7th International Conference on Wireless, Intelligent and Distributed Environment for Communication

Professor Isaac Woungang received his Ph.D. degree in Mathematics from University of South, Toulon and Var, France in 1994. From 1999 to 2002, he worked as Senior Software Engineer at Nortel Networks, Ottawa, Canada. Since 2002, he has been with Ryerson University, where he is now a Professor of Computer Science and Director of the DABNEL Research Lab. His current research interests include radio resource management in next generation wireless networks, computer security, computational intelligence and machine learning applications, performance modelling, and optimization. He has published more than 8 edited books, 1 authored book, and over 100 refereed journals and conference papers.Dr. Sanjay Kumar Dhurandher received the M. Tech. and Ph.D. Degrees in Computer Sciences from the Jawaharlal Nehru University, New Delhi, India. He is presently, Professor and Head at the Department of Information Technology, Netaji Subhas University of Technology (formerly NSIT), New Delhi, India. Prior to this, from 1995 to 2000 he worked as a Scientist/Engineer at the Institute for Plasma Research, Gujarat, India which is under the Department of Atomic Energy, India. His current research interests include wireless ad-hoc networks, sensor networks, computer networks, opportunistic networks, network security and Underwater Sensor Networks.  He is serving as the Associate Editor of Wiley’s International Journal of Communication Systems. He is also a Senior Member of IEEE and Fellow of IETE.

• Chapter 1. Implicit Test Case Identification/Selection for Test Case Prioritisation using Natural Language Processing .- Chapter 2. Feasibility of Adversarial Attacks Against Machine Learning Models.- Chapter 3. Enhanced Public Safety: Real-Time Crime Detection with CNN-LSTM in Video Surveillance.- Chapter 4. Deep Reinforcement Learning-Based Open and Hybrid Switching-Driven Software-Defined Networking:  Adaptability and Comparison.- Chapter 5. Machine Learning Algorithms for Energy Consumption Prediction in Smart Homes: A Comparative Study.- Chapter 6. IoT Device Fingerprinting for Anomaly Detection.- Chapter 7. Survey-Based Machine Learning Models for Early Detection of Diabetes .- Chapter 8. OptimizingWearable Sensors with Multi-Feature Approximate Computing.- Chapter 9. Breast Cancer Histology Images Segmentation Using Connected Component Analysis.- Chapter 10. Optimized Smart Insole Design for Temporal Gait Parameters Measurement.- Chapter 11. Transforming Agriculture: Disease and Pest Management through CNN-Based Image Classification in Computer Vision.- Chapter 12. Anomaly detection in PD-NOMA Cognitive Radio IoT Networks.