240 Spring 2000. 3. J Savoy. and D. Desboi, "Information Retrieval in Hypertext Systems: an Approach Using Bayesian Networks," EP-ODD, vol. 4 no. 2, pp. 87–108 , 1991. 4. I. J. Sumana, "Image Retrieval Using Discrete Curvelet Transform," Monash University, Australia November, 2008. 5. V.S.V.S. Murthy, E. Vamsidhar, J.N.V.R. Swarup Kumar and P. Sankara Rao "Content Based Image Retrieval using Hierarchical and K-Means Clustering Techniques," International Journal of Engineering Science and Technology Vol. 2 No. 3 , 2010. 6. M. Henk Blanken, H. Ernst Blok, P. Arjen de Vries and F. Ling, "Multimedia Retrieval," Heidelberg: Springer-Verlag Berlin, 2007. 7. E. J. Candès, L. Demanet, D. L. Donoho and L. Ying, "Fast discrete curvelet transforms. Multiscale Model," Simul: 5, pp. 861-899, 2006. 8. C. Keith, "Information Retrieval," London: Butterworths (2nd ed.), 1979. 9. I. Borg and P.J.F. Groenen "Modern Multidimensional Scaling: Theory and Applications," New York: Springer, (2nd ed.), 2005. 10. M. Ibrahiem and J. Atwan, "Designing and Building an Automatic Information Retrieval System for Handling the Arabic Data," American Journal of Applied Sciences, vol. 2, no. 11, pp. 1520-1525, 2005. 11. J. Magalhães and S. Rüger, "Information-theoretic semantic multimedia indexing," in ACM Conference on Image and Video Retrieval. Amsterdam, Holland, 2007. 12. Y.Y. Chung et al., "Design of a Content Based Multimedia Retrieval System," WSEAS Transactions on Computers, vol. 6, no. 3, March 2007. 13. J. Magalhães, "Statistical Models for Semantic Multimedia Information Retrieval," PhD Dissertation, University of London, UK, 2008. 14. T. C. Siewt, "Feature Selection for Content Based Image Retrieval Using Statistical Discriminate Analysis," M.Sc. Thesis: University of Technology Malaysia, 2008. 15. V. Prasannakumari, "Contextual Information Retrieval for Multi-Media Database with Learning by Feedback Using Vector Space Model," Asian journal of information Management vol. 4 no. 1, pp. 12-18, 2010. Authors: N. Janardhan, P.Ushasri, M.V.S. Murali Krishna, P.V.K. Murthy Exhaust Emissions and Combustion Characteristics of Jatropha Oil in Crude Form and Biodiesel of Paper Title: Low Heat Rejection Diesel Engine Abstract: Investigations were carried out to study the exhaust emissions of a low heat rejection (LHR) diesel engine consisting of air gap insulated piston with 3-mm air gap, with superni (an alloy of nickel) crown, air gap insulated liner with superni insert and ceramic coated cylinder head with different operating conditions of crude jatropha oil (CJO) and biodiesel with varied injection timing and injection pressure. Performance parameters and exhaust emissions were determined at various values of brake mean effective pressure (BMEP) with different versions of the engine with varied injection timing and injection pressure with different operating conditions of jatropha oil in crude form and biodiesel. Combustion characteristics of the engine were measured with TDC (top dead centre) encoder, pressure transducer, console and special pressure-crank angle software package at peak load operation of the engine. Conventional engine (CE) showed deteriorated performance, while LHR engine showed improved performance with crude vegetable operation at recommended injection timing and pressure and the performance of both version of the engine improved with advanced injection timing and higher injection pressure when compared with CE with pure diesel operation. Relatively, smoke levels decreased by 27% and NOx levels increased by 49% with crude vegetable oil operation on LHR engine at its optimum injection timing, when compared with pure diesel operation on CE at manufacturer’s recommended injection timing. Biodiesel operation further decreased smoke levels and increased NOx emissions.
Keywords: Alternate Fuel, CE, LHR engine, Vegetable oil
References: 1. Seshagiri Rao, V.V.R., Reddy, T.K.K., Murali Krishna, M.V.S. and Murthy, P.V.K., “Performance evaluation of high grade low heat rejection diesel engine with carbureted methanol and crude jatropha oil”, International Journal of Advanced Engineering Sciences & Technologies (IJAEST,10(2), 2011, pp.368-387. 2. Murali Krishna, M.V.S., Seshagiri Rao, V.V.R., Murthy, P.V.K. and Reddy, T.K.K., “Performance evaluation of a low heat rejection diesel engine with carbureted ethanol and jatropha oil”, International Journal of Computational and Applied Research in Mechanical Engineering (JCARME), , 1(2),2012, pp.99-110. 3. Cummins, C. Lyle, Jr. Diesel's Engine, Volume 1: From Conception To 1918. Wilsonville, OR, USA: Carnot Press, 1993, ISBN 978-0- 917308-03-1. 4. Surendra, R, K. and Suhash, D.V. “Jatropha and karanj bio-fuel: as alternate fuel for diesel engine”, ARPN Journal of Engineering and Applied Science, 2008.3(1). 5. Canaker, M., Ozsezen, A.N. and Turkcan, A. “Combustion analysis of preheated crude sunflower oil in an IDI diesel engine”, Biomass 19. Bio-energy, 33, 2009, pp.760-770. 6. Venkanna, B.K. and Venkatarama Reddy,C., “Performance, emission and combustion characteristics of DI diesel engine running on blends of honne oil/diesel fuel/kerosene”, International Journal of Agriculture and Biology Engineering, 4(3), 2009, pp.1-10. 91-95 7. Misra, R.D. and Murthy, M.S., “Straight vegetable oils usage in a compression ignition engine—A review”, Renewable and Sustainable Energy Reviews, 14, 2010, pp.3005–3013. 8. Banapurmath, N.R., Tewari, P.G., Hosmath, R.S., “Performance and emission characteristics of direct injection compression ignition engine operated on honge, jatropha and sesame oil methyl ester”, Journal of Renewable energy, 33, 2008, pp.1982-1988. 9. Murat, K., Gokhan, Ergen and Murat, H., “ The effects of preheated cottonseed oil methyl ester on the performance and exhaust emissions of a diesel engine”, Applied Thermal Engineering, 28, 2008, pp. 2136-2143. 10. Jayant Singh, Mishra, T.N., Bhattacharya, T.K. and Singh, M.P., “Emission characteristics of methyl ester of rice bran oil as fuel in compression ignition engine”, International Journal of Chemical and Biological Engineering, 1(2). 2008, pp.62-66. 11. Rasim, B., “Performance and emission study of waste anchovy fish biodiesel in a diesel engine”, Fuel Processing Technology, 92, 2011, pp.1187-1194. 12. Jaichandar, S. and Annamalai, K., “The status of biodiesel as an alternative fuel for diesel engine- An Overview” , Journal of Sustainable Energy & Environment, 2, 2011, pp.71-75 13. Parlak, A., Yasar, H., ldogan O. (2005).The effect of thermal barrier coating on a turbocharged Diesel engine performance and exergy potential of the exhaust gas. Energy Conversion and Management, 46(3), 489–499. 14. Ekrem, B., Tahsin, E., Muhammet, C., “ Effects of thermal barrier coating on gas emissions and performance of a LHR engine with different injection timings and valve adjustments”, Journal of Energy Conversion and Management,47, 2006, pp.1298-1310. 15. Ciniviz, M., Hasimoglu, C., Sahin, F., Salman, M. S., “Impact of thermal barrier coating application on the performance and emissions of a turbocharged diesel engine”, Proceedings of the Institution of Mechanical Engineers Part D-Journal Of Automobile Engineering, 222 (D12), 2008, pp.2447–2455. 16. Kesava Reddy, Ch., Murali Krishna, M.V.S., Murthy, P.V.K., and Ratna Reddy,T., “Performance evaluation of a low grade low heat rejection diesel engine with crude Pongamia oil”, International Scholarly Research Network (ISRN) Renewable Energy, Article ID 489605,2012, pp.1-10. 17. Parker, D.A. and Dennison, G.M. (1987). The development of an air gap insulated piston. SAE Paper No. 870652, 1987. 18. Rama Mohan, K., Vara Prasad, C.M., Murali Krishna, M.V.S., “Performance of a low heat rejection diesel engine with air gap insulated piston”, ASME Journal of Engineering for Gas Turbines and Power, 121(3), 1999, pp.530-540. 19. Ratna Reddy, T., Murali Krishna, M.V.S., Kesava Reddy, Ch and Murthy, P.V.K., “Performance evaluation of a medium grade low heat rejection diesel engine with mohr oil”, International Journal of Recent Advances in Mechanical Engineering (IJMECH), 1(1), 2012, pp.1-17. 20. Chennakesava Reddy, Murali Krishna, M.V.S., Murthy, P.V.K., and Ratna Reddy,T., “Potential of low heat rejection diesel engine with crude pongamia oil”, International Journal of Modern Engineering Research (IJMER), 1(1), 2011, pp.210-224. 21. Janardhan, N., Murali Krishna, M.V.S., Ushasri, P. and Murthy, P.V.K., “Potential of a medium low heat rejection diesel engine with crude jatropha oil”, International Journal of Automotive Engineering and Technologies, 1(2), 2012, pp.1-16. 22. Chowdary, R.P., Murali Krishna, M.V.S., Reddy, T.K.K and Murthy, P.V.K., “Performance evaluation of a high grade low heat rejection diesel engine with waste fried vegetable oil”, International Journal of Scientific & Technology, 2(3), 2012, pp. 440-450. 23. Ratna Reddy, T., Murali Krishna, M.V.S., Kesava Reddy, Ch and Murthy, P.V.K., “Performance evaluation of a low heat rejection diesel engine with mohr oil based biodiesel”, British Journal of Applied Science & Technology, 2(2), 2012, pp.179-198. 24. Kesava Reddy, Ch., Murali Krishna, M.V.S., Murthy, P.V.K. and Ratna Reddy,T., “Performance evaluation of a high grade low heat rejection diesel engine with crude pongamia oil”, International Journal of Engineering Research and Applications, 2(5), 2012, pp.1505- 1516. 25. Murali Krishna, M.V.S., Janardhan, N., Murthy, P.V.K., Ushasri, P. and Nagasarada., “A comparative study of the performance of a low heat rejection diesel engine with three different levels of insulation with vegetable oil operation”, Archive of Mechanical Engineering (Poland), LIX (1), 2012, pp.101-128. 26. Murali Krishna, M.V.S., Chowdary, R.P., Reddy, T.K.K. and Murthy, P.V.K., “A comparative study of the performance of a low heat rejection diesel engine with three different levels of insulation with waste fried vegetable oil operation”, International Journal of Science & Technology (Australia), 2(6), 2012, pp.358-371. Authors: Rajesh Nema, Rajeev Thakur, Ruchi Gupta Paper Title: Design & Implementation of PID Controller Based On FPGA with PWM Modulator Abstract: Proportional-Integral-Derivative (PID) controllers are universal control structure and have widely used in Automation systems, they are usually implemented either in hardware using analog components or in software using Computer-based systems. In this paper, we focused our works designing on building a multi-channel PID controller by Field Programmable Gate Arrays (FPGAs). To overcome the hardware complexity by the use of more processors for multi channel, we are using single PID controller for multi channel .Multi channel can be implemented by the use of FPGA.when the error is more it can differentiate and produce the constant output, when signal is low when compared to reference signal it can integrate it.FPGA can offer parallel processing, more speed.
Keywords: (PID), FPGA, (FPGAs). 20. References: 96-98 1. Efficient Dynamic System Implementation Of Fpga Based Pid Control Algorithm For Temperature Control System. Volume 3, Issue 2, July – September (2012), pp. 306-312 2. High-Speed and Low-Power PID Structures for Embedded ApplicationsPATMOS'11., Madrid : Spain (2011)" 3. ISSN 0974-2190 Volume 2, Number 1 (2010), pp. 71--82 Analysis and Implementation of Discrete Time PID Controllers using FPGA 4. FPGA technology for multi-axis control systems Armando Astarloa *, Jesús Lázaro, Unai Bidarte, Jaime Jiménez, Aitzol Zuloaga Accepted 1 September 2008 5. Design and Implementation of Modular FPGA-Based PID Controllers,Yuen Fong Chan, M. Moallem, Member, IEEE, and Wei Wang, Member, IEEE-2007. 6.Simulink/Modelsim Simulable VHDL PID Core for Industrial SoPC Multiaxis Controllers Jes´us L´azaro, Armando Astarloa, Jagoba Arias, Unai Bidarte, Aitzol Zuloaga IEEE-2006. 6. Xilinx Corp. Multipliers. 7. National Semiconductor. LMD18245 3A, 55V DMOS Full- Bridge Motor Driver Datasheet. http://www.national.com/pf/ LM/LMD18245.html. 8. R. Ruelland, G. Gateau, T. A. Meynard, and J.-C. Hapiot, “Design of FPGA-based emulator for series . Authors: Misha Kakkar, Divya Upadhyay Paper Title: Web Browsing Behaviors Based Age Detection Abstract: Users basic attributes like age, gender location etc… plays an essential role in today’s web applications. Previous research shows that there is relationship between users’ browsing behavior and their basic characteristics. In this paper we made an approach to detect a user’s age depending on his web browsing history. The user’s web browsing behaviors is treated as a variable to propagate age information between different users. Artificial neural network tool is used for this purpose. Uses are divided into two different categories of adult and youngsters. The result is 93.7% accurate.
Keywords: Age prediction, Browsing behavior, Artificial.
References: 1. Lenhart, S. Fox. Bloggers: A portrait of the internet’s new storytellers. 21. http://www.pewinternet.org/pdfs/PIP%20Bloggers%20Report%20July%2019%202006.pdf 2. Burger, J. and Henderson, J. (2006), An Exploration of Observable Features Related to Blogger Age, in `Computational Approaches to 99-101 Analyzing Weblogs, AAAI Spring Symposium. 3. ComScore Media matrix, March 2011: India: Digital Market Overview, Digital Strategy Consulting and Digital Training Academy. 4. Dong Nguyen Noah A. Smith Carolyn P. Ros´e: Author Age Prediction from Text using Linear Regression, Proceedings of the 5th ACL- HLT Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, Portland, OR, USA, 24 June 2011, pp. 115–123. 5. Eric Auchard : 2005, Study: Men want facts, women seek personal connections on Web: Computerworld magazine. 6. Hu, J., Zeng, H. J., Li, H., Niu, C. and Chen, Z. (2007), Demographic prediction based on user's browsing behavior, in `WWW '07: Proceedings of the 16th international conference on World Wide Web', ACM, pp. 151-160. 7. Hassoun Md. H.: 1995, Fundamentals of Neural Network MIT, Liberty of Congress 8. M. Koppel, J. Schler, S. Argamon, and J.W. Pennebaker. Effects of age and gender on blogging. In AAAI 2006 Spring Symposium on Computational Approaches to Analysing Weblogs, 2006. 9. Masters, T.: 1993, Practical neural network recipes in C++. San Diego, CA, USA: Academic Press Professional, Inc. 10. MURRAY, D. AND DURRELL, K. (2000), INFERRING DEMOGRAPHIC ATTRIBUTES OF ANONYMOUS INTERNET USERS, IN `WEBKDD '99: REVISED PAPERS FROM THE INTERNATIONAL WORKSHOP ON WEB USAGE ANALYSIS AND USER PROFILING', PP. 7-20 Authors: L. P. Mishra, A. Acharyya and M. Mitra Paper Title: Transient Thermal Analysis of Pulsed Silicon SDR IMPATT at 35 GHz Abstract: In this paper the transient thermal analysis of 35 GHz pulsed silicon Single-Drift Region (SDR) Impact Avalanche Transit Time (IMPATT) device is presented. A double-iterative field maximum computer 22. method based on drift-diffusion model is used to obtain the DC and high frequency properties of the device. A transient thermal model has been developed by the authors’ to study the temperature transients in pulsed Si SDR 102-106 IMPATT at 35 GHz. Results show that the device is capable of delivering a peak pulsed power output of 7.40 W with 8.46% DC to RF conversion efficiency. The maximum junction temperature rise is 352.5 K for peak pulsed bias current of 1.08 Ampere with 200 ns pulsewidth and 1.0% duty cycle.
Keywords: Millimeter-wave, pulsed Si SDR IMPATTs, temperature transients, thermal analysis.
References: 1. T. A. Midford and R. L. Bernick, “Millimeter Wave CW IMPATT diodes and Oscillators”, IEEE Trans. Microwave Theory Tech., vol. 27, pp. 483-492, 1979. 2. Y. Chang, J. M. Hellum, J. A. Paul and K. P. Weller, “Millimeter-Wave IMPATT Sources for Communication Applications”, IEEE MTT-S International Microwave Symposium Digest, 1977, pp. 216-219. 3. W. W. Gray, L. Kikushima, N. P. Morentc and R. J. Wagner, “Applying IMPATT Power Sources to Modern Microwave Systems”, IEEE Journal of Solid-State Circuits, vol. 4, pp. 409-413, 1969. 4. H. M. Olson, “A Mechanism for Catastropic failure of Avalanche Diodes”, IEEE Trans. on Electron Devices, vol. ED-22, pp. 842-849, 1975. 5. Acharyya, S. Banerjee and J. P. Banerjee, “Dependence of DC and Small-signal Properties of Double Drift Region Silicon IMPATT Device on Junction Temperature”, Journal of Electron Devices, vol. 12, pp. 725-729, 2012. 6. S. K. Roy, M. Sridharan, R. Ghosh, and B. B. Pal, “Computer method for the dc field and carrier current profiles in the IMPATT device starting from the field extremum in the depletion layer”, Proceedings of the 1st Conference on Numerical Analysis of Semiconductor Devices (NASECODE I), J. H. Miller, Ed., Dublin, Ireland, pp. 266-274, 1979. 7. S. K. Roy, J.P. Banerjee and S. P. Pati, “A Computer analysis of the distribution of high frequency negative resistance in the depletion layer of IMPATT Diodes”, Proc. 4th Conf. on Num. Anal. of Semiconductor Devices (NASECODE IV) (Dublin) (Dublin: Boole), pp. 494-500, 1985. 8. H. K. Gummel and J. L. Blue, “A small-signal theory of avalanche noise in IMPATT diodes”, IEEE Trans. on Electron Devices, vol. ED-14, no. 9, pp. 569-580, 1967. 9. H. M. Olson, “Temperature Transients in IMPATT Diodes’, IEEE Trans. on Electron Devices, vol. ED-23, no. 5, pp. 494-503, 1976. 10. D. L. Scharfetter and H. K. Gummel, “Large-Signal Analysis of a Silicon Read Diode Oscillator”, IEEE Trans. on Electron Devices, vol. ED-16, no. 1, pp. 64-77, January 1969. 11. S. M. Sze, and R. M. Ryder, “Microwave Avalanche Diodes”, Proc. of IEEE, Special Issue on Microwave Semiconductor Devices, vol. 59, issue 8, pp. 1140-1154, 1971. 12. W. N. Grant, “Electron and hole ionization rates in epitaxial Silicon”, Solid State Electron, vol. 16, no. 10, pp. 1189-1203, 1973. 13. C. Canali, G. Ottaviani and A. A. Quaranta, “Drift velocity of electrons and holes and associated anisotropic effects in silicon”, J. Phys. Chem. Solids, vol. 32, issue 8, pp. 1707, 1971. 14. Zeghbroeck, B.V.: Principles of Semiconductor Devices, Colorado Press, 2011. 15. “Electronic Archive: New Semiconductor Materials, Characteristics and Properties,” http://www.ioffe.ru/SVA/NSM/Semicond/Si/index.html. 16. M. Sridharan, S. K. Roy, “Computer studies on the widening of the avalanche zone and decrease on efficiency in silicon X-band symmetrical DDR” Electron Lett., vol. 14, pp. 635-637, 1978. 17. M. Sridharan, S. K. Roy, “Effect of mobile space charge on the small signal admittance of silicon DDR”, Solid State Electron, vol. 23, pp. 1001-1003, 1980. Authors: Okoronkwo M. C. Monica N. Agu Paper Title: Providing E-Governance Services To Technologically Challenged Grassroots Environments Abstract: Today a number of government services in developing countries are online. In majority they are merely showcasing more of their assigned responsibilities and in a few cases the endpoint reports of achievements, and providing a feedback link that is rarely attended to. Even in cases where citizens could be involved and benefit from government wide information services, the infrastructure is either not available or is prohibitively costly, thereby inhibiting their engagement and transactions. But technologies abound that could be harnessed to cheaply bring governance services nearer to citizens so that the self-serving government activities may be transformed to e- governance service platform. This paper proposes a framework for harnessing the potentials of current developments in mobile and cloud computing technologies to provide e-governance services to technologically disadvantaged grassroots environments. Firstly, it proposes enablers that would help the citizens to participate in governance and democratic activities by accessing and contributing to it, using tools already available and familiar to them. Secondly, it seeks to galvanise researches into the potentials of emerging technologies; mobile government and cloud computing, which can be use to adapt e-governance for societal transformations.
Keywords: E-governance, M-government, Cloud-computing, Success, Acceptance and Challenges
23. References: 1. United Nations (2007): Compendium of ICT Applications on Electronic Government: Mobile Applications on Health and Learning, Department of Economic and Social Affairs, Vol. 1, New York, 2007. 107-111 2. Thomas Zefferer (2011): E-government for Mobile Societies: Stocktaking of Current trends and Initiatives Version 1.0 – 16.02.2011. Secure Information Technology Center – Austria 3. Jennie Carroll(2006): ‘What’s in It for Me?’: Taking M-Government to the People, BLED 2006 Proceedings, Paper 49 4. Mobi Solutions (2010) Ltd: Mobile Government: 2010 and Beyond, White paper, 2010, 5. http://www.mobisolutions.com/files/Mobile%20Government%202010%20and%20Beyond%20v100.pdf 6. Kavita Karan, Michele Cheng Hoon Khoo (2008): Mobile Diffusion and Development: Issues and Challenges of M-Government with India in Perspective, Proceedings of M4D 2008, Karlstad University, Sweden 7. Rogers W’O Okot-Uma (2004): Building Cyberlaw Capacity for eGovernance: Technology Perspectives1, Regional Pacific Workshop on Law and Technology, November 2004. Wellington, New Zealand. 8. UNESCO (2007): E-Governance Capacity Building Initiative Focus on Africa - Updated: 19-12-2007 10:46 9. Probir Banerjee, Patrick Y.K. Chau (2004): An evaluative framework for analysing e-government convergences capability in developing countries. Electronic Government, an International Journal (EG), Vol. 1 No. 1, 2004 10. Brewer E, Demmer M, Du B, Ho M., Kam M., Nedevschi S., Pal J. Patra R. Surana S. (2005): The case for technology in developing regions. Computer publication Vol. 38, issue 6, Page 25-38. DOI: 10.1109/MC.2005.204 11. Olabode S, Marlien E, S.J Jacobs (2005): ICT provision to disadvantaged urban communities: study in South Africa and Nigeria. International Journal of Education and Development using ICT, Vol. 1 No. 3, 2005. 12. Okoronkwo M.C. and Agu M. N (2011): E-Readiness Assessment of Enugu State, Nigeria. Asian Journal of Information Management, 5(1): 25-34. ISSN 1819-334X / http://scialert.net/abstract/?doi=ajim.2011.25.34 13. Wikipedia: 14. http://www.en.wikipedia.org/wiki/cloud_computing#cite_note-yarmis-28 Authors: J. Navin Sankar, S. Mary Joans, S. J. Grace Shoba, A. Arun Paper Title: Enhanced Object Tracking Using Davinci Processors Abstract: Modular tracking methodologies have shown the promises of great versatility and robustness. In a similar way, the proposed paper, Enhanced Object Tracking Using Davinci Processors, will also possess major challenge for emerging computer vision technology. The Continuously Adaptive Mean Shift [CAMSHIFT] Algorithm used here is based on the Mean Shift Algorithm for object tracking for a perceptual user interface. The main aim of this proposal is to determine the effectiveness of the CAMSHIFT Algorithm as a general purpose object tracking approach in the case where a small portion of image is assumed as region of interest. Then the object within the corresponding region of interest is tracked using CAMSHIFT algorithm. The algorithm performs well mainly on moving objects in video sequences and it is robust to changes in shape of the moving object. The Digital Video Development Platform [DM6437 EVM] is used to obtain the video from the camera and will use the Ethernet media access control address and video processing back end drivers for the real time transmission of the video captured. The video is received and processed at DM6446, where the CAMSHIFT algorithm is implemented and the video object tracking takes place. The experimental results obtained from the proposal proves the consistency 24. and efficiency of the proposed algorithm..
Keywords: CAMSHIFT, CCS, DM6437, DM6446, LINUX, Ubuntu. 112-115
References: 1. “Adaptive object tracking algorithm based on eigenbasis space and compressive sampling”, Li. J, Wang. J, Image Processing, IET, November 2012. 2. “A Change Information based fast algorithm for video object Detection and Tracking”, Subudhi. B. N., Nanda. P. K, Ghosh. A, Circuits and systems for Video Technology, IEEE Transactions, July 2011. 3. “Real Time People Tracking Using DM6437 EVM”, Tomasz Marciniak, Damian Jackowski, Pawel Pawlowski, Adam Dabrowski. 4. Video and Image Processing Blockset, Mathworks.com. 5. “Object Tracking using Improved Camshift Algorithm combined with Motion Segmentation”, Emami. E, Fathy. M, Machine Vision and Image Processing 2011. 6. “An Improved Camshaft Algorithm for Target Tracking in Video Surveillance”, Chunrong Zhang, Yuansong Qiao, Enda Fallon, Chianqiao Xu, IT &T Conference 2009. 7. First Davinci Products for Digital Video Innovation, www.ti.com. 8. TVP5146 NTSC/PAL/SECAM 4x10-bit digital video decoder with Macrovision detection, www.ti.com. 9. TMS320DM6437 DVDP Getting Started Guide, www.ti.com. 10. TMS320DM6446 DVEVM v2.0 Getting Started Guide, www.ti.com. Authors: Nikam Gitanjali Ganpatrao, Jayanta Kumar Ghosh Paper Title: Soft Computation Based Topographic Map Legend Understanding Prototype System Abstract: The goal of the study is to devise an intelligent system to understand topographic map automatically. This paper explains the design of a system to automatically interpret information from scanned Indian topographic map legends set. A method based on perception of shape provides a collective understanding of size, form and orientation as that of human psycho-visual approach, is required towards development of a topographic map legends understanding system. The fundamental of the system are map legend analysis algorithms- Edge detection algorithm and line thinning algorithm to extract patterns and shape features from images of scanned topographic map legends and describe it as primitives which is building entity of shape of legend. An approach is based on feature extraction model and back propagation neural network which allows efficient and coherent management of map legends, recognition processes, recognition results. The system incorporates shape feature and uses back propagation neural network for recognition. The experimental results show that developed system performs well in recognition and understanding of map legends.
Keywords: Back propagation neural network, Edge detection, Legend primitives, Map understanding, Syntactic pattern recognition, Thinning algorithm,. 25. References: 116-120 1. Biederman, I., Ju G., Surface vs. edge-based determinants of visual recognition, Cognitive Psychology, 20 (1), pp. 38-64, 1988. 2. Chai Quek, 1994, A novel single pass thinning algorithm, IEEE trans. on system man and cybernetics. 3. Chaing, Y., Knoblock, C., Chen, C., Automatic extraction of road intersections from raster maps, GIS’05, In: Proceedings of the 13th annual international workshop on geographic information systems, pp. 267-276, 2005. 4. Den Hartog, J., ten Kate, T., Gebrands, J., Knowledge based segmentation for automatic map interpretation. Graphics recognition: methods and applications, Notes in Computer Science 1072, Berlin: Springer 1996, pp. 159-178, 1996. 5. Dhar, D.B. and Chanda, B., Extraction and recognition of geographical features from paper maps, Int. J. Doc. Anal. Reconit, 8 (4), pp. 232-245, 2006. 6. Eric Reiher, Li, Donne, Lalonde, Hayne & Zhu, 1996, A system for efficient and rob ust map symbol recognition, IEEE pro. of ICPR’96, 783-787. 7. Ejiri, M., Kakumoto, S., Miyatake, T., Shimada, S., Ichikawa, T., Automatic recognition of design drawings and maps, In: Proceedings of the seventh international conference on pattern recognition, pp. 1296-1305, 1984. 8. Gamba, P. and Mecocci, A., Perceptual grouping for symbol chain tracking in digitized topographic maps, Pattern recognition letter, 20 (4), pp. 355-365, 1999. 9. Li Fukiang and Gao Shuangxi, 2010, Character Recognition System Based on Back-propagation Neural Network, 2010 Inter. Con. on Machine Vision and Human-machine Interface, 393-396. 10. Norbert B. Ebi, 1995, Image interpretation of topographic maps on a medium scale via frame-based modeling, IEEE, 250-253. 11. Rangachar Kasturi & Juan Alemany, 1988, Information extraction from images of paper-based maps, IEEE trans. of software engg., Vol.14, No.5, 671-675. 12. Samet, H., Soffer, A., A legend driven geographical symbol recognition system, In: Proceedings of the twelfth International conference on Pattern Recognition, Vol. 2, pp. 350-355, 1994. 13. Samet, H., Soffer, A., MAGELLAN: Map acquisition of geographical labels by legend analysis, Int. J. Doc. Anal. Recognition 1 (2), pp. 89-101, 1998. 14. Simon Haykin, 2000, Neural networks a comprehensive foundation, second edition, 112-123. 15. Starr, L.E, Computer assisted cartography research and development report. International cartography association, 1984. 16. Yamada, H., Yamamoto, K., Hosokawa, K., Directional mathematical morphology and reformalized hough transformation for analysis of topographic maps., IEEE Trans. Pattern Anal. Mach. Intell. 15 (4), pp. 380-387, 1997. 17. Y.David & D.Krishana Reddy, 2011, Digital image processing tech. Based on edge feature extraction, International Journal of Advanced Engineering & Application, Jan 2011, 102-105. 18. Ventura, A. D., Schettini, R., Graphic symbol recognition using a signature technique, Proceedings of the 12th International Conference on Pattern Recognition (ICPR’94), Jerusalem, Israel, 2, IEEE Computer Society, Los Alamitos (CA), pp. 533-535, 1994. Authors: V.V.Govind Kumar, Kamal Jain, Ajay Gairola A Study and Simulation of Cloudburst event Over Uttarkashi Region using River Tool and Geomatic Paper Title: Techniques Abstract: In Uttarakhand state, India subjected to frequent occurrence of natural disasters like Cloudburst. Flooding due to Cloudburst is the extreme form of Natural disaster. This leads flash floods/ landslides, house collapse, dislocation of traffic and human casualties on large scale (Sati and Maikhuri, 1992) The average rainfall for Uttarkashi district varies 1500-3000 mm a year. The purpose of this study is to Analyses the Natural Disaster events like CloudBurst using RiverTool and Geographic Information System. In the first stage, locations of Cloudburst were identified from field survey and Indian Atlas. In the second stage, the layers Slope, Drainage pattern and LandUse classification are generated from AsterDEM and Landsat ETM+ data. The influence of Drainage characteristics, slope angle and LandUse Classification were spatially integrated to analyse one of the Natural Disaster like Cloudburst in the Uttarkashi District, Uttarkhand State, Northern part of India where a large number of Cloudburst happened due to extreme weather event of Aug 3–6, 2012. The villages Ravada, Paniyara kala, Andhyara kala, Sangamchetty are totally effected and 34 persons died, 7 Bridges of vehicle and 6 Bridges of footpath were washed away resulting in no connectivity with Bhatwari area, 1700 families are affected from Gangori to Uttarkashi, Around a population of 80000 is affected from this disaster.A quantitative technique of multivariate analysis was performed to analyse theware conducted for different excess rainfalls. A natural disaster is the consequence of the combination of a natural hazard (a physical event e.g. volcanic eruption, earthquake, landslide, flooding, etc.) and human activities. Therefore, for better understanding of this event, Mapping and analysis of hydrological Parameters are carried out in Uttarkashi region. Uttarkashi and its surrounding regions of the trans-Himalaya experienced multiple cloudbursts and associated flash floods during August 3–6, 2012.
