Handbook of Intelligent Computing and Optimization for Sustainable Development

Mukhdeep Singh Manshahia, PhD, is an assistant professor at Punjabi University Patiala, India. He has published more than 40 international and national research papers and edited 1 book.Valeriy Kharchenko, PhD, is the Chief Scientific Officer at the Federal Scientific Agro Engineering Center VIM, Moscow, Russia. Elias Munapo, PhD, is a full professor in the Department of Statistics & Operations Research, North West University, South Africa. He has published more than 100 research articles and book chapters and has edited several volumes. J. Joshua Thomas, PhD, is a senior lecturer at UOW Malaysia KDU Penang University College, Malaysia. Currently, he is working with machine learning, big data, data analytics, deep learning, specifically targeting convolutional neural networks (CNN) and bi-directional recurrent neural networks (RNN) for image tagging with embedded natural language processing, end-to-end steering learning systems, and GAN. He has published more than 40 papers in leading international conference proceedings and peer-reviewed journals. Pandian Vasant, PhD, is a professor at Universiti Teknologi PETRONAS, Malaysia. He has co-authored more than 250 research articles in journals, conference proceedings, presentations, special issues guest editor, book chapters, and is the Editor-in-Chief of International Journal of Energy Optimization & Engineering.

• Foreword xxxiPreface xxxvAcknowledgment xlvPart I: Intelligent Computing and Applications 11 Assessing Mental Workload Using Eye Tracking Technology and Deep Learning Models 3Souvik Das, Kintada Prudhvi and J. Maiti1.1 Introduction 31.2 Data Acquisition Method 41.3 Feature Extraction 41.4 Deep Learning Models 51.5 Results 81.6 Discussion 101.7 Advantages and Disadvantages of the Study 111.8 Limitations of the Study 111.9 Conclusion 11References 122 Artificial Neural Networks in DNA Computing and Implementation of DNA Logic Gates 13Mandrita Mondal and Kumar S. Ray2.1 Introduction 132.2 Biological Neurons 152.3 Artificial Neural Networks 172.4 DNA Neural Networks 222.5 DNA Logic Gates 282.6 Advantages and Limitations 452.7 Conclusion 47Acknowledgment 47References 473 Intelligent Garment Detection Using Deep Learning 49Aniruddha Srinivas Joshi, Savyasachi Gupta, Goutham Kanahasabai and Earnest Paul Ijjina3.1 Introduction 493.2 Literature 503.3 Methodology 523.4 Experimental Results 593.5 Highlights 643.6 Conclusion and Future Works 65Acknowledgements 65References 664 Intelligent Computing on Complex Numbers for Cryptographic Applications 69Ni Ni Hla and Tun Myat Aung4.1 Introduction 694.2 Modular Arithmetic 704.3 Complex Plane 714.4 Matrix Algebra 714.5 Elliptic Curve Arithmetic 734.6 Cryptographic Applications 744.7 Conclusion 78References 795 Application of Machine Learning Framework for Next-Generation Wireless Networks: Challenges and Case Studies 81Satyendra Singh Yadav, Shrishail Hiremath, Pravallika Surisetti, Vijay Kumar and Sarat Kumar Patra5.1 Introduction 825.2 Machine/Deep Learning for Future Wireless Communication 835.3 Case Studies 875.4 Major Findings 955.5 Future Research Directions 955.6 Conclusion 96References 966 Designing of Routing Protocol for Crowd Associated Networks (CrANs) 101Rabia Bilal and Bilal Muhammad Khan6.1 Introduction 1016.2 Background Study 1036.3 CrANs 1176.4 Simulation of MANET Network 1236.5 Simulation of VANET Network 1266.6 CrANs 1306.7 Conclusion 132References 1327 Application