Vol 10, No 6 29/06/20 21.41

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DOI: http://doi.org/10.11591/ijece.v10i6 CITATION ANALYSIS

Dimensions Google Scholar Table of Contents Microsoft Academic Scimagojr Fuzzy logic control of hybrid systems including renewable energy in microgrids PDF Scholar Metrics Omar Feddaoui, Riad Toufouti, Labed Jamel, Salima Meziane 5559-5569 Scilit Scinapse Total views : 193 times Scopus

Performance investigation of stand-alone induction generator based on STATCOM for wind PDF power application 5570-5578 QUICK LINKS Ahmed J. Ali, Mohammed Y. Suliman, Laith A. Khalaf, Nashwan S. Sultan Total views : 33 times Editorial Boards Abstracting and Indexing Fractional-order sliding mode controller for the two-link robot arm PDF Focus and Scope 5579-5585 Trong-Thang Nguyen Author Guideline Total views : 52 times Online Submissions Publication Ethics The Best Journal Power losses reduction of power transmission network using optimal location of low-level PDF Contact Us generation 5586-5591 Marwa M. Marei, Manal H. Nawer Total views : 100 times JOURNAL CONTENT Survey on Deep Learning applied to predictive maintenance PDF Youssef Maher, Boujemaa Danouj 5592-5598 Search Total views : 45 times Search Scope Real-time simulation of static synchronous condenser (STATCOM) for compensation of reactive PDF All power 5599-5608 Search Abdellatif Hinda, Mounir Khiat

Total views : 28 times Browse By Issue Time-domain harmonic extraction algorithms for three-level inverter-based shunt active power PDF By Author filter under steady-state and dynamic-state conditions-an evaluation study 5609-5620 By Title Ali Saadon Al-Ogaili, Agileswari Ramasamy, Yap Hoon, Renuga Verayiah, Marayati Marsadek, Tengku Juhana, Nur Azzammudin Rahmat INFORMATION Total views : 24 times For Readers The assesement of the shunt active filter efficiency under varied power supply source and load PDF For Authors 5621-5630 parameters For Librarians Yuriy Sychev, Boris Abramovich, Veronika Prokhorova Total views : 12 times

Investigation of deformation of the cornea during tonometry using FEM PDF Bharathi R. B., Gopalakrishna Prabhu, Ramesh S. Ve, Rakshath Poojary, S. Meenatchi 5631-5641 Sundaram Total views : 17 times

Design and implementation of 4 bit binary weighted current steering DAC PDF Jayeshkumar J. Patel, Amisha P. Naik 5642-5649 Total views : 69 times

Temperature characteristics of FinFET based on channel fin width and working voltage PDF Yousif Atalla, Yasir Hashim, Abdul Nasir Abd. Ghafar, Waheb A. Jabbar 5650-5657 Total views : 52 times

Speech encryption by multiple chaotic map with fast fourier transform PDF Yahia Alemami, Mohamad Afendee Mohamed, Saleh Atiewi, Mustafa Mamat 5658-5664 Total views : 32 times

A novel algorithm for detection of tuberculosis bacilli in sputum smear fluorescence images PDF Erwin Dianderas, Christian del Carpio, Mirko Zimic, Patricia Sheen, Jorge Coronel, Roberto 5665-5677 Lavarello, Guillermo Kemper Total views : 66 times

http://ijece.iaescore.com/index.php/IJECE/issue/view/564 Page 1 of 7 Vol 10, No 6 29/06/20 21.41

An efficient method to classify GI tract images from WCE using visual words PDF R. Ponnusamy, S. Sathiamoorthy, R. Visalakshi 5678-5686 Total views : 19 times

Motion artifacts reduction in cardiac pulse signal acquired from video imaging PDF Murthad Al-Yoonus, Mustafa H. Alhabib, Mustafa Zuhaer Nayef Al-Dabagh, M. F. L. Abdullah 5687-5693 Total views : 10 times

Recognition of additional myo armband gestures for myoelectric prosthetic applications PDF Jabbar Salman Hussain, Ahmed Al-Khazzar, Mithaq Nama Raheema 5694-5702 Total views : 10 times

Optimization of Boundary Skin Lesions of Different Databases using Swarm Intelligence PDF Technique 5703-5708 mohanad hasan Hassan ali Total views : 17 times

Development of algorithm for identification of maligant growth in cancer using artificial neural PDF network 5709-5713 R. Pandian, D.N.S. Ravi Kumar, R. Raja Kumar Total views : 13 times

Preliminary process in blast cell morphology identification based on image segmentation PDF methods 5714-5725 Retno Supriyanti, Pangestu F. Wibowo, Fibra R. Firmanda, Yogi Ramadhani, Wahyu Siswandari Total views : 12 times

Hiding text in speech signal using K-means, LSB techniques and chaotic maps PDF Iman Qays Abduljaleel, Amal Hameed Khaleel 5726-5735 Total views : 11 times

Color image encryption based on chaotic shit keying with lossless compression PDF Ashwaq T. Hashim, Bahaa D. Jalil 5736-5748 Total views : 22 times

Calculating voltage magnitudes and voltage phase angles of real electrical networks using PDF artificial intelligence techniques 5749-5757 Meriem Fikri, Omar Sabri, Bouchra Cheddadi Total views : 11 times

Gender classification using custom convolutional neural networks architecture PDF Fadhlan Hafizhelmi Kamaru Zaman 5758-5771 Total views : 12 times

A Haptic feedback system based on leap motion controller for prosthetic hand application PDF Hussam K. Abdul-Ameer, Luma Issa Abdul-Kreem, Huda Adnan, Zahra Sami 5772-5778 Total views : 140 times

Short-term wind speed forecasting system using deep learning for wind turbine applications PDF Gokhan Erdemir, Aydin Tarik Zengin, Tahir Cetin Akinci 5779-5784 Total views : 128 times

Performance comparison of different control strategies for the regulation of DC-DC negative PDF output super-lift luo-converter 5785-5792 Hassan Jassim Motlak, Ahmed S. Rahi Total views : 24 times

LMI based antiswing adaptive controller for uncertain overhead cranes PDF Nga Thi-Thuy Vu 5793-5801 Total views : 30 times

Model predictive control of magnetic levitation system PDF Lafta E. Jumaa Alkurawy, Khalid G. Mohammed 5802-5812 Total views : 21 times

A New design of fuzzy logic controller optimized By PSO-SCSO applied To SFO-DTC induction PDF motor drive 5813-5823 Ali Taieb, Abdellaziz Ferdjouni Total views : 25 times

Q-Learning vertical handover scheme in two-tier LTE-A networks PDF Ammar Bathich, Mohd Asri Mansor, Saiful Izwan Suliman, Sinan Ghassan Abid Ali 5824-5831 Total views : 76 times

Cyber DoS attack based security simulator for VANET PDF Muntadher Naeem Yasir, Muayad Sadik Croock 5832-5843 Total views : 16 times

Software engineering based self-checking process for cyber security system in VANET PDF Muntadher Naeem Yasir, Muayad Sadik Croock 5844-5852 Total views : 63 times

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Design and testing of a dynamic reactive signage network towards fire emergency evacuations PDF Christopher S. Baidal, Nestor X. Arreaga, Vladimir Sanchez Padilla 5853-5860 Total views : 48 times