Keywords: Cloudburst, Geographic Information System, Flash floods, Landsat ETM+ and Aster DEM.
References: 1. Anders A.M, Roe GH, Hallet B, Montgomery DR, Finnegan NJ, Putkonen J (2006) Spatial patterns of precipitation and topography in the Himalayas. In: Willett SD, Hovius N, Brandon MT, Fisher DM (eds) Tectonics, climate, and landscape evolution. Geological Society of America Special Paper 398, Penrose Conference Series, pp 39–53 2. Barros AP, Joshi M, Putkonen J, Burbank DW (2000) A study of 1999 monsoon rainfall in a mountainous region in central Nepal using TRMM products and rain gauge observations. Geophys Res Lett 27:3683–3686 26. 3. Barros AP, Lang TJ (2003) Monitoring the monsoons in the Himalayas: observations in Central Nepal, June 2001. Mon Weather Rev 131:1408–1427 4. Barros AP, Chiao S, Lang TJ, Burbank D, Putkonen J (2006) From weather to climate—seasonal and interannual variability of storms 121-126 and implications for erosion processes in the Himalaya. In: Willett SD, Hovius N, Brandon MT, Fisher DM (eds) Tectonics, climate, and landscape evolution. Geological Society of America Special Paper 398, Penrose Conference Series, pp 17–28. 5. Bhaskaran B, Jones RG, Murphy JM, Noguer M (1996) Simulation of Indian summer monsoon using a nested regional climate model: domain size experiments. Clim Dyn 12:573–587 6. Bookhagen B, Burbank DW (2006) Topography, relief and TRMM-derived rainfall variation along the Himalaya. Geophys Res Lett 33:1–5. 7. Bookhagen B, Burbank DW (2006) Topography, relief and TRMM-derived rainfall variation along the Himalaya. Geophys Res Lett 33:1–5. 8. Cevik E, Topal T (2003) GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environ Geol 44:949–962 9. Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48:349–364 10. Das S, Asrit R, Moncrieff MW (2006) Simulation of a Himalayan cloud burst event. J Earth Syst Sci 115(3):299–313 11. Ercanoglu M, Gokceoglu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol 75:229–250. 12. Gemiti. A, Falalakis. G, Eskioglou. P and Petalas C “Evaluating landslide susceptibility using environmental factors, fuzzy membership functions and GIS” Global Nest Journal, Vol 13, pp:28-40,2011. 13. Gokceoglu C, Aksoy H (1996) Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol 44:147–161Sati, V.P. and Maikhuri, R. K. 1992. Cloudburst: A Natural Calamity. Him Prayavaran. Vol. 4 (2) Dec. 1992 pp.11-13 14. Govind, V.V and Kamal Jain “ Monitoring and Analysis of Cloudburst using Geomatic Technicques” 13th ESRI user conference, New Delhi, December 5-6,2012 15. Kriplani RH, Kulkarni A, Sabade SS (2003) Western Himalayan snow cover and Indian monsoon rainfall: a re-examination with INSAT and NCEP/NCAR data. Theor Appl Climatol 74:1–18 16. Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113 17. Lee S, Choi J, Min K (2004a) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Int J Remote Sens 25:2037–2052 18. Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26:1477–1491 19. Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation with a case study in the Himalayas. Landslides 2:61–69 20. Sravan, K.M., Shekhar, M.S., Krishan, S.S.V.S, Bhutiyani, M.R. and Ganju. A “ Numerical simulation of Cloudburst event on August 05,2010, over Leh using WRF mesoscale model” International journal of Natural Hazards(springer), Vol 62,pp:1261-1271, 2012 21. Yalcin A (2005) An investigation on Ardesen (Rize) region on the basis of landslide susceptibility, KTU, PhD Thesis (in Turkish) Authors: Avtar Singh Buttar, Ashok Kumar Goel, Shakti Kumar Paper Title: Intellectual Behavior of a Group of Wild Animals: A Computational Intelligence Study Abstract: Numerous methodologies have been invented inspired by nature and based on real life behavior of species which perform task in a group. In this paper, a novel methodology based on intelligent chasing and hunting methods adopted by the animals in a group to chase & hunt their prey is presented. The dog is taken as prime model for developing the methodology. The method is named as “Dog Group Wild Chase & Hunt Drive (DGCHD) [18]. The algorithm is implemented on Traveling Salesman benchmark problem available in literature. The problem has been solved by different researchers for testing their proposed novel intelligent algorithms in various nature inspired technologies such as Ant Colony System, Genetic Algorithms etc. The results obtained are very optimistic and encouraging.
Keywords: Dogs behavior, Chasing & hunting, Computational Intelligence, Dog Group Wild Chase & Hunt Drive (DGCHD), combinatorial optimization.
References: 1. Natural History museum of Los Angles country 2. Pugs.com “5 Ways Your Dog Senses The World Differently From You” 3. WWW.RCMP-GRC.GC.CA ROYAL CANADIAN MOUNTED POLICE “Dog Senses” 4. http://www.aces.edu/counties “The Dog's Sense of Smell” 5. http://www.pet-yard.com/dogs-senses.php 6. http://www.seefido.com/html/dog_s_5_senses_of_dogs.htm 7. http://www.nature.com/nature/journal/v36/n925/abs/036273a0.html 8. http://www.whole-dog-journal.com/issues/7_11/features/ Canine-Sense-of-Smell_15668-1.html 9. http://www.sciencedaily.com/releases/2006/01/060106002944.htm 10. http://jhered.oxfordjournals.org/cgi/content/full/96/7/812 11. www.dog-health-hand-book.com 27. 12. www.dailymail.co.uk 13. http://www.dog-names.org.uk/hunting-dogs.htm “Hunting Dogs” 127-132 14. http://ezinearticles.com/?Hunting-Dog-Origins---Tracing-The- Evolution-Of-The- Hunting- Dog & id=1659496 15. http://www.sekj.org/PDF/anzf41/anzf41-545.pdf 16. http://www.ehow.com/how-does_5139011_do-dogs-ears-work.html 17. www.charlottesville-area-real-estate.com 18. A. S. Buttar, A. K. Goel and S. Kumar, Patent Title: Wild Intelligence: A novel intelligence as dog group wild chase & hunt drive (DGCHD), Application No.:DEL/ 1965/2008 Indian Patent Office Journal, issue No.14/2010,pp., 7873 April, 2010 19. F. T Lin, C.Y. Kao, and C. C. Hsu, 1993, Applying the genetic approach to simulated annealing in solving some NP-hard problems. IEEE Transactions on Systems, Man, and Cybernetics, 23,1752–1767. 20. S. Eilon, C.D.T. Watson-Gandy, and N. Christofides, 1969, Distribution management: mathematical modeling and practical analysis. Operational Research Quarterly, 20, 37–53. 21. M. Dorigo, L. M. Gambardella, Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem , IEEE Transactions on Evolutionary Computation Vol. 1,No. 1,Pp. 53-66, 1997 22. F.A.N. Huilian “Discrete Particle Swarm Optimization for TSP based on Neighborhood” Journal of Computational Information Systems 6:10 (2010) 3407-3414 23. Hui-Dong Jin,Kwong-Sak Leung,Man-Leung Wong, and Zong-Ben Xu An Efficient Self- Organizing Map Designed by Genetic Algorithms for the Traveling Salesman Problem IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, Vol. 33, No. 6, December 2003 877 24. Wei-Neng Chen, Jun Zhang, Henry S. H. Chung,Wen-Liang Zhong, Wei-Gang Wu and Yu-hui Shi, “A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems” IEEE Transactions on Evolutionary Computation, Vol. 14, No. 2, April 2010 25. M. Albayrak and N. Allahverdi,” Development a new mutation operator to solve the Traveling Salesman Problem by aid of Genetic Algorithms” Elsevier, Available online 23 July 2010. 26. Shyi-Ming Chen and Chih-Yao Chien,” Parallelized genetic ant colony systems for solving the traveling salesman problem” Elsevier, Available online 23 September 2010 27. Y. Marinakisa, M. Marinaki, “A Hybrid Multi-Swarm Particle Swarm Optimization algorithm for the Probabilistic Traveling Salesman Problem” Computers & Operations Research 37 (2010) 432 – 442 28. Shyi-Ming Chen, Chih-Yao Chien, “Solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques” Expert Systems with Applications 38 (2011) 14439–14450. 29. Yen-Far Liao, Dun-Han Yau, Chieh-Li Chen, “Evolutionary algorithm to traveling salesman problems”, Computers and Mathematics with Applications, Elsevier 2012 Authors: Ramandeep Kaur, Pushpendra Kumar Pateriya Paper Title: A Study on Security Requirements in Different Cloud Frameworks Abstract: Cloud computing provides the capability to use computing and other storage resources which are required by various users on a metered basis and reduce the expenditure in an organization’s computing infrastructure. The virtual machines running on physical hardware and being controlled by hypervisors is a cost- efficient and flexible computing technique that is used as a key technology in cloud computing and provides transparency to different cloud users as there is no actual physical allocation of the machine. As cloud computing provides various benefits nowadays, it also brings some of the concerns about the security and privacy of 28. information. In this paper, we made a study about different security risks that pose a greatest threat to the cloud computing. This paper describes about the different security issues that are occurring in the various cloud 133-136 computing frameworks and the areas where security lacks and measures can be taken to enhance the security mechanisms.
Keywords: Internet protocol, Infrastructure as a service, Platform as a service, Software as a service, Virtual machine
References: 1. Wayne Jansen, Timothy Grance (2011) “Guidelines in security and privacy in cloud computing” National institute of standards and technology U.S department of commerce, NIST special publication 800-144. 2. Yashpal Kadam(2011) “Security issues in cloud computing- A transparent view” Int. J Comp Sci. Emerging Tech, Vol- 2 No 5 October, 2011. 3. Kevin Hamlen, The University of Texas at Dallas, USA (2010) “Security issues in cloud computing” International Journal of Information Security and Privacy, 4(2), 39-51. 4. Volker Fusenig and Ayush Sharma (2012) “Security Architecture for Cloud Networking” International Conference on Computing, Networking and Communications, Cloud Computing and Networking Symposium 978-1-4673-0009-4/12. 5. V.Krishna Reddy (2011) “Security Architecture of Cloud Computing” International Journal of Engineering Science and Technology (IJEST), ISSN: 0975-5462 Vol. 3. 6. Pankaj Arora, Rubal Chaudhary Wadhawan(2012) “Enhancing security and privacy in the cloud computing” ijccr volume 2. 7. Peter Mell(2012) “What’s special about cloud security” IEEE computer society, 1520-9202/12. 8. Hsun Chuang (2011) “An Effective Privacy Protection Scheme for Cloud Computing” ICACT ISBN 978-89-5519-155-4. 9. Pardeep kumar, Vivek Kumar Sehgal(2011) “Effective Ways of Secure, Private and Trusted Cloud Computing” IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3,ISSN (Online): 1694-0814. 10. Gaurav Raj, Kamaljit Kaur(2012) “Secure Cloud Communication for Effective Cost Management System through MSBE” International Journal on Cloud Computing: Services and Architecture(IJCCSA),Vol.2, No.3. 11. Jianyong Chen, Yang Wang, and Xiaomin Wang (2012) “On-Demand Security Architecture for Cloud Computing” IEEE Computer Society, 0018-9162/12. 12. Abhishek Gupta, Jatin Kumar(2012)“Design and Implementation of the Workflow of an Academic Cloud” Indian Institute of Technology, Delhi[pdf]. 13. Lan Zhou, Vijay Varadharajan and Michael Hitchens(2011) “Enforcing Role-Based Access Control for Secure Data Storage in the Cloud” The Computer Journal, Vol. 54 No.10, 2011. 14. Cooper R. Verizon Business Data Breach security blog, 2008. 15. Kandukuri BR, Paturi VR, Rakshit A. “Cloud security issues”. In: IEEE international conference on services computing, 2009, p. 517– 20. 16. Kaufman LM. “Data security in the world of cloud computing, security and privacy” IEEE 2009; 7(4):61–4. Authors: S.Vigneshwaran, S.Sreekanth Paper Title: Bit-Mask Based Compression of FPGA Bitstreams Abstract: In this paper, bitmask based compression of FPGA bit-streams has been implemented. Reconfiguration system uses bitstream compression to reduce bitstream size and memory requirement. It also improves communication bandwidth and thereby decreases reconfiguration time. The three major contributions of this paper are; i) Efficient bitmask selection technique that can create a large set of matching patterns; ii) Proposes a bitmask based compression using the bitmask and dictionary selection technique that can significantly reduce the memory requirement iii) Efficient combination of bitmask-based compression and Golomb coding of repetitive patterns.
Keywords: Bitmask-based compression, Decompression engine, Golomb coding, Field Programmable Gate Array (FPGA).
References: 29. 1. J. H. Pan, T. Mitra, and W. F. Wong, “Configuration bitstream compression for dynamically reconfigurable FPGAs,” in Proc. Int. Conf. Comput.-Aided Des., 2004, pp. 766–773. 2. S. Hauck and W. D. Wilson, “Runlength compression techniques for FPGA configurations,” in Proc. IEEE Symp. Field-Program. 137-141 Custom Comput. Mach., 1999, pp. 286–287. 3. Dandalis and V. K. Prasanna, “Configuration compression for FPGA-based embedded systems,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 13, no. 12, pp. 1394–1398, Dec. 2005. 4. D. Koch, C. Beckhoff, and J. Teich, “Bitstream decompression for high speed FPGA configuration from slow memories,” in Proc. Int. Conf. Field-Program. Technol., 2007, pp. 161–168. 5. S. Seong and P. Mishra, “Bitmask-based code compression for embedded systems,” IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., vol. 27, no. 4, pp. 673–685, Apr. 2008. 6. S. Hauck, Z. Li, and E. Schwabe, “Configuration compression for the Xilinx XC6200 FPGA,” IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., vol. 18, no. 8, pp. 1107–1113, Aug. 1999. 7. D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. IRE, vol. 40, no. 9, pp. 1098–1101, 1952. 8. Moffat, R. Neal, and I. H. Witten, “Arithmetic coding revisited,” in Proc. Data Compression Conf., 1995, pp. 202–211. 9. Xiaoke Qin, Chetan Muthry, and Prabhat Mishra, “Decoding Aware Compression of FPGA Bitstreams,” in Proc. Data Compression Conf., 2011, pp. 411–419. 10. S. W. Golomb, “Run Length Encodings,” IEEE Transactions on Information Theory, vol. 12, pp. 399-401, 1966. 11. Quartus II development software literature, available at http://www.altera.com/literature/lit-qts.jsp. Authors: Parul Mohindru, Rajdeep Singh Paper Title: Multi-Sensor Based Forest Fire Detection System Abstract: Wireless Sensor Networks (WSNs) have become hot topic in field of research in recent days. In day to day life we come across many problems which left unresolved by humans, so at that time we think of collaborating human knowledge with technology to eradicate the problems. The efficient approaches of forest fire detection using multi-sensors describes one of the wireless sensor network applications for detecting a parameter that is fire and reporting it to the base station to save the humans and wildlife from destruction which is caused by the fire. The effort offered in this paper conveys the idea of implementing Fuzzy Logic on the information collected by multiple 30. sensors. Thus multiple sensors are used for detecting probability of fire with variations during different time in a day. Each sensor node senses Temperature, Humidity, Light Intensity, CO Density and Time for calculating 142-145 probability of fire. It will improve precision of the detection system, as well as false alarm rate will be reduced.
Keywords: Forest Fire Detection, Fuzzy Logic, Sensor Networks.
References: 1. Bayo, D. Antolín, N. Medrano, B. Calvo, S. Celma,” Early detection and monitoring of forest fire with a wireless sensor network system”, Procedia Engineering, Volume 5, 2010, Pages 248-251, ISSN 1877-7058. 2. YunusEmreAslan, IbrahimKorpeoglu, and OzguUluso, “A framework for use of wireless sensor networks in forest fire detection and monitoring,” Science direct, vol 36 pp.1-12, Mar 2012. 3. Al-Abbass Y. Al-Habashneh, Mohamed H. Ahmed, and Taher Husain, “Adaptive MAC Protocols for Forest Fire Detection Using Wireless Sensor Networks ,” in proceeding of IEEE electrical and communication system engineering confrence’, 2009,pp.329-333. 4. ÇağdaşDöner*, GökhanŞimşek, Kasım Sienna Yıldırım, and AylinKantarc, “Forest Fire Detection with Wireless Sensor Networks,”in academia Computer Engineering Department, Ege University’, 2010, pp.107-109. 5. ArnoldoDíaz-Ramíreza,*, Luis A. Tafoyaa, Jorge A. Atempa, and PedroMejía-Alvarezb, “Wireless Sensor Networks and Fusion Information Methods for Forest Fire Detection✩,” in Science direct on Electronics Engineering and Computer Science ’,2012, pp.69-79. 6. A.K. Singh, and Harshit Singh, “Forest Fire Detection through Wireless Sensor Network using Type-2 Fuzzy System”,International Journal of Computer Applications,” vol 52– No.9, pp. 19-23,August 2012. 7. M. Ganesh, Introduction to fuzzy sets and fuzzy logic, Prentice Hall of India Private Limited, New Delhi, 2006. Authors: Kapil Sharma, Sheveta Vashisht, Heena Sharma, Richa Dhiman, Jasreena Kaur Bains Paper Title: A Hybrid Approach Based On Association Rule Mining and Rule Induction in Data Mining Abstract: Data Mining: extracting useful insights from large and detailed collections of data. With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, this subject has become of increasing importance. This interest has inspired a rapidly maturing research field with developments both on a theoretical, as well as on a practical level with the availability of a range of commercial tools. In this research work titled a hybrid approach based on Association Rule mining and Rule Induction in Data Mining we using induction algorithms and Association Rule mining algorithms as a hybrid approach to maximize the accurate result in fast processing time. This approach can obtain better result than previous work. This can also improves the traditional algorithms with good result. In the above section we will discuss how this approach results in a positive as compares to other approaches.
Keywords: Association Rule mining, A priori algorithm, Rule Induction, Decision list induction, Data mining
References: 1. http://en.wikipedia.org/wiki/Inductive_Logic_Programming. 31. 2. Khurram Shehzad(2012)” EDISC: A Class-Tailored Discretization Technique for Rule-Based Classification”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 8, AUGUST 2012. 3. Ning Zhong, Yuefeng Li(2012)” Effective Pattern Discovery for Text Mining”, IEEE TRANSACTIONS ON KNOWLEDGE AND 146-148 DATA ENGINEERING, VOL. 24, NO. 1, JANUARY 2012. 4. Anil Rajput, S.P. Saxena(2012)” Rule based Classification of BSE Stock Data with Data Mining”, International Journal of Information Sciences and Application. ISSN 0974-2255 Volume 4, Number 1 (2012), pp. 1-9. 5. K. Shehzad(2011)” Simple Hybrid and Incremental Post-pruning Techniques for Rule Induction”, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. 6. Alexander Borisov(2011)” Rule Induction for Identifying Multilayer Tool Commonalities”, IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, VOL. 24, NO. 2, MAY 2011. 7. Alexander Borisov(2011)” Rule Induction for Identifying Multilayer Tool”,IEEE. 8. Fernando E. B. Otero(2011)” A New Sequential Covering Strategy for Inducing Classification Rules with Ant Colony Algorithms”,IEEE. 9. Thomas R. Gabriel and Michael R. Berthold(2010)” Missing Values in Fuzzy Rule Induction”, IEEE. 10. Nick F Ryman-Tubb(2010)” SOAR – Sparse Oracle-based Adaptive Rule Extraction: Knowledge extraction from large-scale datasets to detect credit card fraud”, IEEE. 11. Alberto Fern´andez(2010)” Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study”, IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 14, NO. 6, DECEMBER 2010. 12. Jeremy Davis (2010)” Methods of Information Hiding and Detection in File Systems”, 2010 Fifth International Workshop on Systematic Approaches to Digital Forensic Engineering. 13. Richard Jensen, Chris Cornelis(2009)” Hybrid Fuzzy-Rough Rule Induction and Feature Selection”, R. Jensen and Q. Shen are with the Department of Computer Science, Aberystwyth University, UK. Authors: D.Gladiya Lincy, S.Mary Joans Paper Title: Segmentation of Image Using Enhanced Morphological Gradient Hit Method Abstract: Many biomedical applications require the detection of infected structures in images. In order to get the originality of the image, it needs to undergo several steps of processing. This will vary from image to image depending on the type of image format, initial condition of the image and the information of interest and the composition of the image scene. While several algorithms have been proposed for semiautomatic extraction of these structures, branching points usually need specific treatment. Medical image segmentation is essential for diagnosing various problems occurs in eye. Retinal image segment is one of the critical issues because these images contain very small nerves and some artifacts present in it. This paper proposes a MGH approach to identify branching points in images. This method is used to change the representation of an image into something that is more meaningful and easier to analyze the interested object. A vector field is calculated using a novel contrast- 32. independent tensor representation based on local phase. Our method extracting image components that are useful in the representation and description of region shape, such as boundaries, infected objects, etc. Non-curvilinear 149-153 structures, including junctions and end points, are detected using directional statistics of the principal orientation as defined by the tensor. Results on synthetic and real biomedical images show the robustness of the algorithm against changes in contrast, and its ability to detect junctions in highly complex images. This proposed method is based in a model of MGH function which applies the color image to a gray scale image. This method is used to segment the image and selecting the specific image objects, thinning the object to diagnose the region.
Keywords: Detection, MGH, Segmentation.
References: 1. F.A.peres F.R.OliveiraL.A Neves,M.F.godoy, “Automatic Segmentation of Digital Images Applied in Cardiac Medical Image”march 15-19,LIMA,PERU,2010 IEEE 2. Piotr S.Windyga,”Fast Impulsive Noise Removal” IEEE Trans Image Processing, vol.10,no.1.pp 173-179,2002. 3. Khanh Vu, Kien A. Hue and Duc A. Tran,”An Efficient Core-Area Detection algorithm for fast Noise- Free Image Query Processing,”In Proc.of the 16thACM_SIGAPP Annual Symposium on Applied computing pp.228-269,mar.2003. 4. Xiaohui Hao, Charles Bruce, Cristina Pislaru and James F.Greenleaf,”A Novel Region Growing Method for Segmentating Ultrasound Image ,”IEEE Ultrasonic Symposium vol 2,pp.1717-1720,2000. 5. Jiankang Wang and Xiaobo Li,:A System for Sementing Ultrasound Images,”Pattern Recognition Proceedings 14th international conference,vol 1pp. 456-461,1999. 6. N.Otsu,”A Threshold Selection Meyhod from Gray Level Histogram,”IEEE Trans.Systems,Man,and cypernetics,vol SMC-8 pp 64- 67,1999. 7. TheerapattanakulJ,PlodpaiJ,Pintavirooj C”An efficient method for segmentation step of automated White blood cell Classification “IEEE Region 10 Conference 2002. 8. Anoraganingrum, D.”Cell segmentation with median filter and Mathematical morphology operation”, International Conference on image Analysis and ocessing,1999,9,185-186. 9. A.Laine,”In Spotlight Biomedical Imaging”,IEEE Rev.BiomedEng.,vol 2,pp.6-8,2009. 10. J.Swedlow,I.Goldberg,E.Brauner,and P.Sorger. “Informatics and quantitative analysis in Biological imaging analysis,”Science vol,300,no.5613, pp.100-102,2003. 11. K.Kyilekval, D.fedoroy, B.Obara, A.K>Singh, And B>Manjunath,”Bisque: A Platform for the bioimage analysis and management,” Bioinformatic vol,26,no.4,Feb.2011. 12. E.Argyle,”Techniques For edge detection,”Proc.IEEE,vol57,no 2,286-267,feb.1971. 13. S.Hadjidemetriou,D.Toomre,and J.S.Duncan,”Segmentation and 3d reconstruction of microtubules in total internal reflection microscopy(TIRFM)’’in Proc.Med.Image Comput.Comput-assist,Oct 26-30,2005,vol. 8,pp.754-768. 14. L.Gang,O.Chutatape.and S.Krishnan,”Detection and measurement of retinal vessels in Fundus images using amplitude modified secondorder Gaussianfilter,”IEEE tranc.Biomed Enfg vol 49 no.2,pp,169-174 Feb 2002. 15. J.H.Moltz. I.Stuke. and T.Aach,”Histogram-based orientation analysis for junctions,”in proc.Eur.Signal Process Conf.Sep.4-8 2006,pp 1-4. Authors: R.Harikumar, T.Vijayakumar, R.Kasthuri Paper Title: Analysis of PSO and Hybrid PSO in Calculation of Epileptic Risk Level in EEG Abstract: The main aim of this paper is to compare and analyze the performance of the PSO algorithm and the hybrid PSO output in determining the epileptic risk level for the given Electroencephalogram signal inputs. Various parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance are calculated from the EEG signals. The two optimization technique has been used for classifying the risk level of the given inputs and the efficacy of the above two methods have been analyzed and compared using mean square error and quality value. 20 patients input are taken for analysis in both methods in calculation of risk level. Comparing to PSO output hybrid PSO method is efficient based on performance index and quality value.
Keywords: Electroencephalogram signals, Epileptic risk level, Particle swarm optimization (PSO), Hybrid PSO optimization, mean square error, quality value..
