Data Science and Applications -

Data Science and Applications

Proceedings of ICDSA 2023, Volume 1
Buch | Softcover
571 Seiten
2024 | 1st ed. 2024
Springer Verlag, Singapore
978-981-99-7861-8 (ISBN)
235,39 inkl. MwSt
This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2023), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 14 to 15 July 2023. The book is divided into four volumes, and it covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Dr. Satyasai Jagannath Nanda is an assistant professor at the Department of Electronics and Communication Engineering, Malaviya National Institute of Technology Jaipur, since June 2013. Prior to joining MNIT Jaipur, he has received the Ph.D. degree from School of Electrical Sciences, IIT Bhubaneswar, and M.Tech. degree from the Department of Electronics and Communication Engg., NIT Rourkela. He received the B.E. degree in Electronics and Telecommunication Engineering from Institute of Technical Education and Research (ITER), Bhubaneswar, in the year 2006.  He was the recipient of Canadian Research Fellowship—GSEP, from the Department of Foreign Affairs and Intern. Trade (DFAIT), Government of Canada, for the year 2009-10. He was awarded Best Ph.D. Thesis Award at SocPros 2015 by IIT Roorkee.  He received the best research paper awards at ODICON-2023 at SOA University Bhubaneswar, SocPros-2020 at IIT Indore, IC3-2018 at SMIT Sikkim, SocPros-2017 at IITBhubaneswar, IEEE UPCON-2016 at IIT BHU, and Springer OWT-2017 at MNIT. He is the recipient of prestigious IEI Young Engineers Award by Institution of Engineers, Government of India, in the field of Electronics and Telecommunication Engineering for the year 2018-19. Prof. Rajendra Prasad Yadav is currently working as a professor-HAG at the Department of Electronics and Communication Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. He has more than four decades of teaching and research experience. He was instrumental in starting new B.Tech. and M.Tech. courses and formulating Ph.D. Ordinances for starting research work in Rajasthan Technical University (RTU), Kota, and other affiliated engg. colleges as the vice chancellor of the University.  He has served as the HOD of Electronics and Comm. Engg., the president Sports and Library, the hostel warden, and the dean student affairs at MNIT Jaipur. At present he is also the Chief Vigilance Officer of MNIT Jaipur since 2015. Prof. Yadav received the Ph.D. degree from MREC Jaipur and M.Tech. degree from IIT Delhi. Under his supervision, 15 Ph.D. students have received Ph.D. degree, and 7 students are working for their Ph.D. degree. Forty M.Tech. students have carried out their dissertation work under his guidance. Amir H. Gandomi is a professor of Data Science and an ARC Discovery Early Career Research Award (DECRA) fellow at the Faculty of Engineering & Information Technology, University of Technology Sydney. Prior to joining UTS, Prof. Gandomi was an assistant professor at the School of Business, Stevens Institute of Technology, USA, and a distinguished research fellow in BEACON center, Michigan State University, USA. Prof. Gandomi has published over two hundred journal papers and seven books which collectively have been cited more than 17,000 times (H-index = 60). He has been named as one of the most influential scientific mind and a highly cited researcher (top 0.1%) for four consecutive years, 2017 to 2020. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as an associate editor, an editor, and a guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Dr. Mukesh Saraswat is an associate professor at Jaypee Institute of Information Technology, Noida, India. Dr. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 20 years of teaching and research experience. He has guided 03 Ph.D. students, more than 70 M.Tech. and B.Tech. dissertations, and presently guiding 04 Ph.D. students. He has published more than 75 journal and conference papers in the area of image processing, pattern recognition, data mining, and soft computing. He was part of successfully completed DRDE-funded project, SERB-DST (New Delhi)-funded project, and CRS-funded project. He has been an active member of many organizing committees of various conferences and workshops. He is also a guest editor of the Array, Journal of Swarm Intelligence, and Journal of Intelligent Engineering Informatics. He is an active member of IEEE, ACM, and CSI Professional Bodies.

