{"product_id":"intelligent-and-soft-computing-systems-for-green-energy-hardback-9781394166374","title":"Intelligent and Soft Computing Systems for Green Energy (Hardback) 9781394166374","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eIntelligent and Soft Computing Systems for Green Energy\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eA. Chitra (Edited by), Chitra (Author), V. Indragandhi (Edited by), W. Razia Sultana (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394166374, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 6 June 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e384 pages\u003cbr\u003e22.9 x 15.2 x 2.4 cm, 0.767 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eINTELLIGENT AND SOFT COMPUTING SYSTEMS FOR GREEN ENERGY\u003c\/b\u003e \u003cp\u003e\u003cb\u003eWritten and edited by some of the world’s top experts in the field, this exciting new volume provides state-of-the-art research and the latest technological breakthroughs in next-generation computing systems for the energy sector, striving to bring the science toward sustainability.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eReal-world problems need intelligent solutions. Across many industries and fields, intelligent and soft computing systems, using such developing technologies as artificial intelligence and Internet of Things, are quickly becoming important tools for scientists, engineers, and other professionals for solving everyday problems in practical situations. \u003c\/p\u003e\n\u003cp\u003eThis book aims to bring together the research that has been carried out in the field of intelligent and soft computing systems. Intelligent and soft computing systems involves expertise from various domains of research, such as electrical engineering, computer engineering, and mechanical engineering. This book will serve as a point of convergence wherein all these domains come together. \u003c\/p\u003e\n\u003cp\u003eThe various chapters are configured to address the challenges faced in intelligent and soft computing systems from various fields and possible solutions. The outcome of this book can serve as a potential resource for industry professionals and researchers working in the domain of intelligent and soft computing systems. \u003c\/p\u003e\n\u003cp\u003eTo list a few soft computing techniques, neural-based load forecasting, IoT-enabled smart grids, and blockchain technology for energy trading. Whether for the veteran engineer or the student learning the latest breakthroughs, this exciting new volume is a must-have for any library.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Placement and Sizing of Distributed Generator and Capacitor in a Radial Distribution System Considering Load Growth 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eG. Manikanta, N. Kirn Kumar, Ashish Mani and V. Indragandhi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Problem Formulation 3\u003c\/p\u003e \u003cp\u003e1.3 Algorithm 5\u003c\/p\u003e \u003cp\u003e1.4 Results \u0026amp; Discussions 9\u003c\/p\u003e \u003cp\u003e1.5 Discussion 20\u003c\/p\u003e \u003cp\u003e1.6 Conclusions 21\u003c\/p\u003e \u003cp\u003eReferences 21\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Security Issues and Challenges for the IoT-Based Smart Grid 25\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePrathiga, Kavya K., Nanthitha N., Nithishkumar K., Ritika T. and Vishal T.