References: 1. Dr.R.Harikumar,T.Vijayakumar,(2011)“Comprehensive Analysis of Hierarchical Aggregation Functions Decision Trees, SVD, K- means Clustering, PCA and Rule Based AI Optimization in the Classification of Fuzzy based Epilepsy Risk Levels from EEG Signals “ISSN 2150-7988 Volume 3. 2. Tanyawat Sanguanchue, Kietikul Jearanaitanakij (2012) “Hybrid Algorithm for training feed-forward neural network using PSO- Information gain with back propagation algorithm.” IEEE 978-1-4673-2025. 3. Dr.R.Harikumar,Dr.C.Palanisamy(2011) ”Performance Analysis of Fuzzy Techniques Hierarchical Aggregation Functions Decision Trees and Support Vector Machine (SVM)for the Classification of Epilepsy Risk Levels from EEG Signals” IEEE ERIPNO.:ER/0904480/M/01/1193. 4. Alison A Dingle et al (1993) ‘A Multistage System to Detect Epileptic form Activity in the EEG’, IEEE Transactions on Biomedical Engineering, 40(12):1260-1268. 5. J.Kennedy and R.Eberhart, Particle Swarm Optimization, Proc. IEEE International Conf. on Neural Networks, Perth , Vol. 4, pp 1942- 33. 1948,1995. 6. C.R. Hema, M.P.Paulraj, R. Nagarajan,S. Yaacob, A.H. Adom, “Application of Particle Swarm Optimization for EEG Signal Classification” BMFSA(2008-13-1-11) . 154-159 7. R. Eberhart and Y. Shi, “Evolving Artificial Neural Networks,” Proceedings of the 1998 International Conference on Neural Networks and Brain, pp. PL5 - PL13, 1998. 8. J. Salerno, “Using the particle swarm optimization technique to train a recurrent neural model,” IEEE International Conference on Tools with Artificial Intelligence, pp. 45-49, 1997. 9. M. Omran, A. Salman, and A. P. Engelbrecht, “Image classification using particle swarm optimization,” Proceedings of the 4th Asia- Pacific Conference onSimulated Evolution and Learning 2002 (SEAL 2002), pp.370-374, 2002. 10. C. A. Coello, E. H. Luna, and A. H. Aguirre, “Use of particle swarm optimization to design combinational logic circuits,” Lecture Notes in Computer Science(LNCS), No.2606, pp. 398-409, 2003. 11. S. Ujjin and P. J. Bentley, “Particle swarm optimization recommender system,” Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), pp. 124-131, 2003. 12. R. Eberhart and Y. Shi, “Evolving Artificial Neural Networks,” Proceedings of the 1998 International Conference on Neural Networks and Brain, pp. PL5 - PL13,1998. 13. J. Salerno, “Using the particle swarm optimization technique to train a recurrent neural model,” IEEE International Conference on Tools with Artificial Intelligence, pp. 45-49, 1997. 14. R. Mendes, P. Cortez, M. Rocha, and J. Neves, “Particle swarms for feedforward neural network training,”Proceedings of the 2002 International Joint Conference onNeural Networks (IJCNN 2002), pp. 1895-1899, 2002. 15. Kennedy, J. and Mendes, R. Population structure and particle swarm performance. In In Proceedings of the IEEE Congress on Evolutionary Computation, pages 1671–1676, Hawaii, USA, 2002. 16. Omran, M. Particle Swarm Optimization Methods for Pattern Recognition and Image Processing.PhD thesis, Department of Computer Science, University of Pretoria, South Africa, 2005. 17. Schwefel, H. Evolution and Optimum Seeking.Wiley, New York, 1995. 18. Shi, Y. and Eberhart, R. Parameter selection in particle swarm optimization. In In: Proceedings of Evolutionary Programming 98, pages 591–600,1998. 19. Shi, Y. and Eberhart, R. C. A modified particle swarm optimiser. In IEEE International Conference on Evolutionary Computation, Anchorage,Alaska, 1998. 20. Arthur C Gayton (1996), ‘Text Book of Medical Physiology’, Prism Books Pvt. Ltd., Bangalore, 9th Edition. 21. Michael Meissner, Michael Schmuker and Gisbert Schneider” optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training” BMC Bioinformatics, 7:125 doi:10.1186/1471-2105-7-125,2006. 22. Nowak, J. Szamrej, and B. Latane. From private attitude to public opinion: A dynamic theory of social impact. Psychological Review, 97(3):362-376, 1990. 23. R. Poli. Analysis of the publications on the applications of particle swarm optimisation. Journal of Artificial Evolution and Applications, Article ID 685175, 10 pages, 2008. 24. Shermeh ,Ata E. Zadeh Ghaderi, Reza” An intelligent system for classification of the communication formats using PSO” ISSN: 0350- 5596,2008. 25. Principe, “Brain Machine Interfaces: Mind over Matter”, 2005. 26. http://www.ece.ufl.edu/publications/Archives/int henews/2005 /brainmachine.html 27. M. Teplan, “Fundamentals of EEG Measurement”, Measurement Science Review,Vol. 2, Section 2, 2002. 28. N.J Huan and R. Palaniappan, “Classification of Mental Tasks using Fixed and Adaptive Autoregressive Models of EEG Signals” IEEE EMBS Conference, pp 507 – 510, 2004. 29. Z. A Keirn and J. I. Aunon, “A New Mode of Communication between Man and hisSurroundings” IEEE Transactions on Biomedical Engineering, Vol. 37.no. 12. pp 1209-1214, 19. Authors: Chandra Bhan Yadav, Himansu Narayan Singh In-Silico Identification of LTR type Retrotransposons and Their Transcriptional Activities in Paper Title: Solanum Tuberosum Abstract: Eukaryotes genomes contains large amount of mobile genetic elements. More than two million EST (expressed sequence tags) sequences have been sequenced from potato crop plant and this amount of ESTs allowed us to analyze the transcriptional activity of the potato transposable elements. We predicted the full length LTR from potato genomic database using LTR finder software. Maximum number of full length Gypsy type LTRs were present on chromosome 03 (197) and Copia type retrotransposons on chromosome number 01 (172). We have also investigated the transcriptional activities of LTR type retrotransposons in different potato organs based on the systematic search of more than two million expressed sequence tags. At least 0.86% potato ESTs show sequence similarity with LTR type retrotransposons. According to these data, the patterns of expression of each LTRs (Gypsy & Copia) is variable among various tissue specific EST libraries. In general, transcriptional activity of the Gypsy- like retrotransposons is higher compared to Copia type. Transcriptional activity of several transposable elements is especially high in Flower, Callus and root tissues. The use of powerful high-throughput sequencing technologies allowed us to elucidate the transcriptional activation in various cells of potato. In this study, we observed that Gypsy and Copia like retrotransposons have a considerable transcriptional activity in some tissues which indicate that the transposition is more frequent in various tissues specific EST libraries. .
Keywords: Retrotransposons, LTR, Solanum tuberosum, Gypsy, Copia
References: 1. Roderick et al., “Retrotransposon Sequence Variation in Four Asexual Plant Species”. J. Mol. Evol. 62:375–387, 2006 2. Feschotte et al., “Plant transposable elements: Where genetics meets genomics”. Nat. Rev. Genet. 3:329–341, 2002. 3. Bennetzen J. E. and Kellogg A. “Do plants have a one-way ticket to genomic obesity?” Plant Cell 9:1509-1514, 1997. 4. Meyers et al., “Abundance, distribution, and transcriptional activity of repetitive elements in the maize genome”. Genome Res. 34. 11:1660–1676, 2001. 5. SanMiguel et al., “The paleontology of intergene retrotransposons of maize”. Nat. Genet. 20:43–45, 1998. 6. Flavell et al., “Retrotransposonbased insertion polymorphisms (RBIP) for high throughput marker analysis”. Plant J. 16:643–650, 1998. 160-164 7. Kumar A., and Bennetzen J.L. “Plant retrotransposons”. Annu. Rev. Genet. 33:479–532, 1999. 8. Rabinowicz et al., “Differential methylation of genes and retrotransposons facilitates shotgun sequencing of the maize genome”. Nat. Genet. 23:305-308, 1999. 9. Vianey et al., “Control of female gamete formation by a small RNA pathway in Arabidopsis”. Nature 464:628–632, 2010. 10. Macas et al., “Zaba: a novel miniature transposable element present in genomes of legume plants”. Mol. Genet. Genomics 269:624-31, 2003. 11. Echenique et al., “Frequencies of Ty1-copia and Ty3- gypsy retroelements within the Triticeae EST databases”. Theor. Appl. Genet. 104:840–844, 2002. 12. Jones-Rhoades et al., “MicroRNAS and their regulatory roles in plants”. Annu Rev Plant Biol 57:19–53, 2006. 13. Wei et al., “Characterization and comparative profiling of the small RNA transcriptomes in two phases of locust”. Genome Biol 10: R6, 2009. 14. Bartel et al. “MicroRNAs: Genomics, biogenesis, mechanism, and function”. Cell 116:281–297, 2004. 15. Khraiwesh et al., “Role of miRNAs and siRNAs in biotic and abiotic stress responses of plants”. Biochim Biophys Acta. 1819(2):137- 48, 2011. 16. Massa1 et al., “The Transcriptome of the Reference Potato Genome Solanum tuberosum Group Phureja Clone DM1-3 516R44”. PLoS One 6:10 | e26801, 2011. 17. Zhao and Wang “LTR_FINDER: an efficient tool for the prediction of full-length LTR retrotransposons”. Nucleic Acids Res. 35:W265-W268, 2007. 18. Jurka et al., “Repbase Update, a database of eukaryotic repetitive elements”. Cytogenet. Genome Res. 110(1-4): 462-467, 2005. 19. Zhou and Ying Xu “RepPop: a database for repetitive elements in Populus trichocarpa” BMC Genomics 1471-2164-10-14, 2009. 20. Gribbon et al., “Phylogeny and transpositional activity of Ty1- copia group retrotransposons in cereal genomes”. Mol. Gen. Genet. 261:883–891, 1999. 21. Tanurdzic et al., “Epigenomic consequences of immortalized plant cell suspension culture”. PLoS Biol. 6:2880-2895, 2009. 22. Kasschau et al., “Genome-wide profiling and analysis of Arabidopsis siRNAs”. PLoS Biol. 5:e57, 2007. 23. Picault et al., “Identification of an active LTR retrotransposon in rice”. Plant J. 58:754-765, 2009. 24. Pouteau et al., “Specific expression of the tobacco Tnt1 retrotransposon in protoplasts”. EMBO J. 10:1911-1918, 1991. 25. Hirochika “Activation of tobacco retrotransposons during tissue culture”. EMBO J. 12:2521-2528, 1993. 26. Mhiri et al., “The promoter of the tobacco Tnt1 retrotransposon is induced by wounding and by abiotic stress”. Plant Mol. Biol. 33:257- 266, 1997. Authors: Angshuman Khan, Ratna Chakrabarty Novel Design of High Polarized Inverter Using Minimum Number of Rotated Cells and Related Kink Paper Title: Energy Calculation in Quantum dot Cellular Automata 35. Abstract: Quantum Dot Cellular Automata (QCA) has been emerged as a cut-in nano-technology in the field of digital logic architecture. It is the most emerging technology in nanoscience. QCA designed circuits require lesser 165-169 power & it has high switching speed and high packaging density with respect to current CMOS technology. One of the basic building blocks of QCA circuits is QCA inverter. The conventional QCA inverters require more normal cells and it has less polarization. In this paper, we have designed high polarized inverters using minimum number of rotated (45˚) QCA cells. Till now, the conventional inverters which have large polarization, they require three to five normal cells. We have designed the novel inverter using three rotated cells whose polarization is more than the conventional three normal cells inverter. We increasing the polarization i.e. make the three rotated cells inverter circuit more fault- free by adding extra rotated cells at the output section. In each case, the designed rotated cells inverters have more polarization (i.e. more fault free) than conventional inverters though it has same number of cells. Our finally designed high polarized rotated cells inverter has five cells and its polarization is greater than any type of conventional inverters designed till now. Also, here we calculate the kink energy of each rotated cells inverters.
Keywords: Kink energy, Majority gate, Polarization, QCA.
References: 1. C. Lent, and P. Tougaw, “A device architecture for computing with quantum dots,” Proceeding of IEEE, vol. 85-4, pp. 541-557, April 1997. 2. M. Wilson et al., Nanotechnology: Basic Science and Emerging Technologies. London, U.K.: Chapman & Hall, 2002. 3. C. S. Lent et al., “Quantum cellular automata,” Nanotechnology, vol. 4, pp. 49-57, 1993. 4. C. S. Lent and P.D. Tougaw, “A device architecture for computing with quantum-dots,” Proc. IEEE, vol. 85, pp. 541-557, Apr. 1997. 5. W. Porod, “Quantum-dot devices and quantum-dot cellular automata,” Int. J. Bifurcation and Chaos, vol. 7, no. 10, pp. 2199-2218, 1997. 6. G. Toth and C.S. Lent, “Quasiadiabatic switching for metal-island quantum-dot cellular automata,” J. Appl. Vol. 85, no. 5, pp. 2977- 2984, 1999. 7. Amalani et al., “Experimental demonstration of a leadless quantum dot cellular automata cell,” Appl. Phys. Lett., vol. 77, no. 5, pp. 738-740, 2000. 8. Vetteth et al., “RAM design using quantum dot cellular automata,” in Nanotechnology Conf., vol. 2, 2003, pp. 160-163. 9. Vetteth et al., “Quantum dot cellular automata carry look ahead adder and barrel shifter,” presented at IEEE Emerging Telecommunications Technologies Conf., 2002. 10. S. Frost, A. F. Rodrigues, A. W. Janiszewski, R. T. Raush, and P. M. Kogge, “Memory in motion: A study of storage structures in QCA,” presented at the 1st Non Silicon Computing Workshop, 2002. 11. D. Berzon and T. J. Fountain, “A memory design in QCA using the SQUARES formalism,” Univ. College, London, U.K., Tech. Rep., 1998. 12. R. Chakrabarty, A. Khan, “Design of a fault free inverter circuit using minimum number of cells and related kink energy calculation in quantum dot cellular automata,” proceeding of 1st International Conference IC3A2013, pp. 369-373, January 2013. 13. Univ. of Calgary ATIPS Lab., QCA Designer. [Online]. Available: http://www.qcadesigner.ca. 14. Orlov et al., “Experiment demonstration of a binary wire for quantum dot cellular automata,” Appl. Phys. Lett., vol. 74, no. 19, pp. 2875-2877, 1997. 15. R. Zhang, K. Wang and G. A. Jullien, “A method of majority logic reduction for quantum cellular automata,” IEEE Trans. Of nanotechnology, vol. 3, no. 4, Dec. 2004. 16. Orlov et al., “Experimental demonstration of clocked single-electron switching in quantum-dot cellular automata,” Appl. Phys. Lett., vol. 77, no. 2, pp. 295-297, 2000. 17. G. Toth, “Correlation and coherence in quantum-dot cellular automata,” Ph.D. dissertation, Dept. of Elect. Eng., Univ. Notre Dame, Notre Dame, IN, 2000. 18. Amlani et al., “Digital logic gate using quantum-dot cellular automata,” Science, vol. 284, pp. 289-291, 1999. 19. M. Crocker, X. Hu, and M. Niemier, “PLAs in quantum-dot cellular automata,” IEEE Trans. Nanotechnol., vol. 7, no. 3, pp. 376-386, May 2008. 20. Threshold logic. Delft Univ. Technol., Delft, The Netherlands. [Online].Available:http://einsteni.et.tudelft.nl/sorin/open/98MSprops8.html 21. Capacitive threshold –logic circuits. Worcester Polytech. Inst., Worcester,MA.[Online].Available:http://turquoise.wpi.edu/ CT/ 22. K. Hennessy and C. S. Lent, “Clocking of molecular quantum-dot cellular automata,” J. Vac. Sci. Technol. B, Microelectron. Process. Phenom., vol. 19, no. 5, pp. 1752–1755, Sep. 2001. 23. R. Chakrabarty, D. Dey , A. Khan, C. Mukherjee, S. Pramanik, “Effect of temprature & kink energy in multilevel, digitial circuit using quantum dot cellular automata”, Proceeding of 5th International Conference CODEC2012, December 2012. 24. S.Srivastava, “Probalistic modeling of quantum dot cellular automata”, Graduate school thesis and dissertations,2007. 25. R. Farazkish, S. Sayedsalehi, K. Navi, “Novel design for quantum dot cellular automata to obtain fault to lerant majority gate”, Journal of Nanotechnology, vol. 12, 2012. Authors: Meenu Chinwan, Harshpreet Kaur Paper Title: Feeding Techniques to Improve Bandwidth of MPA Abstract: The comprehensive study of MPA shows its important role in the modern wireless communication devices. Detailed literature review of past few decades’ papers on MPA, the MPA has emerged into wide range of communication field. Inherently the patch antenna is narrowband; various techniques were developed to enhancement of bandwidth. Different parameter affect the efficiency of antenna .Specification of MPA has low weight, low profile. This is Omni-directional antenna whose fabrication is easy.
Keywords: Patch design, Electromagnetic wave, and radiation, Microstrip, Antenna 36. References: 170-172 1. Ramesh Garg, Prakash Bartia, Inder Bahl, Apisak Ittipiboon, ‘’Microstrip Antenna Design Handbook’’, 2001, pp 1‐68, 253‐316 Artech House Inc. Norwood, MA. 2. Alla I. Abunjaileh, Ian C. Hunter, Andrew H. Kemp,”Multi‐Band Matching Technique for Microstrip Patch Antenna Receivers”, School of electronic and electrical engineering, The University of Leeds” IEEE, EUMC.2007.4405174. 3. Yasir Ahmed, Yang Hao and Clive Parini, “A 31.5 GHZ Patch Antenna Design for Medical Implants”, University of London, International Journal of Antennas & Propagation”, volume 2008, (2008), article ID 167980. 4. S. Satthamsakul, N. Anantrasirichai, C. Benjangkapraset, and T. Wakabayashi, ”Rectangular Patch Antenna with inset feed and modifier ground plane for wide band antennas”, IEEE, Aug, 2008. 5. Richard C. Johnson, Henry Jasik, ‘’Antenna Engineering Handbook’’ Second Edition 1984, pp 7‐1 to 7‐14, McGraw Hill, Inc. NY, USA. 6. Pozar, D. M., ‘’Microstrip Antennas’’, Proc. IEEE, Vol. 80, 1992, pp. 79‐91 Authors: Pakkiraiah Chakali, Madhu Kumar Patnala Paper Title: Design of High Speed Ladner-Fischer Based Carry Select Adder Abstract: In this paper, we propose a high speed Carry Select Adder by replacing Ripple Carry Adders with parallel prefix adders. Adders are the basic building blocks in digital integrated circuit based designs. Ripple Carry Adders (RCA) are usually preferred for addition of two multi-bit numbers as these RCAs offer fast design time among all types of adders. However RCAs are slowest adders as every full adder must wait till the carry is generated from previous full adder. On the other hand, Carry Look Ahead (CLA) adders are faster adders, but they required more area. The Carry Select Adder is a compromise on between the RCA and CLA in term of area and delay. CSLA is designed by using dual RCA: due to this arrangement the area and delay are still concerned factors. It is clear that there is a scope for reducing delay in such an arrangement. In this research, we have implemented CSLA with prefix adders. Prefix adders are tree structure based and are preferred to speed up the binary additions. This work estimates the performance of proposed design in terms of Logic and route delay. The experimental results show that the performance of CSLA with parallel prefix adder is faster and area efficient compared to conventional modified CSLA.
Keywords: prefix adder, CSLA, delay, Carry Operator, area-efficient.
References: 37. 1. B. Ramkumar, Harish M Kittur, “Low –Power and Area-Efficient Carry Select Adder”, IEEE transaction on very large scale integration (VLSI) systems, vol.20, no.2, pp.371-375, Feb 2012. 2. Kuldeep Rawat, Tarek Darwish. and Magdy Bayoumi, “A low power and reduced area Carry Select Adder”, 45th Midwest Symposium 173-176 on Circuits and Systems, vol.1, pp. 467-470,March 2002. 3. O. J. Bedrij, “Carry-Select Adder”, IRE transactions on Electronics Computers, vol.EC-11, pp. 340-346, June1962. 4. Youngjoon Kim and Lee-Sup Kim, “64-bit carry-select adder with reduced area”, Electronics Letters, vol.37, issue 10, pp.614-615, May 2001. 5. Y. Choi, “Parallel Prefix Adder Design,” Proc. 17th IEEE Symposium on Computer Arithmetic, pp 90-98, 27th June 2005. 6. J. M. Rabaey, “Digital Integrated Circuits- A Design Perspective”, New Jersey, Prentice-Hall, 2001.. 7. T.-Y. Chang and M.-J. Hsiao,“Carry-Select Adder using single Ripple-Carry Adder”, Electronics letters, vol.34, pp.2101-2103, October 1998. 8. Youngjoon Kim and Lee-Sup Kim, “A low power carry select adder with reduced area”, IEEE International Symposium on Circuits and Systems, vol.4, pp.218-221, May 2001. 9. Behnam Amelifard, Farzan Fallah and Massoud Pedram, “Closing the gap between Carry Select Adder and Ripple Carry Adder: a new class of low-power high-performance adders”, Sixth International Symposium on Quality of Electronic Design, pp.148-152. April 2005. 10. Akhilesh Tyagi, “A Reduced Area Scheme for Carry-Select Adders”, IEEE International Conference on Computer design, pp.255-258, Sept 1990 11. M. Snir, “Depth-size trade-offs for parallel prefix computation,” in Journal of Algorithms 7, pp.185–201, 1986. 12. Richard P. Brent and H. T. Kung, “A Regular Layout for Parallel Adders”, IEEE transactions on Computers, vol.c-31, pp.260-264, March 1982. 13. Belle W.Y.Wei and Clark D.Thompson, “Area-Time Optimal Adder Design”, IEEE transactions on Computers, vol.39, pp. 666-675, May1990. 14. David Jeff Jackson and Sidney Joel Hannah, “Modelling and Comparison of Adder Designs with Verilog HDL”, 25th South-eastern Symposium on System Theory, pp.406-410, March 1993. 15. R. Ladner and M. Fischer, “Parallel prefix computation,” Journal of ACM. La Jolla, CA, vol.27, no.4, pp. 831-838, October 1980. Authors: Adilakshmi Siliveru, M. Bharathi Paper Title: Design of Ladner-Fischer and Beaumont-Smith Adders Using Degenerate Pass Transistor Logic Abstract: In this paper, we propose Kogge-Stone and Brent-Kung parallel prefix adders based on degenerate pass transistor logic (PTL). Threshold loss problem are the main drawback in most pass transistor logic family. This threshold loss problem can be minimized by using the complementary control signals. These complementary control signals are obtained by 5-Transistor XOR-XNOR module. By using these complementary outputs we designed parallel prefix adders based on 10-Transistor full adder. Parallel prefix adders are used to speed up the binary addition and these adders are more flexible to perform addition of higher order bits in complex circuits. The transistor level implementation of parallel prefix adders based on degenerate PTL gives better performance compared to CPL and DPL pass transistor logic.
Keywords: Power Dissipation, degenerate, complexity, Threshold loss.
38. References: 1. Jin-Fa Lin, Yin-Tsung Hwang and Ming-Hwa Sheu, “Low Power 10-Transistor Full Adder Design Based on Degenerat Pass Transistor 177-181 Logic,” IEEE Trans. VLSI, vol. 13, no. 6, pp. 686–695, Jun. 2012. 2. C.-H. Chang, J. Gu, and M. Zhang, “A review of 0.18-um full adder performances for tree structured arithmetic circuits,” IEEE Trans. VLSI, vol. 13, no. 6, pp. 686–695, Jun. 2005. 3. D. Radhakrishnan, “Low-voltage low-power CMOS full adder,” IEE Proc. Circuits Devices Syst., vol. 148, no. 1, pp. 19–24, Feb.2001. 4. Y. Choi, “Parallel Prefix Adder Design,” Proc. 17th IEEE Symposium on Computer Arithmetic, pp 90-98, 27th June 2005 5. H. T. Bui, Y. Wang, and Y. Jiang, “Design and analysis of low-power 10-transistor full adders using XOR–XNOR gates,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process. vol.49, no. 1, pp. 25–30, Jan. 2002. 6. J.-F. Lin, Y.-T. Hwang, M.-H. Sheu and C.-C. Ho, “A novel high speed and energy efficient 10-transistor full adder design,” IEEE Trans. Circuits Syst. I, vol. 54, no. 5, pp. 1050–1059, May 2007. 7. Y. Jiang, Al-Sheraidah. A, Y. Wang, Sha. E, and J. G. Chung, “A novel multiplexer-based low-power full adder,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process. vol. 51, pp.345–348, July 2004. 8. J. Wang, S. Fang, and W. Feng, “New efficient designs for XOR and XNOR functions on the transistor level,” IEEE J. Solid-State Circuits, vol. 29, pp. 780–786, July 1994. 9. J.-B. Kim, et al., “New circuits for XOR and XNOR circuits,” International Journal of Electronics, vol. 82, pp. 131–143, Feb.1997. 10. K. Taki, A survey for pass-transistor logic technologies — Recent researches and developments and future prospects, Proceedings of the ASP-DAC’98 Asian and South Pacific Design Automation Conference, Feb. 1998, pp. 223–226 11. P. Buch, A. Narayan, A.R. Newton, A. Sangiovanni-Vincentelli, Logic synthesis for large pass transistor circuits, Proceeding of the IEEE International Conference on Computer-Aided Design (ICCAD), November 1997, pp. 633–670. A. Jaekel, S. Bandyopadhyay, G.A. Jullien, Design of dynamic pass transistor logic using 123 decision diagrams, IEEE Trans. on CAS-I: Fundamental Theory and Applications 45 (11) (1998) 1172–1181. 12. K. Yano, Y. Sasaki, K. Rikino, K. Seki, Top–down pass-transistor logic design, IEEE Journal of Solid-State Circuits 31 (6) (1996) 792–803. 13. R. Ladner and M. Fischer, “Parallel prefix computation,” Journal of ACM. La Jolla, CA, vol.27, no.4, pp. 831-838, October 1980. 14. Andrew Beaumont-Smith and Cheng-Chew Lim, “Parallel Prefix Adder Design”, Department of Electrical and Electronic Engineering, the University of Adelaide, 2001.. Authors: Debasis Dwibedy, Laxman Sahoo, Sujoy Dutta Paper Title: A New Approach to Object Based Fuzzy Database Modeling Abstract: The requirements in diversified application domains like Engineering, Scientific technology, Multimedia, Knowledge management in expert systems etc shift the momentum of current trends in designing database models to an innovative concept of Object Based fuzzy Database Model. The ongoing research concentrates on representing the imprecise information by taking object modelling methodology and fuzzy techniques through different levels of class hierarchy and abstractions. Still, a formal definition of fuzzy class is not yet given by which we can represent all standards of fuzzy objects and attributes. In this paper, we redefine the fuzzy class in an efficient manner and propose the structure of the fuzzy class using more effective generalized techniques to develop a new object based fuzzy data model in order to manipulate imprecise information and exposed to wider range of applicability. Also, we define a formal framework for generalized fuzzy constraints which can be applied effectively to fuzzy specialized classes in fuzzy class hierarchy.
Keywords: Fuzzy, Class, Constraints, Generalization, Object Model, Specialization, Fuzzy object Model.
References: 1. Zadeh, L.A. Fuzzy sets. Information and control, 8(3), pp. 338-353, 1965. 2. Zadeh, L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy sets and systems, 1(1), PP. 3-28, 1978 3. Cross, V.Caluwe, R. & Vangyseghem N.A perspective from the fuzzy object data management group (FODMG). In proceedings of the 1997 IEEE International conference on Fuzzy systems, 2, PP. 721-728, 1997. 4. Bordogna, G.,Pasi, G. & Lucarella,D. A Fuzzy Object oriented data model for managing vague and uncertain information. International Journal of Intelligent system,14, PP. 623-651, 1999 5. Zvieli, A. & Chen P.P. Entity relationship modeling and fuzzy databases. In proceeding of the 1986 IEEE International Conference on Data Engineering, PP. 320-327, 1986. 6. Ma, Z.M, Zhang, W.J, MA, W.Y., & Chen, G,Q.Conceptual design of fuzzy object oriented databases using extended entity relation 39. model 16, PP. 697-711, 2001. 7. Marin, N., Vila, M.A. & Pons, O. Fuzzy type: A new concept of type for managing vague structure. International Journal of Intelligent systems, 15, PP. 1061-1085, 2000. 182-186 8. Nahle Ibrahim 2008. Creation of Fuzzy Object Database. KMITL Sci.J vol.8, No.1. 9. Z.M. Ma. Fuzzy Information modeling with UML in advances in fuzzy object oriented database modeling and applications, eds. Z.Ma,Idea group publishing, PP. 153-175, 2004. 10. Sahoo Laxman & Shukla Praveen. Fuzzy Techniques in object based modeling. International Journal on Information Science and computing, Vol.2, No.1, PP. 93-97, 2008. 11. Cross, V., & Firat, A. Fuzzy objects for geographical Information systems. Fuzzy sets and systems, 113, PP. 19-36, 2000. 12. Tre De G. An algebra for querying a constraint defined fuzzy and uncertain object oriented database model. IEEE Transactions on Fuzzy Systems, PP. 2138-2143, 2001. 13. Yazici.A, Koyuncu.M. IFOOD: An Intelligent Fuzzy Object oriented Database Architecture. IEEE Transaction on knowledge and Data mining, Vol.15, No.5, PP. 1137-1154, 2003 14. Ma, Z.M, Zhang, W.J. Extending Object oriented Databases for Fuzzy Information modeling. Information Systems, 29(5), PP. 421-435, 2004. 15. Vladarean Cristina . Extending Object oriented databases for fuzzy Information modeling. ROMAI J., 2, PP. 225-237, 2006. 16. Chen G., Kerre E.E. Extending ER-EER concepts towards Fuzzy conceptual Data modeling. Proceedings of 1998 IEEE International conference on Fuzzy systems, PP. 1320-1325, 1998. 17. Yazici. A, & Bosan-Korpeoglu. An active Fuzzy Object oriented Database approach. IEEE International conference on Fuzzy systems, PP. 885-888, 2004. 18. Ma. Z. Fuzzy Database modeling with XML. Advances in Database Systems, Vol.29, springer 2005. 19. Dubois, D. Prade, H., & Rossazza, J.P. Vagueness, typicality and uncertainty in class hierarchies. International Journal of Intelligent Systems, 6, PP. 167-183, 1991. 20. Cueves L., Marin N., Pons. O., Vila, Ma. Pg4DB: A Fuzzy Object Relational system. Fuzzy Sets and systems, Vol. 159, PP. 1500-1514, 2008. 21. Conred, R., Scheffiner, D.,& Freytag, J.C.. XML conceptual modeling using UML. In proceedings of 9th I nternational conference on conceptual modeling,PP. 558-571, 2000 22. Ma. Z.M, Shen.S. Modeling of Fuzzy information in the IF2O and Object oriented data models. Journal of Intelligent and fuzzy systems, Vol.17, No. 6, PP. 597-612. 2006 23. Marin, N. Medina, J. M., Pons, Sanchez, D., & vila Ma. Complex Object comparison in a Fuzzy context. Information and software Technology, 45(7), PP. 431-444, 2003. Authors: Vijay. G.R, A.Rama Mohan Reddy Paper Title: Data Security in Cloud based on Trusted Computing Environment Abstract: In recent years Cloud Computing has become one of the growing fields in computer science. In which the security problem of cloud computing has become a hot research topic. It must be verified in the trusted 40. status of the platform which actually carries out the computing task in the cloud, and the remote mechanism in Trusted Computing is suited for the cloud user's verification need.This paper briefly sketches out the method to 187-191 build a Trusted Computing Environment for cloud computing system by integrating the Trusted Computing Platform (TCP) with Trusted Platform Module (TPM) into the security of cloud computing system. The RC4 stream cipher algorithm is most used algorithm to provide the confidentiality over the different networks. In this paper we propose the discussion of Simulation Results with its Analysis and the Performance Evaluation with the representation of data and time.