Radiation performance enhancement of an ultra wide band antenna using metamaterial band- PDF pass filter 5861-5870 Marwa Daghari, Hedi Sakli Total views : 16 times

Automatic recognition of the digital modulation types using the artificial neural networks PDF Saad S. Hreshee 5871-5882 Total views : 136 times

Design and implementation of a java based virtual laboratory for data communication PDF simulation 5883-5890 Obinna Okoyeigbo, Edevbie Agboje, Evioghene Omuabor, Uyi Aiyudubie Samson, Abidemi Orimogunje Total views : 57 times

Internet of things–based vital sign monitoring system PDF Alamsyah Alamsyah, Mery Subito, Mohammad Ikhlayel, Eko Setijadi 5891-5898 Total views : 20 times

Compressive spectrum sensing using two-stage scheme for cognitive radio networks PDF Montadar Abas Taher, Mohammad Z. Ahmed, Emad Hmood Salman 5899-5908 Total views : 14 times

Improving keyword extraction in multilingual texts PDF Bahare Hashemzahde, Majid Abdolrazzagh-Nezhad 5909-5916 Total views : 12 times

Sentiment analysis of comments in social media PDF Abdulrahman Alrumaih, Ali Al-Sabbagh, Ruaa Alsabah, Harith Kharrufa, James Baldwin 5917-5922

Total views : 9 times

Distributed differential beamforming and power allocation for cooperative communication PDF networks 5923-5931 Samer Alabed, Issam Maaz, Mohammad Al-Rabayah Total views : 14 times

Design and implement a smart system to detect intruders and firing using IOT PDF Hussam Jawad Kadhim, Mohammed Jabbar MohammedAmeen 5932-5939 Total views : 83 times

Design and implementation a network mobile application for plants shopping center using QR PDF code 5940-5950 Saja Nasir, Salih Al-Qaraawi, Muayad Croock Total views : 8 times

An effective RGB color selection for complex 3D object structure in scene graph systems PDF Chung Le Van, Gia Nhu Nguyen, Tri Huu Nguyen, Tung Sanh Nguyen, Dac-Nhuong Le 5951-5964 Total views : 89 times

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic PDF hill climbing 5965-5973 Mr. Raghavendra Y. M., Dr. U. B. Mahadevaswamy Total views : 82 times

Medical vision: web and mobile medical image retrieval system based on google cloud vision PDF I Ketut Gede Darma Putra, Dewa Made Sri Asra, I Gusti Ngurah Dwiva Hardijaya, I Gede 5974-5984 Galang Surya Prabawa, I Made Aris Satia Widiatmika Total views : 24 times

An analysis of software aging in cloud environment PDF Shruthi P., Nagaraj G. Cholli 5985-5991 Total views : 42 times

Multilingual twitter sentiment analysis using machine learning PDF K. Arun, A. Srinagesh 5992-6000 Total views : 45 times

An image-based gangrene disease classification PDF Pramod Sekharan Nair, Tsrity Asefa Berihu, Varun Kumar 6001-6007 Total views : 88 times

An efficient data masking for securing medical data using DNA encoding and chaotic system PDF Siddartha B. K., Ravikumar G. K. 6008-6018 Total views : 16 times

Video content analysis and retrieval system using video storytelling and indexing techniques PDF Jaimon Jacob, M. Sudheep Elayidom, V. P. Devassia 6019-6025 Total views : 13 times

Examining relationship between service quality, user satisfaction, and performance impact in PDF http://ijece.iaescore.com/index.php/IJECE/issue/view/564 Page 3 of 7 Vol 10, No 6 29/06/20 21.41

the context of smart government in UAE 6026-6033 Ali Ameen, Dawoud Al-Ali, Osama Isaac, Fathey Mohammed Total views : 38 times

A statistical analysis of corpus based approach on learning sentence patterns PDF S. Bhargavi, K. Anbazhagan 6034-6038 Total views : 12 times

A risk and security assessment of VANET availability using attack tree concept PDF Meriem Houmer, Moulay Lahcen Hasnaoui 6039-6044 Total views : 14 times

Transformation of WSDL files using ETL in the E-orientation domain PDF Adib Jihad, Moutachaouik Hicham, Marzak Abdelaziz, Hain Mustapha 6045-6052 Total views : 17 times

Development modeling methods of analysis and synthesis of fingerprint deformations images PDF Haider Hassan Majeed AlKaraawi, Mohammed Qasim Dhahir, Ibrahim Ahmed Alameri, 6053-6060 Mowafak K. Mohsen Total views : 32 times

Automated server-side model for recognition of security vulnerabilities in scripting languages PDF Rabab F. Abdel-Kader, Mona Nashaat, Mohamed I. Habib, Hani M. K. Mahdi 6061-6070 Total views : 13 times

An approach for a multi-stage under-frequency based load shedding scheme for a power 6071-6100 system network Mkhululi Elvis Siyanda Mnguni, Yohan Darcy Total views : 0 times

Development of a photovoltaic characteristics generator based on mathematical models for four PV panel technologies Samia Jenkal, Mustapha Kourchi, Driss Yousfi, Ahmed Benlarabi, Mohamed Larbi Elhafyani, Mohamed Ajaamoum, Mhand Oubella, Azeddine Rachdy, Otmane Oussalem Total views : 47 times

Optimal coordinated design of PSS and UPFC-POD using intelligent optimization technique based on DEO algorithm to enhance the damping performance Omar Mohammed Nida Total views : 20 times

A real-time fault diagnosis system for high-speed power system transmission line protection based on machine learning algorithms Elmahdi Khoudry, Abdelaziz Belfqih, Tayeb Ouaderhman, Jamal Boukherouaa, Faissal Elmariami Total views : 40 times

Sliding mode performance control applied to a DFIG system for a wind energy production Mansouri FatimaZohra, Bendjebbar Mokhtar, Mazari Benyounes Total views : 36 times

Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm Mohammed Hamouda Ali, Mohammed Mehanna, Elsaied Othman Total views : 54 times

A new exact equivalent circuit of the medium voltage three-phase induction motor Laura Collazo Solar, Angel A. Costa Montiel, Miriam Vilaragut Llanes, Vladimir Sousa Santos, Abel Curbelo Colina Total views : 49 times

Application of swarm intelligence algorithms to energy management of prosumers with wind power plants P. V. Matrenin, V. Z. Manusov, N. Khasanzoda, D. V. Antonenkov Total views : 4 times

Fuel enhancement of parallel hybrid electric two-wheeler motorcycle (PHETM) V. Krithika, C. Subramani Total views : 8 times

A generalized switching function-based SVM algorithm of single-phase three-leg converter with active power decoupling Watcharin Srirattanawichaikul Total views : 2 times

Evaluation of lightweight battery management system with field test of electric bus in campus transit system Watcharin Srirattanawichaikul, Paramet Wirasanti Total views : 1 times

Feasibility and optimal design of a hybrid power system for rural electrification for a small village in nigeria Bankole Adebanji, Gafari Abiola Adepoju, Paul Olulope, Taiwo Fasina, Oluwumi Adetan Total views : 8 times

GA_PI controller for stability of TCP network Mohammed Qasim Sulttan, Manal Hadi Jaber, Salam Waley Shneen Total views : 22 times http://ijece.iaescore.com/index.php/IJECE/issue/view/564 Page 4 of 7 Vol 10, No 6 29/06/20 21.41

