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Big Data, Machine Learning, and Applications: Proceedings of the 2nd International Conference, BigDML 2021: 1053 (Lecture Notes in Electrical Engineering, 1053) - Hardcover

 
9789819934805: Big Data, Machine Learning, and Applications: Proceedings of the 2nd International Conference, BigDML 2021: 1053 (Lecture Notes in Electrical Engineering, 1053)

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This book constitutes refereed proceedings of the Second International Conference on Big Data, Machine Learning, and Applications, BigDML 2021. The volume focuses on topics such as computing methodology; machine learning; artificial intelligence; information systems; security and privacy. This volume will benefit research scholars, academicians, and industrial people who work on data storage and machine learning.

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About the Author

Dr. Laiphrakpam Dolendro Singh is an Assistant Professor in the Department of Computer Science & Engineering, National Institute of Technology Silchar, Assam, India. He receives his Master’s Degree and a Ph.D. degree from the National Institute of Technology Agartala, India, and the National Institute of Technology Manipur, India respectively. His research interests are cryptography, cryptanalysis, watermarking, and steganography. He has published several research papers in reputed journals. He is a life member of the Cryptography Research Society of India. He has acted as chair of various international conferences. 

Dr. Malaya Dutta Borah is an Assistant Professor in the Department of Computer Science and Engineering, National Institute of Technology Silchar, Assam, India. Her research areas include data mining, BlockChain technology, cloud computing, e-Governance, and machine learning. She has authored several book chapters and over 44 papers in reputedjournals and conferences. She is awarded two Australian Patents. She has edited several books published by reputed international publishers. 

Dr. Nitin Auluck is an Associate Professor in the Computer Science and Engineering Department of the Indian Institute of Technology Ropar. He obtained his B. Tech. in Electrical and Electronics Engineering from Poojya Dodappa Appa College of Engineering Gulbarga in 1998 and a Ph.D. in Computer Science and Engineering from the University of Cincinnati USA in 2005. His research interest is in fog/edge computing. He has published several research papers in top-tier journals and conferences. Currently, he is serving as an Editor for the journal Concurrency and Computation: Practice and Experience (CCPE), published by Wiley.

Prof. Valentina Emilia Balas is currently a Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. She holds a Ph.D. Cum Laude, in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Dr. Balas is the author of more than 350 research papers in refereed journals and International Conferences. Her research interests are in intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling, and simulation. Dr. Balas is the director of the Intelligent Systems Research Centre at the Aurel Vlaicu University of Arad and the Director of the Department of International Relations, Programs, and Projects at the same university. Dr. Balas was past Vice-president (responsible for Awards) of IFSA - International Fuzzy Systems Association Council (2013-2015), is a Joint Secretary of the Governing Council of the Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, in India, and recipient of the “Tudor Tanasescu” Prize from the Romanian Academy for contributions in the field of soft computing methods (2019).

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This book constitutes refereed proceedings of the Second International Conference on Big Data, Machine Learning, and Applications, BigDML 2021. The volume focuses on topics such as computing methodology; machine learning; artificial intelligence; information systems; security and privacy. This volume will benefit research scholars, academicians, and industrial people who work on data storage and machine learning.

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