This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox's Bazar, Bangladesh, during 23-25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Autorentext

Professor Dr. Mohammad Shamsul Arefin is affiliated with the Department of Computer Science and Engineering (CSE), Chittagong University of Engineering and Technology, Bangladesh. Earlier he was the Head of the Department. Prof. Arefin received his Doctor of Engineering Degree in Information Engineering from Hiroshima University, Japan with support of the scholarship of MEXT, Japan. As a part of his doctoral research, Dr. Arefin was with IBM Yamato Software Laboratory, Japan. His research includes privacy preserving data publishing and mining, distributed and cloud computing, big data management, multilingual data management, semantic web, object oriented system development and IT for agriculture and environment. Dr. Arefin has more than 110 referred publications in international journals, book series and conference proceedings. He is a senior member of IEEE, Member of ACM, Fellow of IEB and BCS. Dr. Arefin is the Organizing Chair of BIM 2021; TPC Chair, ECCE 2017; Organizing Co-Chair, ECCE 2019; and Organizing Chair, BDML 2020. Dr. Arefin visited Japan, Indonesia, Malaysia, Bhutan, Singapore, South Korea, Egypt, India, Saudi Arabia and China for different professional and social activities. Dr. M Shamim Kaiser is currently working as Professor at the Institute of Information Technology of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. He received his Bachelor's and Master's degrees in Applied Physics Electronics and Communication Engineering from the University of Dhaka, Bangladesh, in 2002 and 2004, respectively, and the Ph. D. degree in Telecommunication Engineering from the Asian Institute of Technology, Thailand, in 2010. His current research interests include data analytics, machine learning, wireless network and signal processing, cognitive radio network, big data and cyber security, renewable energy. He has authored more than 100 papers in different peer-reviewed journals and conferences. He is Associate Editor of the IEEE Access Journal, Guest Editor of Brain Informatics Journal and Cognitive Computation Journal. He is Life Member of Bangladesh Electronic Society; Bangladesh Physical Society. He is also a senior member of IEEE, USA, and IEICE, Japan, and active volunteer of the IEEE Bangladesh Section. He is the founding Chapter Chair of the IEEE Bangladesh Section Computer Society Chapter. He organized various international conferences such as ICEEICT 2015-2018, IEEE HTC 2017, IEEE ICREST 2018 and BI2020. Anirban Bandyopadhyay is Senior Scientist in the National Institute for Materials Science (NIMS), Tsukuba, Japan. He received Ph.D. from Indian Association for the Cultivation of Science (IACS), Kolkata, 2005, December, on Supramolecular Electronics. From 2005 to 2007, he was ICYS Research Fellow NIMS, Japan, and, 2007, is now a permanent Scientist in NIMS, Japan. He has ten patents on building artificial organic brain, big data, molecular bot, cancer and Alzheimer drug, fourth circuit element, etc. From 2013 to 2014, he was a visiting scientist in MIT, USA, on biorhythms. He worked in World Technology Network, as WTN Fellow, (2009 continued); he received Hitachi Science and Technology Award 2010, Inamori Foundation Award 2011-2012, Kurata Foundation Award, Inamori Foundation Fellow (2011), Sewa Society International SSS Fellow (2012), Japan; SSI Gold Medal (2017). Md Atiqur Rahman Ahad, SMIEEE, SMOSA; Professor, University of Dhaka (DU); Specially Appointed Associate Professor, Osaka University. He studied at the University of Dhaka, University of New South Wales, and Kyushu Institute of Technology. His authored/edited 10 books in Springer, e.g., "IoT-sensor based Activity Recognition"; "Motion History Images for Action Recognition and Understanding"; "Computer Vision and Action Recognition". He published 180+ journal/conference papers, chapters, 120+ keynote/invited talks, 35+ Awards/Recognitions. He is an Editorial Board Member of Scientific Reports, Nature; Assoc. Editor of Frontiers in Computer Science; Editor of Int. Journal of Affective Engineering; Editor-in-Chief: IJCVSP; Guest-Editor: PRL, Elsevier; JMUI, Springer; JHE, Hindawi; IJICIC; Member: ACM, IAPR. Kanad Ray (Senior Member, IEEE) received the M.Sc. degree in physics from Calcutta University and the Ph.D. degree in physics from Jadavpur University, West Bengal, India. He has been Professor of Physics and Electronics and Communication and is presently working as Head of the Department of Physics, Amity School of Applied Sciences, Amity University Rajasthan (AUR), Jaipur, India. His current research areas of interest include cognition, communication, electromagnetic field theory, antenna and wave propagation, microwave, computational biology and applied physics. He has been serving as Editor for various Springer book series. He was Associate Editor of the Journal of Integrative Neuroscience (The Netherlands: IOS Press). He has been visiting Professor to UTM & UTeM, Malaysia, and visiting Scientist to NIMS, Japan. He has established MOU with UTeM Malaysia, NIMS Japan and University of Montreal, Canada. He has visited several countries such as Netherlands, Turkey, China, Czechoslovakia, Russia, Portugal, Finland, Belgium, South Africa, Japan, Singapore, Thailand and Malaysia for various academic missions. He has organized various conferences such as SoCPROS, SoCTA, ICOEVCI and TCCE as General Chair and Steering Committee Member.

Inhalt

Performance Analysis of Classi er for Chronic Kidney Disease Prediction Using SVM, DNN, and KNN.- Comparative Analysis of Machine Learning Techniques in Classi cation Cervical Cancer using Isolation Forest with ADASYN.- Computer-Aided Cataract Detection Using Random Forest Classi er.- COV-Doctor: A Machine Learning Based Scheme for Early Identi cation of COVID-19 in Patients.- Ovarian Cancer Prediction from Ovarian Cysts Based on TVUS Using Machine Learning Algorithms.- A Comprehensive Analysis of Most Relevant Features Causes Heart Disease using Machine Learning Algorithms.- Early Stage Detection of Heart Failure using Machine Learning Techniques.- Automatic License Plate Recognition System For Bangladeshi Vehicles Using Deep Neural Network.- Vulnerability Analysis and Robust Training with Additive Noise for FGSM attack on Transfer Learning based Brain Tumor Detection from MRI.- Performance Evaluation of Convolution Neural Network based Object Detection Model for Bangladeshi Träc Vehicle Detection.- Hyperspectral Image Classi cation Using Factor Analysis and Convolutional Neural Networks.- A Convolutional Neural Network Model for Screening COVID-19 Patients Based on CT Scan Images.- Real-Time Face Recognition System for Remote Employee Tracking.