Data, Engineering and Applications: Select Proceedings of IDEA 2021: 907 (Lecture Notes in Electrical Engineering) - Tapa blanda

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Sanjeev Sharma is a Professor and Director of the School of Information Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, MP, India. Dr. Sharma has over 29 years of teaching and research experience and received the World Education Congress Best Teacher Award in Information Technology. His research interests include mobile computing, ad hoc networks, image processing, and information security. He has edited proceedings of several national and international conferences and published over 150 research papers. He is a Member of IEEE, CSI, ISTE, and IAENG.

Sheng-Lung Peng is a Professor at the Department of CS and Information Engineering, National Dong Hwa University, Taiwan. He did his education in Doctor of Information Engineering from National Tsinghua University. His research interests are designing and analyzing algorithms for bioinformatics, combinatorics, data mining, and networks areas in which he has published over 100 research papers.

Rajesh K Shukla is a Director of Oriental Institute of Science and Technology, Bhopal, India. With over 23 years of teaching and research experience, he has authored/edited 12 books and has published more than 45 papers in international journals and conferences. He was the chair of the CSI Bhopal Chapter and Treasurer of IETE Bhopal. He is the founder chair of the ACM Bhopal Chapter. He is the recipient of several awards such as the ISTE-UP Govt National award 2015, Best Chapter Patron Award and Significant contribution CSI service award from Computer Society of India, Certificate of Exceptional Contribution in Smart India Hackathon 2017 from AICTE. He is a Fellow of IETE, a life member of CSI, ISTE, IETE, IE(India), ISCA, senior member of IEEE and ACM.

Jitendra Agrawal is an Associate Professor and Dean- Student Welfare in the School of Information Technology at the Rajiv Gandhi Proudyogiki Vishwavidyalaya, MP, India. He is a Teacher, Researcher, and Consultant inthe field of Computer Science and Information Technology. He has 23 years of teaching and 18 years of research experience with a good number of citations with h-index and i-index. 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, 04 patents filed, 12 chapters, and five books. He is a senior member of the IEEE (USA), a life member of the Computer Society of India (CSI), a life member of the Indian Society of Technical Education (ISTE), member of the Youth Hostel Association of India (YHAI) and IAENG. He has been associated with the International Program Committees and Organizing Committees of several regular international conferences held in different countries like the USA, India, New Zealand, Korea, Indonesia, Tunisia, Thailand, Morocco, etc. 

Dac-Nhuong Le received M.Sc. and Ph.D. degrees in computerscience from Vietnam National University, Vietnam, in 2009 and 2015, respectively. He is an Associate Professor in the Department of Computer Science, Dean of Faculty of Information Technology, Haiphong University, Vietnam. He has over 20 years of teaching experience with over 80 publications in reputed international conferences and journals. His research areas are intelligent computing, multi-objective optimization, network security, cloud computing, virtual reality/argument reality. Presently, he is serving on the editorial board of international journals and edited/authored 20+ computer science books published by International publishers.

De la contraportada

The book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems and applications. This book will be a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of big data applications.