Keywords: Cloud Computing, TCP, TCM, Trusted Computing, RC-4.
References: 1. B.BazeerAhamed, S. Syed Sabir Mohamed, “Implementation of Trusted Computing Technologies in Cloud Computing” International Journal of Research and Reviews in Information Sciences(IJRRIS),Vol. 1, No. 1, March 2011.pp 7-9 2. P radeep Kumar,Vivek Kumar Segal, Durg Singh Chauhan, “Effective Ways of Secure, Private and Trusted Computing”, International Journal of Computer Science Issues (IJCSI), vol8, Issues3,No2,May2011 ,pp412-421. 3. Jason Reid Juan M. González Nieto Ed Dawson, "Privacy and Trusted Computing", Proceedings of the 14th International Workshop on Database and Expert Systems Applications, IEEE, 2003 4. Balakrishnan.S,Saranya.G,Shobana.S,Karthikeyan.S,“Introducing Effective Third Party Auditing (TPA) for Data Storage Security in Cloud”. International Journal of Computer Science and Technology Vol. 2, Issue 2, June 2011,pp398-400. 5. T.W Edgar, S.L Clements“Cryptographic Trust Management Design Document”, U.S. Department of Energy, Pacific Northwest National Laboratory, Vol. 2, Version 1.1, January 2010, pp1.1-17.2. 6. Abhishek Mohta ,Ravi Kant Sahu,Lalit Kumar Awasthi, “ Robust Data Security for Cloud while using Third Party Auditor”, International Journal of Advanced Research in Computer Science and Software Engineering(IJARCSSE), Volume 2, Issue 2, February 2012,pp1-5 7. David A.Fisher “Trust and Trusted Computing Platform” Technical Note, Software Engineering Institute, January 2011. 8. Xiao-Yong Li , Li-Tao Zhou ,Yong Shi and Yu Guo, “A trusted computing environment model in cloud architecture”, International Conference on Machine Learning and Cybernetics (ICMLC), July 2010, Volume 6, pp. 2843-2848 9. Controlling Data in the Cloud: Outsourcing Computation without Outsourcing Control: 10. http://www.parc.com/content/attachments/ControllingDataInTheCloud-CCSW-09.pdf 11. Xuan Zhang Wuwong, N. Hao Li Xuejie Zhang, “Information Security Risk Management Framework for the Cloud Computing Environments” IEEE 10th International Conference Computer and Information Technology (CIT), 2010, pp. 1328 – 1334. Authors: Shakti Bajaj, Ravinder Kumar Bhataia, J. Sandeep Soni Paper Title: Speed Regulation of DC Drive Using Mobile Communication Abstract: The importance of the speed control of DC motors in manufacturing industries like plastic, textile, chemical and pharmaceutical hardly needs any emphasis as it ensures efficient and consistent production. In this paper, the authors present implementation of a hardware circuit which is designed for remote speed control of a DC motor by using Dual Tone Multi Frequency (DTMF) tone of mobile phone. The hardware circuit includes the use of DTMF decoder IC MT8870 and Relay driver IC ULN2003. The mobile keypad keys have been mapped to the speeds of ‘High Speed’, ‘Medium Speed’, ‘Low Speed’ and ‘Stop’ to regulate the speed of DC motor.
Keywords: DC motor, DTMF, IC MT8870, IC ULN2003
41. References: 1. G.K. Dubey, “Fundamentals of Electrical drives”,Narosa Publishing House Pvt. Ltd., 2nd edition, PP:60, 2011, ISBN 978-81- 7319-428-3. 192-195 2. S. M. Bashi, I. Aris and S.H. Hamad, “Development of Single Phase Induction Motor Adjustable Speed Control Using M68HC11E-9 Microcontroller,” Journal of Applied Sciences 5 (2), pp. 249-252. 3. T. Kenjo and A. sugawara, “stepping motors and their Microprocessor controls”, 2nd Edition, Oxford university press, 1994. 4. R.Siwy, "Generation and Recognition of DTMF Signals with the Microcontroller MSP430", Texas Instruments Deutschland GmbH SLAAE16 (October 1997) 5. M.K. Parai, D.Misra, B.Das, “CPLD Based Speed Control Of DC Motor Operated through Cellphone” , International Journal of Soft Computing and Engineering, ISSN: 2231-2307, Volume-2, Issue-4, September 2012. 6. http://www.datasheetcatalog.com/datasheets_pdf/M/T/8/8/MT8870.shtml 7. http://www.datasheetcatalog.com/datasheets_pdf/U/L/N/2/ULN2003. shtml 8. M.R.Chaurasia, N.Naiyar , “Stepper Motor Controller using XC9572 CPLD through Mobile As a Remote” , International Journal of Soft Computing and Engineering, ISSN: 2231-2307, Volume-1, Issue-6, January 2012.S. Khakurel, A. Kumar Ojha , S.Shrestha, R.N. Dhavse “Mobile Controlled Robots for regulating DC motor s and their Domestic Application” International Journal of Scientific and Engineering Reserch, Volume 1, Issue 3, December 2010 1 ISSN 2229-5518. Authors: Akshat Agrawal, Sumit Kumar Yadav Paper Title: Technique for Searching of Similar Code Segments Abstract: In this paper, we will be studying about various artifacts and constructs about many tools to help developer in their task of developing. These tools will try to fulfill the basic need of any developer which is to have similar code segments to help him to reduce his efforts. For this we have various tools available in market. After reading this paper the developer will be able to choose the best suitable code detection tool for his work.
Keywords: Artifacts, Code detection, Code segment, Constructs.
References: 42. 1. Collin McMillan, Mark Grechanik, Denys Poshyvanyk, Chen Fu, Qing Xie, “Exemplar: A Source Code Search Engine For Finding Highly Relevant Applications,” IEEE, 2010. 2. Mu-Woong Lee, Seung-won Hwang, Sunghun Kim, “Integrating Code Search into the Development Session,” IEEE 2011. 196-198 3. L. Jiang, G. Misherghi, Z. Su, and S. Glondu, “DECKARD: Scalable and accurate tree-based detection of code clones,” ICSE, 2007. 4. J. Johnson, “Identifying Redundancy in Source Code Using Fingerprints,” Proceedings of the 1993 Conference of the Centre for Advanced Studies on Collaborative Research, CASCON 1993, pp. 171–183. 5. U. Manber, “Finding Similar Files in a Large File System,” Proceedings of the Winter 1994 Usenix Technical Conference, pp. 1-10. 6. S. Ducasse, M. Rieger and S. Demeyer, “A Language Independent Approach for Detecting Duplicated Code,” Proceedings of the 15th International Conference on Software Maintenance, ICSM 1999, pp. 109-118. 7. B. Baker, “On Finding Duplication and Near-Duplication in Large Software Systems,” Proceedings of the 2nd Working Conference on Reverse Engineering, WCRE 1995, pp. 86-95. 8. T. Kamiya, S. Kusumoto and K. Inoue, “CCFinder: A Multilinguistic Token-Based Code Clone Detection System for Large Scale Source Code,” IEEE Transactions on Software Engineering, 28(7) pp. 654-670. 9. R. Komondoor and S. Horwitz, “Using Slicing to Identify Duplication in Source Code,” Proceedings of the 8th International Symposium on Static Analysis, SAS 2001, pp. 40-56. 10. Simone Livieri, Yoshiki Higo, Makoto Matushita, Katsuro Inoue “Very-Large Scale Code Clone Analysis and Visualization of Open Source Programs Using Distributed CCFinder: D-CCFinder,” in IEEE 2007. Authors: Ajay Sharma, Anand Singh, Manish Khemariya Paper Title: Homer Optimization Based Solar PV; Wind Energy and Diesel Generator Based Hybrid System. Abstract: Through this Paper we are introducing a new Design Idea Of Optimized PV-Solar And Wind Hybrid Energy System , Mobile Base Station Over Conventional Diesel Generator For A Particular Site In village imaliya ( bhanpur) . The aim of this paper to generate electricity and transferring it mobile tower with extra electricity begging transfer to village . For this particular hybrid system ,we are taking the meteorological data of Solar Insolation and hourly wind speed, for village imaliya ( bhanpur) (Longitude 77ο.41’and Latitude 23ο.29’ ) and through the study of pattern of load consumption of mobile base station and we have designed a modeled for optimization of the hybrid energy system using HOMER software. The hybrid energy system is a combination of wind, solar, diesel generation and batteries. Hybrid Optimization Model for Electric Renewable (HOMER) software is used for the analysis of sizing and sensitivity, performed in order to obtain the most feasible configuration of a hybrid renewable energy system.
Keywords: Hybrid system,PV,Wind,DG.HOMER
References: 1. Mohamed El Badawe¹, Tariq Iqbal and George K. I. Mann” Optimization And Modeling Of A Stand-Alone Wind/Pv Hybrd Energy System” 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) 2012 IEEE 2. Shahriar Ahmed Chowdhury1, Shakila Aziz2 “Solar-Diesel Hybrid Energy Model for Base Transceiver Station (BTS) of Mobile Phone Operators” Centre for Energy Research, United International University, Dhaka, Bangladesh. 3. Pragya Nema1, R.K. Nema2, Saroj Rangnekar1” PV-Solar / Wind Hybrid Energy System For GSM/CDMA Type Mobile Telephony Base Station” ISSN 2076-2895 (Print), ISSN 2076-2909 (Online) ©2010 International Energy & Environment Foundation. All rights reserved. 4. Sthitaprajna Rath, S.M Ali, Md. Nadeem Iqbal “ Strategic Approach Of Hybrid Solar-Wind Power For Remote Telecommunication Sites In INDIA” International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012 1 ISSN 2229-5518. 5. Dulal Ch Das, A K Roy, N Sinha, “PSO Based Frequency Controller For Wind- Solar- Diesel Hybrid Energy Generation/Energy 43. Storage System” 978-1-4673-0136-7/11 ©2011 IEEE 6. Agus Yogianto(1), Hendra Budiono(2), Indra A. Aditya(3)”Configuration Hybrid Solar System(Pv), Wind Turbine, And Diesel” @2012 Ieee 199-204 7. E. C. Dos Santos Jr.2, C. B. Jacobina1, M. B. R. Correa1, N. Rocha1” Distributed Generation System Based On Single-Phase Grid, Induction Generator And Solar Photovoltaic Panel” ©2008 IEEE 8. Saeed lahdi Loi Lei Lai, Daniel Nankoo,” Grid Integration Of Wind-Solar Hybrid Renewables Using AC/DC Converters As DG Power Sources” ©2011 IEEE 9. B. Mangu, K. Kiran Kumar and B. G. Fernandes” A Novel Grid Interactive Hybrid Power Supply System For Telecom Application” Indian Institute of Technology Bombay, Powai, Mumbai-400076, India. 10. Kumaravel S. Dr. Ashok S.” Adapted Multilayer Feedforward Ann Based Power Management Control Of Solar Photovoltaic And Wind Integrated Power System” ©2011 IEEE. 11. R.Goutham Govind Rajul M. Vinothkurnar3 N.Kamalakannan .P.Subramaniam “A Hybrid Alternative Energy System with Photovoltaic and Fuel Cell” ©2011 IEEE. 12. Razak, N.A.B.A.; Bin Othman, M.M.; Musirin, I, “Optimal Sizing And Operational Strategy Of Hybrid Renewable Energy System Using Homer”, 4th International Power Engineering And Optimization Conference (PEOCO), 2010, Pp495-501, June 23-24, 2010. 13. Lagorse, J; Giurgea, S; Paire, D; Cirrincione, M; Simoes, M.G ; Miraoui, A; , “Optimal Design Analysis Of A Stand-Alone Photovoltaic Hybrid System”, IEEE Industry Applications Society Annual Meeting, 2008. IAS '08, Pp1-7, Oct 5-9, 2008. 14. Reaz Ul Haque ; M. T. Iqbal ; John E. Quaicoe ; “Sizing, Dynamic Modeling And Power Electronics Of A Hybrid Energy System”, Canadian Conference On Electrical And Computer Engineering, 2006. CCECE '06. , Pp1135-1138, May 2006. 15. Juhari Ab. Razak, Kamaruzzaman Sopian, Yusoff Ali, “Optimization Of Renewable Energy Hybrid System By Minimizing Excess Capacity”, International Journal Of Energy, Vol. 1, 2007. 16. Bajpai, P. ; Kumar, S. ; Kishore, N.K. ; “Sizing Optimization And Analysis Of A Stand-Alone Wtg System Using Hybrid Energy Storage Technologies”, International Conference On Energy And Sustainable Development: Issues And Strategies (Esd 2010), Pp1-6, June 2-4, 2010. 17. Furat Abdal; Rassul Abbas; Mohammed Abdulla Abdulsada; “Simulation Of Wind-Turbine Speed Control By MATLAB”, International Journal Of Computer And Electrical Engineering, Vol. 2, October, 2010 18. Yang HX, Lu L, Burnett J. Weather Data And Probability Analysis Of Hybrid Photovoltaic–Wind Power Generation Systems In Hong Kong. Renew Energy 2003, 28(11), 1813–24. 19. Celik A.N. The System Performance Of Autonomous Photovoltaic–Wind Hybrid Energy Systems Using Synthetically Generated Weather Data. Renewable Energy 2002, 27, 107–121. 20. Shaahid SM, Elhadidy MA. Opportunities For Utilization Of Stand-Alone Hybrid (Photovoltaic+ Diesel+Battery) Power Systems In Hot Climates. Renew Energy 2003, 28 (11), 1741–53. Authors: Mohammed Hammed Yasen Paper Title: Enhanced Control of Power System by Using Smart Grid and Possibility of Applying it in Iraq Abstract: the best control of power system very important for High quality energy. And the smart grid technology so need for Solve more problem about stability in electrical power system. In This paper present one problem in Iraqi electrical system it is unstable problem in electrical power system. And this problem Effected to control of power system and this problem effect to Economic of Iraq because more time happened the total shut 44. Down in Iraqi electrical system. So by using Smart grid will do Enhance to control of power system. And check if can be Applicability the smart grid in Iraq. 205-207
Keywords: Power, Smart grid, systems, control, students conference on engineering and systems (SCES).
References: 1. Eduardo F. Camacho, Tariq Samad, Mario Garcia-Sanz, and Ian Hiskens, “Control for Renewable Energy and Smart Grids,”, January 2011. 2. Sameer Saadoon Mustafa,Iraq,Mahmud Khidr Salman, “Study the Iraqi National Super Grid Power Flow Based,”, 201O 7th International Multi-Conference on Systems, Signals and Devices,pp. 978-983. 3. Iraqi ministry of electricity,” frequency chart daily report”, october 2012. 4. Eng. Adnan Sahen, “ Smart Grid ”, 4NEWHAMAK,Suria, September 2012 5. Richard DeBlasio, “Standards for the Smart Grid” ,IEEE Energy,USA, November, 2008. 6. UCAIug: SG Net SRS, “Smart Grid Networks System Requirements Specification”, RELEASE CANDIDATE 3 REVISION DRAFT, Saturday, December 29, 2012. Authors: K.Venkatraman, J.Vijay Daniel, G.Murugaboopathi Paper Title: Various Attacks in Wireless Sensor Network: Survey Abstract: Today wireless communication technique has become an essential tool in any application that requires communication between one or more sender(s) and multiple receivers. Since multiple users can use this technique simultaneously over a single channel, security has become a huge concern. Even though there are numerous ways to secure a wireless network and protect the network from numerous attacks, providing 100% security and maintaining confidentiality is a huge challenge in recent trends. This journal will present you a survey about the various threats to wireless networks, the various advancements in securing a network and the various challenges in implementing the same.
Keywords: wireless sensor networks, denial of service attacks, Sybil attacks, node replication attack, traffic analysis attack, secure routing protocols, trust management, intrusion detection
45. References: 1. Tamara Bonaci, Linda Bushnell and Radha Poovendran “Node Capture Attacks in Wireless Sensor Networks: A System Theoretic 208-211 Approach” 2. Pitipatana Sarkarindr and Nirwan Ansari, New Jersey Institute of Technology “Security Services In Group Communications Over Wireless Infrastructure, Mobile Ad hoc, and wireless Sensor Networks” 3. Fadi Farhat University of Windsor “Eavesdropping attack over Wi-Fi” 4. Sachin Dev Kanawat and Pankaj Singh Parihar “Attacks in Wireless Networks” IJSSAN 2011 5. Prateek Suraksha Bhushan, Abhishek Pandey, and R.C. Tripathi of IIT Allahabad “A Scheme for Prevention of Flooding Attack in Wireless Sensor Network” ISSN: 2047-0037 (IJRRWSN) 6. Alejandro Proano, Loukas Lazos of University of Arizona, “Selective Jamming Attacks in Wireless Networks” 7. Wazir Zada Khan, Yang Xiang, Mohammed Y Aalsalem, Quratulain Arshad “Comprehensive Study of Selective Forwarding Attack in Wireless Sensor Networks” published on February 2011 in MECS. 8. Yih-Chun Hu, Adrian Perrig and David B. Johnson, Members, IEEE “Wormhole Attacks in Wireless.Networks” 9. Ioannis Krontiris, Thanassis Giannetsos, Tassos Dimitriou “Launching a Sinkhole Attack in .Wireless Sensor.Networks;.t he.Intruder.Side” 10. James Newsome, Elaine Shi, Dawn Song and Adrian Perrig of Carnegie Mellon University “The Sybil Attack in Sensor Networks: Analysis & Defenses” Authors: G. Murugaboopathi, C.Chandravathy, P. Vinoth Kumar Paper Title: Study on Cloud Computing and Security Approaches Abstract: This paper highlights the basic concept of cloud computing and some of the security measures which have been taken into consideration till now. This paper also includes various ways which can be implemented for the betterment of cloud computing. With the recent advancement of technologies cloud computing has become a hotcake on which multiple organizations are working (e.g. Dell, IBM, Sun, Microsoft, Amazon etc.). It is out of reach for most of the organizations and/or individuals to purchase all the required hardware/software resources. So, using the resources available on the cloud one can perform required task by paying the applicable amount. But, always with popularity security issues come into picture and in this case security involves privacy and consistency of user data, durability of systems, protection from hacking and specially protection of contents which are vulnerable to potential threats. So, cloud computing must be launched with a strong security system so, that both service provider and user can be benefited.
46. Keywords: Cloud Computing, Security, Vulnerable, Threats, Resources.
212-215 References: 1. What is Cloud Computing?” at http://www.salesforce.com/ cloudcomputing accessed on 10/ 02/2010 2. “How Cloud Computing Works?” at http://communication.howstuffworks.com/ cloud-computing1.htm accessed on 19/02/2010 3. “Introduction to Cloud Computing architecture”, White Paper 1st Edition, June 2009 at http://www.sun.com/featured- articles/CloudComputing.pdf accessed on 14/02/2010 4. “The new geek chic: Data centers”, June 25, 2008 at http://news.cnet.com/8301-13953_3-9977049-80.html accessed on 14/02/2010 5. “Software as a Service” at http://en.wikipedia.org/ wiki/Software_as_a_service accessed on 16/02/2010 6. “Platform as a Service” at http://en.wikipedia.org/wiki/Platform_as_a_service accessed on 16/02/2010 7. “Infrastructure as a Service” at http://en.wikipedia.org/wiki/Infrastructure_as_a_service accessed on 16/02/2010 8. “Security Authorization - An Approach for Community Cloud Computing Environments” by, Perry Bryden, Daniel C. Kirkpatrick, Farideh Moghadami at http://www.boozallen.com/ media/file/Security-Authorization-An-Approach-for-CCEs.pdf accessed on 16/02/2010 9. “ Controlling Data in the Cloud: Outsourcing Computation without Outsourcing Control”, Richard Chow, Philippe Golle, Markus, Ryusuke Masuoka, Jesus Molina, Elaine Shi, Jessica at http://www2.parc.com/csl/members/eshi/docs/ccsw.pdf accessed on 17/02/2010 10. D. Paul Benjamin, Ranjita Shankar-Iyer, Archana Perumal - “VMSoar: A Cognitive Agent for Network Security” a research paper from Computer Science Department, Pace University. Authors: Naresh Kumar, A. S. Zadgaonkar, Abhinav Shukla Evolving a New Software Development Life Cycle Model SDLC-2013 with Paper Title: 47. Client Satisfaction Abstract: In the era of software development there exist a large number of Models to develop software. Each 216-221 model has its own characteristics, limitations and working environment. According to the requirements, software industry people use different models to develop different software. There are various models but none of them is capable to address the issues of client satisfaction. In this paper we develop a new model (SDLC-2013) for software development that lays special emphasis on client satisfaction and also tries to fulfil the objective of the Software Engineering of developing high quality product within schedule and budget. The new proposed model is designed in such a way that it allows client and developer to interact freely with each other in order to understand and implement requirements in a better way.
Keywords: SDLC, Software Development, SDLC Phases, SDLC-2013 Model, Client Satisfaction
References: 1. K. K. Aggarwal, Yogesh Singh Software Engineering 3rd Edition. 2. Software Development Life Cycle (SDLC) – the five common principles.htm 3. Software Methodologies Advantages & disadvantages of various SDLC models.mht 4. www.shazsoftware.com/software-development-life-cycle.html 5. www.waterfall-model.com/sdlc/ 6. Roger Pressman titled Software Engineering - a practitioner's approach. 7. www.en.wikipedia.org/wiki/Systems_development_life-cycle 8. Analysis and tabular comparison of popular SDLC models, International Journal of Advance in Computer and Information Technology (IJACIT), July 2012, Sema, SonaMalhotra. 9. Comparing various SDLC models and the new proposed model on the basis of available methodology, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), volume 2, April 2012,Vishwas Massey, Prof. K. J Satao. 10. Evolving a new Software Development Life Cycle Model (SDLC) incorporated with release management, International Journal of Engineering and Advanced Technology (IJEAT), volume-I, Aril 2012, Vishwas Massey, Prof. K. J Satao. 11. Comparative analysis of different types of models in Software Development Life Cycle, International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), Volume 2, May 2012, Ms. Shikhamaheshwari, Prof. Dinesh Ch. Jain. Authors: Abdur Rahaman Sardar, J. K. Sing, Subir Kumar Sarkar Fuzzy Logic Based Alternate Routing Scheme for the Minimization of Connection Set up Time and Paper Title: Blocking Rate in WDM Optical Network Abstract: An alternate routing can improve the blocking performance of an optical network by providing multiple possible paths between source and destination nodes. Wavelength conversion can also improve the blocking performance of an optical network by allowing a connection to use different wavelengths along its route. But wavelength conversion scheme is not an economical proposition. We perform simultaneous study of the relationship between traditional alternate routing scheme and fuzzy logic based alternate routing scheme for comparative studies of those two schemes. Connection set up time and blocking rate reduction are the two important parameters of any optical data communication networks. These two parameters are computed in the present work. It is observed that fuzzy logic based alternate routing scheme provides better performance by reducing the connection set up time and blocking rate in optical network. The effect of the variation of number of wavelengths is also studied to see their effects on connection set up time and blocking rate.
Keywords: Alternate routing, connection set up time, blocking rate, Fuzzy Logic, Wavelength Division Multiplexing.
References: 1. S. K. Sarkar, "Optical fibre and fibre optic communication system": S. Chand and Company Ltd. (2003). 2. C. Siva Ram Murthy and Mohan Gurusamy, "WDM Optical Networks Concepts”, Design, and Algorithms" : Prentice-Hall of India Private Limited(2002). 48. 3. M. Jamshidi, N. Vadiee, and T. J. Rose,"Fuzzy Logic and Control: Software and Hardware Applications", PTR Prentice Hall, Englewood Cliffs, New Jersey 07632(1993). 4. Zang Hui, Jue Jason P.,Sahasrabuddhe Laxman, Ramamurthy R. and Mukherjee B., “Dynamic Light path Establishment in Wavelength 222-228 Routed WD Networks”, IEEE Communication Magazine,September 2001. 5. Zang Hui, Sahasrabuddhe L., Jue Jason P., Ramamurthy S. and Mukherjee B., "Connection Management for Wavelength-Routed WDM Network",Global Telecommunication Conference- Globecom '99. 6. Jun Zhou, Xin Yuan,"A Study of Dynamic Routing and Wavelength Assignment with Imprecise Network State Information,", icppw, pp.207, 2002 International Conference on Parallel Processing Workshops (ICPPW'02), 2002 7. Li Ling and Somani Arun K., "Dynamic Wavelength Routing using Congestion andNeighborhood Information", IEEE/ ACM Transactions on Networking, 1063-6692(99), 08252- 7, 779-786. 8. Ramaswami R., Segall A., "Distributed Network Control for Optical Networks", IEEE/ACM Transactions on Networking, Vol. 5, No.6 (1997) 9. Birman Alexander, "Computing Approximate Blocking Probabilities for a class of all Optical Networks", IEEE Journals on selected areas in communications, Vol. 14, No.5, June 1996. 10. Tripathi T. and Kumar N. Sivarajan, "Computing Approximate Blocking Probabilities in Wavelength-Routed All-Optical Networks with Limited Range Wavelength Conversion", IEEE Journals on selected areas in communications, Vol. 18, No. 10, Oct 2000. 11. Chlamtac, A. Ganz and G. Karmi, “Lightpath communications: an approach to high bandwidth WAN’s,” IEEE Transaction on Communications, vol. 40, no. 7, July 1992, pp. 1171-1182. 12. Ramaswami, R., and Sivarajan, K. N., “Routing and Assignment in All-Optical Networks,” IEEE/ACM Transactions on Networking, vol. 3, pp. 489-499, Oct. 1995. 13. R. M. Krishnaswamy, K. N. Sivarajan, “Algorithms for Routing and Wavelength Assignment Based on Solutions of LP Relaxations”, IEEE CommunicationsLetters 5(10), pp. 435-437, 2001. 14. Pan Z., “Genetic Algorithm for Routing and WavelengthAssignment Problem in All optical Networks”, A Technical Report Submitted to the of Electrical and Computer Engineering, University of California, Davis, 2002. 15. Bisbal D., et al., “Dynamic Routing and Wavelength Assignment in Optical Networks by means of Genetics Algorithms”, Photonic Networks Communications, vol. 7, no. 1, pp. 43-58, 2004. Authors: N.Ashokkumar, M.RathinaKumar, M.Yogesh 49. Flexible AC Transmission Devices as a Means for Transmission Line Congestion Management -A Paper Title: Bibliographical Survey Abstract: through this paper we have given a bibliographical survey and general environment that is prevailing among researchers and their ideas in the field of transmission line congestion management. More than 124 published articles and research papers from various sources like transactions, journals and conferences have been analyzed and referred in this bibliography. 229-234
Keywords: Bibliography, Transmission line congestion.
References: Authors: Sukhvir Singh, Rahul Rishi, Gulshan Taneja, Amit Manocha Reliability and Availability Analysis of Database System with Standby Unit Provided by the System Paper Title: Provider Abstract: The present paper deals with the study of a database system having Primary database and hot standby database unit which is provided by the system provider itself. There is an agreement with the system provider that on the failure of the hot standby unit, another similar unit is immediately provided by him. The primary unit is a production unit and synchronized with hot standby unit through online transfer of archive redo logs. Data being saved in the primary unit gets simultaneously stored in the hot standby unit. When the primary database unit fails, the hot standby database unit becomes the production database and primary database unit goes under repair. The system is analyzed by making use of semi-Markov processes and regenerative point technique. Expression for Mean Time to System Failure, Mean Time to Failure of Primary Database Unit and Availability of Primary Unit are obtained. Graphical study has also been done.
Keywords: System Failure, Mean Time to Failure of Primary Database Unit and Availability of Primary Unit are obtained. Graphical study has also been done.