Design and implementation of a grid-tied emergency back-up power supply for medium power applications Dhiman Chowdhury, Mohammad Sharif Miah, Md. Feroz Hossain, Uzzal Sarker Total views : 274 times

Enhance the chromatic uniformity and luminous efficiency of WLEDs with triple-layer remote phosphor structures Nguyen Thi Phuong Loan, Anh Tuan Le Total views : 13 times

Design and optimization of cost-effective coldproof portable enclosures for polar environment Behzad Parsi, Lihong Zhang Total views : 2 times

A stage-structured delayed advection reaction-diffusion model for single species Raed Ali Alkhasawneh Total views : 1 times

Oscillations minimization at MPP by controlling non-linear dynamics in SEPIC converter based MPPT in PV system M. Vaigundamoorthi, R. Ramesh, V. Vasan Prabhu, K. Arul Kumar Total views : 204 times

PSO-CCO_MIMO-SA:A Particle Swarm Optimization based channel capacity optimzation for MIMO system incorporated with smart Shivapanchakshari T. G., H. S. Aravinda Total views : 20 times

Identification of interstitial lung diseases using deep learning Nidhin Raju, Anita H. B., Peter Augustine Total views : 9 times

Object gripping algorithm for robotic assistance by means of deep learning Robinson Jimenez-Moreno, Astrid Rubiano Fonseca, Jose Luis Ramirez Total views : 17 times

Tool delivery robot using convolutional neural network Javier Pinzon-Arenas, Robinson Jimenez-Moreno Total views : 5 times

PID vs LQR controller for tilt rotor airplane Aoued Houari, Imine Bachir, Della Krachai Mohame, Mohamed Kara Mohamed Total views : 25 times

Cuckoo search algorithm based for tunning both PI and FOPID controllers for the DFIG-wind energy conversion system Mostafa A. Al-Gabalawy, N. S. Hosny, Shimaa A. Hussien Total views : 49 times

Visual control system for grip of glasses oriented to assistance robotics Robinson Jimenez-Moreno, Astrid Rubiano, Jose L. Ramirez Total views : 121 times

Improving the delivered power quality from WECS to the grid based on PMSG control model Shimaa A. Hussien, M. A. Deab, N. S. Hosny Total views : 1 times

Evaluation of non-parametric identification techniques in second order models plus dead time Carlos Robles-Algarín, Omar Rodríguez, Adalberto Ospino Total views : 11 times

Text documents clustering using modified multi-verse optimizer Ammar Kamal Abasi, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, Syibrah Naim, Mohammed A. Awadallah, Osama Ahmad Alomari Total views : 22 times

Design and implementation of proposed 320 bit RC6-Cascaded encryption/decryption cores on altera FPGA Ashwaq T. Hashim, Ahmed M. Hasan, Hayder M. Abbas Total views : 39 times

Demand robust counterpart open capacitated vehicle routing problem time windows and deadline (DRC-OCVRPtw,d) model of garbage transportation in sukarami sub-district, palembang with LINGO 13.0 Fitri Maya Puspita, Ani Sahara Br. Simanjuntak, Rima Melati, Sisca Octarina Total views : 11 times

Automated Smart Hydroponics System Using Internet of Things raed abdulla, Ravi Lakshmanan, Mohamed Djama, Sathish Perumal Total views : 15 times

A decentralized consensus application using blockchain ecosystem http://ijece.iaescore.com/index.php/IJECE/issue/view/564 Page 5 of 7 Vol 10, No 6 29/06/20 21.41

Chetana Pujari, Balachandra Muniyal, Chandrakala C. B. Total views : 24 times

Physical layer security and energy efficiency over different error correcting codes in wireless sensor networks Mohammed Ahmed Magzoub, Azlan Abd Aziz, Mohammed Ahmed Salem, Hadhrami Ab Ghani, Azlina Abdul Aziz, Azwan Mahmud Total views : 1 times

The effect of technology-organization-environment on adoption decision of big data technology in thailand Wanida Saetang, Sakchai Tangwannawit, Tanapon Jensuttiwetchakul Total views : 1 times

reliable and efficient data dissemination scheme In VANET : A Review Sami Abduljabbar Rashid, Lukman Audah, Mustafa Maad Hamdi, Mohammed Salah Abood, Sameer Alani Total views : 9 times

Analysis of threats and security issues evaluation in mobile P2P networks Ali Abdulwahhab Mohammed, Dheyaa Jasim kadhim, Saba Qasim Jabbar Total views : 22 times

Improving the initial values of VFactor suitable for balanced modulus Kritsanapong Somsuk Total views : 3 times

The feasibility of obstacle awareness forwarding scheme in a visible light communication vehicular network (VLC-VN) Lisa Kristiana, Arsyad Ramadhan Darlis, Irma Amelia Dewi Total views : 12 times

A new hybrid text encryption approach over mobile ad hoc network Mohammed Amin Almaiah, Ziad Dawahdeh, Omar Almomani, Adeeb Alsaaidah, Ahmad Al- Khasawneh, Saleh Khawatreh Total views : 27 times

Spectrum sharing in cognitive radio networks Julian Martinez, Cesar Hernandez, Luis Pedraza Total views : 3 times

Investigating a theoretical framework for E-learning technology acceptance Barween Al Kurdi, Muhammad Alshurideh, Said A. Salloum Total views : 14 times

Numerical algorithm for solving second order nonlinear fuzzy initial value problems A. F. Jameel, N. R. Anakira, A. H. Shather, Azizan Saaban, A. K. Alomari Total views : 13 times

Ontology-Based context-sensitive software security knowledge management modeling Mamdouh Alenezi Total views : 25 times

On solving fuzzy delay differential equation using bezier curves Ali F. Jameel, Sardar G. Amen, Azizan Saaban, Noraziah H. Man Total views : 6 times

An effective identification of crop diseases using faster region based convolutional neural network and expert systems P. Chandana, G. S. Pradeep Ghantasala, J. Rethna Virgil Jeny, Kaushik Sekaran, Deepika N., Yunyoung Nam, Seifedine Kadry Total views : 16 times

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fMRI-based brain decoding with visual semantic model Piyawat Saengpetch, Luepol Pipanmemekaporn, Suwatchai Kamolsantiroj Total views : 17 times

Multi-objective PF and PSO algorithms for power dissipation reduction in microprocessors Diary R. Sulaiman Total views : 6 times

Courses timetabling based on hill climbing algorithm Abdoul Rjoub Total views : 3 times

Prediction of atmospheric pollution using neural networks model of fine particles in the town of kennedy in bogotá Juan Camilo Pedraza, Oswaldo Alberto Romero, Helbert Eduardo Espitia Total views : 44 times

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Authentication and password storing improvement using SXR algorithm with a hash function Jakkapong Polpong, Pongpisit Wuttidittachotti Total views : 0 times

A mathematical model of movement in virtual reality through thoughts Ivan Trenchev, Radoslav Mavrevski, Metodi Traykov, Ilire Zajmi–Rugova Total views : 3 times

Feature extraction of electrocardiogram signal using machine learning classification Sumanta Kuila, Namrata Dhanda, Subhankar Joardar Total views : 3 times

Evaluation of graphic effects embedded image compression Chanintorn Jittawiriyanukoon, Vilasinee Srisarkun Total views : 8 times

A native enhanced elastic extension tables multi-tenant database Magy El Banhawy, Walaa Saber, Fathy Amer Total views : 0 times

