Emerging Technologies in Data Mining and Information Security
Description
This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during 23-25 February 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT) and information security.
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Dr. Paramartha Dutta is currently Professor in the Department of Computer and System Sciences in, Visva-Bharati University, Shantiniketan, India. He did Bachelors and Masters in Statistics from ISI, Kolkata, India. Subsequently, he did Master of Technology in Computer Science from ISI, Kolkata, India. He did Ph.D. (Engineering) from BESU, Shibpore, India. He is a co-author of eight authored books apart from thirteen edited books and more than 200 and 40 research publications in peer reviewed journals and conference proceedings. He is a co-inventor of 17 published patents. He is Fellow of IETE, Optical Society of India, IEI, Senior Member of ACM, IEEE, Computer Society of India, International Association for Computer Science and Information Technology and Member of Advanced-Computing and Communications Society, Indian Unit of Pattern-Recognition and AI, the Indian Affiliate of the International Association for Pattern Recognition, ISCA, Indian Society for Technical Education, SystemSociety of India.
Dr. Satyajit Chakrabarti is Pro-Vice Chancellor, University of Engineering & Management, Kolkata and Jaipur Campus, India, and Director of Institute of Engineering & Management, IEM. As Director of one of the most reputed organizations in Engineering and Management in Eastern India, he launched a PGDM Programme to run AICTE approved management courses, toppers academy to train students for certificate courses, and software development in the field of ERP solutions. He was Project Manager in TELUS, Vancouver, Canada, from February 2006 to September 2009, where he was intensively involved in planning, execution, monitoring, communicating with stakeholders, negotiating with vendors and cross-functional teams, and motivating members. He managed a team of 50 employees and projects with a combined budget of $3 million.
Dr. Abhishek Bhattacharya is Assistant Professor at Institute of Engineering & Management, India. He has completed his Ph.D. (Engineering), BIT, Mesra. He is certified as Publons Academy Peer Reviewer, 2020. His research interests are data mining, cybersecurity, and mobile computing. She has published 25 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. He has 3 book chapters in Taylor & Francis Group EAI. He is a peer reviewer and TPC member in different international journals. He was the editor in IEMIS 2020, IEMIS 2018 and special issues in IJWLTT. He is the member of several technical functional bodies such as IEEE, IFERP, MACUL, SDIWC, Internet Society, ICSES, ASR, AIDASCO, USERN, IRAN, and IAENG. He has published 3 patents.
Dr. Soumi Dutta is Associate Professor at Institute of Engineering & Management, India. She has completed her Ph.D. (Engineering), IIEST, Shibpur. She received her B.Tech. (IT) and M.Tech. (CSE) securing 1st position (gold medalist), from MAKAUT. She is certified as Publons Academy Peer Reviewer, 2020, andCertified Microsoft Innovative Educator, 2020. Her research interests are data mining, OSN data analysis, and image processing. She has published 30 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. She has 5 book chapters in Taylor-&-Francis Group and IGI-Global. She is a peer reviewer and TPC member in different international journals. She was the editor in CIPR-2020, CIPR2019, IEMIS-2020, CIIR-2021, IEMIS-2018 special issues in IJWLTT. She is member of several technical functional bodies such as IEEE, ACM, IEEE, IFERP, MACUL, SDIWC, Internet-Society, ICSES, ASR, AIDASCO, USERN, IRAN, and IAENG. She has published 4 patents. She has delivered more than Keynote talks in Different International Conferences.
Dr. Celia Shahnaz received Ph.D. degree in electrical and computer engineering from Concordia University, Montreal, QC, Canada, in 2009. Currently she is serving as a Professor in the Department of Electrical and Electronic Engineering, BUET, from where she received her B.Sc. and M.Sc. degrees in 2000 and 2002, respectively. Dr. Celia is a senior member of IEEE, a fellow of IEB and has published more than 80 international journal and conference papers. Recently, she has been selected as the recipient of IEEE Member and Geographic Activities (MGA) Leadership award with citation " For leadership in engineering and technology driven innovative IEEE Women in Engineering activities for enhanced membership development and engagement in Region 10 and across the globe. Dr. Shahnaz was a recipient of the Canadian Commonwealth Scholarship and Fellowship for pursuing Ph.D. study in Canada. She is the recipient of Bangladesh-Academy of Science gold model for her contribution in science and Engineering in Bangladesh. Her research interests include the areas of speech analysis, speech enhancement, digital watermarking, biomedical signal processing, audio-visual recognition for biometric security, pattern recognition, multimedia communication, control system, robotics and signal processing & pattern recognition for power signals.
Content
Part 1: Data Science and Data Analytics.- Chapter 1. Iot Security: Recent Trends And Challenges.- Chapter 2. Assistive Technology for Pedagogical Support and Application of Data Analysis in Neurodevelopmental Disability.- Chapter 3. Developing Smart ML Based Recommendation System.- Chapter 4. Unsupervised Hybrid Change Detection using Geospatial Spectral Classification of Time Series Remote Sensing Datasets.- Chapter 5. Trust based resolving of conflicts for collaborative data sharing in online social networks.- Chapter 6. Startup Profit Predictor using Machine Learning Techniques.- Chapter 7. Right To Be Forgotten In A Post- Ai World: How Effective Is This Right Where Machines Do Not Forget?- Chapter 8. Age, Gender, and Gesture Classification using Open-Source Computer Vision.- Chapter 9. Estimated Time of Arrival for Sustainable Transport using Deep Neural Network.- Chapter 10. Texture Feature based on ANN for Security aspects.- Chapter 11. ML based prediction model for cardiovascular disease.- Chapter 12. Sentiment Analysis in Airlines Industry using Machine Learning Techniques.- Chapter 13. Facial recognition to detect mood and play songs using Machine Intelligence.- Chapter 14. Banana Leaf Diseases and Machine Learning Algorithms Applied To Detect Diseases: A Study.- Chapter 15. Covid-19 prediction analysis using machine learning approach.
