http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Synergistic interaction of big data with cloud computing for Industry 4.0
1 online resource (xii, 204 pages) : illustrations (some color).
"Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 discusses how to develop adaptive, robust, scalable, and reliable applications used in solutions for day-to-day problems. It reviews the advantages and consequences of utilizing Cloud Computing to tackle Big Data issues within the manufacturing and production sector as part of Industry 4.0. Top Big Data experts throughout the world have contributed their expertise to this book, addressing the major challenges, issues, and advances in Big Data and Cloud Computing for Industry 4.0"--
Bigdata based on fuzzy time series forecasting for stock index prediction / Ruchismita Majumder, Partha Pratim Deb, Diptendu Bhattacharya -- Big data based time series forecasting using FB prophet for stock index / Debankita Mukhopadhyay, Sourabarna Roy, Partha Pratim Deb -- The impact of artificial intelligence and big data in the postal sector / Mary Olawuyi Ojo, Indranath Chatterjee, Sheetal Gaikwad -- Advances in cloud technologies and future trends / Indra Kumari, Jungsuk Song, Buseung Cho -- Reinforcement of the multi-cloud infrastructure with edge computing / L. Steffina Morin, P. Murali -- Study and investigation of PKI based blockchain infrastructure / R. Deshmukh, S. Gaikwad -- Stock index forecasting using stacked LTSM -- deep learning & big data / Debasmita Pal, Partha Pratim Deb -- A comparative study and analysis of time-series and deep learning algorithms for bitcoin price prediction / Sagar Chakraborty, Nivedita Das, Kisor Ray -- Machine learning for healthcare / Udeechee, T.V. Vijay Kumar -- Transfer learning and fine tuning based early detection of cotton plant disease / Himani Bhatheja, N. Jayanthi -- Recognition of facial expressions of infrared images for lie detection with the use of support vector machine / Rupali Dhabarde, D.V. Kodavade, Rashmi Deshmukh, Sheetal Gaikwad -- SVM for classification of remote sensing images -- a review / Parijata Majumdar, Suchanda Dey, Sourav Bardhan, Sanjoy Mitra -- A study on data cleaning of hydrocarbon resource under deep sea water using imputation technique based approach of data science / Dipjyoti Deb.
edited by Sheetal S. Zalte-Gaikwad, Indranath Chatterjee, and Rajanish K. Kamat.
Includes bibliographical references and index.
Dr. Sheetal S. Zalte-Gaikwad is an assistant professor in Computer Science Department at Shivaji University, Kolhapur, India. She pursued a Bachelor of Computer Science from Pune University, India, in 2002 and a Master of Computer Science from Pune, India, in the year 2004. She earned her Ph.D. in Mobile Adhoc Network at Shivaji University. She has 14 years of teaching experience in computer science. She has published 20+ research papers in reputed international journals and conferences, including IEEE, and it's also available online. She has also authored book chapters with Springer. Her research areas are Manet, Vanet, Blockchain Security. Dr. Indranath Chatterjee is working as a Professor in the Department of Computer Engineering at Tongmyong University, Busan, South Korea. He received his Ph. D. in Computational Neuroscience from the Department of Computer Science, University of Delhi, India. His research areas include Computational Neuroscience, Schizophrenia, Medical Imaging, fMRI, and Machine learning. He has authored and edited 8 books on Computer Science and Neuroscience published by renowned international publishers. He has published numerous research papers in international journals and conferences. He is a recipient of various global awards in neuroscience. He is currently serving as a Chief Section Editor of a few renowned international journals, a member of the Editorial board of various international journals, and an Advisory board member in various "Open-Science" organizations worldwide. He is presently working on several projects for government & non-government organizations as PI/co-PI, related to medical imaging and machine learning for a broader societal impact, collaborating with several universities globally. He is an active professional member of the Association of Computing Machinery (ACM, USA), Organization of Human Brain Mapping (OHBM, USA), Federations of European Neuroscience Society (FENS, Belgium), Association for Clinical Neurology and Mental Health (ACNM, India), The Korean Society of Brain and Neural Science (KSBNS, Korea), and International Neuroinformatics Coordinating Facility (INCF, Sweden). Dr. Rajanish. K. Kamat is Dean of Computer Science and Technology, Shivaji University, Kolhapur, India. He received both B.Sc. and M.Sc. in Electronics with distinction in 1991 and 1993. Further, he completed his Mphil and Ph.D. in electronics at Goa university. Presently, he is working with the Department of Electronics and Department of Computer Science at Shivaji University, Kolhapur. He has published more than 150+ research papers in reputed international journals, including IEEE, and authored 12 books with Springer, CRC Press, and IGI global USA.
COMPUTERS / Database Management / Data Mining
Innovations in big data and machine learning