A systematic review of text classification research based on deep learning models in language Ahlam Wahdan, Sendeyah AL Hantoobi, Said A. Salloum, Khaled Shaalan Total views : 6 times

Development in building fire detection and evacuation system-A comprehensive review Gajanand S. Birajdar, Rajesh Singh, Anita Gehlot, Amit Kumar Thakur Total views : 15 times

Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care Rafid Sagban, Haydar Abdulameer Marhoon, Raaid Alubady Total views : 8 times

Software engineering based fault tolerance model for information system in plants shopping center Saja Nasir, Muayad Croock, Salih Al-Qaraawi Total views : 90 times

Improved feature exctraction process to detect seizure using CHBMIT-dataset Raveendra Kumar T. H., C. K. Narayanappa Total views : 146 times

ISSN 2088-8708, e-ISSN 2722-2578

http://ijece.iaescore.com/index.php/IJECE/issue/view/564 Page 7 of 7 Editorial Team 29/06/20 21.42

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Editor-in-Chief CITATION ANALYSIS Prof. nzw. dr hab. inz. Lech M. Grzesiak, Warsaw University of Technology, Poland Dimensions Managing Editors Google Scholar Microsoft Academic Scimagojr Assoc. Prof. Dr. Tole Sutikno, Universitas Ahmad Dahlan, Indonesia Scholar Metrics Dr. Auzani Jidin, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia Scilit Scinapse Associate Editors Scopus

Prof. Dr. Ahmad Saudi Samosir, Universitas Lampung, Indonesia Prof. Dr. Ahmed Attiya, Electronics Research Institute of , Egypt QUICK LINKS Prof. Dr. Fateh Krim, Université Sétif 1, Prof. Dr. Faycal Djeffal, University of Batna 2, Algeria Prof. Dr. Geetam Singh Tomar, University of Kent, Editorial Boards Prof. Dr. Jia-Chin Lin, National Central University, Taiwan Abstracting and Prof. Dr. Mihaela M. Albu, Politehnica University of Bucharest, Romania Indexing Focus and Scope Prof. Dr. Nidhal Bouaynaya, Rowan University, Glassboro, Author Guideline Prof. ing. Salvatore Favuzza, Ph.D., University of Palermo, Italy Online Submissions Prof. Dr. Sayed M. El-Rabaie, Minufiya University, Egypt Publication Ethics Prof. Dr. Tarek Bouktir, Ferhat Abbes University, Setif, Algeria The Best Journal Prof. Dr. Valeri M. Mladenov, Technical University of Sofia, Bulgaria Contact Us Prof. Dr. Abdullah M. Iliyasu, Tokyo Institute of Technology, Japan and Prince Sattam Bin Abdulaziz University, Saudi Arabia Assoc. Prof. Dr. Angela Amphawan, Universiti Utara Malaysia, Malaysia and Massachusetts Institute of Technology, United States Assoc. Prof. Dr. Chau Yuen, Singapore University of Technology and Design, Singapore Assoc. Prof. Dr. Giovanni Pau, Kore University of Enna, Italy JOURNAL CONTENT Assoc. Prof. Dr. Jaime Lloret Mauri, Polytechnic University of Valencia, Spain Assoc. Prof. Dr. Ke-Lin Du, Concordia University, Canada Search Assoc. Prof. Dr. Larbi Boubchir, University of Paris 8, Assoc. Prof. Dr. Lisandro Lovisolo, Universidade do Estado do Rio de Janeiro, Brazil Search Scope Assoc. Prof. Dr. Ming-Fong Tsai, National United University, Taiwan All Assoc. Prof. Dr. Naci Genc, Yuzuncu Yil University, Turkey Assoc. Prof. Dr. Nik Rumzi Nik Idris, Universiti Teknologi Malaysia, Malaysia Search Assoc. Prof. Dr. Winai Jaikla, King Mongkut's Institute of Technology Ladkrabang, Thailand Assoc. Prof. Dr. Wudhichai Assawinchaichote, King Mongkut's University of Technology Thonburi, Thailand Browse Asst. Prof. Dr. Luca Cassano, Politecnico di Milano, Italy Dr. Brij Bhooshan Gupta, National Institute of Technology Kurukshetra, India By Issue By Author Dr. Imran Shafique Ansari, Texas A&M University, Qatar By Title Dr. Junjie Lu, Broadcom Corp., United States Dr. Laura García-Hernández, University of Córdoba, Spain Dr. Makram Abdulmuttaleb Fakhry, University of Technology, Baghdad, Iraq INFORMATION Dr. Mohd Ashraf Ahmad, Universiti Malaysia Pahang, Malaysia Dr. Nizam Uddin Ahamed, University of Calgary, Canada For Readers Dr. Omar Naifar, University of Sfax, For Authors Dr. Santhanakrishnan Anand, New York Institute of Technology, United States For Librarians Dr. Tossapon Boongoen, Mae Fah Luang University, Thailand Dr. Vicente Garcia Diaz, University of Oviedo, Spain Dr. Zheng Xu, IBM Corporation, United States Editorial Board Members

Prof. Dr. Abdel Ghani Aissaoui, University of Bechar, Algeria Prof. Dr. Addisson Salazar, Universidad Politécnica de Valencia, Spain Prof. Dr. Jun Ma, Lanzhou University of Technology, Prof. Dr. Kewen Zhao, Qiongzhou University, China Prof. Dr. Krzysztof Szczypiorski, Warsaw University of Technology, Poland Prof. Dr. Raj Senani, Netaji Subhas University of Technology, India Prof.univ.dr.ing. Radu A. Vasiu, Politehnica University of Timisoara, Romania Prof. Dr. Abdelhamid Benaini, Normandy University, France Assoc. Prof. Dr. Chatchawal Wongchoosuk, Kasetsart University, Thailand Prof. Dr. Chia-Hung Wang, Fujian University of Technology, China Assoc. Prof. Farrokh Attarzadeh, Ph.D., University of Houston, United States Assoc. Prof. Dr. Jinsong Wu, Universidad de Chile, Chile Assoc. Prof. Dr. Kottakkaran Sooppy Nisar, Prince Sattam bin Abdulaziz University, Saudi Arabia Assoc. Prof. Dr. Mochammad Facta, Universitas Diponogoro (UNDIP), Indonesia Assoc. Prof. Dr. Mohammed Issam Younis, University of Baghdad, Iraq Assoc. Prof. Dr. Nabil Neggaz, Université des Sciences et de la Technologie d’Oran , Algeria Assoc. Prof. Dr. Panagiotis Varzakas, Technological Educational Institute (T. E. I.) of Lamia, Greece Assoc. Prof. Dr. Y. V. Pavan Kumar, VIT-AP University, Amaravati, India Dr. Achinta Baidya, Mizoram University, India Dr. Ali Hakam, General Electric, United Arab Emirates Dr. Alivelu Manga Parimi, Birla Institute of Technology and Science (BITS), Pilani, India Dr. Amit Prakash Singh, Guru Gobind Singh Indraprastha University, India Dr. Athanasios Salamanis, Information Technologies Institute, Greece Dr. Brijesh B. Mehta, S. V. National Institute of Technology, India Dr. Ceren Kaya, Zonguldak Bulent Ecevit University, Turkey Dr. Chrysovalantou Ziogou, Chemical Process and Energy Resources Institute (CPERI), Greece

http://ijece.iaescore.com/index.php/IJECE/about/editorialTeam Page 1 of 2 Editorial Team 29/06/20 21.42