of Group Method of Data Handling–Based Neural Network (GMDH-NN) for Forecasting Permeate Flux (%) of Disc-Shaped Membrane 135Anirban Banik, Mrinmoy Majumder, Sushant Kumar Biswal and Tarun Kanti Bandyopadhyay7.1 Introduction 1357.2 Experimental Procedure 1387.3 Methodology 1397.4 Results and Discussions 1427.5 Conclusions 146Acknowledgements 147References 1478 Automated Extraction of Non-Functional Requirements From Text Files: A Supervised Learning Approach 149M. Sunil Kumar, A. Harika, C. Sushama and P. Neelima8.1 Introduction 1498.2 Literature Survey 1538.3 Methodology 1568.4 Dataset 1658.5 Evaluation 1668.6 Conclusion 169References 1709 Image Classification by Reinforcement Learning With Two-State Q-Learning 171Abdul Mueed Hafiz9.1 Introduction 1719.2 Proposed Approach 1739.3 Datasets Used 1749.4 Experimentation 1769.5 Conclusion 178References 17810 Design and Development of Neural-Fuzzy Control Model for Computer-Based Control Systems in a Multivariable Chemical Process 183Pankaj Mohindru, Pooja and Vishwesh Akre10.1 Introduction 18410.2 Distributed Control System 18710.3 Fuzzy Logic 19210.4 Artificial Neural Network 19310.5 Neuro-Fuzzy 19410.6 Case Study 19710.7 Software Implementation on Graphical User Interface 20310.8 Results and Discussion 21210.9 Discussion 21410.10 Conclusion 21410.11 Scope for Future Work 215References 215Appendix 10.1 MATLAB Simulation Configuration Using Sugeno 217Appendix 10.2 MATLAB Window Displaying Desired Training-Data Fed to Neuro-Fuzzy Model 218Appendix 10.3 MATLAB Window Displaying Checking-Data Fed to Neuro-Fuzzy Model 21811 Artificial Neural Network in the Manufacturing Sector 219Navriti Gupta11.1 Introduction 21911.2 Optimization 22111.3 Artificial Neural Network: Optimization of Mechanical Systems 22311.4 ANN vs. Human Brain 22811.5 Architecture of Artificial Neural Networks 22911.6 Learning Algorithm(s) 23511.7 Different Type of Data 23711.8 Case Study: Hard Machining of EN 31 Steel 23811.9 Advantages of Using ANN in Manufacturing Sectors 24211.10 Disadvantages of Using ANN in Manufacturing Sectors 24211.11 Applications 24211.12 Conclusions 24311.13 Future Scope of ANN in Manufacturing Sectors 244References 24512 Speech-Based Multilingual Translation Framework 249Saloni and Williamjeet Singh12.1 Introduction 24912.2 Literature Survey 25012.3 Phases of ASR 25212.4 Modules of ASR 25312.5 Speech Database for ASR 25312.6 Developing ASR 25512.7 Performance of ASR 25612.8 Application Areas 25712.9 Conclusion and Future Work 258References 25813 Text Summarization: A Technical Overview and Research Perspectives 261Korrapati Sindhu and Karthick Seshadri13.1 Introduction 26213.2 Summarization Techniques 26313.3 Evaluating Summaries 27913.4 Datasets and Results 28113.5 Future Research Directions 28113.6 Conclusion 282References 28214 Democratizing Sentiment Analysis of Twitter Data Using Google Cloud Platform and BigQuery 287Sitendra Tamrakar, B. K. Madhavi and V. Mohan14.1 Introduction 28714.2 Literature Review 28914.3 Understanding the Google Cloud Platform 29114.4 Using BigQuery in the Google Cloud Console 29414.5 Sentiment Analysis 29414.6 Turning to Google BigQuery Analysis 29514.7 Proposed Method 297Streaming API 29814.8 Experimental Setup and Results 30014.9 Conclusion 302References 30315 A Review of Topic Modeling and Its Application 305R. Sandhiya, A. M. Boopika, M. Akshatha, S. V. Swetha and N. M. Hariharan15.1 Introduction 30515.2 Objective of Topic Modeling 30615.3 Motivations and Contributions 