References: 1. Lyu, M. R. (Ed.), Handbook of Software Reliability Engineering, IEEE Computer Society Press, 1996. 2. Denton, A. D. Accurate Software Reliability Estimation, Master of Science Thesis, Colorado State University, Fort Collins, Colorado, Fall 1999. 3. Lyu M. R., Nikora A., and Farr W., “A Systematic and Comprehensive Tool for Software Reliability Modeling and easurement”, in 50. Proceedings of IEEE FTCS-23, Toulouse, France, June 22-24 1993, pp. 648-653. 4. Stark, G., Software reliability tools, in: The Handbook of Software Reliability Engineering, (M. Lyu, Eds.), McGraw- Hill, New York, 1996. 235-237 5. Kanoun, K., Kaaniche, M., Laprie, J. C., and Metge, S., "SoRel: A Tool for Software Reliability Analysis and Evaluation from Statistical Failure Data", in Proceedings of 23rd IEEE International Symposium on Fault-Tolerant Computing, Toulouse, France, June 1993, pp. 654-659. 6. Chen, M. H., Mathur, A. P., and Rego,V. J., “TERSE, A Tool For Evaluating Software Reliability Models”, in proceedings of the Fourth International Symposium on Software Reliability Engineering, Nov. 3-6, Colorado, 1993. pp. 274-283. 7. Gokhale, S. S., Marinos, P. N. and Trivedi, K. S., "Important Milestones in Software Reliability Modeling", in Proceedings of Software Engineering and Knowledge Engineering (SEKE '96), Lake Tahoe, NV, 1996, pp. 345- 352. 8. Hiroyuki Okamura and Tadashi Dohi, “Building Phase-Type Software Reliability Models”, IEEE, 17th International Symposium on Software Reliability Engineering, 2006. 9. R.K. Tuteja, and G.Taneja, “Profit analysis of one server one unit system with partial failure and subject to random inspection”, “Microelectron.Reliab.”,vol 33,pp 319-322.1993. 10. S.M. Gupta,N.K. Jaiswal,L.R. Goel,” Stochastic behavior of a two unit cold standby system with three modes and allowed downtime”,”Microelectron Reliability”vol. 23,pp. 333-336. 11. R.K.Tuteja, G.Taneja, and U.Vashistha, “ Two-dissimilar units system wherein standby unit in working state may stop even without failure”, International Journal of Management and Systems”, vol 17 no1,pp 77-100,2001 12. Khaled, M.E.S. and Mohammed, S.E.S,. “Profit evaluation of two unit cold standby systemwith preventive and random changes in units.”Journal of Mathematics and Statistics. vol 1, pp. 71-77. 2005 13. G.Taneja, V.K.Tyagi, and P. Bhardwaj,. “Profit analysis of a single unit programmable logic controller (PLC)”,” Pure and Applied Mathematika Sciences”, vol. LX no (1-2),pp 55-71,2004 14. G.Taneja, “Reliability and profit analysis of a system with PLC usedas hot standby”. Proc.INCRESE Reliability Engineering Centre, IIT, Kharagpur India, pp: 455-464.,2005(Conference proceedings) 15. B. Parasher, and G.Taneja,. “Reliability and profit evaluation of standby system based on a master-slave concept and two types of repair facilities”. IEEE Trans. Reliabiity., 56: pp.534-539, 2007 Authors: Sukhvir Singh, Rahul Rishi, Gulshan Taneja, Amit Manocha Reliability and Availability Analysis of Database System with Standby Unit Provided by the System Paper Title: Provider Abstract: Optical Character Recognition (OCR) Systems aim to recognize text and bring it to editable form from the given document image, where the input text can be in machine printed, hand written or hand printed form. Many recognition systems have been developed for languages based on various scripts and digits all over the world, taking input in either of the online and offline modes, with considerable efficiencies. These systems have proved to be highly applicable in the fields of Banking, Education, IT systems and Postal Sector for digitization of processes and automated information retrieval. In this paper, we present a survey of techniques for recognition of handwritten 51. and hand printed documents in off-line mode, with an emphasis on the Feature Extraction phase and the corresponding classification technique has also been mentioned with the recognition rates achieved. 238-241
Keywords: Optical Character Recognition, Feature Extraction, Classification .
References: 1. Jayashree R. Prasad, U.V. Kulkarni 2010. “Trends in Handwriting Recognition” IEEE 2010 2. Plamondon and Srihari, “On-line and Off-line Handwriting Recognition-A Comprehensive Survey” IEEE Transactions on Pattern Analysis and Machine Intelligence,Vol 22, No.1, January 2000 3. Ivind Due Trier, Anil K. Jain and Torfinn Taxt , “Feature Extraction Methods for Character Recognition-a Survey”, Pattern Recognition Vol.29, No.4, p.p.641-662 (1996) 4. J. R .Parker, “Vector Templates and Hand printed Digit Recognition”, 1051-4651, IEEE-1994 5. M. Shridhar and A. Badreldin, “A High Accuracy Syntactic Recognition Algorithm for handwritten Numerals”, Proceedings of the IEEE International Conference on Systems , Man and Cybernetics, Vol. SMC-15, No. 1, January/February 1985 6. L. Heutte, T. Paquet, J. Moreau, Y. Lecourtier and C. Olivier, “Combining Structural and Statistical Features for the Recognition of Handwritten Characters”, ICPR, Vol. 19, pp. 629-641, 1998. 7. C.- L. Liu, K. Nakashima, H. Sako and H. Fujisawa, “Handwritten Digit Recognition: Benchmarking of State-of-the-Art”, Pattern Recognition, No. 36, pp. 2271- 2285 , 2003. 8. de S. Britto Jr., et al., “Improvement in handwritten numeral string recognition by slant normalization and contextual information”. Proceedings of the Seventh International Workshop on Frontiers of Handwriting Recognition, Amsterdam, 2000, pp. 323–332. 9. J.T. Favata, G. Srikantan, S.N. Srihari, “Hand printed character/digit recognition using a multiple feature/resolution philosophy”. Proceedings of the Fourth International Workshop on Frontiers of Handwriting Recognition, Taipei, 1994, pp.57–66. 10. J.T. Favata, G. Srikantan, S.N. Srihari, “Hand printed character/digit recognition using a multiple feature/resolution philosophy”, Proceedings of the Fourth International Workshop on Frontiers of Handwriting Recognition, Taipei, 1994, pp.57–66. 11. L. Koerich, “Large Vocabulary Off-line Handwritten Word Recognition”, Ph. D. Thesis, Ecole de Technologie Superieure, Montreal - Canada, 2004. 12. G.Siva Reddy, Puspanjali Sharma, S.R.M Prassana, C.Mahanta , L.N. Sharma, “Combined online and Offline Assamese Numeral Recognizer” /978-1-4673-0816-8/12 IEEE 2012 13. Omid Rashnoodi,Asgher Rashnoodi and Aref Rashnoodi, “Offline Recognition of Handwritten Persian Digits using Statistical Concepts”. International Journal of Computer Applications (0975 – 8887) Volume 53– No.8, September 2012 14. A. Amin and S. Singh, “Machine Recognition of Hand Printed Chinese Characters” Intelligent Data Analysis (1997) 101- 118 15. Ithipian Methasate, Sanparith Marukatat, Sutat Saetang and Thanarak Theeramunkong, “The Feature Combination Technique for Offline Thai Character Recognition System” IEEE, Eighth ICDAR 2005 16. S.Kumar , “Performance Comparison of Features on Devanagari Hand Printed Dataset”, International Journal of Recent Trends in Engineering, Vol.1, No.2 , May 2009 17. S.Kumar, “Study of Features for Handprinted Recognition”, World Academy of Science, Engineering and Technology 60 2011 18. R.Jayadevan, Satish R.Kolhe, Pradeep M. Patil, Umapada Pal. 2011. “Offline Recognition of Devanagari Script-A Survey”, IEEE transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, Vol.41, No.6, November 2011 19. Ashutosh Aggarwal, Rajneesh Rani, RenuDhir, “Handwritten Devanagari Character recognition Using Gradient Features”, IJARCSSE Volume 2, Issue 5, May 2012 20. J. Gilewski , Phil Phillips, S. Yanushkevich, D.Popel, “Education Aspects-Handwriting Recognition using Neural Networks, fuzzy Logic” Pattern recognition and Information processing, vol 1,(1997 )p.p. 39-47. 21. Rafael M.O Cruz,George D.C Cavalcanti, Tsang Ing Ren, “Ensemble Classifier for Offline Cursive Character Recognition Using Multiple Feature Extraction Techniques”.IEEE 22. A.Gupta, M. Srivastava, C.Mahanta.2011, “Offline Handwritten Character Recognition” ICCAIE (2011) Authors: Said EL KAFHALI, Abdelkrim HAQIQ Paper Title: Effect of Mobility and Traffic Models on the Energy Consumption in MANET Routing Protocols Abstract: A Mobile Ad hoc Network (MANET) is a group of mobile nodes that can be set up randomly and formed without the need of any existing network infrastructure or centralized administration. In this network the mobile devices are dependent on battery power, it is important to minimize their energy consumption. Also storage capacity and power are severely limited. In situations such as emergency rescue, military actions, and scientific field missions, energy conservation plays an even more important role which is critical to the success of the tasks performed by the network. Therefore, energy conservation should be considered carefully when designing or evaluating ad hoc routing protocols. In this paper we concentrated on the energy consumption issues of existing routing protocols in MANET under various mobility models and whose connections communicate in a particular traffic model (CBR, Exponential, and Pareto). This paper describes a performance comparison of the AODV, DSR and DSDV routing protocols in term of energy consumed due to packet type (routing/MAC) during transmission and reception of control packets. The mobility models used in this work are Random Waypoint, Manhattan Grid and Reference Point Group. Simulations have been carried out using NS-2 and its associated tools for animation and analysis of results.
Keywords: Energy Consumption, Mobile Ad-hoc Network, Mobility Models, Network Simulator (NS-2), Routing Protocols, , Traffic Models.
52. References: 1. .F. Akyildiz, S.M. Ho, and Y.-B. Lin, “Movement-based location update and selective paging for PCS networks”, Journal of 242-249 IEEE/ACM Transactions on Network, Vol. 4 (4), pp. 629–639, 1996. 2. R. Al-Ani, “Simulation and performance analysis evaluation for variant MANET routing protocols”, International Journal of Advancements in Computing Technology, Volume 3, Number 1, February 2011. 3. Ahmed Al-Maashri and M. Ould-Khaoua, “Performance analysis of MANET routing protocols in the Presence of self-similar traffic”, Proceeding 31st IEEE Conference on Local Computer Networks, pp- 801-807, 2006. 4. Fan Bai, Narayanan Sadagopan, and Ahmed Helmy, “IMPORTANT: A framework to systematically analyze the impact of mobility on performance of routing protocols for ad hoc networks,” in IEEE INFOCOM, 2003. 5. J. Broch, D.B. Johnson and D.A. Maltz, “The dynamic source routing protocol for mobile ad hoc networks”, IETF MANET Working Group, Internet-Draft, October 1999. 6. Tracy Camp, Jeff Boleng, and Vanessa Davies, “A survey of mobility models for ad hoc network research,” in Wireless Communications & Mobile Computing (WCMC): Special issue on Mobile Ad Hoc Networking: Research, Trends and Applications, vol. 2, no. 5, pp. 483-502, 2002. 7. E. P. Charles, and M. R. Elizabeth, “Ad hoc on-demand distance vector routing”, In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, pp. 80–100, IEEE, February 1999. 8. E. P. Charles, and Pravin Bhagwat, “Highly dynamic destination-sequenced distance-vector routing (dsdv) for mobile computers”, SIGCOMM, 1994. 9. S. Corson and J. Macker,“Mobile ad hoc networking (MANET): routing protocol performance issues and evaluation considerations,” RFC 2501, Jan. 1999. 10. B. J. David, and A. M David, “Dynamic Source Routing in ad hoc wireless networks“, chapter 5, pages 153–181. Kluwer Academic Publishers, 1996. 11. Shivendu Dubey and Rajesh Shrivastava, “Energy consumption using traffic models for MANET routing protocols”, International Journal of Smart Sensors and Ad Hoc Networks (IJSSAN) Volume-1, Issue-1, pp. 84-89, 2011. 12. K. Fall and K. Varadhan, (Eds.) “Ns notes and documents”, The VINT Project. UC Berkeley, LBL, USC/ISI, and Xerox PARC, February 25, 2000. 13. S. Gopinath, Dr.A.Rajaram, and N.Suresh Kumar, “Improving minimum energy consumption in ad hoc networks under different scenarios”, International Journal of Advanced And Innovative Research (IJAIR) , pp. 40-46, September 2012. 14. X. Hong, M. Gerla, G. Pei, and C.-C.Chiang, ”A group mobility model for ad hoc wireless networks,” in Proc. Of ACM/IEEEMSWiM’99, Seattle,WA,Aug.1999. 15. Jun-Hoong and Au-Yong, “Comparison of on demand mobile ad hoc network routing protocols under ON/OFF source traffic effect”, Proc. of IASTED International Conference, Chiang Mai, Thailand, March 29-31, 2006. 16. Ejiro. E.Igbesoko, Thaddeus Onyinye Eze, and Mona Ghassemian, ”Performance analysis of MANET routing protocols over different mobility models”, In proceedings of London Communications Symposium (LCS), University College London, Sepember 2010. 17. T. Issariyakul and E. Hossain, “Introduction to Network Simulator - NS2”, ISBN: 978-0-387-71760-9, Springer, 2008. 18. D.B. Johnson and D.A. Maltz, “Dynamic source routing in ad hoc wireless networks”, chapter 5, pp. 153–181, Mobile Computing (Kluwer Academic, 1996). 19. Ashish Kumar, M. Q. Rafiq, and Kamal Bansal, “Performance evaluation of energy consumption in MANET”, International Journal of Computer Applications (975 – 8887), Volume 42– No.2, pp. 7-12, March 2012. 20. M.S. Murty and M.V. Das,“Performance evalution of MANET routing protocols using reference point group mobility and random waypoint models”, International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC), Vol.2, No.1, March 2011. 21. Dhiraj Nitnaware and Ajay Verma, “Performance evaluation of energy consumption of reactive protocols under self-similar traffic”, International Journal of Computer Science & Communication, Vol. 1, No. 1, pp. 67-71, January-June 2010. 22. C. Perkins and P. Bhagwat, “A mobile networking system based on internet protocol,” IEEE Pers. Commun. Mag., vol. 1, no. 1, pp. 32–41, Febreary 1994. 23. Youssef SAADI, Said EL KAFHALI, Abdelkrim HAQIQ and Bouchaib NASSEREDDINE, “Simulation analysis of routing protocols using manhattan grid mobility model in MANET”, International Journal of Computer Applications (IJCA) (0975 – 8887), Volume 45– No.23, pp. 24-30, May 2012. 24. Shailendra Singh Raghuwanshi and Brajesh Patel, “Identification of energy consumption packets in MANET routing protocols under CBR and exponential traffic models”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (3) ,4171-4175, 2012. 25. S. Suganya and S. Palaniammal, “A dynamic approach to optimize energy consumption in mobile ad hoc network”, European Journal of Scientific Research ISSN 1450-216X Vol. 85 No 2, pp. 225- 232, September, 2012. 26. Nor Surayati Mohamad Usop, Azizol Abdullah and Ahmad Faisal Amri Abidin,” Performance evaluation of AODV, DSDV & DSR routing protocol in grid environment”, IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.7, July 2009. 27. VALENTINA TIMCENKO, MIRJANA STOJANOVIC and SLAVICA BOSTJANCIC RAKAS, “MANET routing protocols vs. mobility models: performance analysis and comparison”, Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09), pp. 271-276, Moscow, Russia, August 20-22, 2009. 28. S. Umang, B.V.R. Reddy& M.N. Hoda , “Enhanced intrusion detection system for malicious node detection in ad hoc routing protocols using minimal energy consumption”, IET Commun., Vol. 4, Iss. 17, pp. 2084–2094, November 2010. 29. Christian de Waal and Michael Gerharz, “BonnMotion: a mobility scenario generation and analysis tool,” Communication Systems group, Institute of Computer Science IV, University of Bonn, Germany. 2003. Authors: Akansha Rao, Vijay Trivedi, Vineet Richaria Paper Title: Mobile Positioning System Using a Mathematical Approach Abstract: In this era of advanced communication, there are large number of location and positioning based applications which are introduced and implemented practically and theoretically. In this paper, a design and implementation of new location measurement technology is being proposed by which this parameter could easily be estimated. This proposed system is based on trigonometric theory, projectile path estimation and iterative error correction methodology. After implementation, a comparative study is being provided for justification of the results, with distance weighted method being taken as bench mark, based on previous location estimation technique. The results analysis of both these systems is being provided.
Keywords: AOA, TOA, Regression, Comparative Study, Mathematical Approach.
References: 1. Mobile Positioning Using Wireless Networks, 1053-5888/05/ $20.00©2005 IEEE, IEEE SIGNAL PROCESSING MAGAZINE [41] JULY 2005 2. HYBRID TOA/AOA SCHEMES FOR MOBILE LOCATION IN CELLULAR COMMUNICATION SYSTEMS, International Journal of Ad hoc, Sensor & Ubiquitous Computing( IJASUC ) Vol.1, No.2, June 2010. 3. Network-Based Wireless Location, IEEE SIGNAL PROCESSING MAGAZINE [24] JULY 2005 1053-5888/05/$20.00 © 2005 IEEE 53. 4. Localization Algorithms in Wireless Sensor Networks: Current Approaches and Future Challenges, Network Protocols and Algorithms ISSN 1943-3581 2010, Vol. 2, No. 1 5. Issues and Challenges of Wireless Sensor Networks Localization in Emerging Applications, 978-0-7695-4647-6/12 $26.00 © 2012 250-254 IEEE, DOI 10.1109/ICCSEE.2012.44 6. Towards Accurate Mobile Sensor Network Localization in Noisy Environments, IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. X, NO. X, JANUARY 2010 7. A Multi-Technology Indoor Positioning Service to Enable New Location-aware Applications, Pierpaolo Loreti University of Rome Tor Vergata Electric Engeneering Dept. Rome , Italy Email: [email protected] 8. Gaussian Process Regression for Sensor Networks Under Localization Uncertainty, IEEE TRANSACTIONS ON SIGNAL PROCESSING (VOL. 61, NO. 2), (JANUARY 15, 2013) 9. P. Bahl, and V. N. Padmanabhan, “Radar: An in-building RF-based user location and tracking system,” In Proc. IEEE Infocom 2000, (vol. 2, pp. 775-84). 10. T. He, et al., “Range-free localization schemes for large scale sensor networks,” MobiCom ’03, ACM Press, 2003, pp. 81-95. 11. C. J. Ancker, “Airborne direction nding - theory of navigation errors,” IRE Transactions on Aeronautical and Navigational Electronics, 1958, pp. 199-210. 12. POSSIBILITIES AND FUNDAMENTAL LIMITATIONS OF POSITIONING USING WIRELESS COMMUNICATION NETWORKS MEASUREMENTS, Fredrik Gustafsson∗ and Fredrik Gunnarsson, Department of Electrical Engineering Link¨oping University, SE-581 83 13. A Framework for Indoor Geo-location using an Intelligent System Chahé Nerguizian, Charles Despins and Sofiène Affes, INRS-Télé communications Chahé Nerguizian, 3rd WLAN Workshop 2001 14. A Novel Single Base Station Location Technique for Microcellular Wireless Networks: Description and Validation by a Deterministic Propagation Model, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 53, NO. 5, SEPTEMBER 2004 15. Localization via Ultra Wide band Radios, IEEE SIGNAL PROCESSING MAGAZINE, 70 JULY 2005 1053-5888/05/$20.00©2005 IEEE 16. Error Modeling and Estimation Fusion for Indoor Localization, 2012 IEEE International Conference on Multimedia and Expo, 978-0- 7695-4711-4/12 $26.00 © 2012 IEEE DOI 10.1109/ICME.2012.106 Authors: D Mary, Shinosh Mathew, Sreejith K Paper Title: Modelling and Simulation of Grid Connected Wind Energy System Abstract: Modeling and simulation of a grid connected wind-driven electricity generation system has been done. The power conversion unit features a wind-turbine-driven PMSG, a diode rectifier, and a dc/ac inverter. The Permanent Magnet Synchronous Generator (PMSG) offers better performance than other generators because of its higher efficiency and of less maintenance since they don’t have rotor current and can be used without a gearbox, which also implies a reduction of the weight of the nacelle and a reduction of costs. Therefore, in this paper the modeling and control of a PMSG is presented. All the components of the wind turbine and the grid-side converter are developed and implemented in MATLAB/Simulink.
Keywords: Modeling, PMSG, Wind Turbine, Inverter, SVPWM, PLL.
References: 1. S. Venkatraj and G. Mohan, “Modeling of Wind Farms with Variable Speed Direct Driven Permanent Magnet Synchronous Generator Wind Turbine” International Journal of Research and Reviews in Electrical and Computer Engineering (IJRRECE), Vol 1, No 3, pp 982- 990, September 2011 2. Alejandro Rolan', Alvaro Luna, Gerardo Vazquez, Daniel Aguilar, “Modeling of a Variable Speed Wind Turbine with a Permanent 54. Magnet Synchronous Generator” IEEE International Symposium on Industrial Electronics (ISlE 2009,) July 5-8, 2009, pp 734 – 739 3. K. Vinoth Kumar, Prawin Angel Michael, Joseph P. John and Dr. S. Suresh Kumar “ Simulation and Comparison of SPWM and SVPWM Control for three phase inverter” ARPN Journal of Engineering and Applied Sciences, Vol. 5, No. 7, July 2010, pp 61 – 74 255-259 4. D. Sandhya Rani , A.Appaprao, “A Space Vector PWM Scheme for Three level Inverters Based on Two-Level Space Vector PWM” International Journal Of Power System Operation and Energy Management (IJPSOEM) Volume-1, Issue-1, 2011, pp 6 – 10 5. Aryuanto Soetedjo, Abraham Lomi, Widodo Puji Mulayanto, “Modeling of Wind Energy System with MPPT Control” International Conference on Electrical Engineering and Informatics, 17-19 July 2011, E4 6. P.Tripura, Y.S.Kishore Babu, Y.R.Tagor, “Space Vector Pulse Width Modulation Schemes for Two-Level Voltage Source Inverter” ACEEE Int. J. on Control System and Instrumentation, Vol. 02, No. 03, October 2011 pp 34 – 38 7. C. N. Bhende, S. Mishra, Siva Ganesh Malla, “Permanent Magnet Synchronous Generator-Based Standalone Wind Energy Supply System” IEEE Transactions On Sustainable Energy, Vol. 2, No. 4, October 2011, pp 361 – 373 8. Chalasani Hari Krishna, J. Amarnath, and S Kamakshiah, “ A Simplified SVPWM Algorithm for Multilevel Inverter Fed DTC of Induction Motor Drive” International Journal of Engineering and Innovative Technology (IJEIT, Volume 1, Issue 4, April 2012, pp 61 – 67 9. C.O. Omeje; D.B. Nnadi; and C.I. Odeh, “ Comparative Study of Space Vector Pulse – Width Modulation and Third Harmonic Injected Modulation on Industrial Drives” The Pacific journal of Science and Technology, Volume 13, No 1, May2012, pp 12 - 19 10. Sachin Khajuria, Jaspreet Kaur, “ Implementation of pitch Control of Wind Turbine Using Simulink (MATLAB)”, International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, Issue 4, June 2012, pp 196 – 200 11. Manoj Kumar Nigam, Ankit Dubey, “Design and Implementation of SVPWM Inverter using Soft Computing” International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 7, September – 2012, pp 1 – 5 12. Preeti Soni, Kavita Burse, “Analysis of Voltage Source Inverters Using Space Vector PWM for Induction Motor Drive” IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), Volume 2, Issue 6 (Sep-Oct. 2012), PP 14-19. Authors: Debarshi Datta, Partha Mitra, Avisek Sen Paper Title: Low Power Configuration Logic Block Design Using Asynchronous Static Abstract: Low power Configuration Logic Block (CLB) for FPGA is highly desirable in VLSI circuit and system. The CLB is the main block of any FPGA architecture. Each CLB block consists of three static LUT’s for implementing NCL logic function. 27 fundamental NCL logic gates are implemented in each LUT. The proposed CLB has 10 inputs and 3 different outputs, each with resettable and inverting variations. There are two operating modes in each CLB, Configuration mode and Operation mode. The NCL FPGA logic element is simulated at the transistor level using 130nm TSMC CMOS process technology.
Keywords: Configuration Logic Block (CLB), Field Programmable Gate Array (FPGA), Look Up Table (LUT), NULL Conventional Logic (NCL).
References: 1. Indira P. Dugganapally, Waleed K. Al-Assadi, Tejaswini Tammina and Scott Smith, “Design and Implementation of FPGA 55. Configuration Logic Block Using Asynchronous Static NCL,” IEEE Region 5 Conference, pp. 1-6, 2008. 2. S. C. Smith, “Design of Logic Element for implementing an Asynchronous FPGA,” IEEE Transaction on VLSI Systems, Vol. 15/6, 260-263 June 2007. 3. S. Hauck, S. Burns, G. Borriello and C. Ebeling, “ An FPGA for Implementing Asynchronous Circuits,” IEEE Design & Test of Computer, Vol. 11, No. 3, pp 60-69, 1994. 4. R. E. Payne, “Self-Timed FPGA Systems,” 5th International Workshop on Field Programmable Logic and Applications, pp. 21-35, 1995. 5. C. Traver, R. B. Reese and M. A. Thornton, “Cell Designs for Self-Timed FPGAs,” 14th Annual IEEE International ASIC/SOC Conference, pp. 175-179, 2001. 6. J. Teifel, R. Manohar, “ An Asynchronous Dataflow FPGA Architecture,” IEEE Transactions on Computers, Vol. 53, No. 11, pp. 21-24, 2002. 7. C. G. Wong, A. J. Martin, and P. Thomas, “An Architecture for Asynchronous FPGAs,” IEEE International Conference on Field Programmable Technology, pp. 170-177, 2003. 8. K. Meekins, D. Ferguson, M. Basta, “Delay Insensitive NCL Reconfigurable Logic,” IEEE Aerospace Conference, Vol. 4, pp. 1961- 1966, 2002. 9. D. H. Linder and J. H. Harden, “Phased logic: supporting the synchronous design paradigm with delay-insensitive circuitry,” IEEE Transaction on Computers, Vol. 45/9, pp. 1031-1044, 1996. 10. Synopsys Design Compiler 2007 User Guide. 56. Authors: Ansuman DiptiSankar Das, Abhishek Mankar, N Prasad, K. K. Mahapatra, Ayas Kanta Swain Paper Title: Efficient VLSI Architectures of Split-Radix FFT using New Distributed Arithmetic Abstract: Fast Fourier transform (FFT) has become ubiquitous in many engineering applications. Efficient algorithms are being designed to improve the architecture of FFT. Among the different proposed algorithms, split- radix FFT has shown considerable improvement in terms of reducing hardware complexity of the architecture compared to radix-2 and radix-4 FFT algorithms. New distributed arithmetic (NEDA) is one of the most used techniques in implementing multiplier-less architectures of many digital systems. This paper proposes efficient multiplier-less VLSI architectures of split-radix FFT algorithm using NEDA. As the architecture does not contain any multiplier block, reduction in terms of power, speed, and area can greatly be observed. One of the proposed architectures is designed by considering all the inputs at a time and the other is designed by considering 4 inputs at a time, the total number of inputs in both cases being 32. The proposed designs are designed using both FPGA as well as ASIC design flows. 180nm process technology is used for ASIC implementation. The results show the improvements of proposed designs compared to other architectures.
Keywords: Split-radix, FFT, VLSI, NEDA, multiplier-less, FPGA, ASIC.
References: 1. P. Duhamel and M. Vetterli, “Fast Fourier Transforms: A Tutorial Review and A State of The Art,” IEEE Signal Processing Society, vol. 4, no. 19, 1990, pp. 259 – 299. 2. Y.-W. Lin, H.-Y. Liu, and C.-Y. Lee, “A 1-GS/s FFT/IFFT processor for UWB applications,” IEEE Journal of Solid-State Circuits, vol. 40, no. 8, Aug. 2005, pp. 1726 – 1735. 3. S.-N. Tang, J.-W. Tsai, and T.-Y. Chang, “A 2.4-GS/s FFT Processor for OFDM-Based WPAN Applications,” IEEE Trans. Circuits Syst. II: Exp. Briefs, vol. 57, no. 6, Jun. 2010, pp. 451 – 455. 4. John G. Proakis, Dimitris G. Manolakis, “Digital Signal Processing: Principles, Algorithms, and Applications”, Prentice- Hall, 1998. 264-271 5. Z. Ismail, N. H. Ramli, Z. Ibrahim, T. A. Majid, G. Sundaraj, and W. H. W. Badaruzzaman, “Design Wind Speeds using Fast Fourier Transform: A Case Study,” Computational Intelligence in Control, Idea Group Publishing, 2012, ch. XVII. 6. Robert Frey, “The FFT Analyzer in Mechanical Engineering Education,” Sound and Vibration: Instrumentation Reference Issue, Feb. 1999, pp. 1 – 3. 7. James W. Cooley and John W. Tukey, “An Algorithm for Machine Calculation of Complex Fourier Series,” Mathematics of Computation, vol. 19, 1965, pp. 297 – 301. 8. Mario Garrido, J. Grajal, M. A. Sánchez, and Oscar Gustafsson, “Pipelined Radix-2k Feedforward FFT Architectures,” IEEE Trans. VLSI Syst., vol. 21, no. 1, Jan. 2013, pp. 23 – 32. 9. Y. Chen, Y. Tsao, Y. Wei, C. Lin, and C. Lee, “An indexed- scaling pipelined FFT processor for OFDM-based WPAN applications,” IEEE Trans. Circuits Syst. II: Exp. Briefs, vol. 55, no. 2, Feb. 2008, pp. 146–150. 10. M. Shin and H. Lee, “A high-speed four-parallel radix-24 FFT processor for UWB applications,” Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), 2008, pp. 960–963. 11. F. Arguello and E. Zapata, “Constant geometry split-radix algorithms,” Journal of VLSI Signal Processing, 1995. 12. Steven G. Johnson and Matteo Frigo, “A Modified Split-Radix FFT with Fewer Arithmetic Operations,” IEEE Trans. Signal Processing, vol. 55, no. 1, Jan. 2007, pp. 111 – 119. 13. Stanley A. White, “Applications of Distributed Arithmetic to Digital Signal Processing: A Tutorial Review,” IEEE ASSP Magazine, vol. 6, no. 3, Jul. 1989, pp. 4 – 19. 14. Wendi Pan, Ahmed Shams, and Magdy A. Bayoumi, “NEDA: A NEw Distributed Arithmetic Architecture and its Application to One Dimensional Discrete Cosine Transform,” Proc. IEEE Workshop on Signal Processing Syst., Oct. 1999, pp. 159 – 168. 15. Keshab K. Parhi, “VLSI Digital Signal Processing Systems: Design and Implementation”, Wiley, 1999. 16. P. Duhamel and H. Hollmann, “Split-radix FFT algorithm,” Electron. Lett., vol. 20, no. 1, Jan. 1984, pp. 14 – 16. 17. P. Duhamel, “Implementation of split-radix FFT algorithms for complex, real, and real-symmetric data,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-34, Apr. 1986, pp. 285 – 295. 18. Cynthia Watanabe, Carlos Silva, and Joel Muñoz, “Implementation of Split-Radix Fast Fourier Transform on FPGA,” Proc. Programmable Logic Conference, vol. 6, Mar. 2010, pp. 167 – 170. Authors: Saruti Gupta, Geetanjali Wassson Performance of BER for BPSK and DPSK (Coherent and Non-Coherent) Modulation in Turbo- Paper Title: Coded OFDM with Channel Equalization Abstract: With the increasing demand of wireless communication, there will be growing need of design of high- speed wireless communication system. But gross frequency selective fading of wireless channel is a problem difficult to solve in design of system. Orthogonal frequency division multiplexing (OFDM) is quite effective to eliminate frequency selective fading of wireless channel, and is a simple and effective technique, so OFDM has been one of the most important techniques for high-speed wireless communication system. Then, the influence of cyclic prefix and adaptive channel equalization on the system performance is analyzed in various fading channel. However in fading environments the bit error rate (BER) increases. The performance can be improved by using some kind of channel coding. This form of OFDM is called coded-OFDM (COFDM). The turbo coding also allows achieving the Shannon’s bound Performance. In this paper we will design the OFDM system with channel 57. Equalization under the powerful concatenated turbo codes to it. This will help to maintain the system performance under a desired bit error rate, as there were errors occurring in burst form which eventually degrades the efficiency 272-278 of the system .This paper deals with the optimization to analyze the comparative study of BER for the BPSK and DPSK (coherent and non-coherent) modulation scheme to achieve higher data speed and less probability of error for robust and reliable communication under our proposed system model.
