Innovations in Electrical and Electronics Engineering
Description
This book features selected high-quality papers presented at the 2024 International Conference on Electrical and Electronics Engineering (ICEEE 2024), Jointly organized by ADSRS Education and Research and Swinburne University of Technology, Melbourne, Australia during September 11-12, 2024, at Advanced Technologies Centre, Swinburne University of Technology, 427-451 Burwood Rd, Hawthorn VIC 3122. The book covers electrical engineering topics-power and energy including renewable energy, power electronics and applications, control, and automation and instrumentation and book two covers the areas of robotics, artificial intelligence and IoT, electronics devices, circuits and systems, wireless and optical communication, RF and microwaves, VLSI, signal processing, and others. The book brings both single- and multidisciplinary research on these topics to provide the most up-to-date information in one place. The book offers an asset for researchers from both academia and industries involved in advanced studies.
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Akhtar Kalam has been associated with Victoria University (VU) since 1985. He is a former deputy dean of the Faculty of Health, Engineering, and Science and Head of Engineering of the College of Engineering and Science. Currently, he is the head of External Engagement. He is also the current chair of the Academic Board in the Engineering Institute of Technology, Perth, Australia, and the editor in chief of the Australian Journal of Electrical & Electronics Engineering. Further, he has a distinguished professorship position at the University of New South Wales, Sydney, Australia, three Indian and five Malaysian universities. He has also been appointed as the editor in chief of the Australian Journal of Electrical and Electronic Engineering. He received his B.Sc. and B.Sc. Engineering from Calcutta University and Aligarh Muslim University, India, respectively.
Saad Mekhilef is an IEEE and IET fellow. He is a distinguished professor at the School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Melbourne, Australia, an honorary professor at the Department of Electrical Engineering, University of Malaya, and a distinguished visiting professor at the Institute of Sustainable Energy, Universiti Tenaga Nasional, Malaysia. He authored and co-authored more than 700 publications in academic journals and proceedings, five books with more than 55,000 citations, and more than 85 Ph.D. students who graduated under his supervision. He serves as an editorial board member for many top journals, such as IEEE Transactions on Power Electronics, IEEE Open Journal of Industrial Electronics, IET Renewable Power Generation, E-Prime, Journal of Power Electronics, and International Journal of Circuit Theory and Applications. His research interests include Power Conversion Techniques, Control of Power Converters, Maximum Power Point Tracking (MPPT), Renewable Energy, and Energy Efficiency.
Sheldon Williamson (sheldon.williamson@ontariotechu.ca) is a professor with the Department of Electrical, Computer, and Software Engineering and the director of the Smart Transportation Electrification and Energy Research Group, Faculty of Engineering and Applied Sciences, Ontario Tech University, Oshawa, ON LIG 0C5, Canada. His research interests include advanced power electronics, electric energy storage systems, and motor drives for transportation electrification. He holds the prestigious Natural Sciences and Engineering Research Council of Canada research chair in electric energy storage systems for transportation electrification.
Content
1. SPP CNN Spatial Pyramid Pooling for Optimizing Brain Tumor Classification.- 2. KAN PDEs A Novel Approach to Solving Partial Differential Equations Using Kolmogorov Arnold Networks Enhanced Accuracy and Efficiency.- 3. Dynamic Indian Sign Language Sentence Captioning System Using Machine Learning.- 4. The Rehab Reco A Therapy Recommender System for Dementia.- 5. Implementation of Machine learning and Ensemble learning models for the prediction of CKD and drugs side effect.- 6. Adverse Weather Object Detection using Customised YOLO models.- 7. Cryptographic Security and Decentralization A Blockchain based Approach to Healthcare Data Integrity.- 8. Predicting Brain Age Using Lightweight 3D CNN Architecture from T1 Weighted MRI Images.- 9. Performance analysis of a Deep Learning-based Object Detection Approach for Post disaster Buildings Damage Level Assessment using YOLO and Faster R CNN.- 10. LSTM based Predictive Leader Follower Control Scheme for Networked Drones.