30715.4 Detailed Survey of Research Articles 308Information Extraction Systems by Gibbs Sampling 316Monte Carlo Algorithm 31615.5 Comparison Table of Previous Research 31915.6 Expected Future Work 32015.7 Conclusion 320References 321Part II: Optimization 32316 ROC Method for Identifying the Optimal Threshold With an Application to Email Classification 325Fasanya, Oluwafunmibi O., Adediran, Adetola A., Ewemooje, Olusegun S. and Adebola, Femi B.16.1 Introduction 32516.2 Related Works 32616.3 Methodology 32816.4 Results and Discussion 33416.5 Conclusion 337References 33817 Optimal Inventory System in a Urea Bagging Industry 339C. Vijayalakshmi, R. Subramani and N. Anitha17.1 Introduction 33917.2 Continuous Review Policy 34517.3 Inventory Optimization Techniques 34517.5 Numerical Calculations 35317.6 Conclusion 354References 35418 Design of a Mixed Integer Linear Programming Model for Optimization of Supply Chain of a Single Product With Disruption Scenario 357C. Vijayalakshmi18.1 Introduction 35718.2 Mixed Integer Programming Methods 35918.3 Introduction to Supply Chain Management System 35918.4 Mathematical Model Formulation 36218.5 Conclusion 368References 36819 Development of Base Tax Liability Insurance Premium Calculator for the South African Construction Industry—A Machine Learning Approach 371Blanche Mabusela-Motsosi, Senzosenkosi Myeni and Elias Munapo19.1 Introduction 37219.2 Literature Review 37319.3 The Aim and Objectives of the Study 37419.4 Research Methodology 37419.5 Study Results and Discussions 37619.6 Conclusions 381References 38220 A 90-Degree Schiffman Phase Shifter and Study of Tunability Using Varactor Diode 385Partha Kumar Deb, Tamasi Moyra and Bidyut Kumar Bhattacharyya20.1 Introduction 38520.2 Designing of 90° SPS 38620.3 Designing of Tunable Schiffman Phase Shifter 39120.4 Major Finding and Limitation 39820.5 Conclusion 398References 39921 Optimizing Manufacturing Performance Through Fuzzy Techniques 401Chandan Deep Singh, Harleen Kaur and Rajdeep Singh21.1 Introduction 40121.2 Literature Review 40321.3 Performance Optimization through Fuzzy Techniques 40821.4 Conclusions 441References 44322 Implementation of Non-Linear Inventory Optimization Model for Multiple Products 447Thiripura Sundari P.R. and Vijayalakshmi C.22.1 Introduction 44722.2 Literature Review 44822.3 Symbols and Assumptions 44922.4 Model Formulation 45122.5 Conclusion 459References 459Part III: Meta-Heuristics: Applications and Innovations 46123 Pufferfish Optimization Algorithm: A Bioinspired Optimizer 463Mehmet Cem Catalbas and Arif Gulten23.1 An Introduction to Optimization 46323.2 Optimization and Engineering 46523.3 Meta-Heuristic Optimization 46923.4 Torquigener Albomaculosus 47123.5 Pufferfish and Circular Structures 47123.6 Results 47523.7 Conclusion 483References 48324 A Hybrid Grey Wolf Optimizer and Sperm Swarm Optimization for Global Optimization 487Hisham A. Shehadeh and Nura Modi Shagari24.1 Introduction 48724.2 Background on Sperm Swarm Optimization (SSO) and GreyWolf Optimizer (GWO) 48924.3 Hybrid Grey Wolf Optimizer and Sperm Swarm Optimization(HGWOSSO) 49324.4 Experimental and Results 49424.5 Discussion 50424.6 Conclusion 505References 50525 State-of-the-Art Optimization and Metaheuristic Algorithms 509Vineet Kumar, R. Naresh, Veena Sharma and Vineet Kumar25.1 Introduction 50925.2 An Overview of Traditional Optimization Approaches 51125.3 Properties of Metaheuristics 51225.4 Classification of Single Objective Metaheuristic Algorithms 51425.5 