Keywords: OFDM, cyclic prefix, AWGN, Rayleigh, equalization,turbo encoder,turbo decoder,BPSK,DPSK,BER,
References: 1. Sklar B. Rayleigh fading channels in Mobile digital communication systems Part II: Mitigation, IEEE communication Magazine, 1997, vol.35(9):148-155. 2. Arun Agarwal, S. K. Patra, Senior Member IEEE ―Performance prediction of OFDM based Digital Audio Broadcasting system using Channel protection mechanisms‖ in IEEE journal © 2011. 3. M.X. Chang and Y.T. Su, “Performance Analysis of Equalized OFDM Systems in Rayleigh Fading”, in IEEE Transactions Wireless Communication, vol.I, No. 4, Oct. 2002,pp. 721–732. 4. Jin Goog Kim,Tae Joon and Jong Tae Lim,, ―Channel estimation for OFDM over Fast Rayleigh Fading Channels,‖ Proceedings of world Academy of science and technology, vol. 21, pp. 455-458, Jan. 2007. 5. Zhengdao Wang,”OFDM or single carrier block transmission,” IEEE Trans. On comm., vol. 52, no. 3, pp.380-394, mar-2004. 6. Z.Wang and G. B. Giannakis, ―Wireless multicarrier communications, IEEE Signal Processing Mag., pp. 29–48, May 2000. 7. L. J. Cimini, Jr., “Analysis and simulation of a digital mobile channel using orthogonal frequency division multiplexing,” IEEE Trans. Commun., vol. COM-33, no. 7, pp. 665–675, Jul. 1985. 8. Armour S., A. Nix, D. Bull, Pre-FFT equalizer design for OFDM, Electronics Letters, vol. 35, Apr. 1999, pp. 539-540. 9. Iliev G., N. Kasabov, Channel equalization using adaptive filtering with averaging, Proc. 5th Joint Conference on Information Sciences, vol. 2, Atlantic City, USA, Mar. 2000, pp. 870-873. 10. Y.-S. Choi, P. J. Voltz, and F. A. Cassara, “On channel estimation and detection for multicarrier signals in fast and selective Rayleigh fading channels,” IEEE Trans. Commun., vol. 49, no. 8, pp. 1375–1387, Aug. 2001. 11. C. Berrou, A. Glavieux, and P. Thitimajshima, ―Near Shannon Limit Error-Correcting Coding: Turbo Codes‖, Proceedings of the IEEE International Conference on Communications, ICC ‘93, Geneva., pp. 1064-1070, May 1993. 12. Hanjong Kim,‖ Performance improvement of Block Turbo Coded OFDM System Using channel state information‖ the 23rd international conference on circuits/systems, computers and communications (ITC-CSCC 2008). 13. W. J. Blackert, E. K. Hall, and S. G. Wilson, “Turbo Code Termination and Interleaver Conditions”, IEE Electronics Letters, vol. 31, no. 24, pp.2082–2084, Nov 1995. 14. C. Berrou and A. Giavieux, " Near optimum error correcting coding and decoding: Turbo-codes," IEEE Trans. Commun., vol 44, no. 10,Oct, 1996: 126 1- 127 1 15. M. K. Gupta, Vishwas Sharma ―To improve BER of turbo coded OFDM channel over noisy channel‖ in Journal of Theoretical and Applied Information Technology © 2005 - 2009 JATIT. 16. Yu Tang, Xiao-lan Lv “Research on the modulation and demodulation of BPSK and BDPSK simulator based on Matlab”Pg no -1239 - 1241 ,IEEE transactions ,2011. 17. Joshi, Alok and Saini, Davinder S, "COFDM performance in various Multipath fading environment ", in proceedings of IEEE International Conference (ICCAE 2010) ,vol.3, pp 127-131,Singapore, Feb 26-28 ,2010. Authors: Kumar Karan Gupta, Aditya Sharma, Parth Raj Singh, A K Malik Optimal Ordering Policy for Stock-Dependent Demand Inventory Model with Non-Instantaneous Paper Title: Deteriorating Items Abstract: In this paper we have discussed optimal ordering policy for inventory model with non-instantaneous deteriorating items and stock-dependent demand. Here shortage is not allowed. The necessary and sufficient conditions of the existence and uniqueness of the optimal solution have been shown. Sensitivity analysis of the optimal solution with respect to major parameters is carried out. A numerical example is presented to demonstrate the developed model and the solution procedure.
Keywords: Non-instantaneous deterioration, Inventory, purchasing cost, Sales revenue cost, Stock-dependent demand.
References: 1. Gupta, R., Vrat, P., 1986. Inventory model with multi-items under constraint systems for stock dependent consumption rate. Operations 58. Research 24, 41–42. 2. Baker, R.C., Urban, T.L., 1988. A deterministic inventory system with an inventory-level-dependent demand rate. Journal of the Operational Research Society 39, 823–831. 279-281 3. Mandal, B.N., Phaujdar, S., 1989. An inventory model for deteriorating items and stock-dependent consumption rate. Journal of the Operational Research Society 40, 483–488. 4. Pal, S., Goswami, A., Chaudhuri, K.S., 1993. A deterministic inventory model for deteriorating items with stock-dependent demand rate. International Journal of Production Economics 32, 291–299. 5. Giri, B.C., Pal, S., Goswami, A., Chaudhuri, K.S., 1996. An inventory model for deteriorating items with stock-dependent demand rate. European Journal of Operational Research 95, 604–610. 6. Ray, J., Goswami, A., Chaudhuri, K.S., 1998. On an inventory model with two levels of storage and stock-dependent demand rate. International Journal of Systems Science 29, 249–254. 7. Soni H, Shah NH (2008). Optimal ordering policy for stock-dependent demand under progressive payment scheme. European Journal of Operational Research 184:91–10. 8. Chun-Tao Chang, Jinn-Tsair Teng, Suresh Kumar Goyal (2010). Optimal replenishment policies for non-instantaneous deteriorating items with stock-dependent demand, International Journal of Production Economics, Volume 123, 62–68. 9. Sana, S.S., (2012). An EOQ model for perishable item with stock-dependent demand and price discount rate. American Journal of Mathematical and Management Sciences. Authors: Saurabh A. Bobde, S.D. Kshirsagar Improving The Sink Roll Life In Galvalume Using Material AT101 & The various Thermal-Spray Paper Title: Coating on SS3l6L Roll Surface Abstract: Galvalume is a Continuous Galvanizing Line. In Galvalume the Zn-Al coating is done on the CR sheets to inprove their corrosion resistance and to improve their life. JSW Ispat Steel Ltd. Kalmeshwar has to frequently replace the sink roll assembly used in Zn-Al tank of the Galvalume.The mean time between replacements is very less as compared to expected mean time between failures (expected MTBF). This is due to deposition of zinc dross on the surface of roller. This result in uneven or improper Zn-Al coating on sheet surface. To avoid this sink roll has to replace. The frequent replacement of roller assembly results in Stoppage of production, material loss, 59. start-up loss and increased cost of production. This paper proposes an alternative material to extend the life of sink roll and the thermal-spray coating of various materials on traditionally used sink roll of SS316L roll surface. 282-286
Keywords: CR sheets, Galvalume, MTBF, Sink roll, SS316L, start-up loss, Zinc dross.
References: 1. Patent on Method of Manufacturing Hot-dip Galvanized sheet by Sang-Heon Kim,Yeong-Sool Jin. 2. Zinc-Pot Maintenance Services “Tungsten carbide/cobalt roll Coatings” by SMS MILLCRAFT Grou 3. Paper on “ Progress In Development of Galvanizing Bath Management Tools “ by N.Y. Tang, M. Dubosis, F.E. Goodwin.. 4. Paper on “ Utilizing Pumps To Remove Zinc Dross From Inside The Inlet Snout “ by Gregory C. Becherer 5. Reasearch paper on “Improving the efficiency of galvanizing plant with optimizing Techniques” by Dilip Joshi,Richard Jige. 6. Sink role manufacturing by Yentai Chintiago Alloy Steel Pvt. Ltd. 7. Performance of Submerged Hardware in Continuous Galvanizing by N.Y. Tang, Daniel Liu, Keith Zhang. 8. “Dross formation mechanism on Stainless steel hardware in a Zinc- 55 Al bath” by Ashok Varadrajan,Bruce Kang and Mark Bright. 9. Liquid Metal Corrosion of 316L in Molten Zn-Al Baths by Vinod Sikka 10. Patent on “Material formulation for galvanizing equipement submerged in molten Aluminum and Aluminum/Zinc bath melts” 11. “Investigating Galvanneal Reactions on pot hardware material” by Mark Bright. 12. Loth, J., “Zinc Pot Bearing Design Modification for Increased Life”, Galvatech 2004 Conference Proceedings, Chicago, IL, pp. 657-666 13. Yao M.X., Wu.J.B.C., Liu.R., “Microstructural characteristics and corrosion resistance in molten Zn-Al bath of Co-Mo-Cr-Si alloys”, Materials Science and Engineering A 407 (2005) 299-305. 14. Liu, X., Barbero, E., Sikka, V., “Corrosion of Several Alloys in Industry 15. Dipping Baths”, Galvatech 2004 Conference Proceedings, Chicago, IL,pp.629-636 16. Essentials in Hot-Dip Galvanizing by Jason Fargotti 17. Hemrick, J.G., J. Xu, K. Peters, X. Liu, and E. Barbero. “Wetting and ReactionCharacteristics of Al2O3/SiC Composite Refractories By Molten Aluminum and Aluminum Alloy”, International Journal of Applied Ceramic Technologies 4 (2007): 514-523. 18. K. Chang, G. Psaros, J.J. Brinsky, R.L. Nester, R. Carter, V. Sikka, "New Material Research and Life Improvement for Pot Hardware in Continuous Hot-Dipping Processes," Steel Industry of the Future. 19. Rabinowicz, Ernest, Friction and Wear of Materials, John Wiley & Sons, Inc., New York, 1995, pgs 239-250. 20. El-Madg, M.A. Shaker, R. Hechor, A.E. Nasser, Mechanical Behavior of Stellite 6 Produced by Powder. Metallurgicaly Process, 6th Int. Conf. On Mechanical Design and Production (mpd-6). Cairo, Egypt. 1996. 21. Machine Design: A CAD Approach, Andrew D. DiMarogonas, John Wiley and Sons,Inc., 2001 22. Use of Stabilizer Rolls for Strip Flatness While Wiping, Michel DuBois,1998Galvanizer’s Association Proceedings, October 1998 23. Reactions of Various Materials with a Galvanizing Bath, K. Zhang & N.-Y. Tang, 2003 Galvanizer’s Association Proceedings, October 2003 24. Durability of Bath Hardware Materials in Continuous Galvanizing, M.S. Brunnock, et. al., 1996 Galvanizer’s Association Proceedings, October 1996 25. Empirical Wear Rate Modeling of Zinc Pot Bearing Materials Using the WVU Small-Scale Tester, J. M. Snider II and J. L.Loth, 6th International Conference on Zinc and Zinc Alloy Coated Sheet Steels, April 2004 Authors: Meriem Amoura, Noureddine Zeraibi Thermal Study of Viscoelastic Material between Two Rotating Concentric Annuli: Application at Paper Title: Drilling Process Abstract: This article presents a numerical investigation of the thermal convection for a viscoelastic material in the annular space between two coaxial rotating cylinders. The problem is considered when the inner cylinder rotates about the common axis with constant angular velocity and the outer cylinder at the rest. The horizontal endplates are assumed adiabatic. The Carreau stress-strain constitutive equation was adopted to model the rheological material characteristics. The governing equations are numerically solved by a time-marching finite element algorithm. It is employed to compute numerical solution through a semi-implicit Taylor-Galerkin / pressure-correction scheme, based on a fractional-step formulation. The effect of rheological parameters on the heat transfer and on the flow is analysed. The results of natural, forced and mixed convections are presented and discussed.
60. Keywords: Drilling process, Numerical simulation, Rotating concentric cyloinders, Thermal study, Viscoelastic material. 287-289 References: 1. R. B. Bird, R. C. Amstrong, O.Hassager, Dynamics of Polymeric Liquids, Volume 1, Wiley, New York 1987. 2. J.R.Ivrine, J.Karni, Non Newtonian fluid flow and heat transfer. In: Kakaç, S., Shah, R.K., Aung, W. (Eds), Handbook of Single-phase Convective Heat Transfer. Wiley, N°20, 1987, pp. 1. 3. S.D.Joshi, A.E. Bergels,. Journal of Heat Transfer. N°102, 1980, pp. 397. 4. V.Sirocco, R.Devienne, M.Lebouché, International Journal of Heat and Mass Transfer. N°28, 1985, pp. 91-99. 5. E.Longatte, Z.Bendjeddou, M.Souli, Journal of Fluids and Structures, N°18, Vol.5, 2003, pp.513-528. 6. E.Longatte, Z.Bendjeddou, M Souli., Journal of Pressure Vessel and Technology N°125, 2003, pp. 411-417. 7. M. Amoura, N.Zeraibi, A.Smati, M.Gareche, International communication in heat and mass transfer N°33, 2006, pp. 780-789. 8. H.Moghadam, E.Aung, Numerical Heat Transfer; Part A: Applications N°18, Vol. 33, 1998, pp. 357- 370. 9. N.Zeraibi, M.Amoura, A.Smati, M.Gareche, International Communication in Heat and Mass Transfet. N°34 , 2007, pp.740. 10. M Soares., M.F.Naccache, P.R. Souza Mendes, Proc. 7th Brazilian Cong. Thermal Sciences, N°, 1998; pp. 1146-1151. 11. D.Ding, P.Townsend, M.F. Webster, Journal of non-Newtonian Fluid Mechanics, N°47, 1993, pp. 239-265. 12. G.De Vahl Davis, International Journal for Numerical Methods in Fluids, N°3 , 1983, pp. 249-264. Authors: P.Sreenivasulu, K.Srinivasa Rao, J.I.R Prakash, A.Vinaya babu Paper Title: Power Optimization Technique for Pulsed Latches Abstract: In this paper, we implement a design technique for registers used in pulsed latches in order to make leakage current low thus reducing standby power consumption. This is made by considering short or long timing path and launching or capturing register. In this work each register trades clock-to-Q delay maintaining the same timing constraints, setup time and hold time maintaining clock-to-Q delay constant for reducing the leakage current by developing three different dual threshold voltage registers. The overall reduction in the leakage current of a 61. register can exceed 90% while maintaining the clock frequency and other design parameters such as area and dynamic power the same. This work presents an elegant methodology using pulsed latch instead of flip-flop without 290-295 altering the existing design style. It reduces the dynamic power of the clock network, which can consume half of a chip's dynamic power. Real designs have shown approximately a 20 percent reduction in dynamic power using the below methodology. Three ISCAS 89 benchmark circuits are utilized to evaluate the methodology, demonstrating, on average, 23% reduction in the overall leakage current. The overall reduction in leakage current is compared for each case in different technologies. Predictive device models are used for each technology. The analysis is performed using H-SPICE.
Keywords: leakage current; low leakage register design; power consumption; static power.
References: 1. Pavlidis, V.F.; Friedman, E.G. Three-Dimensional Integrated Circuit Design; Morgan Kaufmann: Boston, MA, USA, 2009. 2. Tai, K.L. System-in-Package (SIP): Challenges and Opportunities. In Proceedings of the ASP-DAC 2000, Asia and South Pacific, Yokohama, Japan, 25–28 January 2000; pp. 191–196. 3. Konstadinidis, G.K.; Tremblay, M.; Chaudhry, S.; Rashid, M.; Lai, P.F.; Otaguro, Y.; Orginos, Y.;Parampalli, S.; Steigerwald, M.; Gundala, S.; et al. Implementation of a Third-Generation 16-Core 32-Thread Chip-Multithreading SPARC Processor. In Proceedings of the IEEE International Solid-State Circuits Conference, Lille, France, 30 December 2008; pp. 84–85. 4. Rusu, S.; Tam, S.; Muljono, H.; Stinson, J.; Ayers, D.; Chang, J.; Varada, R.; Ratta, M.;Kottapalli, S.; Vora, S.; A 45 nm 8-Core Enterprise Xeon Processor. In Proceedings of the IEEE International Solid-State Circuits Conference, Taipei, Taiwan, 22 December 2009; pp. 56–57. 5. Ferre, A.; Figueras, J. Characterization of Leakage Power in CMOS Technologies. In Proceedings of the Electronics, Circuits and Systems, 1998 IEEE International Conference, Lisboa, Portugal,7–10 September 1998; pp. 185–188. 6. Taur, Y.; Wann, C.H.; Frank, D.J. 25 nm CMOS Design Considerations. In Proceedings of the Electron Devices Meeting, 1998, IEDM ’98 Technical Digest., International, San Francisco, CA,USA, 6–9 December 1998; pp. 789–792. 7. Kursun, V.; Friedman, E.G. Multi-Voltage CMOS Circuit Design; John Wiley & Sons: Hoboken,NJ, USA, 2006. 8. Jiao, H.; Kursun, V. Low-leakage and compact registers with easy-sleep mode. J. Low Power Electron. 2010, 6, 1–17. 9. Salman, E.; Dasdan, A.; Taraporevala, F.; Kucukcakar, K.; Friedman, E.G. Exploiting setup-hold time interdependence in static timing analysis. IEEE Trans. Comput.-Aid. Des. Integr. Circuits Syst. 2007, 26, 1114–1125. 10. Stojanovic, V.; Oklobdzija, V.G. Comparative analysis of master-slave latches and flip-flops for high-performance and low-power systems. IEEE J. Solid-State Circuits 1999, 34, 536–548. 11. Weste, N.; Harris, D. CMOS VLSI Design; Addison Wesley: White Plains, NY, USA, 2004. 12. Predictive Technology Model (PTM). Available online: http://www.eas.asu.edu/˜ptm (accessed on 1 September 2010). 13. Cao, Y.; Sato, T.; Orshansky, M.; Sylvester, D.; Hu, C. New Paradigm of Predictive MOSFET and Interconnect Modeling for Early Circuit Design. In Proceedings of the IEEE Custom Integrated Circuits Conference, Orlando, FL, USA, 21–24 May 2000; pp. 201–204. 14. Brglez, F.; Bryan, D.; Kozminski, K. Combinational Profiles of Sequential Benchmark Circuits.In Proceedings of the IEEE International Symposium on Circuits and Systems, Portland, OR, USA,8–11 May 1989; pp. 1929–1934. 15. Homepage of H-SPICETM. Available online:http://www.synopsys.com (accessed on 1 September, 2010). Authors: Supriya Dadabhau Tambe, Nikhil Gorksh Pawar, Mahadev Sudhakar Garad, Sagar Ravindra Patil Paper Title: Unite Clinic: Connecting Clinics Online Abstract: This system is designed to improve clinical workflow, and perform advanced appointment scheduling. This application shows how clinics and patient are connected online through web based application. In today’s life no one has time to visit clinic and wait for appointment. This application will help for getting online appointment. Patient can get appointment through SMS or Internet.Receptionist will manage all the appointment. Doctor can make his schedule according to patient’s appointment. Patient can see online how many people are waiting for appointment. Doctor will upload all the patient medical history on website. This information is visible to only that patient and to the visiting Doctors. Thus privacy is maintained. As patient and clinic are connected online if patient goes from one clinic to another clinic, visited clinics doctor can see medical history of that patient and personal information of patient. It is waiting room solution. All this services provided to users at free of cost.
62. Keywords: Alert Notification, Appointment scheduling, Database management, Online Appointment, Report Generation, Secure private information, Unique ID. 296-299
References: 1. Bo Hang, “Web based long-distance appointment registered system,” CCTAE, 2010 International Conference, vol. 3, Page(s): 232 – 235. 2. Lu, K.M.; Hamid, S.H.A., “Conceptual Design of Web-Based Appointment Management System using Object WebML,” ISITAE '07, Page(s): 354 – 359. 3. Marinos, S.; Nikolopoulos, P.; Pavlopoulos, S., “A WEB-based patient record and appointment management system,” BMES/EMBS Conference, 1999, Vol. 2. 4. Wijewickrama, A. “Simulation analysis of appointment scheduling in an outpatient department of internal medicine,” Simulation Conference, Dec. 2005. 5. Hung, K.; Yuan-Ting Zhang “Implementation of a WAP-based telemedicine system for patient monitoring,” Information Technology in Biomedicine, Vol.7 , Issue: 2, 2003 , Page(s): 101 – 107. 6. Marinos, S ,“A WEB-based patient record and appointment management system Assessment of user satisfaction with an Internet-based integrated patient education system for diabetes management,” Engineering in Medicine and Biology, 1999 ,vol.2. Authors: Barun K. Pandhwal, Devendra S. Chaudhari Paper Title: An Overview of Digital Watermarking Techniques Abstract: One of the biggest technological events of the last two decades was the invasion of digital media in an entire range of everyday life aspects. Digital data can be stored efficiently with a very high quality and it can be manipulated very easily using computers. Furthermore, digital data can be transmitted in a fast and inexpensive way through data communication networks without losing quality. Digital media offer several distinct advantages over analog media. The quality of digital audio, images and video signals are better than that of their analog 63. counterparts. Editing is easy because one can access the exact discrete locations that need to be changed. Copying is simple with no loss of information and a copy of a digital media is identical to the original. With digital 300-304 multimedia distribution over World Wide Web, Intellectual Property Rights (IPRs) are more threatened than ever due to the possibility of unlimited copying. This problem can be handled by hiding some ownership data into the multimedia data, which can be extracted later to prove the ownership, a concept called watermarking. Continuous efforts are being made to device an efficient watermarking scheme and this paper conducts a literature survey of digital watermarking within an image. It describes the early work carried out on digital watermarks, including the brief analysis of various watermarking schemes and its potential applications.
Keywords: Digital watermarking, Least significant bit, Discrete Cosine Transform, Discrete Wavelet Transform
References: 1. Y. Wang, J. Doherty and R.Van Dyck, “A Wavelet-Based Watermarking Algorithm for Ownership Verification of Digital Images,” IEEE Trans. Image processing, vol. 11, no. 2, 2002, pp.77-88. 2. M. Hsieh, D. Tseng and Y. Huang, “Hiding Digital Watermarks Using Multiresolution Wavelet Transform,” IEEE Trans. Industrial Electronics, vol. 48, no. 5, 2001, pp.875-882. 3. B. Gunjal and R. Manthalkar, “ An Overview Of Transform Domain Robust Digital Image Watermarking Algorithms,” Journal of Emerging Trends in Computing and Information Sciences vol. 2, no. 1, 2011, pp.37-42. 4. C. Lin and Y. Ching, “A Robust Image Hiding Method Using Wavelet Technique,” Journal of Information Science and Engineering, vol. 22, 2006, pp.163-174. 5. R. van Schyndel, A. Tirkel, and C. Osborne, “A digital watermark,” Proc. IEEE Int. Conf. Image Processing, vol. 2, 1994, pp. 86–90. 6. W. Bender, D. Gruhl, N. Morimoto, A. Lu, “Techniques for data hiding,” IBM Systems Journal, vol. 35, nos. 3,4, 1996, pp.313-336. 7. F. Hartung and M.Kutter, “Multimedia watermarking techniques,” Proc. IEEE, vol. 87, 1999, pp. 1079–1107. 8. B. Kaur, A. Kaur, J. Singh, “Steganographic Approach For Hiding Image In Dct Domain,” International Journal Of Advances In Engineering & Technology, Vol. 1,Issue 3, 2011, pp.72-78. 9. Cox, J. Kilian, F. Leighton, and T. Shamoon, “Secure Spread Spectrum Watermarking For Multimedia,” IEEE Trans. Image Processing, vol. 6, 1997, pp. 1673–1687. 10. X. Xia, C. Boncelet, and G. Arce, “A Multiresolution Watermark For Digital Images,” in Proc. IEEE Int. Conf. Image Processing, vol. 1, 1997, pp. 548–551. 11. M. Barni, F. Bartolini, and A. Piva, “Improved Wavelet-Based Watermarking Through Pixel-Wise Masking,” IEEE Trans. Image processing, vol. 10, no. 5, 2002, pp.783-791. 12. D. Kundur and D. Hatzinakos, “A robust digital image watermarking method using wavelet-based fusion,” Proc. IEEE Int. Conf. Image Processing, vol. 1, 1997, pp. 544–547. 13. G. Bhatnagar and B. Raman, “A New Robust Reference Watermarking Scheme Based on DWT-SVD,” Computer Standards and Interfaces, vol.31, no.5, 2009, pp. 1002-1013. 14. S. Wang and Y. Lin, “Wavelet Tree Quantization for Copyright Protection Watermarking,” IEEE Trans. Image processing, vol. 13, no. 2, 2004, pp.154-165. 15. K. Ramani, E. V. Prasad, Dr. S. Varadarajan, “Steganography Using Bpcs To The Integer Wavelet Transformed Image,” International Journal of Computer Science and Network Security, vol.7 no.7, 2007, pp. 293-302. 16. Haj and A. Errub, “Performance Optimization of Discrete Wavelets Transform Based Image Watermarking Using Genetic Algorithms,” Journal of Computer Science, vol.4, no.10, 2008, pp.834-841. 17. Singh and A. Mishra, “Wavelet Based Watermarking On Digital Image,” Indian Journal of Computer Science and Engineering Vol 1 No 2, 2011, pp. 86-91. 18. L. Feng, L. Zheng and P. Cao, “A DWT-DCT Based Blind Watermarking Algorithm for Copyright Protection,” Proc. IEEE Int. Conf. Computer Science and information tech., vol.7, 2010, pp.455-458. Authors: Dattatray S. Waghole, Vivek S. Deshpande Paper Title: Reducing Delay Data Dissemination Using Mobile Sink in Wireless Sensor Networks Abstract: Wireless Sensor Networks (WSNs) is a collection of sensor nodes, which is spread in environmental area. These sensor nodes sense the data, information, Temperature and environmental changes from environmental area. Later it will be provide sensing information to the Sink node. In Wireless Sensor Networks hop by hop and Multi-hop communication is done. A data packet is send to the sink node via hop to hop or Multi-hop communication. Important Parameters like congestion, energy, Average End-to-End Delay consider at the time of data packets communication from one node to sink node. Many times due to congestion above mention parameters Average End-to-End Delay will be increased and energy also loss at the instance of communication. Initial aim of this paper is reduce average End-to-End Delay using Movable Mobile Sink in uniform Random Wireless Sensor Network. Energy Consumption and Traffic control also other important parameters consider at the time of analysis. Movable mobile sink node reduces Average End-to -End Delay drastically when mobile Sink node moves from left side to Right side Direction. Mobile Sink is also moving different Direction so Mobile sinks collect the data moving through different direction. So, delay is reducing drastically for data packets collection from the networks. In this paper there solve energy consumption, congestion and Average End-to –End Delay problem for collection of data packets in the network.
