Computing for Data Analysis: Theory and Practices

This book covers various cutting-edge computing technologies and their applications over data. It discusses in-depth knowledge on big data and cloud computing, quantum computing, cognitive computing, and computational biology with respect to different kinds of data analysis and applications. In this book, authors describe some interesting models in the cloud, quantum, cognitive, and computational biology domains that provide some useful impact on intelligent data (emotional, image, etc.) analysis. They also explain how these computing technologies based data analysis approaches used for various real-life applications. The book will be beneficial for readers working in this area.

Covers various cutting-edge computing technologies and their applications Discusses in-depth knowledge on big data and cloud computing, quantum computing, cognitive computing Serves as a reference resource for researchers and practitioners in academia and industry

Auteur

Dr. Sanjay Chakraborty is currently working as an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He did his B-Tech from the West Bengal University of Technology, India Information Technology in the year 2009. He completed his Master of Technology (M-Tech) from the National Institute of Technology, Raipur, India in the year of 2011. He completed his Ph.D. at the University of Calcutta in 2022. Dr. Chakraborty is the recipient of the University Silver Medal from NIT Raipur in 2011 for ranking first class second in M-Tech. He has nearly 12 years of teaching and research experience. He has published over 55 research papers in various international journals, conferences, and book chapters. He has two authored books published by Lap Lambert, Germany, and Springer EAI series respectively. Dr. Chakraborty attended many international conferences in India and abroad. His research interests include Data Mining & Machine Learning and Quantum Computing. He is a professional member of Internet society Kolkata, IAENG and UACEE. Dr. Chakraborty is an active member of the board of reviewers in various International Journals, IEEE Transactions, and Conferences. He is the recipient of "INNOVATION AWARD" for outstanding achievement in the field of Innovation by Techno India Institution's Innovation Council 2019. He is also the recipient of "IEEE Young Professional Best Paper Award" in 2017. He has also achieved the top five best paper recognition by Ain Shams Engineering Journal, Elsevier, and the most cited author award from Biomedical Journal, Elsevier in 2021.

Dr. Lopamudra Dey completed B-Tech from West Bengal University of Technology, Kolkata, India in Computer Science and Engineering in 2009. She received a Bronze medal for her Bachelor's degree. In 2011, she completed her M.Tech. from the University of Kalyani, West Bengal India. She obtained her Ph.D. in Computer Science from Kalyani University in 2021. She is currently working as an Assistant Professor in the Department of Computer Science and Engineering at Heritage Institute of Technology, Kolkata, India. She has nearly 12 years of teaching and research experience. Her areas of interest include Bioinformatics, Data Mining, and Network Security. She has published more than 15 research articles in journals, conferences, and books.

Contenu
Part 1. Introduction.- Chapter 1. Introduction.- Part 2. Integration of Cloud, Internet of Things, Virtual Reality and Big Data Analytics.- Chapter 2. Impact of Big Data and Cloud Computing on Data Analysis.- Chapter 3. Edge Computing with Internet of Things (IoT) and Data Analysis.- Chapter 4. Virtual and Augmented Reality with Embedded Systems.- Part 3. Biological Applications of Data Analytics.- Chapter 5. Computational Biology towards Data Analysis.- Chapter 6. Data Classification through Cognitive Computing.- Part 4. Quantum Computing for Data Analysis.- Chapter 7. Quantum Computing in Machine Learning.- Chapter 8. Quantum Computing in Image Processing.- Part 5. Computations for Various Data Applications and Future.- Chapter 9. Challenges and Future Research Directions on Data Computation