Advances in Distributed Computing and Machine Learning (eBook, PDF)
Proceedings of ICADCML 2024, Volume 1
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Advances in Distributed Computing and Machine Learning (eBook, PDF)
Proceedings of ICADCML 2024, Volume 1
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This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by the School of Electronics and Engineering, VIT - AP University, Amaravati, Andhra Pradesh, India, during January 5–6, 2024. This book presents recent innovations in the field of scalable distributed systems in addition to cutting-edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.
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This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by the School of Electronics and Engineering, VIT - AP University, Amaravati, Andhra Pradesh, India, during January 5–6, 2024. This book presents recent innovations in the field of scalable distributed systems in addition to cutting-edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.
Produktdetails
- Produktdetails
- Verlag: Springer Nature Singapore
- Seitenzahl: 483
- Erscheinungstermin: 17. Juni 2024
- Englisch
- ISBN-13: 9789819718412
- Artikelnr.: 70981654
- Verlag: Springer Nature Singapore
- Seitenzahl: 483
- Erscheinungstermin: 17. Juni 2024
- Englisch
- ISBN-13: 9789819718412
- Artikelnr.: 70981654
Umakanta Nanda is a distinguished academician in the field of Electronics Engineering. He received the MTech and Ph.D. degrees in Electronics and Communication Engineering from the National Institute of Technology, Rourkela, India, in 2010 and 2017, respectively. He is currently working as an Associate Professor and Dean of the School of Electronics Engineering at VIT-AP University, India. He has more than 15 years of teaching and research experience in different educational institutions. He has guided more than 20 UG and PG student projects. 5 PhD scholars have received their Doctorate degree and another 4 scholars are working under him in areas like Analog and Mixed-signal integrated circuits, beyond CMOS devices and circuits, application-specific processor design, and embedded systems design. He has published more than 90 research papers, including reputed SCI and SCOPUS-indexed journals, conference proceedings, and book chapters. He is also co-inventor of 6 patents which have been published. He has successfully conducted many workshops, FDPs, STTPs, seminars, value-added courses, training programs, and conferences. He has also worked as a reviewer and editor of numerous journals and conferences.
Asis Kumar Tripathy is a professor in the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He has more than ten years of teaching experience. He completed his Ph.D. from the National Institute of Technology, Rourkela, India, in 2016. His areas of research interests include wireless sensor networks, cloud computing, Internet of things and advanced network technologies. He has several publications in refereed journals, reputed conferences and book chapters to his credit. He has served as a program committee member in several conferences of repute. He has also been involved in many professional and editorial activities. He is a senior member of IEEE and a member of ACM.
Jyoti Prakash Sahoo is an experienced Assistant Professor and a Senior Member of IEEE, currently working at the Dept of Computer Science and Information Technology, Institute of Technical Education and Research, Siksha ’O’ Anusandhan (Deemed to be University). He previously worked as an Assistant Professor with CV Raman College of Engineering, Bhubaneswar (now C. V. Raman Global University). He is an active member of several academic research groups, including the Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Group at the Queen Mary University of London, the Intelligent Computing & Networking (ICN) Research Group at East China Normal University, and the Modern Networking Lab at National Taiwan University of Science and Technology. He has expertise in the field of Edge Computing and Machine learning. He also serves several journals and conferences as an editorial or reviewer board member. He served as Publicity Chair, Web Chair, Organizing Secretary, and Organizing Member of technical program committees for many national and international conferences. Being a WIPRO Certified Faculty, he has also contributed to industry-academia collaboration, student enablement, and pedagogical learning.
Mahasweta Sarkar is currently working as a professor of the Department of Electrical and Computer Engineering and senior associate dean, Global Campus at San Diego State University. Her M.S. and Ph.D. degrees were completed at the University of California, San Diego (UCSD), in 2003 and 2005, respectively. She received her B.S. degree in Computer Science and Engineering (Summa Cum Laude) in May 2000 from San Diego State University. Dr. Sarkar is a recipient of the "President's Leadership Award for Faculty Excellence" for the year 2010. She delivered invited lectures and keynotes at different universities spread all over the globe. The talks were on wireless body area networks and brain–computer interfaces. Her research interest lies in the area of MAC layer power management algorithms and quality-of-service issues and protocols in WLANs, WMANs, WBANs, sensor networks and wireless ad-hoc networks.
