International Conference on Intelligent and Smart Computing in Data Analytics

This book is a collection of best selected research papers presented at International Conference on Intelligent and Smart Computing in Data Analytics (ISCDA 2020), held at K L University, Guntur, Andhra Pradesh, India. The primary focus is to address issues and developments in advanced computing, intelligent models and applications, smart technologies and applications. It includes topics such as artificial intelligence and machine learning, pattern recognition and analysis, computational intelligence, signal and image processing, bioinformatics, ubiquitous computing, genetic fuzzy systems, hybrid evolutionary algorithms, nature-inspired smart hybrid systems, Internet of things, industrial IoT, health informatics, human-computer interaction and social network analysis. The book presents innovative work by leading academics, researchers and experts from industry.

Auteur

Siddhartha Bhattacharyya, FIET (UK), is currently Professor in Christ University, Bangalore, India. He served as a Senior Research Scientist at the Faculty of Electrical Engineering and Computer Science of VSB Technical University of Ostrava, Czech Republic, from October 2018 to April 2019. Prior to this, he was the Principal of RCC Institute of Information Technology, Kolkata, India. He is a co-author of 5 books and a co-editor of 65 books and has more than 300 research publications in international journals and conference proceedings to his credit. His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing.

Janmenjoy Nayak is working as Associate Professor, Aditya Institute of Technology and Management (AITAM), (An Autonomous Institution) Tekkali, K Kotturu, AP- 532201, India. He has published more than 100 research papers in various reputed peer-reviewed refereed journals, international conferences and book chapters. Being two times Gold Medallist in Computer Science in his career, he has been awarded with INSPIRE Research Fellowship from the Department of Science & Technology, Govt. of India (both as JRF and SRF level) and Best Researcher Award from Jawaharlal Nehru University of Technology, Kakinada, Andhra Pradesh, for the AY: 2018-19 and many more awards to his credit. He has edited 11 books and 8 special issues in various topics including data science, machine learning and soft computing with reputed International Publishers like Springer, Elsevier, Inderscience, etc. His area of interest includes data mining, nature-inspired algorithms and soft computing.

Dr. Kolla Bhanu Prakash is working as Professor and Research Group Head in CSE DEPARTMENT, K L University, VIJAYAWADA, Andhra Pradesh, India. He received his M.Sc. and M.Phil. in Physics from Acharya Nagarjuna University, Guntur, India, and M.E. and Ph.D. in Computer Science Engineering from Sathyabama University, Chennai, India. He has 15+ years of experience working in the academia, research, teaching and academic administration. His current research interests include deep learning, data science, smart grids, cyber-physical systems, cryptocurrency, blockchain technology and image processing. He is an IEEE senior member. He has reviewed more than 125 peer-reviewed journals which are indexed in Publons. He is Editor for 6 books in Elsevier, CRC Press, Springer, Wiley and De Gryuter publishers. He published 65 research papers, 6 patents, 8 books + 4 accepted. His Scopus h-index is 14. He is a frequent editorial board member and a TPC member in flagship conferences and refereed journals.

Dr. Bighnaraj Naik is Assistant Professor in the Department of Computer Application, Veer Surendra Sai University of Technology (Formerly UCE Burla), Odisha, India. He received his Ph.D. in Computer Science and Engineering, M.Tech. in Computer Science and Engineering and B.E. in Information Technology in 2016, 2009 and 2006, respectively. He has published more than 80 research papers in various reputed peer-reviewed journals, conferences and book chapters. He has edited more than 10 books from various publishers such as Elsevier, Springer and IGI Global. At present, he has more than ten years of teaching experience in the field of Computer Science and IT. He is a member of IEEE. His area of interest includes data mining, computational intelligence, and its applications. He has been serving as Guest Editor of various journal special issues from Elsevier, Springer and Inderscience.

Dr. Ajith Abraham is Director of Machine Intelligence Research Labs (MIR Labs), a Not-for-Profit Scientific Network for Innovation and Research Excellence connecting Industry and Academia. As Investigator/Co-Investigator, he has won research grants worth over 100+ Million US$ from Australia, USA, EU, Italy, Czech Republic, France, Malaysia and China. Dr. Abraham works in a multi-disciplinary environment involving machine intelligence, cyber-physical systems, Internet of things, network security, sensor networks, Web intelligence, Web services, data mining and applied to various real-world problems. In these areas, he has authored/co-authored more than 1,400+ research publications out of which there are 100+ books covering various aspects of Computer Science. About 1,100+ publications are indexed by Scopus and over 900+ are indexed by Thomson ISI Web of Science. He has 1,100+ co-authors originating from 40+ countries. Dr. Abraham has more than 39,000+ academic citations (h-index of 95 as per google scholar).

Contenu

Performance Analysis of Machine Learning Algorithms over a Network Traffic.- Parkinson's Disease Prediction Using Swarm Intelligence.- An Evolutionary based Additive Tree for Enhanced Disease Prediction.- Novel Defense Frame work for Cross Layer Attacks in Cognitive Radio Networks.- Texture Based Image Retrieval Using GLCM and LBP.- Design and Development of Bayesian Optimization Algorithms for Big data Classification Using Map Reduce Framework.- An IoT Based BLYNK Server Application for Infant Monitoring Alert System to Detect Crying and Wetness of a Baby.- Analysis of DEAP Dataset for Emotion Recognition.- A Machine Learning Approach for Air Pollution Analysis.- Facial Expression Detection Model of Seven Expression Types Using Hybrid Feature Selection and Deep CNN.- Naive Bayes Approach for Retrieval of Video Object Using Trajectories.- An Extensive Survey on IOT Protocols and Applications.