Advanced Mathematics in Computing, Communication and Security

Dipti Jadhav, PhD is an Associate Professor in the Department of Information Technology in the Ramrao Adik Institute of Technology at D.Y. Patil University with more than 18 years of research and teaching experience. She has edited one book, authored more than 30 research papers in international journals and conferences, and holds one Australian and one German patent. Her research focuses on image processing, computer vision, pattern recognition, software engineering, machine learning, and artificial intelligence. Pritam Wani, PhD is a Professor at the Ramrao Adik Institute of Technology. Nerul, India. She has published papers in national and international journals. Narendrakumar Dasre, PhD is an Associate Professor of Applied Mathematics at the Ramrao Adik Institute of Technology with more than 21 years of teaching experience. He has authored and reviewed 14 national and international books and published 11 research papers in national and international journals. His areas of interest include image processing, topology, number theory, and applied mathematics. Niranjanamurthy M., PhD is an Assistant Professor in the Department of Artificial Intelligence and Machine Learning at the BMS Institute of Technology and Management with more than 14 years of experience. He has published more than 25 books and more than 95 articles in various national and international conferences and journals. He has also filed 30 patents, six of which have been granted. His areas of interest include data science, machine learning, e-commerce and m-commerce, software testing and engineering, and cloud computing. Biswadip Basu Mallik, PhD is an Associate Professor of Mathematics in the Department of Basic Sciences and Humanities at the Institute of Engineering and Management with more than 22 years of research and teaching experience. He has published several research papers and book chapters in various scientific journals, authored five books, edited an additional 13, and published five Indian patents. His research focuses on computational fluid dynamics, mathematical modeling, machine learning, and optimization.

• Preface xxi1 Comparative Analysis of Secure Multi-Party Techniques in the Cloud 1Janak Dhokrat, Namita Pulgam, Tabassum Maktum and Vanita Mane1.1 Introduction 21.2 Related Work 51.3 Comparative Analysis 91.4 Summary 111.5 Conclusion 161.6 Compliance with Ethical Standards 172 Exploring the Role of Mathematics in Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) Applications 21R. Venkatesh2.1 Introduction to Mathematics in Artificial Intelligence 232.2 Mathematical Foundations of AI 292.3 Advanced Mathematical Techniques in Machine Learning 332.4 Applications of Mathematics in Deep Learning 412.5 Future Directions and Challenges 472.6 Conclusion 533 ChatGPT as Rough Set Model Bridging Conversation Gap and Uncertainty 57Anshit Mukerjee, Biswadip Basu Mallik and Sudeshna Das3.1 Introduction 583.2 Literature Review 583.3 Methodology 623.4 Results 683.5 Discussions 763.6 Conclusion and Future Works 774 Simulating M/G/1 Queuing Network with Time-Varying Arrival Rates and Server Failure Using Python Programming 81Sreelekha Menon, Surya K.A. and Reshma R.4.1 Introduction 824.2 Methodology 844.3 Numerical Example 864.4 Python Code 894.5 Negative Arrivals 894.6 Conclusion 895 A Technique of Watermarking Using DGT and DCT 91Narendrakumar R. Dasre and Pritam Gujarathi5.1 Introduction 915.2 Proposed Algorithm Using DGT and DCT 935.3 Experimental Results 955.4 Statistical Analysis 995.5 Conclusion 1136 Performance and Economic Study of an Impatient Consumer Queue with Working Vacations, Secondary