Proceedings of World Conference on Artificial Intelligence: Advances and Applications

Dr. Ashish Kumar Tripathi (Member, IEEE) received his M.Tech and Ph.D. degrees in Computer Science and Engineering from Delhi Technological University, Delhi, India, in 2013 and 2019 respectively. He is currently working as an Assistant Professor with the Department of Computer Science & Engineering, Malviya National Institute of Technology (MNIT), Jaipur, India. His research interests include big data analytics, social media analytics, soft computing, image analysis, and natural language processing. Dr. Tripathi has published several papers in international journals and conferences including IEEE transactions. He is an active reviewer for several journals of repute. Prof. Darpan Anand is a Qualified Ph.D. (CS) contributing over 20+ years in Teaching (CS) Computer Science and Engineering at various top universities and engineering schools/institutes with 20+ years in Teaching (CS), Research as well as academics, and 6+ years of industrial experience including 2+ years of onsitesoftware development. Currently spearheading efforts as Professor and Head of Department (CSE) at Sir Padampat Singhania University, Udaipur, India. Possessing a flair for teaching with the proven ability to apply the best practice-based & innovation-oriented teaching-learning practices, Outcome-based education in engineering education as well as a collaborative approach to research and a decentralized & supportive style to academic administration. He is an academic leader in Teaching, Curriculum Design & Improvisation, Supervise Departmental research efforts, Technical Evaluation of Prospective faculty, Budgetary and Academic Management of the Department, and targets outcome of projects. Current research interests include Information Security, Software Defined Network, Data Science-AI& ML, and e-governance. He has guided several Ph.D. & PG Dissertations. He is an author/co-author of more than 60+research papers (indexed in SCI, ESCI, Scopus, etc.), various books and book chapters (IET, Springer, and Elsevier), patents, etc. He is also a member of various esteemed research associations such as IEEE, ACM, IAENG, TAEI, CSI, AIS, CSTA, etc. Dr. Atulya Nagar is the Foundation Chair as Professor of Mathematics at Liverpool Hope University and  Pro-Vice-Chancellor for Research since October 2019. He is the Dean of Faculty of Science from May 2014 to September 2019; and Head of School of Mathematics, Computer Science, and Engineering from September 2007 to August 2022. A mathematician by training, he possess multi-disciplinary expertise in nonlinear mathematics, natural computing, bio-mathematics and computational biology, operations research, and control systems engineering. He has an extensive background and experience of working in Universities in the UK and India. He is also an expert reviewer for the Biotechnology and Biological Sciences Research Council (BBSRC) grants peer-review committees for Bioinformatics Panel; Engineering and Physical Sciences Research Council (EPSRC) for High Performance Computing Panel; and serve on the Peer-Review College of the Arts and Humanities Research Council (AHRC) as a scientific expert member. He has edited volumes on Intelligent Systems, and Applied Mathematics; he is the founding series editor for Springer Book Series on Algorithms for Intelligent Systems (AIS) and the Editor-in-Chief of the International Journal of Artificial Intelligence and Soft Computing (IJAISC) until 2021. Dr. Nagar has published over 200 publications in prestigious publishing outlets and journals such as the Journal of Applied Mathematics and Stochastic Analysis; the International Journal of Advances in Engineering Sciences and Applied Mathematics; the International Journal of Foundations of Computer Science; the IEEE Transactions on Systems, Man, and Cybernetics; Discrete Applied Mathematics; Fundamenta Informaticae; IET Control Theory & Applications, to name a few.

A pragmatic study of machine learning models used during data retrieval: An empirical perspective.- Patient-Centric Electronic Health Records Management System Using Blockchain Based on Liquid Proof of Stake.- Prediction of Children Age Range Based on Book Synopsis.- Exploring Jaccard Similarity and Cosine Similarity for Developing an Assamese Question Answering System.- Artificial Neural Network modelling for simulating catchment runoff: a case study of East Melbourne.- Effective Decision Making through Skyline Visuals.- A Review Paper on The Integration of Blockchain Technology With IoT.- Survey and analysis of Epidemic Diseases Using Regression Algorithms.- Cauliflower Plant Disease Prediction Using Deep Learning Techniques.- Disease Detection and Prediction in plants through Leaves using Convolutional Neural Networks.- Classification of Breast Cancer Using Machine Learning: An In-Depth Analysis.- Prediction of Age, Gender and Ethinicity Using Haar Cascade Algorithm In ConvolutionalNeural Networks.- A Lightweight Solution to Intrusion Detection and Non-Intrusive Data Encryption.- Efficiency of cellular automata filters for noise reduction in digital images.- Scheming of silver nickel magnopsor for Magneto-Plasmonic (MP) activity.- Heart Stroke Prediction Using Different Machine Learning Algorithms.- Credit Card Fraud Detection using Hybrid Machine Learning Algorithm.- Smart Air Pollution Monitoring System for Hospital Environment using Wireless Sensor and LabVIEW.- Mining optimal patterns from transactional data using Jaya Algorithm.- Accurate Diagnosis of Leaf Disease based on Unsupervised Learning Algorithms.- Modified teaching-learning based algorithm for long short-term memory optimization: an application for univarate individual household energy consumption forecasting.- Chaotic Quasi-Oppositional Chemical Reaction Optimization for Optimal Tuning of Single Input Power System Stabilizer.- Network Intrusion Detection System for Cloud Computing security usingDeep Neural Network framework.- Detection of Alzheimer’s Disease using Deep Learning Technique.- Performance Evaluation of Multiple ML Classifiers for Malware detection.- An analysis of feature engineering approaches for unlabeled dark web data classification.- Anomaly Detection to prevent Sensitive Data Exposure usiang GMM Clustering Model.- Real-time Driver Drowsiness detection system using Machine Learning.- Nature-Inspired Information Retrieval Systems: A Systematic Review of Literature and Techniques.- Deep Learning based Smart Attendance System.- Optical Character Recognition and Text Line Recognition of Handwritten Documents: A Survey.- Advanced Pointer-Generator Networks Based Text Generation.