Applications of Single Objective Metaheuristic Approaches 51925.6 Classification of Multi-Objective Optimization Algorithms 51925.7 Hybridization of MOPs Algorithms 52125.8 Parallel Multi-Objective Optimization 52125.9 Applications of Multi-Objective Optimization 52525.10 Significant Contributions of Researchers in VariousMetaheuristic Approaches 52625.11 Conclusion 52825.12 Major Findings, Future Scope of Metaheuristics and Its Applications 52925.13 Limitations and Motivation of Metaheuristics 529Acknowledgements 530References 53026 Model Reduction and Controller Scheme Development of Permanent Magnet Synchronous Motor Drives in the Delta Domain Using a Hybrid Firefly Technique 537Souvik Ganguli, Tanya Srivastava, Gagandeep Kaur and Prasanta Sarkar26.1 Introduction 53826.2 Proposed Methodology 54126.3 Simulation Results 54226.4 Conclusions 545References 54627 A New Parameter Estimation Technique of Three-Diode PV Cells 549Shilpy Goyal, Parag Nijhawan, Yashonidhi Srivastava and Souvik Ganguli27.1 Introduction 54927.2 Problem Statement 55127.3 Proposed Method 55327.4 Simulation Results and Discussions 55527.5 Conclusions 603References 603Part IV: Sustainable Computing 60528 Optimal Quantizer and Machine Learning–Based Decision Fusion for Cooperative Spectrum Sensing in IoT Cognitive Radio Network 607Saikat Majumder and Mukhdeep Singh Manshahia28.1 Introduction 60728.2 System Model and Preliminaries 61028.3 Machine Learning Techniques of Decision Fusion 61328.4 Optimum Quantization of Decision Statistic and Fusion 61828.5 Measurement Setup 62128.6 Performance Evaluation 62328.7 Conclusion 63328.8 Limitations and Scope for Future Work 633References 63429 Green IoT for Smart Agricultural Monitoring: Prediction Intelligence With Machine Learning Algorithms, Analysis of Prototype, and Review of Emerging Technologies 637Parijata Majumdar, Sanjoy Mitra and Diptendu Bhattacharya29.1 Introduction 63829.2 Green Approaches: Significance and Motivation 63829.3 Machine Learning Algorithms for Prediction Intelligence in Smart Irrigation Control 63929.4 Green IoT–Based Smart Irrigation Monitoring 63929.5 Technology Enablers for GIoT–Based Irrigation Monitoring 64229.6 Prototype of the Layered GIoT Framework for Intelligent Irrigation 64229.7 Other Recent Developments on GIoT–Based Smart Agriculture 64329.8 Literature Review of Edge Computing–Based Irrigation Monitoring 64529.9 LPWAN for GIoT–Based Smart Agriculture 64629.10 Analysis and Discussion 64729.11 Research Gap in GIoT–Based Precision Agriculture 64929.12 Analysis of Merits and Shortcomings 65029.13 Future Research Scope 65129.14 Conclusion 651References 65230 Prominence of Sentiment Analysis in Web-Based Data Using Semi-Supervised Classification 655B. Bazeer Ahamed and Z. A. Feroze Ahamed30.1 Introduction 65530.2 Related Works 65630.3 Proposed Approach 65730.4 Experimental Details and Results 66030.5 Conclusion 662References 66231 A Three-Phase Fuzzy and A* Approach to Sensor Deployment and Transmission 665R. Deepa, Revathi Venkataraman and Soumya Snigdha Kundu31.1 Introduction 66531.2 Related Work 66631.3 Proposed Model 66731.4 Complexity Analysis of Algorithms for Data Transmission 67131.5 Experimental Analysis 67231.6 Motivation and Limitations of Research 67531.7 Conclusion 67531.8 Future Work 675References 67532 Intelligent Computing for Precision Agriculture 677Priyanka Gupta, Kavita Jhajharia and Pratistha Mathur32.1 Introduction 67732.2 Technology in Agriculture 684References 69133 Intelligent