64. Keywords: Average End-to-End Delay, Movable Mobile Sink. Energy Consumption, Wireless Sensor Networks (WSNs), Data Dissemination. 305-308 References: 1. -Wan kim Jeong-Sik In, Kyeong Hur, Jin-Woo and Doo-Sleep Eom”, An Intelligent Agent-based Routing Structure for Mobile Sink in WSNs”, IEEE, Transaction on Consumer Electronics, VOL.56, No.4, pp. 2310-2316, November 2010. 2. Arun K. Kumar and Krishna M. Sivalingam”, Energy-Efficient Mobile Data Collection in Wireless Sensor Network with Delay reducing using Wireless Communication”, IEEE Communication Systems and Networks, 2010. 3. Elyes Ben Hamida and Guillaume Chelius”, A Line-based Data Dissemination protocol for Wireless Sensor Networks with Mobile Sink”, IEEE International Conference on Communication-ICC, pp.2201-2205, 2008. 4. Elyes Ben Hamida and Guillaume Chelius”, Strategies for Data Dissemination to Mobile Sinks in Wireless Sensor Networks”, IEEE Wireless Communication Magazine, VOL.15, No.6, pp.31-37, February 2008. 5. Oscar F.Gonzalez, Michael Howarth, George Pavlou”, An Algorithm to Detect Packet Forwarding Misbehaviour in Mobile Ad-hoc Networks”, 10 Th IEEE International symposium, pp.813-816, 2007. 6. E.Ekici, Y.Gu and D.Bozdag”, Mobility-based communication in wireless sensor networks”, IEEE Communications Magazine, vol.44, no.7, pp.56-62, July 2006. 7. Q.Wu,N.Rao,J.Barhen,S.lynger,V.Vaishnavi,H.QiandK.Chakrabatry”, On computing mobile agent routes for data fusion in distributed sensor networks”, IEEE Transaction on knowledge and Data Engineering,vol.16,no.6,pp.740-753, june 2004. 8. S.Kim, T.Abdelzaher and W.H. Kwon”, Minimum Energy asynchronous Dissemination to Mobile sinks in Wireless sensor Networks”, ACM Sensys, Los Angeles, CA, pp.193-204, November 2003. 9. W.Wang, V.Srinivasan, and K.C.Chua”, Using mobile relays to prolong the lifetime of wireless sensor networks”, In Mobicom, International Conference on Mobile computing and Networking. New York, NY, USA: ACM press, pp.270-283, 2005. 10. H.Yang, j.Shu, X.Meng and S.Lu”, SCAN: self-organized network-layer security in mobile ad hoc network”, IEEE journal on Selected Areas in Communication, vol.24, No.2, pp.261-273, February 2006. Authors: Devika Joshi, Rutuja Kulkarni, Arundhati Rao, Pooja Wagh, Roma Kudale Paper Title: Amigos: Social Networking with Advertisement Management Abstract: With the vast growth of Internet use nowadays, business advertising has enjoyed a more advanced phase. There is a wider selection for media, advertising cost and market range. The challenge is to find which one to focus on. Among the many options, social networking site has turned out to be one of the most promising media today. Keeping this motive Amigos offers completely redesigned advertisement management algorithm which takes advantage of the profile data and hence targets advertisement directly to user according to his interests. Amigos covers most of the essential aspects of social network including editable profiles, messages, groups , events , status updates , uploading photos. Although that is true , the social network does have some unique features of its own like segregation of personal and professional information and displaying the UI accordingly. It would help people willing to join a single networking site and yet be able to control the two fronts of their lives separately. The advertising module looks over the space management of ads and displays them according to user preferences. Not only that, it also gives the advertiser different options to choose from fixed spaces for frequently accessed pages or real time bidding for inner pages .Thus using Social networking the advertising industry can target masses and lead 65. the advertisers to build long term success in the performance advertising industry. 309-313 Keywords: Not only that, it also gives the advertiser different options to choose from fixed spaces for frequently accessed pages or real time bidding for inner pages
References: 1. Gavin Bell , “Building Social Web Applications Establishing Community at the Heart of Your Site , O'Reilly Media,,” September 2009 2. Boyd, D. M., & Ellison, N. (2007) One history of social networking sites. Retrieved December 16, 2007, from http://yasns.pbwiki.com/ 3. O'Reilly, T. (2004). What Is Web 2.0. Retrieved on 30 May, 2007 from 4. http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web 20.html 5. White, T.; Chu, W.; Salehi-Abari, A.; “Media Monitoring Using Social Networks,” Social Computing (SocialCom), 2010 IEEE Second International Conference on, vol., no., pp.661-668, 20-22 Aug. 2010 doi: 10.1109/ SocialCom.2010.102 6. Java servlet programming : HeadFirst 7. Backstrom, L., Huttenlocher, D., Kleinberg, J., & Lan, X. (2006). Groupformation in large social networks: Membership, growth, and evolution. 8. The Facebook Advertising website. [Online]. 9. Available: https://www.facebook.com/advertising 10. Yahoo Adspecs [Online]. Available: https://in.adspecs.yahoo.com /index.php Authors: Prasad R. Pande, Prashant L. Paikrao, Devendra S. Chaudhari Paper Title: Digital ANFIS Model Design Abstract: Neuro-Fuzzy systems are hybrid intelligent systems which combine features of both paradigms- fuzzy logic and artificial neural networks. Adaptive Neuro Fuzzy Inference System (ANFIS) is one of such architecture which is widely used as solution for various real world problems. This paper describes development of an ANFIS model for FPGA implementation. Model can be realized with hardware descriptive language thus making it reusable, reconfigurable and independent of applications. This digital ANFIS firmware can be proven to be optimal solution in terms of cost, speed of operation and flexibility in design methodology.
Keywords: ANFIS, Digital System, FPGA, HDL, Neuro-Fuzzy System
References: 1. Sulaiman N., Obaid Z. A., Marhaban M. H. and Hamidon M. N., “ FPGA- Based Fuzzy Logic: Design and Applications – a Review”, 66. IACSIT International Journal of Engineering and Technology, Vol.1, No. 5, pp 491-503, 2009. 2. Echanobe J., Campo I. D., Bosque G., “An adaptive neuro-fuzzy system for efficient implementations”, International Journals on Information Sciences, pp. 2150–2162, 2008. 314-318 3. Aldair A., Wang W., “FPGA Based Adaptive Neuro Fuzzy Inference Controller For Full Vehicle Nonlinear Active Suspension Systems”, International Journal of Artificial Intelligence & Applications (IJAIA), Vol.1, No.4, pp 1-15, 2010. 4. Nauck D., “Neuro Fuzzy Systems: Review and Prospects”, European Congress Intelligent Techniques and Soft Computing (EUFIT’97), pp. 1044–1053, 1997 5. Campo I. D., Echanobe J., Bosque G., Tarela J. M., “Efficient Hardware/Software Implementation of an Adaptive Neuro-Fuzzy System” , IEEE Transactions on Fuzzy Systems, Vol. 16, No. 3, pp.761-778, 2008. 6. Abraham A., Adaption of Fuzzy Inference System Using Neural Learning, Nedjah N., Mourelle L. M. (Eds.), Fuzzy Systems Engineering: Theory and Practice, Volume 181, Springer-Verlag Berlin Heidelberg, New York, USA, 53-83, 2005. 7. Jang J. S. R., Sun C.T., “Neuro-fuzzy modeling and control”, Proceedings of the IEEE, Vol. 83, No.3, pp 378-406, 1995. 8. Jang J. S. R., “ANFIS: Adaptive-network-based fuzzy inference systems”, IEEE Trans. on Systems, Man, and Cybernetics, Vol. 23, No. 3, pp 665-685, 1993. 9. Saldana H.J.B., Cardenas C.S., “Design and implementation of an adaptive neuro fuzzy inference system on an FPGA used for nonlinear function generation”, IEEE ANDESCON, pp. 1-5, 2010. 10. Saldana H.J.B., Cardenas C.S., “A digital architecture for a three input one output zero-order ANFIS”, IEEE Third Latin American Symposium on Circuits and Systems (LASCAS), pp. 1-4, 2012. Authors: Gayatri Bhatti, Upma Goyal, Prabhdeep Singh Paper Title: A Meliorated Defense Mechanism for Flooding Based Attacks Abstract: The Distributed Denial of service (DDoS) attacks, over a past few years are found to be a disaster 67. to the Internet. A flooding-based attack attacks the victim machine by sending an excessive amount of illegitimate traffic to it. The defence mechanisms existing before are unable to prevent the systems from these attacks, since it is 319-323 very difficult to trace the spoofed packets and distinguished between the legitimate and illegitimate attack traffic. Flooding-based DDoS attacks use agents to send the traffic and sometimes prefer Reflectors in order to forward the traffic to the target, thereby making it impossible to be detected. So, this paper will propose a defence mechanism pronounced as Hop-based DDoS defence procedure. This mechanism will comprise of three components: detection of illegitimate packets, IP traceback of the illegitimate packets and the traffic control. This framework shows high performance in defending against the flooding-based attacks.
Keywords: DDoS, Defence, Flooding, Hop, Traffic.
References: 1. C. Douligeris and A. Mitrokotsa, “DDoS attacks and defense mechanisms: Classification and state-of-the-art,” Computer Networks: the Int. J. Computer and Telecommunications Networking, Vol. 44, No. 5, April 2004, pp. 643–666. 2. J. Mirkovic, S. Dietrich, D. Dittrich, and P. Reiher, “Internet Denial of Service: Attack and Defense Mechanisms,” Prentice Hall PTR, December 2004. 3. R. K. C. Chang, “Defending against Flooding-Based Distributed Denial-of-Service Attacks: A Tutorial,” IEEE Communications Magazine, pp. 42-51, October 2002. J. Jung, B. Krishnamurthy, and M. Rabinovich, “Flash crowds and denial of service attacks: 4. Characterization and implications for cdns and web sites,” in Proceedings of the International World Wide Web Conference, May 2002, pp. 252–262. 5. G. Carl, G. Kesidis, R. Brooks, and S. Rai, “Denial-of-service attack detection techniques," IEEE Internet Computing, Vol. 10, No. 1, January 2006, pp. 82-89. 6. J. Jiang and S. Papavassiliou, “Detecting network attacks in the internet via statistical network traffic normality prediction," Journal of Network and System Management, Vol. 12, No. 1, 2004, pp. 51-72. 7. S. Tanachaiwiwat and K. Hwang, “Differential packet filtering against DDoS flood attacks,” ACM Conference on Computer and Communications Security (CCS), Washington, DC, October 2003. 8. C. Douligeris and A. Mitrokotsa, “DDoS attacks and defense mechanisms: Classification and state-of-the-art,” Computer Networks: the Int. J. Computer and Telecommunications Networking, Vol. 44, No. 5, pp. 643–666, April 2004. 9. M. Robinson, J. Mirkovic, M. Schnaider, S Michel, and P. Reiher, “Challenges and principles of DDoS defense,” SIGCOMM 2003. 10. B. Bencsath and I. Vajda, “Protection against DDoS attacks based on traffic level measurements,” Western Simulation MultiConference, San Diego, California, USA, January 2004. 11. N. Noureldien, “Protecting web servers from DoS/DDoS flooding attacks: a technical overview,” International Conference on Web- Management for International Organisations. Geneva, October 2002. 12. G.Bhatti, R.Singh and P.Singh, “A look back at Issues in the layers of TCP/IP Model,” International Journal of Enhanced Research in Management & Computer Applications, Vol. 1, Issue 2, November 2012. 13. Y. He, T. Liu, and Q. 14. T. Peng, C. Leckie, and K. Ramamohanarao, “Survey of Network-Based Defense Mechanisms Countering the DoS and DDoS Problems,” ACM Computing Surveys 39. 15. K. Hoffman, D. Zage, and C. Nita-Rotaru, “A survey of attack and defense techniques for reputation systems,” ACM Computing Survey 42, 2010. 16. R. Mahajan, S. Floyd, and D. Wetherall, “Controlling high- bandwidth flows at the congested router," in Proceedings of ACM 9th International Conference on Network Protocols (ICNP), 2001, pp. 192-201. 17. Yaar, A. Perrig, and D. Song, “FIT: fast internet traceback," in Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 2005, pp. 1395-1406. 18. S. Lee, H. Kim, J. Na, and J. Jang, “Abnormal traffic detection and its implementation," Advanced Communication Technology, Vol. 1, February 2005, pp. 246-250 Authors: Rashid Hussain, JL Sahgal, Anshulgangwar, Md.Riyaj Paper Title: Control of Irrigation Automatically By Using Wireless Sensor Network Abstract: In the field of agriculture the most important part is: firstly, to get the information about the fertility of soil and secondly moisture content of soil. After measuring these two factors a farmer can start sowing of seeds. In this paper we are giving the brief outline about different techniques to measure soil fertility in order to check the productivity of crop. We are using here two devices to measure the constituents (potassium, phosphorus, nitrogen) of soil. After measuring fertility, we are proposing a system of automatic drip irrigation through microprocessor to measure the moisture of soil.
Keywords: Fertility, Microprocessor, Drip irrigation. 68. References: 324-328 1. AWATI J.S., PATIL V.S. (Automatic Irrigation Control by using wireless sensor networks) Journal of Exclusive Management Science - June 2012-Vol 1 Issue 6 - ISSN 2277 – 5684. 2. MahirDursun* and SemihOzden (drip irrigation automation supported by soil moisture sensors) Scientific Research and Essays Vol. 6(7), pp. 1573-1582, 4 April, 2011 ISSN 1992-2248 ©2011 Academic Journals. 3. AlineBaggio (Delft University of Technology – The Netherlands)[email protected] at journal magazine of Delft University of Technology. 4. The Toro Company Micro-Irrigation Business1588 N. Marshall Avenue, El Cajon, CA 92020-1523, 5. Purnima, S.R.N. Reddy, Department of Electronics & Communication IGIT, GGSIP University, Delhi, India (International Journal of Computer Applications (0975 – 888) Volume 47– No.12, June 2012) 6. Wayne Schmidt soil testingwww.waynesthisandthat.com 7. 8085 microprocessor.info Authors: Madhuri V. Joseph Paper Title: Significance of Data Warehousing and Data Mining in Business Applications Abstract: Information technology is now required in every aspect of our lives which help business and enterprise to make use of applications like decision support system, query and reporting online analytical processing, 69. predictive analysis and business performance management. In this aspect this paper focuses on the significance and role of Data Warehousing and Data Mining technology in business. A Data Warehouse is a central repository of 329-333 relational database designed for query and analysis. If helps the business organization to consolidate data from different varying sources. These warehouses are analyzed by the latest technique known as Data Mining. In Data Mining data sets will be explored to yield hidden and unknown predictions which can be used in future for the efficient decision making. Now companies use techniques of Data Mining that involves pattern recognition, mathematical and statistical techniques to search Data Warehouses and help the analyst in recognizing significant trends, facts relationships and anomalies.
Keywords: Data Warehousing, Data Mining, OLAP, OLTP, CART & CHAID.
References: 1. Inmon W.H., “Building the Data Warehouse”, Second Edition, JWiley and Sons, New York, 1996. 2. P. Bergeron, C. A. Hiller, (2002), “Competitive intelligence”, in B. Cronin, Annual Review of Information Science and Technology, zedford, N.J.: Information Today, vol. 36, chapter 8 3. B. de Ville, (2001), “Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management”, Boston: Digital press. 4. Frawley W., Piatetsky – Shapiro G. and Matheus C., “Knowledge Discovery in Databases: An Overview”, Al Magazine, Fall 1992, pgs 213-228. 5. C. Date, (2003), “Introduction to Database Systems”, 8th ed., Upper Saddle River, N.J.: Pearson Addison Wesley. 6. Han Jiawei, Kamber Micheline, “Data Mining: Concepts and Techniques”, 2nd edition, Morgan Kaufman Publishers, March 2006. ISBN 1-55860-901-6. 7. Oracle9i Data Warehousing Guide Release 2 (9.2), Part No. A96520-01, March 2002. 8. Berry, M.J.A., and Linoff, G., "Mastering data mining", The Art and Science of Customer Relationship Management, 1999. 9. Bhavani, T., Data Mining: Technologies, Techniques, Tools and Trends, 1999. 10. Jiwei, H., and Micheline, K., Data Mining: Concepts and Techniques, Simon Fraser. 11. D. Pyle, (2003), “Business Modeling and Data Mining”, Morgan Kaufmann, San Francisco, CA. 12. M.H. Dunham, (2005), “Data Mining – Introductory and Advanced Topics”, Prentice Hall. 13. Berson Alex, Smith J. Stephen, Thearling Kurt, (1999), “Building Data Mining Applications for CRM”, McGraw-Hill Companies. 14. Gilman Michael, (2004), “Nuggets and Data Mining”, Data Mining Technologies Inc. Melville, NY 11714, (631) 692-4400 15. Chen, S. H, (2002), “Genetic Algorithms and Genetic Programming in Computational Finance”, Boston, A: Kluwer. 16. Kelly Chuck, (2002), “What is the role of Genetic Algorithms in Data Mining”, Information Management: How your Business Works,Electronic Newsletter, http://www.information-management.com/news/5755-1.html. 17. Barry, D., Data Warehouse from Architecture to Implementation, Addison-Wesley, 1997. 18. Krulj, D., "Design and implementation of data warehouse systems", M Sc. Thesis, Faculty ofOrganizational Sciences, Belgrade, 2003. 19. Chapple Mike, “Data Mining: An Introduction”, (2011), http:/ /databases.about. com/od/datamining/a/datamining.htm. 20. Alexander Doug, “Data Mining”, (2000), http://www.laits.utexas.edu/norman/BUS.FOR /course.mat/Alex/, electronic article. Authors: Kerkoub Youcef, Kerboua Ziari Yasmina, Benzaoui Ahmed Paper Title: Modeling Of Transport Phenomena in A PEM Fuel Cell Abstract: In this paper, a three dimensional non-isothermal and steady state model is presented. This model takes into account the transport of reactants, heat, charge species and fluid flow in all parts of the cell in conjunction with the electrochemical reaction. The solid collectors are also included in this model in view to approach a realistic system representation. These processes have a significant impact on water management. Water management ensures that the membrane remains fully hydrated to maintain good ionic conductivity and performance. This work focuses on the effect of gradients of pressure between the anode and cathode, on the performance of the cell and also investigates the effect of these parameters on water management within the cell. Different cases of these gradients have been investigated and compared to the experimental results reported by Wang [2000].
Keywords: PEMFC fuel cell—energy—hydrogen —electrical performance.
References: 1. Berning, T. Lu, D.M. Djilali, N. [2002], Three-dimensional computational analysis of transport phenomena in a PEM fuel cell, J. Power 70. Sources, Vol. 106, pp 284–294. 2. Gurau, V. Liu, H. Kakac, S . [1998], Two-dimensional model for proton exchange membrane fuel cells, AICHE Journal, vol.44, No. 11, pp 2410-2411. 334-336 3. Hao Wu, [2009], Mathematical Modeling of Transient Transport Phenomena in PEM Fuel Cells,PHD Thesis of Mecanchal En geneering , Waterloo, Ontario, Canada. 4. Lobato, J., Cañizares, P. [2010], Rodrigo, M.A., Linares, J.J., Pinar, F.J. Study of the influence of the amount of PBI-H3PO4 in the catalytic layer of a high temperature PEMFC, International Journal of Hydrogen Energy, 35 (3), pp. 1347-1355. 5. Ozmen Y. [2011], Confined impinging twin air jets at high Reynolds number, ExperimentalThermal and Fluid Science, vol. 35, pp 355- 363. 6. Pinar, F.J., Cañizares, P., Rodrigo, M.A., Úbeda, D., Lobato, J. [2011] Scale-up of a high temperature polymer electrolyte membrane fuel cell based on polybenzimidazole , Journal of Power Sources 196, pp 4306–4313 7. Singh, D. Lu, D.M. Djilali, N.A. [1999], two-dimensional analysis of mass transport in proton exchange membrane fuel cells, International Journal of Engineering Science, vol.37, pp 431-452. 8. Sivertsena, B.R. Djilali, N. [2005], CFD-based modelling of proton exchange membrane fuel cells, Journal of Power Sources, Vol. 141, pp 65–78. 9. Srinivasan, S. Ticianelli, E.A. Derouin, C.R. Redondo, A. [1988], Recent advances in solid polymer electrolyte fuel cell technology with low platinum loading electrodes, Journal of Power Sources, Vol.22, pp 359-375. 10. Ticianelli, E.A. Derouin C.R. Redondo A. Srinivasan S. [1988], Methods to advance technology of proton exchange membrane fuel cells, Journal of the Electrochemical Society, Vol.135, pp 2209-2214. 11. Wang C.Y., Um, S. Chenb, K.S. [2000], Computational fluid dynamics modeling of proton exchange membrane fuel cells, Journal of Electrochemical Society, Vol.147, pp 4485-4493. Authors: P.B.Buchade Paper Title: Microcontroller Based Mobile Platform with Fiber Optic Sensors Abstract: In the present work a mobile platform with optical fiber sensor was designed, built and tested. The IC 71. 89C51RD2 was used as controller on the platform. The platform was designed with two powered wheels on the back and one free turning wheel on the front. Further the platform was outfitted with proximity, weight and touch 337-339 plastic fiber sensors. Home position was sensed by touch sensor, the destination by proximity sensor and weight by the load cell sensor. A program was written to move the platform from home position to the destination where after loading the weights in the pan the platform moves back to the destination, unloading the weight the cycle repeats.
Keywords: Fiber optic sensors, load cell, Microcontroller, Mobile platform, Proximity senso , Touch sensor .
References: 1. Richard D. Klafter, Thomas A. Chmielewski, Michael Negin ‘Robotic Engineering An Integrated Approach’ PHI, New Delhi, 2001,pp.1-82. 2. Shimon Y. Nof, (edited) ‘Hand book of Industrial robotics’, Second edition, Wiley and Sons, INC. pp. 245-265. 3. Y.F.Li, ‘A proximity sensor and its application in real time robot control’ Robotics and Autonomous Systems, 13 (1994) pp. 25-37. 4. Y.F.Li ‘Robot end effector orientation control using proximity sensors’ Robotics & Computer integrated Manufacturing 10 (5) (1993) pp. 323-331. 5. Slotwinski, Anthony R. ‘Integrated fiber optic coupled proximity sensor for robotic end effectors and tools’, Patent No. 04969736 US 11/13/1990. 6. Justin Clark and Rafael Fierro, ‘Cooperative Hybrid Control of Robotic Sensors for Perimeter Detection and Trackink’, American control conference Portland, OR, USA. June 8-10, (2005). 7. B. Jiang, P. Stuart, M. Raymond, D. Villa, and A. V. Mamishev, ‘Robotic Platform For Monitoring Underground Cable Systems’, IEEE/PES Transmission and Distribution Conference, Yokohama, Japan, vol. 2, (2002) pp.1105-1109. 8. P.B. Buchade and A.D. Shaligram ‘Simulation and experimental studies of inclined two-fiber sensor’ Sensors and Actuators: A, 128(2) (2006) pp.312-316. 9. Users Manual for stepping motors Srijan control devices, Pune, India. Authors: Pragya Rajput, Joy Bhattacharjee, Roopali Soni A Proposed Framework to Implicit Measures of User Interests through Country and Predicting Paper Title: Users’ Future Requests in WWW Abstract: WWW has become the center of attraction for business transactions and hence e-commerce due to its ease of use and speed. its ability from tracking the browsing behaviour of any user to even the mouse clicks of any individual has brought the vendor and end customer closer than ever before.WWW has made it possible for vendors to advertize their products i.e. they are personalizing their product messages for individual customers at a very large scale such a phenomenon is termed as mass communication such a utility is not only applicable for e-commerce but also such personalization is aiding several web browsing activities. Any action that tailors the web experience to any individual or several users is termed as web personalization. Web personalization is that the method of customizing an internet website to the wants of specific users, taking advantage of the information noninheritable from the analysis of the user's guidance behaviour(Weblog data) in correlation with alternative data collected within the web context, namely, structure, content and user profile information. The domain of web personalization has gained importance both in the area of research and commerce. In this paper we proposed a framework of web log mining to implicit measures of user interests through Country and predicting users’ future requests in WWW.
Keywords: Web Log, Personalization, Web Usage Mining, Preprocessing, IP-Address, Country, WWW.
References: 1. Kosala, R. and H. Blockeel, Web Mining Research: A Survey. SIGKDD Explorations, 2000. 2(1): p. 1-15. 72. 2. Renáta Iváncsy, István Vajk, "Frequent Pattern Mining in Web Log Data", Acta Polytechnica Hungarica, Vol. 3, No. 1, 2006, Pp 77-90. 3. Haibin Liu, Vlado Kesˇelj . “Combined mining of Web server logs and web contents for classifying user navigation patterns and predicting users’ future requests”. Data & Knowledge Engineering 61 (2007) 305–330. 340-343 4. Federico Michele Facca, Pier Luca Lanzi ”Mining interesting knowledge from web logs: a survey”. Data & Knowledge Engineering 53 (2005) 225–251. 5. Han, J. and M. Kamber, Data Mining: Concepts and Techniques. 2007: Morgan Kaufmann. 6. Arun K Pujari, Data Mining Techniques, Chapter 8, Edition-2007. 7. Liu, B. and K.C.-C. Chang, “Special Issue on Web Content Mining”. ACM SIGKDD Explorations, 6(2): Pp. 1-4, 2004. 8. Mobasher, B., Web Usage Mining and Personalization, in Practical Handbook of Internet Computing, M.P. Singh, Editor. 2005, CRC Press. p. 15.1-37. 9. Eirinaki M., Vazirgiannis M. (2003). Web mining for web personalization. ACM Transactions on Internet Technology (TOIT), 3(1), 1- 27. 10. Srivastava, J., et al., Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. ACM SIKDD Explorations, 1 (2): p. 12-23. Internet Computing, M.P. Singh, Editor. 2005, CRC Press. p. 15.1-37. 11. http://www.apnic.net/ 12. R. Agrawal,R. Shrikanth, ”Fast Algorithm for mining Association Rule” Proc. of VLDB Conference, pp.587-559, Santigo, Chile, 1995. 13. Tanasa, D.; Trousse, B.; “Data preprocessing for WUM”, IEEE Potentials, Vol. 23, No. 3, Pp. 22 – 25, 2004. 14. Srivastava, J.;”Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data”. ACM SIKDD Explorations, 1(2): Pp. 12-23, 2000. 15. R. Cooley, B. Mobasher and J. Srivastava Data preparation for mining World Wide Web browsing patters. Knowledge and Information Systems, 1(1), 1999. 16. Nikos Koutsoupias, " Exploring Web Access Logs with Correspondence Analysis", 2nd Hellenic Conf. on AI, SETN-2002, Thessaloniki, Greece, Proceedings, Companion Volume, Pp. 229-236, 11-12 April 2002. 17. COOLEY, R., TAN, P-N., AND SRIVASTAVA, J. 1999b. "WebSIFT: The web site information filter system. In Proceedings of the Web Usage Analysis and User Profiling" Workshop (WEBKDD’99), Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Boston, August). Authors: Sangeetha G M, Prasanna Kumar M Mining Technique Defined For Improving User- Based Recommendations in Diverse Environment Paper Title: (MTIURD) Abstract: Recommender systems are being extensively used in the present generation. Today’s consumer are facing with millions of goods and services when shopping online. Recommender systems help consumers by 73. making product recommendations that are likely to be of interest to the user such as books, CDs, movies, restaurants, online news articles, and other services. Recommender systems are gradually increasingly harder to find 344-351 the relevant contents of information in the vast abundant current age of information overload. Thus, recommender systems are needed to help individual users find the most relevant items or products or data sets from an abundant number of choices, collection. Through this gradually increase sales by exposing users to what they might like. E.g. In real time or real world applications consider a product say laptop, the laptop present in numerous patterns with different applications in number depending upon different user’s requirements. Thus providing a user or the customer with relevant information about the product as per their requirements with the help of recommender systems would ease the work of an user. Hence we can conclude saying that the volume of information available in the current age is huge to individual users (for e.g., e-commerce sites applications such as Amazon, Netflix) and hence focusing in developing some recommendation techniques within both industry and academia. Most, research to date is focusing on improving the recommendation accuracy i.e. the accuracy with which the recommender system predicts users ratings for items that are yet to be rated. The diversity of recommendation also plays an important role to be considered, it is important to explore the relationship between the accuracy and diversity and also the recommendation quality. Empirical analysis consistently shows the diversity gains of different recommendation techniques which is being used in several real world rating applications or datasets and uses different rating prediction algorithms. Individual users and online content providers will also benefit from the proposed approaches, where in which each user can find more relevant and personalized items or products from accurate and diverse recommendations provided by these recommender systems. These approaches, ranking techniques and algorithms could potentially lead to increased loyalty and sales in e-commerce application sites, thus benefiting the providers as well. Thus, serving these needs can result in greater success regarding cross-selling of related products, up selling, product affinities, and one-to –one promotions, larger baskets and customer retention.
Keywords: Recommender systems, recommendation accuracy, diverse recommendation, empirical analysis, ranking techniques, collaborative filtering, performance evaluation metrics, aggregate diversity, RMSE, extensions of recommendation approaches.
