Inventive Communication and Computational Technologies

Dr. G. RANGANATHAN working as a professor and the head in Gnanamani College of Engineering and Technology, Namakal, India. He has done his Ph.D. in the Faculty of Information and Communication Engineering from Anna University, Chennai. in the year 2013. His research thesis was in the area of bio-medical signal processing. He has total of 29+ years of experience in industry, teaching, and research. He has guided several project works for many UG and PG students in the areas of bio-medical signal processing. He has published more than 35 research papers in International and National Journals and Conferences. He has also co-authored many books in electrical and electronics subjects. He has served as a referee for many reputed international journals published by Elsevier, Springer, Taylor and Francis, etc. He has membership in various professional bodies like ISTE, IAENG etc. and has actively involved himself in organizing various international and national level conferences, symposiums, seminars, etc.   Dr. Xavier Fernando is the director of Ryerson Communications Lab that has received total research funding of $3,185,000.00 since 2008 from industry and government (including joint grants). He has (co-)authored over 200 research articles, three books (one translated to Mandarin), and several book chapters and holds few patents. The present and past members and affiliates of this lab can be found at this LinkedIn group and Facebook page. He was an IEEE Communications Society Distinguished Lecturer and has delivered over 50 invited talks and keynote presentations all over the world. He was a member in the IEEE Communications Society (COMSOC) Education Board Working Group on Wireless Communications. He was the chair of IEEE Canada Humanitarian Initiatives Committee 2017-18. He was also the chair of the IEEE Toronto Section and IEEE Canada Central Area.   Dr. Fuqian Shi was graduated from College of Computer Science and Technology, Zhejiang University, and got his Ph.D. on Engineering and was a visiting associate professor at the Department of Industrial Engineering and Management System, University of Central Florida, USA, from 2012 to 2014. Dr. Shi is currently serving for Rutgers Cancer Institute of New Jersey, USA. Dr. Shi is a senior member of IEEE, Membership of ACM, and served as over 30 committee board membership of international conferences. Dr. Shi also served as an associate editors of International Journal of Ambient Computing and Intelligence (IJACI), International Journal of Rough Sets and Data Analysis (IJRSDA), and special issue editors of IEEE Access. He published over 100 journal papers and conference proceedings; his research interests include fuzzy inference system, artificial neuro-networks, and bio-mechanical engineering.   

Chapter 1. Dimensionality Reduction based Component Dicriminant Factor Implication for Mushroom Edibility Classification using Machine Learning.- Chapter 2. Flip-Flop based Approach for Logic Encryption Technique.- Chapter 3. Analysis and Implementation of Less Delay and Low Area DT Multiplier.- Chapter 4. An exploration on Feature Extraction and Classification Techniques for Dysphonic Speech Disorder in Parkinson’s Disease.- Chapter 5. Intelligent Recommender System based on Deep Learning for Recognition of COVID-19 from Lungs Radiograms.- Chapter 6. Generation of Structured Query Language from Natural Language using Recurrent Neural Networks.- Chapter 7. Machine Learning and Deep Learning Approaches for Intrusion Detection: A Comparative Study.- Chapter 8. Improving Text Classifiers through Controlled Text Generation using Transformer Wasserstein Autoencoder.- Chapter 9. Topological analysis of Cube based and Linearly Extensible Networks using MATLAB.- Chapter 10. Implementation of Rule based Testing for Dgital Circuits using Inductive Logic Programming .- Chapter 11. Design of a High Speed Binary Counter using a Stacking Circuit.- Chapter 12. Feature Level Fusion of Multimodal Biometric for Individual Identification by Training a Deep Neural Network.- Chapter 13. Design of Multistage Counters using Linear Feedback Shift Register.- Chapter 14. Machine Learning based and Reconfigurable Architecture with a Countermeasure for Side Channel Attacks.- Chapter 15. Autonomous Scheduling and Distributed Graph Routing Algorithm (ASDGRA) for Hybrid Wireless Sensor Networks.