Nanda / Yadav / Gandomi Data Science and Applications

Proceedings of ICDSA 2023, Volume 4
1. Auflage 2024
ISBN: 978-981-99-7814-4
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 821, 545 Seiten, eBook

Reihe: Lecture Notes in Networks and Systems

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.

Zielgruppe

Research

Autoren/Hrsg.

Nanda, Satyasai Jagannath

Yadav, Rajendra Prasad

Gandomi, Amir H.

Saraswat, Mukesh

Inhaltsverzeichnis

Crop Classification Using Deep Learning on Time Series SAR Images:  A Survey.- Improvement of the Teaching-Learning Process using Feature-Driven Opinion Mining of Stakeholders Comments.- Safeguarding Privacy and Security in the Internet of Vehicles: Current and Emerging Strategies.- Two Factor Authentication for Internet of Drones using PUF and Blockchain.- REXOBOT- Simplifying Rescue Operations using Arduino.- Design and analysis of a dual-band wearable antenna integrated with an AMC reflector for biomedical applications.- An optimized approach for Sarcasm Detection using Machine learning Classifier.- Medical Image segmentation Using Deep Learning Method.- Implementation of Solar Array Integration with PID & MPPT(P&O) Incorporating Input Variations.- Cemetery Allocation Management System Using Ethereum Blockchain.- An Efficient Predictive Resource Analysis using Deep Dyna Q-based VARMA LSTM Model for Fluctuating Cloud Workloads.- SIW based H-plane dual horn radiator for next generation wireless communication.- RNN based model predictive control of multi agent system using switching topologies.- LDCCAES: A Concomitant Perception Methodology Facilitating Real-Time Detection and Estimation of Medifan-Lane Positioning for Prototype Autonomous Vehicle.- Enhancing Federated Learning Performance for IoT Anomaly Detection under Label-Skewed Data.- Panel Data Analysis to Investigate Factors Influencing Profitability: Empirical Study on Indian Oil and Gas Companies.- Predictive Modeling for Marketing Strategies: A Case Study of a Superstore’s Gold Membership Offer using Advanced Analytics and Machine Learning Techniques.- Design and Development of energy harvesting system for wireless local area Network.- Hybrid Principal Component Analysis Using Boosting Classification Techniques: Categorical Boosting.- Moth swarm algorithm with centre-based sampling technique for the optimal operation of a hybrid power system incorporating static synchronous compensator.- Land use andland Change detection of the eco system by processing Sentinel images.- An Enhanced Laryngeal Tissue Classification Model Using Deep Learning Techniques.- Machine Learning-based Detection of API Security Attacks.- A Comparative Study on End-to-End Learning for Self-Driving Cars.- Climatological Rainfall Forecasting using LSTM: An Analysis of Sequential Input and Data Window Input Approaches .- Enhancing Anonymity of Internet of Vehicle Identities in Connected Vehicle Security Services Using Batch Verification Algorithm.- A Deep Learning based Framework for Android Malware Family Classification.- iCardo 3.0: A Machine Learning Framework for Prediction of Conduction Disturbance in Heart.- ANDROID-BASED MALARIA DETECTION USING DEEP LEARNING.- Recuperating Image Captioning with Genetic Algorithm and Red Deer Optimization: A Comparative Study.- A Radial Basis Function Neural Network trained with Aquila Optimizer for Solving Inverse Modeling Problems.- Future Generation Elastic Optical Networks: A State-of-Art Review.- Empirical analysis on fake news detection using feature extraction & feature optimization techniques.- Enhancing the Performance of Heart Disease Prediction Models with Ensemble Learning.- Towards a Person-Job-Fit Recruitment: Job Prediction with Deep Neural Networks based on Various Pre-trained Models.- Hyperparameter Optimization of Machine Learning Models using grid search for Amazon Review Sentiment Analysis.- Towards the testbed and dataset for analysis of water treatment systems security.- Accurate Prediction of Stage of Hepatitis C Virus through a Stacking Ensemble.- Alzheimer Brain Imaging Dataset Augmentation using Wasserstein Generative Adversarial Network.- FireNet-Tiny: Very-Low Parameter Count High Performance Fire Detection Model.- 2D Medical Image Segmentation.

Über Autor(innen)

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.