Computing for Green Sustainability 693Chandan Deep Singh and Harleen Kaur33.1 Introduction 69333.2 Modified DEMATEL 69733.3 Weighted Sum Model 70633.4 Weighted Product Model 70833.5 Weighted Aggregated Sum Product Assessment 70933.6 Grey Relational Analysis 71233.7 Simple Multi-Attribute Rating Technique 71733.8 Criteria Importance Through Inter-Criteria Correlation 72133.9 Entropy 72633.10 Evaluation Based on Distance From Average Solution 73133.11 MOORA 73933.12 Interpretive Structural Modeling 73933.13 Conclusions 74833.14 Limitations of the Study 74933.15 Suggestions for Future Research 749References 750Part V: AI in Healthcare 75334 Bayesian Estimation of Gender Differences in Lipid Profile, Among Patients With Coronary Artery Disease 755Vivek Verma, Anita Verma, Ashwani Kumar Mishra, Hafiz T.A. Khan, Dilip C. Nath and Rajiv Narang34.1 Introduction 75634.2 Methods 75734.3 Statistical Analysis 75734.4 Results 75934.5 Discussion 76134.6 Conclusion 767Acknowledgements 767References 76735 Reconstruction of Dynamic MRI Using Convolutional LSTM Technique 771Shashidhar V. Yakkundi and Subha D. Puthankattil35.1 Introduction 77135.2 Methodologies 77335.3 Problem Formulation 77435.4 Network Architecture 77635.5 Results 77835.6 Discussion 78035.7 Conclusion 782References 78436 Gender Classification Using Multispectral Imaging: A Comparative Performance Analysis Between Affine Hull and Wavelet Fusion 785Narayan Vetrekar, Aparajita Naik and R. S. Gad36.1 Introduction 78536.2 Literature Review 78736.3 Multispectral Face Database 79136.4 Methodology 79236.5 Experiments 79436.6 Results and Discussion 79436.7 Conclusions 796Acknowledgments 797References 79737 Polyp Detection Using Deep Neural Networks 801Nancy Rani, Rupali Verma and Alka Jindal37.1 Introduction 80137.2 Literature Survey 80337.3 Proposed Methodology 80637.4 Implementation and Results 81037.5 Conclusion and Future Work 812References 81338 Boundary Exon Prediction in Humans Sequences Using External Information Sources 815Neelam Goel, Shailendra Singh and Trilok Chand Aseri38.1 Introduction 81538.2 Proposed Exon Prediction Model 81738.3 Homology-Based Exon Prediction 81938.4 Results and Discussion 82738.5 Conclusion 83038.6 Motivation and Limitations of the Research 83138.7 Major Findings of the Research 831References 83239 Blood Glucose Prediction Using Machine Learning on Jetson Nanoplatform 835Jivan Parab, M. Sequeira, M. Lanjewar, C. Pinto and G.M. Naik39.1 Introduction 83539.2 Sample Preparation 83739.3 Methodology 83939.4 Results and Discussion 84239.5 Discussion 84539.6 Conclusion 84639.7 Future Scope 846Acknowledgement 847References 84740 GIS-Based Geospatial Assessment of Novel Corona Virus (COVID-19) in One of the Promising Industrial States of India—A Case of Gujarat 849Azazkhan I. Pathan, Pankaj J. Gandhi , P.G. Agnihotri and Dhruvesh Patel40.1 Introduction 84940.2 The Rationale of the Study 85240.3 Materials and Methodology 85440.4 GIS and COVID-19 (Corona) Mapping 85940.5 Results and Discussion 86040.6 Conclusion 865References 86641 Mobile-Based Medical Alert System for COVID-19 Based on ZigBee and WiFi 869Munish Manas and Shivam Kumar41.1 Introduction 86941.2 Hardware Design of Monitoring System 87041.3 Software Design of Monitoring System 87341.4 Working of ZigBee Module 87441.5 Developed App for the Monitoring of Health 87441.6 Google Fusion Table—Online Database 87541.7 Application Developed for Health Monitoring System 87641.8 Conclusion and Future Work 877References 877Index 879