Service and Server Failures 117K. Jyothsna, P. Vijaya Kumar and P. Vijaya Laxmi6.1 Introduction 1186.2 Model Overview 1216.3 Steady-State Analysis 1226.4 Performance Characteristics 1256.5 Sensitivity Analysis 1286.6 Conclusion 1357 Optimal Strategies for Multi-Item Stochastic Inventory Model for Convertible Items 139Mamta Keswani and Uttam Kumar Khedlekar7.1 Introduction 1397.2 Literature Survey 1427.3 Problem Statement 1447.4 Assumptions 1457.5 Notations 1467.6 Model Formulation 1477.7 Optimization by Using Dynamic Programming 1487.8 Numerical Validations 1587.9 Conclusion 1638 Sampling Statistics-Based Predictive Machine Learning Model for Large Scale Data Set 165Kamlesh Kumar Pandey, Anurag Singh and Sudeep Kumar Verma8.1 Introduction 1668.2 Challenging Issues of Big Data for Machine Learning 1688.3 Big Data Strategies for Machine Learning 1708.4 Sampling 1728.5 Sampling Model for Machine Learning 1808.6 Experimental Analysis 1848.7 Conclusion 1889 Correlation of Family History with Tumor Grade and Lymph Node Involvement in Breast Cancer Patients 195Suganthi P. and Ebenesar Anna Bagyam J.9.1 Introduction 1969.2 Literature Review 1979.3 Methodology 2019.4 Data Collection and Analysis of Parameters 2019.5 Analysis of Parameters Using Statistical Tool 2069.6 Conclusion 20910 Unlocking AI, ML, and DL Innovations: "The Essential Role of Mathematics" 211R. Roselinkiruba, Vasumathy M., C.P. Koushik, C. Saranya Jothi, S. Divya and A. Keerthika10.1 Introduction for the Mathematical Concepts in AI, ML and DL 21210.2 Linear Algebra 21510.3 Calculus: Foundations for Optimization and Training Algorithms 22110.4 Probability and Statistics: Analyzing and Validating Models 22510.5 Optimization: Refining Models and Resource Allocation 23010.6 Discrete Mathematics: Graph Theory and Combinatorics in AI 23510.7 Information Theory: Guiding Feature Selection and Model Evaluation 24010.8 Applications in Various Domains 24310.9 Conclusion 24511 Optimization and Metaheuristics: Mathematical Approaches in AI, Machine Learning, and Deep Learning 247C. Saranya Jothi, J.P. Shritharanyaa, E. Surya, R. Roselinkiruba, P. Jeevanasree and B. Lalitha11.1 Introduction to Metaheuristics and Optimization 24811.2 Metaheuristics Algorithms and Their Mathematical Foundations 25211.3 Applications in Artificial Intelligence 26311.4 Metaheuristics in Machine Learning Applications 26611.5 Metaheuristics in Deep Learning Applications 26811.6 Challenges and Future Directions 27111.7 Conclusions 27212 A Survey on Mathematics for Edge Detection Algorithms in Image Processing 275Maheshkumar D. Kudre, Narendrakumar R. Dasre and Pritam Wani12.1 Introduction 27512.2 Literature Review 27612.3 Conclusion 28613 PUF Inspired AES Cryptosystem for Securing Information 289Sivasankari Narasimhan, Sumathy Raju, Kavya Sri and Anitha N.13.1 Introduction 29013.2 Related Works 29113.3 Proposed PUF with AES Approach 29213.4 Simulation Results and Discussion 29613.5 AES-PUF Against Machine Learning Attacks 30213.6 Conclusion 30314 Leveraging Honeypots and Stochastic Gradient Descent for Advanced Cybersecurity 305J. Esther, Regi Anbumozhi and S. Subbulakshmi14.1 Introduction 30614.2 Literature Review 30814.3 Methodology 30914.4 Result & Discussion 31514.5 Conclusion 31915 Review of "Optimizing Peer Review Workflows with AI: A Queuing Model Approach" 321Sreelekha Menon, Reshma R. and Surya K.A.15.1 Introduction 32215.2 Queuing Models to Analyze the Impact of AI Peer Review Process 32315.3 Methodology 32415.3.4 Challenges and Drawbacks 32615.4 Conclusion 32716 To Analyze the Success of Prostate Cancer Prediction Using Machine Learning 329Bhaskar Nandi, Soumit Chowdhury, Subrata Jana, Biswadip