Kuan-Ching Li is currently appointed as a distinguished professor at Providence University, Taiwan. He is a recipient of awards and funding support from several agencies and high-tech companies and also received distinguished chair professorships from universities in several countries. He has been actively involved in many major conferences and workshops in program/general/steering conference chairman positions and as a program committee member and has organized numerous conferences related to high-performance computing and computational science and engineering. Professor Li is the editor-in-chief of technical publications Connection Science (Taylor & Francis), International Journal of Computational Science and Engineering (Inderscience) and International Journal of Embedded Systems (Inderscience) and serves as an associate editor, editorial board member and guest editor forseveral leading journals. Besides publication of journal and conference papers, he is the co-author/co-editor of several technical professional books published by CRC Press, Springer, McGraw-Hill and IGI Global.
Asis Kumar Tripathy is a professor in the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He has more than ten years of teaching experience. He completed his Ph.D. from the National Institute of Technology, Rourkela, India, in 2016. His areas of research interests include wireless sensor networks, cloud computing, Internet of things and advanced network technologies. He has several publications in refereed journals, reputed conferences and book chapters to his credit. He has served as a program committee member in several conferences of repute. He has also been involved in many professional and editorial activities. He is a senior member of IEEE and a member of ACM.
Jyoti Prakash Sahoo is an experienced Assistant Professor and a Senior Member of IEEE, currently working at the Dept of Computer Science and Information Technology, Institute of Technical Education and Research, Siksha ’O’ Anusandhan (Deemed to be University). He previously worked as an Assistant Professor with CV Raman College of Engineering, Bhubaneswar (now C. V. Raman Global University). He is an active member of several academic research groups, including the Scalable Adaptive Yet Efficient Distributed (SAYED) Systems Group at the Queen Mary University of London, the Intelligent Computing & Networking (ICN) Research Group at East China Normal University, and the Modern Networking Lab at National Taiwan University of Science and Technology. He has expertise in the field of Edge Computing and Machine learning. He also serves several journals and conferences as an editorial or reviewer board member. He served as Publicity Chair, Web Chair, Organizing Secretary, and Organizing Member of technical program committees for many national and international conferences. Being a WIPRO Certified Faculty, he has also contributed to industry-academia collaboration, student enablement, and pedagogical learning.
Mahasweta Sarkar is currently working as a professor of the Department of Electrical and Computer Engineering and senior associate dean, Global Campus at San Diego State University. Her M.S. and Ph.D. degrees were completed at the University of California, San Diego (UCSD), in 2003 and 2005, respectively. She received her B.S. degree in Computer Science and Engineering (Summa Cum Laude) in May 2000 from San Diego State University. Dr. Sarkar is a recipient of the "President's Leadership Award for Faculty Excellence" for the year 2010. She delivered invited lectures and keynotes at different universities spread all over the globe. The talks were on wireless body area networks and brain–computer interfaces. Her research interest lies in the area of MAC layer power management algorithms and quality-of-service issues and protocols in WLANs, WMANs, WBANs, sensor networks and wireless ad-hoc networks.
Kuan-Ching Li is currently appointed as a distinguished professor at Providence University, Taiwan. He is a recipient of awards and funding support from several agencies and high-tech companies and also received distinguished chair professorships from universities in several countries. He has been actively involved in many major conferences and workshops in program/general/steering conference chairman positions and as a program committee member and has organized numerous conferences related to high-performance computing and computational science and engineering. Professor Li is the editor-in-chief of technical publications Connection Science (Taylor & Francis), International Journal of Computational Science and Engineering (Inderscience) and International Journal of Embedded Systems (Inderscience) and serves as an associate editor, editorial board member and guest editor forseveral leading journals. Besides publication of journal and conference papers, he is the co-author/co-editor of several technical professional books published by CRC Press, Springer, McGraw-Hill and IGI Global.