Dr. Deris Stiawan, C|EH, C|HFI, Universitas Sriwijaya, Indonesia Dr. Hanane Arahmane, Mohammed V University, Dr. Haruna Chiroma, Federal College of Education Technical, Nigeria Dr. Hedieh Sajedi, University of Tehran, Iran, Islamic Republic of Dr. Hidayat Zainuddin, Universiti Teknikal Malaysia Melaka, Malaysia Dr. Jiashen Teh, Universiti Sains Malaysia, Malaysia Dr. Jinqi Zhu, Tianjin Normal University, China Dr. Jun-Cheol Jeon, Kumoh National Institute of Technology, Korea, Republic of Dr. Koushik Dutta, Netaji Subhash Engineering College, India Dr. Laith Abualigah, Amman Arab University, Jordan Dr. M. Bhargav Sri Venkatesh, Indian Institute of Technology Bombay, India Dr. Mehrdad Ahmadi Kamarposhti, Jouybar Branch, Islamic Azad University, Iran, Islamic Republic of Dr. Meng Li, The Hong Kong Polytechnic University, China Dr. Mohammad Alibakhshikenari, University of Rome “Tor Vergata”, Italy Dr. Mohammad Yazdani-Asrami, University of Strathclyde, United Kingdom Dr. Mowafak K. Mohsen, University of Kerbala, Iraq Dr. Munawar A Riyadi, Universitas Diponegoro, Indonesia Dr. Nuri Yilmazer, Texas A&M University-Kingsville, United States Dr. Omer Saleem, National University of Computer and Emerging Sciences, Pakistan Dr. P. Gopi Krishna, K L University, India Prof. Peng Zhang, Stony Brook University, United States Dr. Prabira Kumar Sethy, Veer Surendra Sai University of Technology, India Dr. Rajvikram Madurai Elavarasan, Sri Venkateswara College of Engineering, India Dr. Ranjit Kumar Barai, Jadavpur University, India Dr. Sandipann P. Narote, Government Women Residence Polytechnic, India Dr. Shadi A. Alboon, Yarmouk University, Jordan Dr. Wei Liu, University of Sheffield, United Kingdom

ISSN 2088-8708, e-ISSN 2722-2578

http://ijece.iaescore.com/index.php/IJECE/about/editorialTeam Page 2 of 2 International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 6, December 2020, pp. 5974∼5984 ISSN: 2088-8708, DOI: 10.11591/ijece.v10i6.pp5974-5984 Ì 5974 Medical vision: Web and mobile medical image retrieval system based on google cloud vision

I Ketut Gede Darma Putra, Dewa Made Sri Arsa, I Gusti Ngurah Dwiva Hardijaya, I Gede Galang Surya Prabawa, I Made Aris Satia Widiatmika Information Technology, Faculty of Engineering, Universitas Udayana, Indonesia

Article Info ABSTRACT

Article history: The application of information technology is rapidly utilized in the medical system. Received Jul 28, 2019 There is also a massive development in the automatic method for recognizing and detecting objects in the real world. In this study, we present a system called Medical Revised Apr 1, 2020 Vision which is designed for people who has no expertise in medical. Medical Vi- Accepted May 2, 2020 sion is a web and mobile-based application to give an initial knowledge in a medical Keywords: image. This system has 5 features; object detection, web detection, object labeling, safe search, and image properties. These features are run by embedding Google Vi- Image retrieval sion API in the system. We evaluate this system by observing the result of some Medical imaging medical images which inputted into the system. The results showed that our system Mobile application presents a promising performance and able to give relevant information related to the Web application given image.

Copyright c 2020 Insitute of Advanced Engineeering and Science. All rights reserved. Corresponding Author: I Ketut Gede Darma Putra, Information Technology, Faculty of Engineering, Universitas Udayana, Mengwitani, Bali, Indonesia. Email: [email protected]

1. INTRODUCTION In this globalization era, technology has been in touch in numerous living aspects. In education, massive technological development brings a new learning method which is called online learning or distance learning. Barbara et al. [1] show that students who take online learning performed better than those who take face-to-face instruction. In the medical field, moreover, intelligent technology is adapted to present and analyze the medical image to help the reader (doctor, nurse, etc.) in making the right decision. A computerized analysis system was firstly initiatedby Lusted in 1960s. He showed that an automatic system could be used to determine the abnormality in chest photofluorograms [2]. Others work later studied a computer analysis and diagnosis on bone cancer image [3]. Since then, various computer-assisted diagnosis (CAD) systems were developed in medical image. When designing CAD, the characteristic of image has to address firstly to ensure the kind of method needed to improve the performance of the system. Medical image is taken from a high-end medical device which cannot gain by human vision capabilities. This image has two characteristics; high resolution and high pixel depth [4]. However, in a certain condition, the produced image is not clear enough because of noises. Therefore, improving the quality of the image is necessary to deliver valuable information to the doctor. In advance, an intelligent system can be used to provide an early diagnosis for them. To deal with medical image challenges, various research tried to addopt an intelligent method to pro- cess and provide analysis automatically. In breast cancer, the research area is detecting cancer in hyperspectral imaging [5], breast cancer classification [6, 7], optical imaging and augmented reality visualization [8, 9]. Then, automatic methods were build to Lung diseases on CT images [10, 11]. Moreover, similar methods were also created to analyze skin diseases from skin image [12-21]. If we take a look in more detail on the method,

Journal homepage: http://ijece.iaescore.com Int J Elec & Comp Eng ISSN: 2088-8708 Ì 5975 deep learning has been chosen recently and massively as one of the methods for automatically analyzing the medical image [22-39]. Deep learning has been widely used to analyze medical images in skin lesion classifica- tion [19-21], breast cancer classification [23-26], and melanoma detection [27-29]. From those research, their methods are built for the medical environment for specific task. Since advancing method in machine learning, like deep learning, and availability tons of image processing libraries which can be used freely, a system which can assist human to improve their understanding on the medical image is highly needed. In this paper, different with previous research, we proposed a system with deep analysis on medical image. Our system is design to produce extensive analysis on a given medical image. Our system can detect medical object and analyze it for better understanding on it. We design our system to run on web-based system. To improve mobility of our system, we also develope a mobile-based application. These systems are embedded five features. The first feature is medical object detection. Its purpose is detecting all objects occurred in the scene. The second feature is medical website detection which is designed to search related articles or images associate with the given image. The third feature is object labeling. This feature performs entity categorization and rank the results based on confidence score. The fourth feature is safe search which aims to classify the type of content related to the given image. The last feature is image properties. It provides the detail of the image based on pixel information. This study is written as follows. In section 2. we provide brief information about Google Vision. Then, we present our proposed system in section 3. After that, in section 4. we present the detail of system implementation, the result of the experiments, and some discussions of the result. Then, we give the conclusion of this study and insight for future research in section 5.