Climate Change Parameter Dataset (CCPD): A Benchmark Dataset for Climate Change parameters in Jammu and Kashmir.- Brain Tumor Classification Using Deep Learning Techniques.- Machine learning Based Hardware Trojans Detection in Integrated Circuits: A Systematic Review.- Impact of Techno Stress on Employee Retention and Employee Turnover.- Single image dehazing using DCP with varying scattering constant.- Detecting IoT malware using federated learning.- A Deep learning approach for BGP security Improvement.- Wireless Sensor Network Protocols in Underwater Communication.- A Genetic Algorithm Approach for Portfolio Optimization.- Security Issues and Solutions in Post Quantum Authenticated Key Exchange for Mobile Devices.- Towards Decentralized Fog Computing: A comprehensive review of Models, Architectures, and Services.- Analysis of various MAC protocol 802.11 AX.- Monkeypox Disease Classification Using HOG-SVM Method.- A Deep Learning Model for Automatic Recognition of Facial Expressionsusing Haar Cascade Images.- Sensing Performance Analysis using Choatic Signal based SCMA Codebook For Secure Cognitive Communication System in 5G.- Identification of severity level for diabetic retinopathy detection using neural networks.- Metaheuristic optimized BiLSTM univariate time-series forecasting of gold prices.- Improvised Neural Machine Translation Model for Hinglish to English.- Recording of Class Attendance using DL Based Face Recognition Method.- Machine Learning Enabled Hairstyle Recommender System using Multilayer Perceptron.- Automated Health Insurance Management Framework with Intelligent Fraud Detection, Premium Prediction and Risk Prediction.- Responsible Artificial Intelligence for Music Recommendation.- A robot mapping technique for indoor environments.- A Novel Approach to Docking System for Autonomous Unmanned Aerial Vehicles.- Predicting Brain Tumor Survival using MRI Images and Machine Learning Techniques.- Intelligent Approaches of Clinical and Nonclinical Type-1 Diabetes Data Analysis.- A Learning-Based Approach For Wafer Defect Detection In Production Quality Control.- Setting Importance of Features through Means and Majority of Outcomes of Machine Learning Algorithms: An Empirical Analysis.- A Study of Simulated Working of A* and RRT* for Cargo Ship in ASVs.- ESFMS: Design of an Ensemble Sentiment analysis model for Feedback evaluation via Multimodal feature Selection process.- Towards Transfer Learning based Human Anomaly Detection in Videos.- Speech Signal Analysis Using Hybrid Feature Extraction Technique for Parkinson’s Disease Prediction.- Dataset Construction and Evaluation for Aspect-Opinion Extraction in Bangla Fine-grained Sentiment Analysis.- Improving Speaker Gender Detection by Combining Pitch and SDC.- Sentiment Analysis of Covid-19 Lockdown in India.- Applications of Smart Agriculture and an Automated Irrigation System Based on the Internet of Things.- Sensitivity of stock pricing to the optimistic and pessimistic sentimentof social media: A shreds of evidence from Nifty Indices.- Revolutionizing Cardiac Care: A Comprehensive Review of ECG-based Arrhythmia Prediction Techniques.- Yoga Posture Estimation and Correction using Mediapipe & Deep Learning Models.- Random Modulus Decomposition for Color Images Optical Asymmetric Cryptosystem Using Gyrator Domain.- A Single Line 8T SRAM Bit Cell with Robust Read, Hold Stability and Low Power.- Improving Chronic Kidney Disease Prediction using ANN with Normalization.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Networks and Systems
Zusatzinfo 169 Illustrations, color; 36 Illustrations, black and white; XX, 571 p. 205 illus., 169 illus. in color.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Mathematik / Informatik Informatik Netzwerke
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Schlagworte Data Mining • Data Science applications • Data Science Challenges • ICDSA 2023 Proceedings • machine learning • Models and Algorithms
ISBN-10 981-99-7861-0 / 9819978610
ISBN-13 978-981-99-7861-8 / 9789819978618
Zustand Neuware
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