Computational Methods and Data Engineering

Computational Methods and Data Engineering
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Proceedings of ICCMDE 2021
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Artikel-Nr:
9789811930140
Veröffentl:
2022
Einband:
Paperback
Erscheinungsdatum:
09.09.2022
Seiten:
588
Autor:
Vijayan K. Asari
Gewicht:
986 g
Format:
235x155x30 mm
Serie:
139, Lecture Notes on Data Engineering and Communications Technologies
Sprache:
Englisch
Beschreibung:

Dr. Vijayan Asari is Professor in Electrical and Computer Engineering and Ohio Research Scholars Endowed Chair in Wide Area Surveillance at University of Dayton, Dayton, Ohio. He is Director of the University of Dayton Vision Lab (Center of Excellence for Computer Vision and Wide Area Surveillance Research). Dr. Asari had been Professor in Electrical and Computer Engineering at Old Dominion University, Norfolk, Virginia, till January 2010. He was Founding Director of the Computational Intelligence and Machine Vision Laboratory (ODU Vision Lab) at ODU. Dr. Asari received the Bachelor's degree in electronics and communication engineering from the University of Kerala (College of Engineering, Trivandrum), India, in 1978, the M.Tech. and Ph.D. degrees in Electrical Engineering from the Indian Institute of Technology, Madras, in 1984 and 1994, respectively.

 

Dr. Vijendra Singh is working as Professor in School of Computer Science at The University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India. Dr. Singh received his Ph.D. degree in Engineering and M. Tech. degree in Computer Science and Engineering from Birla Institute of Technology, Mesra, India. He has 20 years of experience in research and teaching including IT industry. Dr. Singh's major research concentration has been in the areas of data mining, image processing, Big data, machine learning, and Deep Learning. He has published more than 85 scientific papers in this domain. He has served as Editor in Chief, Procedia Computer Science, Vol 167, 2020, Elsevier; Editor in Chief, Procedia Computer Science, Vol 132, 2018, Elsevier; Associate Editor, BMC Medical Informatics and Decision Making, Springer Nature; International Journal of Healthcare Information Systems and Informatics, IGI Global, USA; Editor, BMC Digital Health, Springer Nature; Editorial Board Member, International Journal of Information and Decision Sciences, Inderscience, UK.He received the IBM Edu Leader Award. Singh Vijendra is Member of ISTE, IEEE, and ACM.

 

Dr. Rajkumar Rajasekaran is Professor and Researcher, at the Vellore Institute of Technology, India. He earned his Ph.D. in Computer Science and Engineering. He is Professor of Data Analytics at School of Computer Science and Engineering at VIT University in Vellore, India. In his current position, he is responsible for teaching data science, data visualization, and big data analytics. He was Head of data analytics research group. Research focuses on healthcare data analytics, agricultural data analytics, and streaming data analytics. He is Specialist in exploratory data analytics, data visualization, and the development and applications of agricultural data analytics techniques particularly implementing with R programming.  He has published more than 60 papers in Scopus and SCI and chaired many conferences and published three authored books. He has got 6 Indianpatents and 1 Australian patent. His current research looks at the healthcare data analytics of international governance by emerging countries like India. Rajkumar has learned and applied data analytics in healthcare and agriculture data combining case study analysis.

 

Prof. R B Patel is working as Professor in the Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology (CCET), Chandigarh, India. Prior to joining the CCET, he worked as Professor at NIT, Uttarakhand, India, and Dean, Faculty of Information Technology and Computer Science, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, India. His research areas include mobile and distributed computing, machine and deep learning, and wireless sensor networks. Prof. Patel has published more than 150 papers in international journals and conference proceedings. He has supervised 16 Ph.D. scholars and currently 02 are in progress.

The book features original papers from International Conference on Computational Methods and Data Engineering (ICCMDE 2021), organized by School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India, during November 25-26, 2021. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of advanced computing.

Presents recent research in the field of computational methods and data engineering
Chapter 1. A Graph Based Extractive Assamese Text Summarization.- Chapter 2. Internet of Things (IoT) for Secure Data and M2M Communications.- Chapter 3. Deveelopment of Walking Assistants for Visually Challenged Person.- Chapter 4. A PERFORMANCE STUDY OF PREDICTION MODELS FOR DIABETES PREDICTION USING MACHINE LEARNING.- Chapter 5. Orthopantomogram (OPG) Image Analysis using Bounding Box Algorithm.- Chapter 6. Design and Analysis of an Improved Artificial Neural Network Controller for the Energy Efficiency Enhancement of Wind Power Plant.- Chapter 7. Detection of Renal Calculi using Convolutional Neural Networks.- Chapter 8. Question Answering and Text Generation using BERT and GPT-2 Model.- Chapter 9. Improved Lenet Model for Flower Classification Using GPU Computing.- Chapter 10. Distributed computing over the Next Generation Mobile Communication Network (NGMCN) is an emerging technology.- Chapter 11. The ELF Tribe: Redefining Primary Education in a Post-COVID Era.- Chapter 12. An Extreme Machine Learning Mdel for Evaluating Landslide Hazard Zonation in Nilgiris District, Causative Factors and Risk Assessment using Earth Observation Techniques.- Chapter 13. Analysis of Cross-Site Scripting Vulnerabilities in Various Day-to-Day Web Applications.- Chapter 14. Detecting Cyberbullying with text classification using 1DCNN and Glove Embeddings.- Chapter 15. A Bayesian Network Based Software Requirement Complexity Prediction Model.

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