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 25\u003c\/p\u003e \u003cp\u003e2.2 Usage of IoT in the Smart Grid Context 27\u003c\/p\u003e \u003cp\u003e2.3 Advantages of IoT-Based Smart Grid 29\u003c\/p\u003e \u003cp\u003e2.4 Cybersecurity Challenges 30\u003c\/p\u003e \u003cp\u003e2.4.1 Review of Recent Attacks 32\u003c\/p\u003e \u003cp\u003e2.4.1.1 Tram Hack Lodz, Poland 32\u003c\/p\u003e \u003cp\u003e2.4.1.2 Texas Power Company Hack 32\u003c\/p\u003e \u003cp\u003e2.4.1.3 Stuxnet Attack on Iranian Nuclear Power Facility 32\u003c\/p\u003e \u003cp\u003e2.4.1.4 Houston, Texas, Water Distribution System Attack 33\u003c\/p\u003e \u003cp\u003e2.4.1.5 Bowman Avenue Dam Cyberattack 33\u003c\/p\u003e \u003cp\u003e2.5 Other Major Challenges Hindering Growth of IoT Network 33\u003c\/p\u003e \u003cp\u003e2.5.1 Standardization Protocols 33\u003cbr\u003e\u003cbr\u003e2.5.2 Cognitive Capability 34\u003c\/p\u003e \u003cp\u003e2.5.3 Power 34\u003c\/p\u003e \u003cp\u003e2.5.4 Consumer Illiteracy 35\u003c\/p\u003e \u003cp\u003e2.5.5 Weak Regulations 35\u003c\/p\u003e \u003cp\u003e2.5.6 Fear of Reputational Damage 36\u003c\/p\u003e \u003cp\u003e2.6 Future Prospects 36\u003c\/p\u003e \u003cp\u003e2.7 Conclusion 38\u003c\/p\u003e \u003cp\u003eReferences 39\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Electrical Load Forecasting Using Bayesian Regularization Algorithm in Matlab and Finding Optimal Solution via Renewable Source 41\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eChinmay Singh, Yashwant Sawle, Navneet Kumar, Utkarsh Jha and Arunkumar L.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 42\u003c\/p\u003e \u003cp\u003e3.2 Algorithm 43\u003c\/p\u003e \u003cp\u003e3.2.1 Levenberg-Marquardt Algorithm 43\u003c\/p\u003e \u003cp\u003e3.2.2 Bayesian Regularization 45\u003c\/p\u003e \u003cp\u003e3.2.2.1 Comparison of Bayesian Models 46\u003c\/p\u003e \u003cp\u003e3.2.2.2 Bayesian Ways to Neural Network Modeling 46\u003c\/p\u003e \u003cp\u003e3.2.3 Scaled Conjugate Gradient Algorithm 47\u003c\/p\u003e \u003cp\u003e3.2.3.1 Steps of Algorithm 47\u003c\/p\u003e \u003cp\u003e3.2.4 Gradient Descent 48\u003c\/p\u003e \u003cp\u003e3.2.5 Conjugate Gradient 48\u003c\/p\u003e \u003cp\u003e3.3 Methodology and Modelling 49\u003c\/p\u003e \u003cp\u003e3.4 Results and Discussion 52\u003c\/p\u003e \u003cp\u003e3.5 Conclusion 55\u003c\/p\u003e \u003cp\u003eReferences 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Theft Detection Sensing by IoT in Smart Grid 59\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eN. Siva Mallikarjuna Rao, M. Ramu and Lekha Varisa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 60\u003c\/p\u003e \u003cp\u003e4.1.1 Power Theft Identification 60\u003c\/p\u003e \u003cp\u003e4.1.2 Basic Structure of Smart Grid 60\u003c\/p\u003e \u003cp\u003e4.2 Problem Identification 62\u003c\/p\u003e \u003cp\u003e4.2.1 Power Theft Methods 62\u003c\/p\u003e \u003cp\u003e4.3 Methodology for Implementation of IoT to Different Theft Mechanisms in Smart Grid 64\u003c\/p\u003e \u003cp\u003e4.4 Conclusion 66\u003c\/p\u003e \u003cp\u003e4.5 Future Work 67\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Energy Metering and Billing Systems Using Arduino 69\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Ramu, Lekha Varisa and N. Siva Mallikarjuna Rao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 69\u003c\/p\u003e \u003cp\u003e5.2 Smart Meters and Billing Systems 72\u003c\/p\u003e \u003cp\u003e5.2.1 Arduino Mega 72\u003c\/p\u003e \u003cp\u003e5.2.2 Lcd 72\u003c\/p\u003e \u003cp\u003e5.2.3 Proteus Software 73\u003c\/p\u003e \u003cp\u003e5.3 Working 73\u003c\/p\u003e \u003cp\u003e5.4 Applications 74\u003c\/p\u003e \u003cp\u003e5.5 Time of Use 74\u003c\/p\u003e \u003cp\u003e5.6 Observations 74\u003c\/p\u003e \u003cp\u003e5.7 Equations 75\u003c\/p\u003e \u003cp\u003e5.8 Results 75\u003c\/p\u003e \u003cp\u003e5.9 Adoption in India 76\u003c\/p\u003e \u003cp\u003e5.10 Excess Generation of Electricity 76\u003c\/p\u003e \u003cp\u003e5.11 