Artificial Intelligence, Cybersecurity and Game Design
Description
This proceedings volume contains selected chapters on topics related to artificial intelligence, cybersecurity and game design and their sustainable applications, emphasizing sustainable applications that directly address topics related to five SDGs areas (3, 6, 7, 9, 13). Chapters are based on invited talks and contributed papers presented at the International Conference on Artificial Intelligence, Cybersecurity and Game Design (ICAICGD 2024), held at Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India, from 23-25 February 2024. The book offers a diverse array of new results, techniques, applications and perspectives: Out of 23 chapters, 4 chapters deal with security aspects, 2 on network science, 2 on game design, 4 on prediction models, 2 on recognition models, 3 on applications of AI tools such as machine learning and deep learning to agricultural science and 4 chapters are on applications to medical science.
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Persons
S. Arumugam is Adjunct Professor in the Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India. Earlier, he was Professor of Mathematics at St. John's College, Palayamkottai, Tamil Nadu, from 1968-1992; Professor and Founder Head of the Department of Mathematics, Manonmaniam Sundaranar University, Tirunelveli, from 1992-2003; and Senior Professor (Research) and Director, National Centre for Advanced Research in Discrete Mathematics, Kalasalingam Academy of Research and Education, Kalasalingam University, Krishnankoil, from 2003-2017. He has held various visiting professorships in Ball State University, Muncie, USA; Liverpool Hope University, Liverpool, UK; University of Newcastle, Australia; Amrita University, Coimbatore; Birla Institute of Technology and Science, Pilani, Goa Campus; and Ramanujan College, Delhi. He has earned his bachelor's and master's degree from St. Joseph's College, Trichy, and a Ph.D. in Mathematics from Madurai Kamaraj University, Madurai. With more than 325 papers and 32 books (including 2 Tamil textbooks) published to his credit, his current area of research is graph theory and guides more than 48 Ph.D. students. He has organized 28 conferences and workshops and has edited 14 proceedings. He also is the founder Editor-in-Chief of AKCE International Journal of Graphs and Combinatorics.
Jay Bagga is Professor of Computer Science at Ball State University, Indiana, USA. He is the Senior Director of the Voting System Technical Oversight Program (VSTOP). He has extensive experience in Election Systems Testing and Certification, election administration and computer and cyber security. He has collaborated in developing testing and certification protocols for voting systems and electronic poll books. Since 2017, he has served on Indiana Governor's Executive Council on Cybersecurity (IECC). During 2011-13, he was a co-PI for a US Election Assistance Commission Grant on Post-Election Audit and Logic and Accuracy Initiative. He has co-organized the State Certification Testing of Voting Systems National Conferences since 2011. He is a co-Director of the award-winning Certificate Program in Election Administration, Technology and Security (CEATS), which trains election officials in Indiana. He has received several government, university and industry grants, published many papers and organized international conferences. He is a co-author of the recently published Line Graphs and Line Digraphs (Springer).
Xavier Chelladurai is Professor in the Department of Computer Science and Engineering at Christ University, Bengaluru. He specializes in parallel and intelligent algorithms, artificial intelligence and machine learning. He has published over 20 books in computer science fields such as Java programming, programming languages and AI tools in web development. Additionally, he has developed over 10 MOOCs with more than 500 educational videos and study materials on platforms like Udemy, Christ University CDL and Binghamton University Brightspace. Under his mentorship, seven doctoral scholars have completed their Ph.D. degrees. With 20 years of industry experience at leading software companies like HCL Technologies, Tech Mahindra, and Capgemini, he is a Senior Member of IEEE and a Senior Life Member of the Computer Society of India. He also served on the Tamil Nadu government IT Taskforce for three years.
Vinayak Tanksale is Assistant Professor of Computer Science and Data Science at Ball State University, Indiana, USA. He also is the Director of the Graduate Program and Director of the Cardinal Academy of Digital Security and Education at the university. He earned his Ph.D. and MS from Purdue University and BS from the University of Toledo. His current research are on predicting malicious system behavior.
Content
Technology in US Elections.- Graph Theoretical Approach to Determine Rheumatoid Arthritis-related Protein Biomarkers for Drug Target.- Evidence of space weather in Radon Decay Unexpected correlations between GSI222 Rn Data and Protons Detected by EPAM.- Social Network Analysis in a Media Production House Bridging the Gap between Executives and Employees.- Behavior Tree Visualization in Godot Engine.- Data Structure and Algorithm for Problem Solving Intelligent Agents Searching for Solution for the 8-Puzzle Problem.- On the Development Platform and Services for Quantum Machine Learning: A Comparative Study.- Design and Implementation of Threat Intelligence Platform.- A Stacked Deep Neural Network for Cancer Classification and Ensemble Gene Selection Approach.- Machine Learning Based Lung Cancer Detection with Multiview Images.- An Efficient Elderly Fall Monitoring and Detection System Using Machine Learning and Computer Vision.- Multi-Level Security in allocated m-healthcare System Using Otixo Cloud Storage.- Plant Disease Identification Model through Machine Learning Techniques.- Integrated Smart Water Management System for Conserving Crops.- An Efficient Crop Recommendation System Using Optimized Random Forest Approach.- Machine Learning Models for Pre-diction of Heart Disease.- Advancing PM 25 Forecasting: A Comparative Study of Ensembel Machine Learning Algorithms.- Extrapolative Data Feature Exploration-based Air Quality Prediction using Gradient Descent Algorithm.- Multispectral Palm Vein Recognition using Hierarchical Approach and Feature Fusion.- Unveiling Cryptocurrency Markets: A Comprehensive Exploration of Time Series and Deep Learning Models for Bitcoin Price Prediction.- Deep Learning System for ISL Recognition Using Long Short-Term Memory Technique.- EAMVC An Energy Aware Multi Variant based Clustering Algorithm for Energy Efficient Wireless Sensor Networks.- Synchronization of Discrete-time Complex Dynamical Networks with Time-varying Delays.