Machine Intelligence and Smart Systems (eBook, PDF)

Proceedings of MISS 2020
Redaktion: Agrawal, Shikha; Gupta, Manish; Agrawal, Jitendra; H. Chan, Jonathan; Kumar Gupta, Kamlesh

• Format: PDF

Produktbeschreibung

This book is a collection of peer-reviewed best selected research papers presented at the First International Conference on Machine Intelligence and Smart Systems 2020 (MISS 2020), organized during September 24-25, 2020, in Gwalior, India. The book presents new advances and research results in the fields of machine intelligence, artificial intelligence and smart systems. It includes main paradigms of machine intelligence algorithms, namely (1) neural networks, (2) evolutionary computation, (3) swarm intelligence, (4) fuzzy systems and (5) immunological computation.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 701
• Erscheinungstermin: 8. April 2021
• Englisch
• ISBN-13: 9789813348936
• Artikelnr.: 61432574

Autorenporträt

Dr. Shikha Agrawal is Director, Centre for University Placement, Training & Corporate Affairs, Rajiv Gandhi Proudyogiki Vishwavidyalaya, and Associate Professor in the Department of Computer Science & Engineering at the University Institute of Technology, RGPV, Bhopal (MP) India. She obtained B.E., M.Tech. and Ph.D. in Computer Science & Engineering. She has more than seventeen years of teaching experience. Her area of interest is artificial intelligence, soft computing, computational intelligence and particle swarm optimization. She has published more than 50 research papers in different SCI/SCIE/Scopus/UGC approved reputed international journals and 03 patents. She authored one book on "Advanced Database Management System" and 12 chapters with international publishers. She is heading research projects from various government organizations. For her outstanding research work in Information Technology, she has been awarded as "Young Scientist" by Madhya Pradesh Councilof Science and Technology, Bhopal. She has been elected as an IEEE senior member and participated in numerous (more than 15) conference presentations (including invited and peer-reviewed oral presentations and panel discussions) and chaired technical sessions in various international conferences and also served as a member of reviewer committee of International Journal of Computer Science and Information Security, USA, and many international conferences of IEEE, Springer, etc. Dr. Kamlesh Kumar Gupta is Principal in Rustamji Institute of Technology (RJIT), BSF Academy, Tekanpur, MP, India. He completed B.E., M.Tech. and Ph.D.  in Computer Science & Engineering from RGPV Bhopal MP, India. He has published more than 40 research papers in various journals and conferences. He organized international conference in emerging trends of computer science and its applications in RJIT.  He also organized various training courses on computer literacy in BorderSecurity Force Academy Tekanpur (MHA). He has guided many Ph.D.s in various universities like RGPV, Uttarakhand Technical University and  Amity University, Gwalior. He is a member of CSI and IETE and a member in BOG of RGPV University Bhopal. Dr. Jonathan H. Chan is an Associate Professor of Computer Science at the School of Technology, King Mongkut's University of Technology Thonburi (KMUTT), Thailand. Jonathan holds a B.A.Sc., M.A.Sc. and Ph.D. degree from the University of Toronto and is currently Visiting Professor there until the end of 2019. He was also Visiting Scientist at The Centre for Applied Genomics at Sick Kids Hospital in Toronto in several occasions. He is Section Editor of Heliyon Computer Science (Cell Press), Action Editor of Neural Networks (Elsevier) and a member of the editorial board of International Journal of Machine Intelligence and Sensory Signal Processing (Inderscience), International Journal of Swarm Intelligence (Inderscience) and Proceedings in Adaptation, Learning and Optimization (Springer). He is a senior member of IEEE, ACM and INNS and a member of the Professional Engineers of Ontario (PEO). His research interests include intelligent systems, cognitive computing, biomedical informatics, and data science and machine learning in general. Dr. Jitendra Agrawal is Associate Professor in the School of Information Technology, at the Rajiv Gandhi Proudyogiki Vishwavidyalaya, MP, India. He earned his master's degree from Samrat Ashok Technology Institute, Vidisha (MP), in 1997, and was awarded Doctor of Philosophy in Computer & Information Technology in 2012. His research interests include database, data structure, data mining, soft computing and computational intelligence. He has published more than 70 publications in international journals and conferences. He authored 4 books and 10 chapters in international publishers. He has also published 3 patents. He is the recipient of the Best Professor in Information Technology Award by the World Education Congress in 2013. He has delivered numerous invited talks and keynote addresses at different academic forums on various emerging issues in the field of Information Technology and Innovations in Teaching Learning System. He is a senior member of the IEEE (USA), a life member of Computer Society of India (CSI), a life member of Indian Society of Technical Education (ISTE) and a member of Youth Hostel Association of India (YHAI) and IAENG.  Mr. Manish Gupta is Assistant Professor in Computer Science & Engineering in Vikrant Institute of Technology & Management Gwalior, MP, India. He has done B.E. from MITS Gwalior MP, India, and M.Tech. from ABV-IIITM Gwalior MP, India, and pursuing Ph.D. from RGPV Bhopal MP, India. He has published more than 25 research papers in various journals, IEEE conferences and Springer conferences. He has published two books. He is currently working on a Central Govt. Project "Unnat Bharat Abhiyan" sanctioned by Govt. of India.

Inhaltsangabe

Synesthetic Learning Pedagogy (SLP): An Exploratory Investigation.- MSB/LSB Prediction Based Reversible Data Hiding In Encrypted Images: A Survey.- A Review of Image Enhancement Techniques in Medical Imaging.- Smartphone User Identification and Authentication based on Raw Accelerometer Walking Activity Data Using Convolutional Neural Networks.- Elastic Optical Network: A Promising Solution For Future Communication Networks Considering Differentiated CoS.- Smart Home Energy Prediction With GTU Recurrent Neural Network Model.