Advances in Communication, Devices and Networking (eBook, PDF)

Proceedings of ICCDN 2024, Volume 1
Redaktion: Dhar, Sourav; Imoize, Agbotiname Lucky; Sur, Samarendra Nath; Do, Dinh-Thuan; Mukhopadhyay, Subhas

• Format: PDF

Produktbeschreibung

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on January 19-20, 2024. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals, it helps young and experienced scientists and developers alike to explore new perspectives and offers them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 539
• Erscheinungstermin: 20. November 2024
• Englisch
• ISBN-13: 9789819764655
• Artikelnr.: 72198432

Autorenporträt

Dr. Sourav Dhar (Senior Member, IEEE) is currently Professor of the ECE Department, SMIT and Director, CDOE, SMU. His current research interests include IoT, WSN, remote sensing and microwave filter design. He is a Senior member of IEEE  and member of IEI, India. He has published more than 60 research papers in SCI/Scopus-indexed international journals and conferences. Two Ph.D. scholars are awarded degree under his supervision and he is currently guiding four Ph.D. scholars. He also served as a reviewer for several journals like Wireless Personal Communication, IEEE Transactions on Vehicular Technology etc. and for several conferences. Dr. Subhas Mukhopadhyay (M'97, SM'02, F'11) holds a B.E.E. (gold medallist), M.E.E., Ph.D. (India) and Doctor of Engineering (Japan). He has over 33 years of teaching, industrial and research experience. Currently, he is working as a professor of Mechanical/Electronics Engineering at Macquarie University, Australia, and is the discipline leader of the Mechatronics Engineering Degree Program. He is also the director of International Engagement for the School of Engineering of Macquarie University. His fields of interest include smart sensors and sensing technology, wireless sensors and network (WSN), Internet of Things (IoT), wearable sensors, medical devices, healthcare, environmental monitoring, mechatronics and robotics. He has supervised 55 postgraduate students and over 150 Honours students. He has examined 80 postgraduate theses. Dr. Thuan-Dinh Do (IEEE Senior Member) received M.Sc. and Ph.D. degrees in Electrical Engineering from the Vietnam National University-Ho Chi Minh City (VNU-HCM) in 2007 and 2012, respectively. Prior to joining academia, Dr. Thuan worked as a senior engineer in the telecommunications industry at VinaPhone Mobile Network (the biggest cellular network provider in Vietnam) (2003-2009). Before to joining University of Mount Union, he worked as a research scientist at University of Colorado Denver (2022), the University of Texas at Austin (2021), and as an assistant professor at Asia University (Taiwan) (2020-2021). He is currently serving as an associate editor in IEEE Transaction on Vehicular Technology, Computer Communications (Elsevier). Dr. Thuan was the recipient of the 2015 Golden Globe Award by Vietnamese Ministry of Science and Technology (top 10 outstanding scientists nationwide). Dr. Samarendra Nath Sur (M2016, SM'20) received M.Tech. degree in Digital Electronics and Advanced Communication from Sikkim Manipal University in 2012 and Ph.D. degree in MIMO signal processing from National Institute of Technology (NIT), Durgapur, in 2019. Currently, he is working as an assistant professor in the Department of Electronics and Communication Engineering. His current research interests include Broadband Wireless Communication (MIMO and Spread Spectrum Technology), Advanced Digital Signal Processing and Remote Sensing, Radar Image/Signal Processing (Soft Computing). He is a senior member of IEEE, member of IEEE-IoT, IEEE Signal Processing Society, and Institution of Engineers (India)(IEI). He has published more than 95 SCI/Scopus-indexed international journal and conference papers. Agbotiname Lucky Imoize (Senior Member, IEEE) received the B.Eng. degree (Hons.) in Electrical and Electronics Engineering from Ambrose Alli University, Nigeria, and the M.Sc. degree in Electrical and Electronics Engineering from the University of Lagos, Nigeria. He is a lecturer in the Department of Electrical and Electronics Engineering at the University of Lagos, Nigeria. He was formerly a lecturer at Bells University of Technology, Nigeria. He was until recently, a research scholar at Ruhr University Bochum, Germany, under the Nigerian Petroleum Technology Development Fund (PTDF) and the German Academic Exchange Service (DAAD) through the Nigerian-German Postgraduate Program. He was awarded the Fulbright Fellowship as a visiting research scholar at the Wireless@VT Lab, Bradley Department of Electrical and Computer Engineering, Virginia Tech., USA, from 2017 to 2018.  He worked as a core network products manager at ZTE Corporation and a Network Switching Subsystem Engineer at Globacom, Nigeria. He is the Vice Chair of the IEEE Communication Society Nigeria Chapter.

Inhaltsangabe

1. High Speed Congestion Aware Routing Algorithm for Network on Chip Architecture.- 2. Impact of Technology Node on Low Power Analog Performance of AU TFET.- 3. Comparative Analysis of the Electrical and Dielectric Characteristics of a Novel Glassy Ceramic and Its Crystalline Analogue.- 4. DFT Investigation of Fe Doped ZnO Monolayer for Adsorption of Toxic Gases.- 5. Printed Circuit Board Assembly Welding Process Based on Computer Aided Design.- 6. Enhancing Endangered Animal Conservation through Deep Learning-Powered Monitoring.- 7. Direct Approach for Modelling a Class of Fractional Order System Using Two Generating Functions.- 8. Classification of Parkinson's and Control Subjects with Machine Learning.