Chapter 1: Comparative Analysis of Deep Learning Based Hybrid Algorithms for Liver Disease Prediction.- Chapter 2: A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method.- Chapter 3: Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients.- Chapter 4: A Review on Satellite Image Segmentation using Metaheuristic Optimization Techniques.- Chapter 5: A framework for enabling artificial intelligence inference for the hardware acceleration of IVIS imaging system.- Chapter 6: Cloud-based Anomaly Detection for Broken Rail Track using LSTM Autoencoders and Cross-modal Audio Analysis.- Chapter 7: A Study on the Mental Health among Indian Population in the Post COVID-19 Pandemic using Computational Intelligence.- Chapter 8: Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing.- Chapter 9: Towards Finger Photoplethysmogram Based Non-Invasive Classification of Diabetic versus Normal.- Chapter 10: Evaluation of Weather Forecasting Models and Handling Anomalies in Short-Term Wind Speed Data. etc.
Chapter 1: Comparative Analysis of Deep Learning Based Hybrid Algorithms for Liver Disease Prediction.- Chapter 2: A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method.- Chapter 3: Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients.- Chapter 4: A Review on Satellite Image Segmentation using Metaheuristic Optimization Techniques.- Chapter 5: A framework for enabling artificial intelligence inference for the hardware acceleration of IVIS imaging system.- Chapter 6: Cloud-based Anomaly Detection for Broken Rail Track using LSTM Autoencoders and Cross-modal Audio Analysis.- Chapter 7: A Study on the Mental Health among Indian Population in the Post COVID-19 Pandemic using Computational Intelligence.- Chapter 8: Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing.- Chapter 9: Towards Finger Photoplethysmogram Based Non-Invasive Classification of Diabetic versus Normal.- Chapter 10: Evaluation of Weather Forecasting Models and Handling Anomalies in Short-Term Wind Speed Data. etc.
Chapter 1: Comparative Analysis of Deep Learning Based Hybrid Algorithms for Liver Disease Prediction.- Chapter 2: A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method.- Chapter 3: Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients.- Chapter 4: A Review on Satellite Image Segmentation using Metaheuristic Optimization Techniques.- Chapter 5: A framework for enabling artificial intelligence inference for the hardware acceleration of IVIS imaging system.- Chapter 6: Cloud-based Anomaly Detection for Broken Rail Track using LSTM Autoencoders and Cross-modal Audio Analysis.- Chapter 7: A Study on the Mental Health among Indian Population in the Post COVID-19 Pandemic using Computational Intelligence.- Chapter 8: Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing.- Chapter 9: Towards Finger Photoplethysmogram Based Non-Invasive Classification of Diabetic versus Normal.- Chapter 10: Evaluation of Weather Forecasting Models and Handling Anomalies in Short-Term Wind Speed Data. etc.
Chapter 1: Comparative Analysis of Deep Learning Based Hybrid Algorithms for Liver Disease Prediction.- Chapter 2: A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method.- Chapter 3: Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients.- Chapter 4: A Review on Satellite Image Segmentation using Metaheuristic Optimization Techniques.- Chapter 5: A framework for enabling artificial intelligence inference for the hardware acceleration of IVIS imaging system.- Chapter 6: Cloud-based Anomaly Detection for Broken Rail Track using LSTM Autoencoders and Cross-modal Audio Analysis.- Chapter 7: A Study on the Mental Health among Indian Population in the Post COVID-19 Pandemic using Computational Intelligence.- Chapter 8: Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing.- Chapter 9: Towards Finger Photoplethysmogram Based Non-Invasive Classification of Diabetic versus Normal.- Chapter 10: Evaluation of Weather Forecasting Models and Handling Anomalies in Short-Term Wind Speed Data. etc.