Data Science and Big Data Analytics -

Data Science and Big Data Analytics

Proceedings of IDBA 2023
Buch | Hardcover
747 Seiten
2024 | 2024 ed.
Springer Verlag, Singapore
978-981-99-9178-5 (ISBN)
246,09 inkl. MwSt
This book features high-quality research papers presented at the Third International Conference on Data Science and Big Data Analytics (IDBA 2023), organized by Sri Aurobindo Institute of Technology, Indore, India, in association with ACM and IEEE Computer Society in hybrid mode during June 16–17, 2023. This book discusses the topics such as data science, artificial intelligence, machine learning, quantum computing, big data and cloud security, computation security, big data security, information security, forecasting, data analytics, mathematics for data science, graph theory and application in data science, data visualization, computer vision, and analytics for social networks.

Durgesh Mishra obtained his Ph.D. in Computer Engineering from DAVV Indore. He worked at IIT Indore as a visiting professor. Currently, he is working as a professor and  the director at Symbiosis University of Applied Sciences, Indore. He is the chairman of IEEE Computer Society, Madhya Pradesh section. He served as the national chairman of Computer Society of India for about 5 years and a treasurer for about 3 years. He is the chairman of the ACM Indore chapter.  He has published more than 100 peer-reviewed papers with good citations. He supervised 7 Ph.Ds. and more than 50 master's students. He has 2 patents granted and 12 published. He was awarded with a Lifetime Achievement Award, the International Paper Presenter Award, and the Best Paper Award. He was the chairman of IEEE Computer Society chapter, Bombay section (2010). He was a consultant to Government of Madhya Pradesh sales tax and labor departments. Xin-She Yang obtained his D.Phil. inApplied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a senior research scientist. Now he is the reader at Middlesex University London and a co-editor of the Springer Tracts in Nature-Inspired Computing. He is also an elected fellow of the Institute of Mathematics and its Applications. He was the IEEE Computational Intelligence Society (CIS) chair for the Task Force on Business Intelligence and Knowledge Management (2015 to 2020). He has published more than 300 peer-reviewed research papers with more than 70,000 citations, and he has been on the prestigious list of highly cited researchers (Clarivate Analytics/Web of Sciences) for seven consecutive years (2016–2022). Aynur Unal is educated at Stanford University (doctoral advisers were Prof. George Herrmann of Engineering and Prof. Harold Levine of Mathematics). She built a new computational acoustics program from scratch at Stanford University and had worked on noise reduction in various systems including Mac series and next workstations. She took part in early Silicon Valley start-up companies using ultrasound for diagnostics in both machine and human health. She used the first artificial neural networks in diagnostics. She was the chief technical architect of www.e2open.com. She developed secure and private e-services, e-financial systems, e-manufacturing, e-health, and e-learning as a member of the Executive Team. In 2010, she became the dean of Engineering at Ansal University, the advisor to several universities in India, a visiting professor at IITG, Guwahati, and is an executive advisor at Stanford Medical School. Her research interests are secure, smart, and sustainable digital systems and services. Dharm Singh Jat is a professor of Computer Science and the UNESCO chairholder on Secure High-performance Computing for Higher Education and Research established at Namibia University of Science and Technology (NUST). He received his Master of Engineering and Ph.D. in Computer Science and Engineering. He has supervised 9 Ph.D. and 27 master’s students, the author of more than 200 peer-reviewed articles, and the author or editor of more than 20 books and conference proceedings. He has received more than 19 prestigious awards as a scientist and an engineer. He is a fellow of the Institution of Engineers and the fellow of the Computer Society of India.  His professional awards include the Eminent Scientist Award, Distinguished Academic Achievement, Eminent Engineering Personality, CSI Chapter Patron and Significant Contribution, Best Faculty Researcher, Best Technical Staff, Outstanding University Service, Distinguished ACM Speaker Award, and IEEE Computer Society DVP Speaker Award.

Analysing the role of social influence in adoption of technology for student assessment in Indian management institutions.- Plastic and Non-Plastic Waste Classification using Machine Learning Techniques.- Prediction of  Customer Satisfaction in E- banking Services through Neural Network Approach.- Role of AI and Machine Learning in Mental Healthcare.- Proposed a mechanism to precise diagnostics in X-ray film using Fuzzy Logic  Controller.- Human Gender Classification of Males and Females in a Crowd using Deep Learning Techniques.- Analysis on prediction of crop diseases using TensorFlow with Keras and OpenCV technique of deep learning.- Design of convolutional encoder for multivalued logic.- Improving the efficiency of water quality prediction using the Supertml approach in machine learning.- Probabilistic Data Structure using hashing technique for big data security de- duplication in cloud environment.- Malicious account detection using ANN.- Performance Evaluation of LiCi-2Ultra-lightweight  Block Cipher.

Erscheinungsdatum
Reihe/Serie Data-Intensive Research
Zusatzinfo 248 Illustrations, color; 90 Illustrations, black and white; XIV, 747 p. 338 illus., 248 illus. in color.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik
Technik
Schlagworte Analytics for Social Networks • Big Data • computer vision • Data Science • IDBA 2023 Proceedings • Knowledge Representation • machine learning
ISBN-10 981-99-9178-1 / 9819991781
ISBN-13 978-981-99-9178-5 / 9789819991785
Zustand Neuware
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