2. GOOGLE CLOUD VISION API Google cloud vision API is a service from Google cloud platform (GCP) that can provide an analysis of an image. This API was released on May 18, 2017, with Machine Learning and Big Data technology which became the engine behind it. Cloud Vision API is used to identify objects in an image such as text, symbols, and types of product objects digitally. Google has many scenarios in the Cloud Vision API. For example developers can use Cloud Vision API to detect whether there is a mobile in the image, detect inappropriate content, analyze someone’s emotions recorded in the image, and extract the writing. Cloud Vision API supports the detection of objects in images using the same technology on Google Photos so that developers can find out the names of objects in a photo. Besides, this API can be used to avoid inappropriate image content detected with Google SafeSearch. Cloud Vision API can also be used to analyze people’s emotions and detect various logos from famous products. Google’s API is also able to detect the letters contained in images with automatic language identification.

3. PROPOSED SYSTEM Generally, the process of our proposed system can be seen in Figure 1a. The image will be uploaded to our system. Our engine will analyze it and provide several informations. We realized these information as features. We designed five features on our system. Those features are object detection, label detection, web detection, image properties, and safe search. Each feature delivers different information to the user. Those features will be explained as follows: (a) Object Detection: This feature is used to detect objects which can be found in the uploaded image. The detected objects will be rounded with a square. (b) Label Detection: For each image uploaded by the user, Medical Vision will analyze the type of content occurred in it. For example, an actinic keratosis image is uploaded to the system. This system will produce several labels correlated to the image which have been sorted by their confidence score. For the actinic keratosis case, the detected labels will be finger, skin, hand, and thumb, joint, nail, gesture, flesh, and wrist. (c) Web Detection: This feature is used to recommend related websites which explain the image in more detail. Two types category of website are produced; partially matched images and pages. Beside of this links, two more information are given in this feature. The first information is the best guess la- bel which mostly matched for the given image. Secondly, this feature presents entities information. These entities present related diseases related to the image. For example, given an image labeled as actinic keratoses, our system will produce several entities; actinic keratosis, keratosis, actinic cheilitis,

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skin cancer, a precancerous condition, keratoses, seborrheic keratosis, therapy, skin, and lesion. The first label has the highest confidence score. (d) Image Properties: Image properties feature is used to analyze the image based on its pixel value. This feature gives the detail information of entities produced in web detection feature. For each entity, three values are computed; RGB, score, and pixel fraction. (e) Safe Search: Safe search feature is used to categorize the image into content classes. In this feature, the image will categorize into adult content, spoof content, medical content, violence content, and racy content. For each category, a score will be given as very likely, likely, possible, unlikely, and very unlikely. For example, the image in Figure 1b will be annotated likely as Medical content, possible as Violence and Racy content, and very unlikely as Adult and Spoof content.

(a) (b) Figure 1. a) Medical image will be inputted to our system for analysis process on five features and b) Example of medical image: actinic keratosis disease

Figure 2. The architecture of medical vision system

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To improve ease of access, we designed our system in the form of a web-based system and android application. As seen in Figure 2, the user can upload an image through both applications. This image will be sent to a web server. This server makes a request to Google Vision Server using Google Vision API. After that, this Google Vision Server produces the image references and send it back to the web server in JSON file. Lastly, the web server will send this result to the user.

4. RESULT AND DISCUSSION As stated previously, Medical Vision was developed in a web-based and mobile-based system. The web-based system was developed under HTML while the mobile application was designed for Android only. As shown in Figure 2, the uploaded image in both browser and mobile-apps will be processed in the web server where process this image using Google Vision API. We evaluate this system by inputting several medical images into the system; actinic keratosis, bullous pemphigoid, chickenpox, eczema, herpes zoster, impetigo, keloid, keratoacanthoma, lichen planus, melanoma, pustular psoriasis, seborrheic keratosis, and tinea barbae.

4.1. Web-based implementation The example of our implementation can be seen in Figure 3-8. In this example, we test our system by inputting the Actinic Keratosis image. Actinic keratosis (AK) is a disease that can occur in our skin caused by ultraviolet radiation. As shown in Figure 3, we upload a picture which is classified as AK. The object analysis tells that the image is labeled as Person with confidence score by 86.17%. Then, in Figure 4, the labels predicted by our system shows that the image is related to finger, skin, hand, thumb, joint, nail, gesture, flesh, and whist where the highest score is obtained as finger. Interestingly, in web detection feature, our system accurately predicts the image as AK with confidence score by 87.34% followed by keratos, artinic chelitis, skin cancer, a precancerous condition, keratoses, seborrheic keratosis, therapy, skin, and lesion as shown in Figure 5. When the web detection result is clicked, the page will be directed to the new page which will show some information related to the image. In the safe search feature, furthermore, the system will give a general type of content for the given image as shown in Figure 8. For AK image, the result is classified likely as medical content, possible for violence and racy content, and very unlikely as adult and spoof content.

4.2. Mobile-based implementation The implementation of Medical Vision in mobile apps can be seen in Figure 9. This image is actually hands which were affected by Leprosy disease in https://www.who.int/lep/disease/en/. This disease is showed that it infects the skin but it also may affect peripheral nerves. As shown in Figure 9a, the system detects two objects in the given image. Those objects are glove and animal where glove has the highest confidence score. In label detection, the labels results show that it highly related to the image qualitatively. Interestingly, the web detection presents that the image labeled as Leprosy with 81.49% evidence score. The apps also provide a similar image from the website.

Figure 3. Object detection result for actinic keratosis image

Medical vision: Web and mobile medical image retrieval system... (I Ketut Gede Darma Putra) 5978 Ì ISSN: 2088-8708

Figure 4. Label detection result for actinic keratosis image

Figure 5. Web detection result for actinic keratosis image

Figure 6. Example preview when the link in web detection result was clicked

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Figure 7. Image properties result for actinic keratosis image

Figure 8. Safe search result for actinic keratosis image

(a) (b)

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(c) (d) Figure 9. Implementation result of Medical vision in mobile application, a) Object detection, b) Label detection, c) Web detection, and d) Similar image (continue)

4.3. Performance analysis The previous subsection shows the example of the implementation of Medical Vision in web-based and mobile-based system. Beside of that, we evaluate our system performance for 13 medical images. We gather the results in Table 1 The first column presents the actual label of the image. In the second col- umn, the detected object for each image is presented aside with the highest confidence score. From those result, most of the objects are highly correlated in qualitatively. However, in pustular psoriasis and seborrheic keratosis, the object detection results are not fit the actual image. In pustular psoriasis, a watermelon object is detected while a baked good is identified in seborrheic keratosis. If we observe, however, the pustular psoriasis image, this disease will make a pattern in the skin and has a similar pattern like watermelon. The label detection results show promising result where all of them presents high relation to the disease. In the majority, the skin label has the highest confidence score. For actinic keratosis, the sample image which is shown in Figure 3, is classified as a finger. An interesting result is shown in the web search feature. In Table 1 (see appendix) most guess labels was closely matched the actual image labels. The web search entities are also mostly related to the actual image label. For impetigo, keratoacanthoma, pustular psoriasis, and seborrheic keratosis, web search feature produces uncorrelated labels. However, their entities show that the results for impetigo and pustular psoriasis images are not fit but others match up the labels. This labeling error may occur because of model limitation. The safe search feature also shows promising. The results present that all test images categorize as medical content, but not all images predict VL. In actinic keratosis, the image classifies likely as medical image. From those results, there is a relation between medical and violence content. When the image labeled as medical content, it also will be said as violence content. For example, impetigo image is predicted VL as medical content and L as medical content.