References: 1. G. Adomavicius and A. Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, ii. 734-749, June 2005. 2. Adomavicius, G., Y. Kwon. 2007. New Recommendation Techniques for Multi-Criteria Rating Systems. IEEE Intelligent Systems 22:3 48-55. 3. Adomavicius, G., Y. Kwon. 2009. Toward More Diverse Recommendations: Item Re-Ranking Methods for Recommender Systems. Iroc. of the 19th Workshop on Information Technologies and Systems. 4. Adomavicius, G., Y. Kwon. 2011. Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques. IEEE Transactions on Knowledge and Data Engineering Forthcoming. 5. Adomavicius, G., N. Manouselis, Y. Kwon. 2011. Multi-Criteria Recommender Systems. in I. B. Kantor, F. Ricci, L. Rokach, B. Shaiira (Eds.). Recommender Systems Handbook: A cGuide for Research Scientists and practitioners Chapter 24. Springer. 6. Aggarwal, C.C., J.L. Wolf, K.L. Wu, I.S. Yu. 1999. Horting Hatches An Egg: A New Graph-Theoretic Approach to Collaborative Filtering. Proc. of the 5th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD’99). 201-212. 7. Ahuja, R.K., T.L. Magnanti, J.B. Orlin. 1993. Network Flows: Theory, Algorithms, and Applications. Englewood Cliffs, NJ: Prentice- Hall. 8. Anderson, C. 2006. The Long Tail. New York: Hyperion. 9. Balabanovic, M., Y. Shoham. 1997. Fab: Content-Based, Collaborative Recommendation. Communications of the ACM 40:3 66-72. 10. Bichler, M. 2000. An Experimental Analysis of Multi-Attribute Auctions. Decision Support Systems 29:10 249-268. 11. Billsus, D., M. Iazzani. 1998. Learning Collaborative Information Filters. Iroc.Int’l Conf. Machine R. Bell, Y. Koren, and C. Volinsky, “The BellKor Solution to the Netflix Irize,”www.netflixirize.com/assets/IrogressIrize KorBell.idf, 2007. 12. C. Anderson, The Long Tail. Hyierion, 2006 13. S. Breese, D. Heckerman, and C. Kadie, “Empirical Analysis of Predictive Algorithms for Collaborative Filtering,” Proc. 14th Conf.Uncertainty in Artificial Intelligence, 1998. 14. R.M. Bell, Y. Koren, and C. Volinsky, “The Bellkor 2008 Solution to the Netflix Prize,” htti://www.research.att.com/~volinsky/ netflix/IrogressIrize2008BellKorSolution.idf, 2008. 15. J. Bennett and S. Lanning, “The Netflix Prize,” Proc. KDD-Cui and Workshop at the 13th ACM SIGKDD Int’l Conf. Knowledge and Data Mining, 2007. 16. D. Billsus and M. Iazzani, “Learning Collaborative Information Filters,” Proc. Int’l Conf. Machine Learning, 1998. 17. S. Zhang, W. Wang, J. Ford, F. Makedon, and J. Iearlman, “Using Singular Value Decomposition Approximation for Collaborative Filtering,” Proc. Seventh IEEE Int’l Conf. E-Commerce Technology 18. W. Knight, “Info-Mania’ Dents IQ More than Marijuana.”.NewScientist.comNews, htti://www.newscientist.com/article.ns?id=dn7298, 2005. 19. Y. Koren, “Collaborative Filtering with Temporal Dynamics,” Proc. 15th ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining, ii. 447-456, 2009. 20. B.M. Sarwar, G. Karyiis, J. Konstan, and J. Riedl, “Analysis of Recommender Algorithms for E-Commerce,” Proc. ACM Conf. Electronic Commerce, ii. 158-167, 2000 21. Hemant Palivela, Pushpavathi Thotadara ,Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on computing communication and network technologies, 26th -27th July 2012. Authors: Shaweta Kumar, Sanjeev Bansal Paper Title: Comparative Study of Test DrivenDevelopment with Traditional Techniques Abstract: Test-Driven Development is the evolutionary approach in which unit test cases are incrementally written prior to code implementation. In our research, we will be doing comparative study of Test Driven development with traditional techniques through literature study as well as industrial survey. Through this research, we would like to find out the factors encouraging the use of Test Driven Development and also the obstacles that 74. are limiting the adoption of Test Driven Development in the industry. The TDD method is radically different from the traditional way to create software. In traditional software development models, the tests are written after the 352-360 code is implemented, in other words we could refer it as test-last. This does not drive the design of the code to be testable. Defining the tests with the requirements, rather than after, and using those tests to drive the development effort, gives us much more clearly picture and share focus on the goal. If tests are written after the implementation, there is a risk that tests are written to satisfy the implementation, not the requirements. An important rule in TDD is: “If you can’t write test for what you are about to code, then you shouldn’t even be thinking about coding.”.
Keywords: extreme programming, refactoring, test driven development, test-first methodology, test-last methodology.
References: 1. Shrivastava and Jain, "Metrics for Test Case Design in Test Driven Development", International Journal of Computer Theory and Engineering, Vol.2, No.6, December, 2010, Pg: 1793-8201. 2. Astels, D., Test-Driven Development: A Practical Guide. Upper Saddle River, New Jersey, USA, Prentice Hall, 2003 3. Beck, K, Test-Driven Development By Example. Boston, Massachusetts, USA, Addison-Wesley, 2003 4. Maria Siniaalto, "Test driven development: empirical body of evidence", Agile Software development of Embedded Systems, 2006 5. Kitchenham, B, Procedures for Performing Systematic Reviews. United Kingdom and Australian: Department of Computer Science Keele University, Australian Technology Park, 2004 6. L. Koskela, Test Driven, Manning Publications, Greenwich, Connecticut, USA, 2008. 7. B. George and L. Williams, "An initial investigation of test driven development in industry," presented at ACM Symposium on Applied Computing, Melbourne, Florida, 2003. 8. Adnan Causevic, Daniel Sundmark and Sasikumar Punnekkat "Factors Limiting Industrial Adoption of Test Driven Development: A Systematic Review" IEEE Computer Society Washington, DC, USA ©2011 9. John Huan Vu, Niklas Frojd, Clay Shenkel-Therolf, and David S. Janzen "Evaluating Test-Driven Development in an Industry- sponsored Capstone Project" 2009 Sixth International Conference on Information Technology: New Generations 10. Janzen, D., Software Architecture Improvement through Test-Driven Development. Conference on Object Oriented Programming Systems Languages and Applications, ACM, 2005. Authors: Asha Thapliyal, M.M. Kimothi Paper Title: Comparison and Monitoring of Glacier Retreat using Satellite and Ground Methods Abstract: The study aimed to make the comprehensible thought about the actual recession over the Gangotri glacier using reiteration photographs of glacier. Here we summarizes the understanding and responding to glacier retreat during the period of 1866 to 2011, on the basis of scientific evidence for glacier retreat particularly at Goumukh snout. The ground photographs were taken from internet (http:// www.cseindia.org/userfiles/repeat_photography). Change in snout position was carried out by Elevation transfer method, interpretation of expedition photographs and panochromatic rectified images. Contours at 30 m resolution generated from ASTER satellite data and overlay on Cartosat DEM to locate the shift in snout position. Retreat over the glacier region is compared with the previous studies carried out in the region. Shift in demarcation also observed with overlaying DEM of Quick Bird Satellite data of 2011 and panchromatic image of Gaomukh. Interpretation was carried out of camera photographs over the Gangotri glacier for year-1866 and 2011 and it is concluded that Gaumukh has receded in between 3.25 to 3.5 km within 144 years, while on the basis of satellite data investigation the snout position shift is found to be 3.37 Km. This retreat may be due to direct or indirect effects of climate change and it is caused largely by human activity and may be other anthropogenic activities.
Keywords: Himalaya, Gaumukh Snout, DEM, Snow Retreat
References: 1. Bahuguna, I. M., Kulkarni, A. V., Nayak, S., Rathore, B. P., Negi, H. S. and Mather, P. 2007. Himalayan glacier retreat using IRS 1C PAN stereo data. Int. J. Remote Sensing, , 28, 437-442. 2. Bali R., Agarwal K. K., Ali S. N. and Srivastava P. 2009. Is the recessional pattern of Himalayan glaciers suggestive of anthropogenically induced global warming, Arab J Geosci. Doi.10.1007/s12517-010-0155-9.s 3. Dobhal, D.P. and Kumar, S. 1996. Inventory of glacier basins in Himachal Himalayas. Journal of the Geological Society of India, 48,671–681. 4. Dobhal, D.P., Gergan, J.T., Thayen, R.J. 2007. Recession and mass balance fluctuation on Dokriani glacier from 1991 to 2000, Garhwal 75. Himalaya, India. International seminar: “Climatic and anthropogenic impacts on water resources variability”, Hydrological program (IHP)-VI, UNESCO, Tech.Docu.No.80:53-63. 361-364 5. Dobhal, D.P., Gergan, J.T., Thayyen, R.J. 2008. Mass balance studies of the Dokriani glacier from 1992 to 2000, Garhwal Himalaya India. Bulletin of Glaciological Research, Japanese Society of snow and ice, 25;9-17. 6. Hansen, J. and Nazarenko, L. 2004. Soot climate forcing via snow and ice albedo; PNAS 101(2) 423–428. 7. Hasnain, S.I. 1999. Himalayan glaciers–hydrology and hydrochemistry. New Delhi: Allied Publishers, 234. 8. Hasnain S. I., Ahmad, S. and Yadav, M. 2004. Analysis of ASTER and Panchromatic images for surfacial characteristics of the Gangotri glacier, Garhwal Himalaya, India. In Proceedings of IUGC. 9. IPCC 2007 Summary for Policymakers, In: Climate Change 2007 The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds) Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K B, Tignor M and Miller H L (Cambridge, UK and New York, USA: Cambridge University Press). 10. Kaul. M.K. (1999): Inventory of Himalaya glaciers. GSI Special Publication. No.34. 11. Kulkarni, A.V., and Bahuguna, I. M. 2001. Role of satellite images in snow and Glacial investigations, Geological Survey of India Special Publication, 53, 233-240. 12. Kulkarni A.V., Rathore, B.P., Singh, S.K., Bahuguna, I.M. 2011. Understanding changes in the Himalayan cryosphere using remote sensing techniques; Int. J. Remote Sens.32(3) 601–615. 13. Kumar K, Dumka R K, Miral M S, Satyal G. S and Pant M. 2008. Estimation of retreat rate of Gangotri glacier using rapid static and kinematic GPS survey, Current Science 94(2), 258-262. 14. Mizra M M Q, Warrick R A, Ericksen N J and Kenny G J, 2002. The implications of climate change on flood discharges of the Ganges, Brahmaputra and Meghna Rivers in Bangladesh, Climatic change 57(3), 287-318. 15. Mukherjee, B. P. and Sangewar, C.V. 2001. Recession of Gangotri glacier through 20th century. Geological Survey of India Special Publication Number 65, 1–3. 16. Nainwal H.C., Negi B.D.S., Chaudhary M.S., Sajwan K.S. and Gaurav A. 2008. Temporal changes in rate of recession: evidences from Satopanth and Bhagirathi Khark glaciers, Uttarakhand, using Total Station Survey, Current Science 97(5), 653-660. 17. Naithani, A.K., Nainwal, H.C., Sati, K.K. and Prasad, C 2001. Geomorphological evidences of retreat of the Gangotri glacier and its characteristics. Current Science, 80,87–94. 18. Negi, H.S., Thakur, N.K., Ganju, A., Snehmani, 2012. Monitoring of Gangotri glacier using remote sensing and ground observations. J.Earth Syst. Sci. 121(4), 855-866. 19. Racoviteanu, A.E., Williams, M.W. and Barry, R.G. 2008. Optical remote sensing of glacier characteristics: A review with focus on the Himalaya; Sensors,8,p.3355–3383; doi:10.3390/s8053355. 20. Yadav, R.R., W.-K. Park, J. Singh and B. Dubey. 2004. Do the western Himalayas defy global warming? Geophys. Res. Lett.,31(17), L17201. (10.1029/2004GL020201.) 21. Yasunari T.J., Bonasoni P, Laj P., Fujita K., Vuillermoz E., Marinoni A., Cristofanelli P., Duchi R., Tartari G. and Lau K.M. 2010. Estimated impact of black carbon deposition during pre-monsoon season from Nepal Climate Observatory–Pyramid data and snow albedo changes over Himalayan glaciers; Atmos. Chem. Phys. 10 ,6603–6615. Authors: S.Radha Krishna Reddy, JBV Subrahmanyam, A. Srinivasula Reddy Wind Turbine Transient Stability Improvement in Power System Using PWM Technique and Fuzzy Paper Title: Controller Abstract: In recent years, the increasing concerns to the environmental issues and the limited availability of conventional fossil fuels lead to rapid research and development for more sustainable and alternative electrical sources. Wind energy, as one of the most prominent renewable energy sources, is gaining increasing significance throughout the world. Distributed Generation (DG), based on renewable energy has become a development trend for electric power industry in 21stcentury. The currently worldwide installed capacity of grid connected wind generators grows rapidly. Therefore detailed analysis needs about the impact of wind power on system security and system operation. But DG is affected by natural conditions being not able to output power continuously and steadily. So when large scale wind turbine generators are incorporated into the grid, they will bring impact on electric power system stability.In order to ensure stable operation of electric power system, application of a super capacitor energy storage system (SCESS) superior to other energy storage technologies and Doubly Fed Induction wind Generator (DFIG) are presented in this paper. CESS is connected to the grid at the Point of Common Coupling (PCC). Matlab/Simulink software is used for modelling and simulation analysis. In this paper, transient stability problem if focussed. The simulation results obtained indicate that SCESS can improve transient stability of wind turbine generator system connected to the grid, and by using doubly fed induction generators, electric power system stability can be improved. 76. Keywords: Distributed Generation (DG); Super Capacitor Energy Storage System (SCESS); Transient Stability; Doubly Fed Induction Wind Generator (DFIWG); Fuzzy Controller and PWM Technique. 365-370
References: 1. “Impact of Large Scale Wind Farm Integration on Power System Transient Stability,” Automation of Electric Power Systems, 2008, 2. “Transient Stability Augmentation of PowerSystemIncluding Wind Farms by Using SCESS,” IEEE Trans.Power,2008 3. Wang Chengxu. Zhang Yuan, “wind generation, ” Beijing, 2002. 4. “Performance indices for the dynamic performance of FACTS andFACTS with energy storage,” Elect. power Compon. Syst.2005 5. Z.Yang, C.Shen, L. Zhang, M.L.Crow, and S. Atcitty, “Integration ofa STATCOM and batteryenergy storage,” IEEE Trans. Power Syst.2001 6. Y.Cheng, C.Qian, M.L.Crow, S. Pekarek, and S. Atcitty, “Acomparison of diode-clamped andcascaded multilevel converters fora STATCOMwith energy storage,” IEEE Trans. Ind. Electron, 2006. 7. J.G.Slootweg, H.polinder, W.L.Kling, “Dynamic Modelling of AWind Turbine with Doubly FedInduction Generator,”IEEE PowerEngineering Society Summer Meeting, 2001. 8. Shigenori Inoue. and Hirofumi Akagi, A Bi-Directional DC_DCConverter for an EnergyStorage System, 2007.IEEE. 9. M.R.I. Sheikh, S.M. Muyeen, Rion Takahashi, Toshiaki Murata andJunji Tamura, “Transientstabilityenhancement of wind generatorusingsuperconductingmagnetic energy storage unit,”Proceedings ofthe 2008International ConferenceonElectrical Machines, 2008,IEEE. 10. S.M.Muyeen, M.H.Ali, R.Takahashi, T.Murata, andJ.Tamura.“Stabilization of Wind Farms Connectedwith Multi Machine PowerSystem by Using STATCOM,” 2007.IEEE. 11. Kuang Honghai, Wu Zhengqiu1, Zhu Wenhui “Transient Stability of Multi-Machine Wind Turbine Generators System Connected to the Gird” International Conference on Energy and Environment Technology,2009. Authors: Pinky Chandwal, A. S. Zadgaonkar, Abhinav Shukla Paper Title: Estimation of Software Quality by using fuzzy (FIS) Abstract: As software are being used in more and more critical areas, therefore quality of software becomes a very important factor for business and human safety. Estimation of software quality is the key for achieving a high quality product. Quality of software is associated with number of quality attributes and estimation of software quality involves broad views and various perspectives which might involve natural description, in linguistic terms. Linguistic terms are more convenient to use when human express the subjectivity and imprecision of their evolution but these linguistic variables involve ambiguity and vagueness. Since fuzzy logic deals with the ambiguity, imprecision and vagueness therefore this study proposes the applicability of fuzzy along with ISO 9126 quality model for developing quality estimation framework.
Keywords: Quality, Quality attributes, FIS, Rule base, linguistic variable. 77. References: 1. Software Engineering Fifth Edition -A Practitioner’s approach by Roger S. Pressman. 371-378 2. McCall JA et al (1977)- Factors in Software Quality: Volume 1-3, RADC-TR77-369 Sunnyvale CA: general electric co. 3. ISO (1994) ISO 9000- Quality Management and Quality Assurance Vocabulary 2nd Edition: Geneva ISO. 4. http://www.ima.umn.edu/~arnold/disasters/ariane.html 5. Jyothi G and Ch.Verra babu- An integrated approach for measuring software quality and code readability. 6. Nachippan, Laurie Williams, M laden vauk,Jason Osborne-Early estimation of software quality using in process testing metrics; A controlled case study. 7. Krazysztof Sacha- Evaluation of software quality 8. Shi Zhong,Taghi M.Khoshgoftaar and Naeem Seliya- Unsupervised learning for expert based software quality estimation 9. X.Yuan,T.M.Khoshgoftarar,E.Allen and K.Ganesan-An application of fizzy clustering to software quality predication 10. R.Kumar, S.Rai, and J.L. Trahan-Neural- network techniques for software quality evaluation. 11. Boehm, B.W. et al-Characteristics of Software Quality 12. ISO,International Organization for Standardization,”ISO 9126-1:2001,Software engineering-Product quality,Part1:Quality Model”2001 13. L.A. Zadeh, Fuzzy Sets, Information and Control, 1965 14. Fuzzy Logic Toolbox™ 2 User’s Guide Authors: Rujul R Makwana, Nita D Mehta Single Image Super-Resolution VIA Iterative Back Projection Based Canny Edge Detection and a Paper Title: Gabor Filter Prior Abstract: The Iterative back-projection (IBP) is a classical super-resolution method with low computational complexity that can be applied in real time applications. This paper presents an effective novel single image super resolution approach to recover a high resolution image from a single low resolution input image. The approach is based on an Iterative back projection (IBP) method combined with the Canny Edge Detection and Gabor Filter to recover high frequency information. This method is applied on different natural gray images and compared with different existing image super resolution approaches. Simulation results show that the proposed algorithms can more accurately enlarge the low resolution image than previous approaches. Proposed algorithm increases the MSSIM and the PSNR and decreases MSE compared to other existing algorithms and also improves visual quality of enlarged images.
Keywords: Canny Edge Detection, Gabor Filter, IBP, Super Resolution.
References: 1. Sung Cheol Park, Min Kyu Park,and Moon Gi Kang “Super Resolution:A Technical Overview,”IEEE SIGNAL PROCESSING MAGAZINE 1053-5888/03/$17.00©2003IEEE. 2. C Papathanassiou and M Petrou,” Super resolution: an overview,” 0-7803-9051-2/05/$20.00 (C) 2005 IEEE. 78. 3. Poth Miklos, Image Interpolation Techniques, Available: www.bmf.hu/conferences/sisy2004/Poth.pdf 4. M. Irani and S. Peleg, “Improving resolution by image registration”, CVGIP: Graphical Models and Image Processing, vol. 53, pp. 231- 239, May 1991. 379-384 5. S. Dai, M. Han, Y. Wu and Y. Gong, “Bilateral Back-Projection For Single Image Super Resolution”, IEEE Conference on Multimedia and Expo (ICME), 2007, pp. 1039-1042. 6. F.Qin, “An Improved Super Resolution Reconstruction Method Based on Initial Value Estimation”, in 3rd International Congress on Image and Signal Processing (CISP), 2010. 7. W. Dong, L. Zhang, G. Shi and X. Wu, “Nonlocal back projection for adaptive image enlargement”, in IEEE International Conference on Image Processing, pp. 349-352, November 2009. 8. X. Liang and Z. Gan, “Improved Non-Local Iterative Back Projection Method for Image Super-Resolution”, Sixth International Conference on Image and Graphics (ICIG), 2011. 9. J. Wang, K. Liang, S, Chang and P. Chang, “Super-Resolution Image with Estimated High Frequency Compensated Algorithm”, in IEEE Conf. Communication and Information Technology, 2009, pp. 1039-1042. 10. V. B. Patel, Chintan K. Modi, C. N. Paunwala and S. Patnaik, “Hybrid Approach for Single Image Super Resolution using ISEF and IBP”, in IEEE Conference on Communication System and Network Technology (CSNT), 03-05 june, 2011. 11. Milan N. Bareja and Chintan K. Modi, “A Novel Iterative Back Projection based Hybrid Approach for Single Image Super Resolution”, in National Conference on Power Systems, Embedded Systems, Power Electronics, Communication, Control and Instrumentation (PEPCCI), pp. 283-286, 09-11 January, 2012. 12. John Daugman: "Complete Discrete 2-D Gabor Transforms by Neural Networks for Image Analysis and Compression", IEEE Trans on Acoustics, Speech, and Signal Processing. Vol. 36. No. 7. July 1988, pp. 1169–1179. 13. D. J. Gabor, “Theory of communication”, Journal of the Institute of Electrical, Engineers IEE,VOL. 93, NO. 26, pp 429-457, 1946. 14. Konstantinos G. Derpanis, “Gabor filters”, York University,Version 1.3, April 23, 2007. 15. Liyakathunisa and C N Ravikumar,”A Novel Super Resolution Reconstruction of low resolution images progressively using DCT and Zonal Filter based Denoising”, International Journal of Computer Science & Information Technology(IJCSIT),Vol 3,No 1,Feb 2011. Authors: Tejinder Sharma, Vijay Kumar Banga Paper Title: Efficient and Enhanced Algorithm in Cloud Computing Abstract: A class of systems and applications that procure distributed resources to execute the function in the decentralized manner is referred as cloud computing. It enables a wide range of users to access scalable, virtualized hardware, distributed and/or software infrastructure over the Internet. One of the challenging scheduling problems in Cloud datacenters is to take the allocation and migration of reconfigurable virtual machines into consideration as well as the integrated features of hosting physical machines. In order to select the virtual nodes for executing the task, Load balancing is a methodology to distribute workload across multiple computers, or other resources over the network links to achieve optimal resource utilization, minimum data processing time, minimum average response time, and avoid overload. The objective of this paper to propose efficient and enhanced scheduling algorithm that can maintain the load balancing and provides better improved strategies through efficient job scheduling and modified resource allocation techniques. Load balancing ensures that all the processors in the system as well as in the network does approximately the equal amount of work at any instant of time. The results discussed in this paper, based on existing Equally Spread Current Execution, Round Robin, 79. Throttled and a new proposed enhanced and efficient scheduling algorithms. 385-390 Keywords: Cloud Computing , Cloud Analyst, Equal Spread Current Execution, Round Robin , Throttled, VM.
References: 1. Mishra , Ratan , Jaiswal, Anant,P“Ant Colony Optimiza tion: A Solution Of Load Balancing In Cloud”,April 2012, International Journal Of Web & Semantic Technology;Apr2012, Vol. 3 Issue 2, P33 2. Eddy Caron , Luis Rodero-Merino “Auto-Scaling , Load Balancing And Monitoring In Commercial And Open-Source Clouds “ Research Report ,January2012 3. Nidhi Jain Kansal, “Cloud Load Balancing Techniques : A Step Towards Green Computing”, IJCSI International Journal Of Computer Science Issues, January 2012, Vol. 9, Issue 1, No 1, , Pg No.:238-246, ISSN (Online): 1694-0814 4. Rich Lee, Bingchiang Jeng ”Load Balancing Tactics In Cloud” International Conference On Cyber Enabled Distributed Computing And Knowledge Discovery, 2011 5. Saroj Hiranwal , Dr. K.C. Roy, ”Adaptive Round Robin Scheduling Using Shortest Burst Approach Based On Smart Time Slice” International Journal Of Computer Science And Communication July-December 2011 ,Vol. 2, No. 2 , Pp. 319-323 6. Bhathiya Wickremasinghe “ Cloud Analyst: A Cloud-Sim-Based Tool For Modeling And Analysis Of Large Scale Cloud Computing Environments. MEDC Project” ,Report 2010 . 7. Bhathiya Wickremasinghe ,Roderigo N. Calherios “Cloud Analyst: A Cloud-Sim-Based Visual Modeler For Analyzing Cloud Computing Environments And Applications”. Proc Of IEEE International Conference On Advance Information Networking And Applications ,2010. 8. Zhang, L. Cheng, And R. Boutaba, “Cloud Computing: State-Of-The-Art And Research Challenges”, Journal Of Internet Services And Applications, , April 2010. 9. Bhadani , And S. Chaudhary , “Performance Evaluation Of Web Servers Using Central Load Balancing Policy Over Virtual Machines On Cloud”, Proceedings Of The Third Annual ACM Bangalore Conference (COMPUTE), January 2010. 10. R. P. Mahowald, Worldwide Software As A Service 2010–2014 Forecast: Software Will Never Be Same ,In, IDC, 2010 11. R. Buyya, R. Ranjan, and R. N. Calheiros, “Modeling And Simulation Of Scalable Cloud Computing Environments And The Cloudsim Toolkit: Challenges And Opportunities,” Proc. Of The 7th High Performance Computing And Simulation Conference (HPCS 09), IEEE Computer Society, June 2009. 12. M. Armbrust , A. Fox, R. Griffith, A. D. Joseph, R. Katz, A.Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, And M. Zaharia, “Above The Clouds: A Berkeley View Of Cloud Computing”, Eecs Department, University Of California , Berkeley,, February 2009,Technical Report No., Ucb/Eecs-2009-28, Pages 1-23. 13. K.D. Devine, E.G. Boman , R.T. Hepahy, B.A.Hendrickson, J.D. Teresco, J. Faik,J.E. Flaherty,L.G. Gervasio,” New Challenges In Dynamic Load Balancing,Applied Numerical Mathematics,52(2005)133-152. 14. L. Kleinrock, A Vision For The Internet St Journal Of Research, Nov, 2005,(1),Pg4-5. 15. http://www.livinginternet.com/w/wi_online.htm. 16. www.cloudbus.org/cloudsim. 17. http://www.ca.com/~/media/Files/whitepapers/turnkey_clouds_turnkey_profits.pdf. Authors: N. Jenefa, J. Jayalakshmi Paper Title: A Cloud Storage System with Data Confidentiality and Data Forwarding Abstract: Cloud storage is a model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Organizations cite data confidentiality as their serious concern for cloud computing, with uncrypted data stored on third party’s cloud system, The functionality of the storage system is limited when general encryption schemes are used for data confidentiality. With this consideration, we propose a new threshold proxy re-encryption scheme to form a secure distributed storage system. This distributed storage system also lets a user forward his data in the storage servers to another user without retrieving the data back The distributed storage system not only supports secure and robust data storage and retrieval, but also lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages.
Keywords: Distributed storage system, encoding, proxy re-encryption, uncrypted data. 80. References: 391-394 1. Hsiao-Ying Lin, Member, IEEE, and Wen-Guey Tzeng, Member ”A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding”IEEE Transactions On Parallel And Distributed Systems, VOL. 23, NO. X, XXX 2012. 2. J. Kubiatowicz, D. Bindel, Y. Chen, P. Eaton, D. Geels, R. Gummadi, S. Rhea, H. Weatherspoon, W. Weimer, C. Wells, and B. Zhao, “Oceanstore: An Architecture for Global-Scale Persistent Storage,” Proc. Ninth Int’l Conf. Architectural Support for Programming Languages and Operating Systems (ASPLOS), pp. 190- 201, 2000 3. P. Druschel and A. Rowstron, “PAST: A Large-Scale, Persistent Peer-to-Peer Storage Utility,” Proc. Eighth Workshop Hot Topics in Operating System (HotOS VIII), pp. 75-80, 2001. 4. Adya, W.J. Bolosky, M. Castro, G. Cermak, R. Chaiken, J.R. Douceur, J. Howell, J.R. Lorch, M. Theimer, and R. Wattenhofer, “Farsite: Federated, Available, and Reliable Storage for an Incompletely Trusted Environment,” Proc. Fifth Symp. Operating System Design and Implementation (OSDI), pp. 1-14, 2002. 5. Haeberlen, A. Mislove, and P. Druschel, “Glacier: Highly Durable, Decentralized Storage Despite Massive Correlated Failures,” Proc. Second Symp. Networked Systems Design and Implementation (NSDI), pp. 143-158, 2005. 6. Z. Wilcox-O’Hearn and B. Warner, “Tahoe: The Least-Authority Filesystem,” Proc. Fourth ACM Int’l Workshop Storage Security and Survivability (StorageSS), pp. 21-26, 2008. 7. H.-Y. Lin and W.-G. Tzeng, “A Secure Decentralized Erasure Code for Distributed Network Storage,” IEEE Trans. Parallel and Distributed Systems, vol. 21, no. 11, pp. 1586-1594, Nov. 2010.H. Poor, An Introduction to Signal Detection and Estimation. New York: Springer-Verlag, 1985, ch. 4. Authors: Munqath H. Alattar S.P. Medhane Paper Title: Efficient Solution for SQL Injection Attack Detection and Prevention Abstract: SQL injection is the most common attack for web applications and widely used exploit by hackers all over the world. A malicious hacker can do a lot of harm if he wishes to. SQL injection is a security vulnerability that occurs in the database layers of an application. SQL injection is a technique to pass SQL code into interactive web applications that employ in database services. The employment of SQL Injection Attacks, can lead to the leak of confidential information such as credit card numbers, commercial information & table structure. The attackers can get the entire schema of the original database and also corrupt it. In this paper, we have proposed the Detection Model of SQL Injection Vulnerabilities and SQL Injection Mitigation Framework. These approaches are based on SQL Injection grammar to identify the SQL Injection vulnerabilities during software development and SQL 81. Injection Attack on web-based applications. 395-398 Keywords: SQL Injection; Security Assessment; vulnerabilities; Pattern Matching, SQL Query.
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