Basu Mallik, Krishna Pada Das and Sudipta Banerjee16.1 Introduction 33016.2 Literature Review 33116.3 Objectives 33416.4 Hypothesis 33416.5 Attributes 33516.6 Flow Chart and Data Description 33616.7 Data Analysis 33716.8 Model Evaluation 34416.9 Result Analysis 35016.10 Conclusions 35217 Statistics in Data Science 357Nishant Wanjari, Aashka Gupta, Reshma Gulwani and Aditi Chhabria17.1 Introduction to Statistics 35817.2 Relationships between Data Science and Statistics 36017.3 Correlation and Covariance 36317.4 Regression Analysis 36417.5 Probability and Probability Functions 36517.6 Bayesian Statistics 36817.7 Hypothesis Testing 36817.8 Statistics in Predictive Modeling 37117.9 Statistics Meets Computation to Form Data Science 37317.10 Statistics Applications in Data Science 37517.11 Statistical Software and Packages in Data Science 37718 Frames for Applications in Engineering 381Jamkhongam Touthang18.1 Introduction 38218.2 Finite Frames 38418.3 Frames in Infinite-Dimensional Settings 39018.4 Applications 40018.5 Challenges in Signal Processing 40719 Development and Optimization of an ADRC-Controlled IPMC Actuator for Enhanced Disturbance Rejection and Creep Compensation 415Mohammed Mohaideen M., Seenivasan S., Ravivarman G., Rangarajan R. V., Naveenkumar P., Sekar G., Balachandar K., Girimurugan R. and Biswadip Basu Mallik19.1 Introduction 41619.2 Ionic Polymer Metal Composites Creep Model 41719.3 Design of the ADRC Controller 41919.4 ADRC Controller Parameters Can Be Changed Using the Particle Swarm Optimization Method 42419.5 Conclusions 43220 Industry 4.0: Revolutionizing Production through Cyber-Physical Systems 437Girisha L., Meinathan S., Ravivarman G., Girimurugan R., Irudhayamary Premkumar, Catherene Julie Aarthy C. and Biswadip Basu Mallik20.1 Introduction 43820.2 A Case Study 44020.3 Infrastructure Requirements 44220.4 Legal Issues and Cyber-Security 44520.5 Development of New Business Models 44820.6 Challenges to Achieve Sustainable Development 45120.7 Conclusions 45321 Safeguarding Security and Privacy in the Business Sector: The Role of AI and ML 459Joshua Bapu J., Saranya N., Chacko Jose P., Suresh Kumar K., Jayachandran T., Girimurugan R. and Biswadip Basu Mallik21.1 Introduction 46021.2 An Ethical Investigation into Cyber Security 46221.3 Literature Review 46321.4 Artificial Intelligence Cybersecurity as a Business Ethics Duty 46621.5 Using AI and Big Language Models in Business Settings: Falling for the Marketing Hype 47021.6 Risk Considerations for Cyber Security in Generative AI and Huge Language Models 47121.7 Ethical Implications of Generative AI Risk 47421.8 Ethical Implementations of Generative AI 47921.9 Conclusions 48022 Advancing Women Health: Detecting Polycystic Ovary Syndrome through Machine Learning 485K. DeviPriya, K. V. V. S. Trinadh Naidu, V. Chandra Kumar, Subrata Jana, Biswadip Basu Mallik, K. Bhanu Rajesh Naidu and M. V. Rajesh22.1 Introduction 48622.2 Related Works 48822.3 Proposed Work 48922.4 Dataset 49122.5 Experimental Setup 49422.6 Results & Discussion 49422.7 Conclusions 49823 Personalized Hotel Recommendation System Using Similarity Measures and Heuristic Analysis 501Prapti Sinha, Rajashree Shedge and Dipti Jadhav23.1 Introduction 50223.2 Background 50323.3 Literature Survey 50523.4 Dataset 50823.5 Proposed Framework 50823.6 Result 51923.7 Conclusion 51924 Predictive Structural Equation Modeling for Multi-Dimensional Skill-Development Among Higher Education Learners in Formal Learning Environment 521S. Bhuma Devi, Preeti Jain and Gargi Tyagi24.1 Introduction 52224.2 Related Work 52324.3 Research Methodology 52624.4 Results and Discussion 53524.5 Conclusion 541References 542Index 545