5. CONCLUSION In this study, we have been presented our system which is called Medical Vision. Our system is utilized Google Cloud Vision API for processing the image. This system was built for common people with less knowledge in the medical image. Based on our evaluation, our system may work properly in the given test case. This system still needs some enhancements in the image processing method. In Google Cloud Vision, the model was trained using various objects, so it will not cover all of the medical objects. Therefore, a new model is recommended to be built in the future.

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APPENDIX

Table 1. The result of our system analysis, VU: very unlikely, U: unlikely, P: possible, L: likely, VL: very likely Actual Image label Object Detection Label Detection Web Search (Best guess labels) Web Search (Entities) Safe Search Actinic Keratosis Person : 86.17 Finger : 96.17 Keratose Acinique Actinic Keratosis : 83.34 Adult : VU Keratosis Spoof : VU Actinic chellitis Medical : L Skin cancer Violence : P Precancerous condition Racy : P Bullous Pemhigoid Egg : 53,34 Skin : 97.21 Bullous Pemphigoid Bullous pemphigoid : 73.01 Adult : VU Nose Linear IgA bullous dermatosis Spoof : VU Jaw Bullous dermatoses Medical : VL Mouth Skin condition Violence : VL Flesh Cicatricial pemphigoid Racy : P Chickenpox Skin : 96,61 Chickenpox Chickenpox : 88.36 Adult : VU Pink Smallpox Spoof : VU Close-up Varicella zoster virus Medical : VL Peach Attenuated vaccine Violence : L Flesh MMR vaccine Racy : VU Eczhema Person : 95.12 Skin : 97.37 Eczema on hands Dermatitis : 72.24 Adult : VU Hand Dyshidrosis Spoof : VU Fing Hand eczema Medical : VL Close-up Eczema Violence : P Flesh Dermatitis Racy : P Herpes zoster Skin : 97.47 Herpes Zoster Shingles : 73.59 Adult : U Close-up Varicella zoster virus Spoof : VU Muscle Chickenpox Medical : VL Lip Herpex simplex virus Violence : VL Flesh Therapy Racy : P Impetigo Skin : 97 Close-up Stock photography Adult : U Finger Impetigo Spoof : VU Hand Science photo library Medical : VL Flesh - Violence : L Joint Thumb Racy : VL Keloid Lipstick Skin Hypertropic and keloid scar Scar Adult : VU Scar Keloid Spoof : VU Lip Hypertropic scar Medical : VL Cheek Surgery Violence : L Close-up therapy Racy : P Keratoacanthoma Skin Close up Keratoacanthoma Adult : VU Nose Spoof : VU Close-up Medical : VL Flesh Violence : VL Novel Racy : U Linchen Planus Skin Lichen planus skin Lichen planus Adult : VU Joint Spoof : VU Hand Medical : VL Close-up Violence : VL Scar Racy : P Melanoma Lipstick Skin Melanoma skin cancer Skin cancer Adult : VU Brown Melanoma Spoof : VU EyeBrow Cancer Medical : VL Cheek Melanocyte Violence : VL Lip Dermatology Racy : P Pustular psoriasis Watermelon Skin Red meat Apple iphone 8 Adult : VU Flesh Apple Spoof : VU Red meat Pustule Medical : VL Water Psoriasis Violence : L Close-up Fine art america Racy : U Seborrheic keratosis Baked Good Skin Rock Seborrheic keratosis Adult : VU Coockie Keratosis Spoof : VU Dessert - Medical : P Food Actinic Keratosis Violence : U Snack Melanoma Racy : VU Tinea Barbae Lipstick Skin Tinea barbae Tinea barbae Adult : VU Lip - Spoof : VU Face Mycosis Medical : VL Chin Tinea caphis Violence : L Nose Tinea corporis Racy : L

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ACKNOWLEDGEMENT This research was funded by Ministry of Research, Technology, and Higher Education of the Republic of Indonesia with grant number 492.67/UN14.4.A/LT/2019 entitled by ”Smart Medical Record (Sistem Rekam Medis Elektronik Online Terintegrasi dengan Dukungan Fingerprint, Tele Image Medicine, Smart Card, dan GIS Google Map)”.

REFERENCES [1] B. Means, et al., ”Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies,” Centre for Learning Technology, 2009. [2] L. B. Lusted, “Logical analysis in roentgen diagnosis: memorial fund lecture,” Radiology, vol. 74, no. 2, pp. 178–193, 1960. [3] G. S. Lodwick, ”Radiographic diagnosis and grading of bone tumors, with comments on computer eval- uation,” Proceedings National Cancer Conference, vol. 5, pp. 369–380, 1964. [4] A. Ortiz, J. Gorriz, J. Ramırez, D. Salas-Gonzalez, and J. M. Llamas-Elvira, “Two fully-unsupervised methods for mr brain image segmentation using som-based strategies,” Applied Soft Computing, vol. 13, no. 5, pp. 2668–2682, 2013. [5] R. Pike, G. Lu, D. Wang, Z. G. Chen, and B. Fei, “A minimum spanning forest-based method for nonin- vasive cancer detection with hyperspectral imaging,” IEEE Transactions on Biomedical Engineering, vol. 63, no. 3, pp. 653–663, 2015. [6] S. Reis, et al., ”Automated classification of breast cancer stroma maturity from histological images,” IEEE Transactions on Biomedical Engineering, vol. 64, no. 10, pp. 2344–2352, 2017. [7] J. Xu, L. Xiang, Q. Liu, H. Gilmore, J. Wu, J. Tang, and A. Madabhushi, “Stacked sparse autoencoder (ssae) for nuclei detection on breast cancer histopathology images,” IEEE transactions on medical imag- ing, vol. 35, no. 1, pp. 119–130, 2015. [8] X. Chen, D. Yang, F. Sun, X. Cao, and J. Liang, “Adaptively alternative light-transport-model-based three- dimensional optical imaging for longitudinal and quantitative monitoring of gastric cancer in live animal,” IEEE Transactions on Biomedical Engineering, vol. 63, no. 10, pp. 2095–2107, 2015. [9] Y. Sato, et al., “Image guidance of breast cancer surgery using 3-d ultrasound images and augmented reality visualization,” IEEE Transac- tions on Medical Imaging, vol. 17, no. 5, pp. 681–693, 1998. [10] Y. Chunran, W. Yuanvuan, and G. Yi, “Automatic detection and segmentation of lung nodule on ct im- ages,” 11th International Congress on Image and Signal Processing, BioMedical Engineering and Infor- matics, pp. 1–6, 2018. [11] X. Liu, L. Ma, L. Song, Y. Zhao, X. Zhao, and C. Zhou, “Recognizing common ct imaging signs of lung diseases through a new feature selection method based on fisher criterion and genetic optimization,” IEEE journal of biomedical and health informatics, vol. 19, no. 2, pp. 635–647, 2014. [12] M. Sadeghi, T. K. Lee, D. McLean, H. Lui, and M. S. Atkins, “Detection and analysis of irregu- lar streaks in dermoscopic images of skin lesions,” IEEE Transactions on Medical Imaging, vol. 32, no. 5, pp. 849–861, 2013. [13] D. H. Chung and G. Sapiro, “Segmenting skin lesions with partial-differential-equations-based image processing algorithms,” IEEE transactions on Medical Imaging, vol. 19, no. 7, pp. 763–767, 2000. [14] R. Suganya, “An automated computer aided diagnosis of skin lesions detection and classification for dermoscopy images,” International Conference on Recent Trends in Information Technology, pp. 1–5, 2016. [15] A. H. Shahin, A. Kamal, and M. A. Elattar, “Deep ensemble learning for skin lesion classification from dermo- scopic images,” 9th Cairo International Biomedical Engineering Conference, pp. 150–153, 2018. [16] T. Polevaya, R. Ravodin, and A. Filchenkov, “Skin lesion primary morphology classification with end- to-end deep learning network,” International Conference on Artificial Intelligence in Information and Communication, pp. 247–250, 2019. [17] M. A. Albahar, “Skin lesion classification using convolutional neural network with novel regularizer,” IEEE Access, vol. 7, pp. 306–313, 2019. [18] K. Shimizu, H. Iyatomi, M. E. Celebi, K.-A. Norton, and M. Tanaka, “Four-class classification of skin lesions with task decomposition strategy,” IEEE transactions on biomedical engineering, vol. 62, no. 1, pp. 274–283, 2014.

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[19] O. Abuzaghleh, B. D. Barkana, and M. Faezipour, “Noninvasive real-time automated skin lesion analysis system for melanoma early detection and prevention,” IEEE journal of translational engineering in health and medicine, vol. 3, pp. 1–12, 2015. [20] J. Kawahara, S. Daneshvar, G. Argenziano, and G. Hamarneh, “Seven-point checklist and skin lesion classifica- tion using multitask multimodal neural nets,” IEEE journal of biomedical and health informat- ics, vol. 23, no. 2, pp. 538–546, 2018. [21] F. Rundo, S. Conoci, G. L. Banna, A. Ortis, F. Stanco, and S. Battiato, “Evaluation of leven- berg–marquardt neural networks and stacked autoencoders clustering for skin lesion analysis, screening and follow-up,” IET Computer Vision, vol. 12, no. 7, pp. 957–962, 2018. [22] D. Mulfari, A. Celesti, M. Fazio, M. Villari, and A. Puliafito, “Using google cloud vision in assistive technology scenarios,” IEEE Symposium on Computers and Communication (ISCC), pp. 214–219, 2016. [23] P. Meyer, V. Noblet, C. Mazzara, and A. Lallement, “Survey on deep learning for radiotherapy,” Com- puters in Biology and Medicine, vol. 98, pp. 126–146, 2018. [24] J. de la Torre, A.Valls, and D. Puig, “A deep learning interpretable classifier for diabetic retinopathy disease grading,” Neurocomputing, 2019. [25] A. B. Levine, C. Schlosser, J. Grewal, R. Coope, S. J. Jones, and S. Yip, “Rise of the machines: Advances in deep learning for cancer diagnosis,” Trends in Cancer, vol. 5, no. 3, pp. 157–169, 2019. [26] M. P. McBee, et al., “Deep learning in radiology,” Academic Radiology, vol. 25, no. 11, pp. 1472–1480, 2018. [27] J. Zhang, Y. Xie, Q. Wu, and Y. Xia, “Medical image classification using synergic deep learning,” Medical Image Analysis, vol. 54, pp. 10 – 19, 2019. [28] R. Wason, “Deep learning: Evolution and expansion,” Cognitive Systems Research, vol. 52, pp. 701–708, 2018. [29] A. Mahbod, G. Schaefer, I. Ellinger, R. Ecker, A. Pitiot, and C. Wang, “Fusing fine-tuned deep features for skin lesion classification,” Computerized Medical Imaging and Graphics, vol. 71, pp. 19–29, 2019. [30] P. M. Burlina, N. J. Joshi, E. Ng, S. D. Billings, A. W. Rebman, and J. N. Aucott, “Automated detection of erythema migrans and other confounding skin lesions via deep learning,” Computers in Biology and Medicine, vol. 105, pp. 151–156, 2019. [31] A. Dascalu and E. David, “Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope,” EBioMedicine, vol. 43, pp. 107–113, 2019. [32] M. Chen, P. Zhou, D. Wu, L. Hu, M. M. Hassan, and A. Alamri, “Ai-skin : Skin disease recognition based on self-learning and wide data collection through a closed loop framework,” Information Fusion, 2019. [33] S. Khan, N. Islam, Z. Jan, I. U. Din, and J. J. P. C. Rodrigues, “A novel deep learning based framework for the detection and classification of breast cancer using transfer learning,” Pattern Recognition Letters, vol. 125, pp. 1–6, 2019. [34] X. Li, M. Radulovic, K. Kanjer, and K. N. Plataniotis, “Discriminative pattern mining for breast can- cer histopathology image classification via fully convolutional autoencoder,” IEEE Access, vol. 7, pp. 433–445,2019. [35] M. K. Elbashir, M. Ezz, M. Mohammed, and S. S. Saloum, “Lightweight convolutional neural network for breast cancer classification using rna-seq gene expression data,” IEEE Access, vol. 7, pp. 338–185, 2019. [36] D. Bardou, K. Zhang, and S. M. Ahmad, “Classification of breast cancer based on histology images using convolutional neural networks,” IEEE Access, vol. 6, pp. 680–693, 2018. [37] S. H. Kassani and P. H. Kassani, “A comparative study of deep learning architectures on melanoma detection,” Tissue and Cell, vol. 58, pp. 76–83, 2019. [38] A. A. Adegun and S. Viriri, “Deep learning-based system for automatic melanoma detection,” IEEE Access, 2019. [39] L. Yu, et al., “Automated melanoma recognition in dermoscopy images via very deep residual networks,” IEEE transactions on medical imaging, vol. 36, no. 4, pp. 994–1004, 2016.

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BIOGRAPHIES OF AUTHORS I Ketut Gede Darma Putra was born in Mengwitani, 24 April 1974. A lecturer in Department of Information Technology, Udayana University Bali, Indonesia. He received his S.Kom degree in Informatics Engineering from Institute of Sepuluh November Technology Surabaya, Indonesia on 1997. He received his Master Degree on Informatics and Computer Engineering from Electrical Engineering Department, Gadjah Mada University, Indonesia on 2000 and achieved his Doctorate Degree on Informatics and Computer Engineering from Electrical Engineering Department, Gadjah Mada University, Indonesia on 2006. His research interests are Biometrics, Image Processing, Data Mining, and Soft Computing.

Dewa Made Sri Arsa is a lecturer in Department of Information Technology, Universitas Udayana, Bali, Indonesia. In 2014, he obtained Bachelor degree in Computer Science, Universitas Udayana. Then, he collected the Master degree in Faculty of Computer Science, Unversitas Indonesia. Cur- rently, he actively studies in the applicaiton of machine learning in various areas. He is also interested in image processing, nature inspired based optimization method, and computer vision.

I Gusti Ngurah Dwiva Hardijaya is undergraduate student in Department of Information Technol- ogy, Universitas Udayana, Bali, Indonesia. He deeply studied data and information management. Beside of it, he actively develops mobile application.

I Gede Galang Surya Prabawa is undergraduate student in Department of Information Technology, Universitas Udayana, Bali, Indonesia. His research interest is UI and UX. He studied more in data and information management.

I Made Aris Satia Widiatmika is undergraduate student in Department of Information Technology, Universitas Udayana, Bali, Indonesia. He was born in Bali, Indonesia. He took data and information management field on study. Moreover, he attracts to learn about big data technology and internet of things.

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