Commercial Use \u0026amp; Home Energy Monitoring 76\u003c\/p\u003e \u003cp\u003e5.12 Conclusion 77\u003c\/p\u003e \u003cp\u003eReferences 77\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Smart Meter Vulnerability Assessment Under Cyberattack Events – An Attempt to Safeguard 79\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKunal Kumar and R. Raja Singh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 80\u003c\/p\u003e \u003cp\u003e6.2 Advanced Metering Infrastructure Architecture 82\u003c\/p\u003e \u003cp\u003e6.2.1 Smart Meter Architecture and Design 83\u003c\/p\u003e \u003cp\u003e6.2.2 AMI Communication Network 83\u003c\/p\u003e \u003cp\u003e6.2.3 Home Area Network 84\u003c\/p\u003e \u003cp\u003e6.2.4 Data Concentrator 84\u003c\/p\u003e \u003cp\u003e6.3 Possible Attacks on AMI 84\u003c\/p\u003e \u003cp\u003e6.3.1 Manual Attacks 84\u003c\/p\u003e \u003cp\u003e6.3.2 Cyberattacks 84\u003c\/p\u003e \u003cp\u003e6.3.3 Threats and Countermeasures of Attacks on Smart Meter 87\u003c\/p\u003e \u003cp\u003e6.4 RSA Attack Detection Model 87\u003c\/p\u003e \u003cp\u003e6.4.1 RSA Keys Creation 89\u003c\/p\u003e \u003cp\u003e6.5 Hash Code for Data Integrity 89\u003c\/p\u003e \u003cp\u003e6.6 Results and Discussion 90\u003c\/p\u003e \u003cp\u003e6.6.1 Attack Detection System 90\u003c\/p\u003e \u003cp\u003e6.6.2 Python Implementation 91\u003c\/p\u003e \u003cp\u003e6.7 Conclusion 93\u003c\/p\u003e \u003cp\u003eReferences 94\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Power Quality Improvement for Grid-Connected Hybrid Wind-Solar Energy System Using a Three-Phase Three-Wire Grid-Interfacing Compensator 97\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBoopathi R. and Dr. Indragandhi V.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 98\u003c\/p\u003e \u003cp\u003e7.2 Proposed Current Control System 100\u003c\/p\u003e \u003cp\u003e7.3 Simulation Analysis and Discussion 103\u003c\/p\u003e \u003cp\u003e7.4 Conclusion 107\u003c\/p\u003e \u003cp\u003eReferences 108\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Energy Trading in Virtual Power Plant Enabled Communities Using Double Auction Technique and Blockchain Technology 111\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRadhika Yadav, Balla Manoj Kumar, Saurav Baid and Padma Priya R.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 112\u003c\/p\u003e \u003cp\u003e8.2 Related Work 113\u003c\/p\u003e \u003cp\u003e8.3 Proposed Methodology 114\u003c\/p\u003e \u003cp\u003e8.3.1 System Model 115\u003c\/p\u003e \u003cp\u003e8.3.2 Problem Formulation 116\u003c\/p\u003e \u003cp\u003e8.3.2.1 Objective 1 (Optimum Reimbursements for both the Traders) 116\u003c\/p\u003e \u003cp\u003e8.3.2.2 Objective 2 (Shortest Line Routing System) 116\u003c\/p\u003e \u003cp\u003e8.3.2.3 Utility Function (Maximum Social Welfare) 116\u003c\/p\u003e \u003cp\u003e8.3.3 Our Approach 117\u003c\/p\u003e \u003cp\u003e8.3.3.1 Double Auction 117\u003c\/p\u003e \u003cp\u003e8.3.3.2 Shortest Line Route Detection 119\u003c\/p\u003e \u003cp\u003e8.3.3.3 Blockchain 119\u003c\/p\u003e \u003cp\u003e8.3.3.4 ElGamal Cryptography 120\u003c\/p\u003e \u003cp\u003e8.4 Performance Evaluation 121\u003c\/p\u003e \u003cp\u003e8.4.1 Evaluation Methodology 121\u003c\/p\u003e \u003cp\u003e8.4.2 Evaluation Results 122\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 123\u003c\/p\u003e \u003cp\u003eReferences 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Sales Demand Forecasting for Retail Marketing Using XGBoost Algorithm 127\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Kavitha, R. Srinivasan, R. Kavitha and M. Suganthy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 128\u003c\/p\u003e \u003cp\u003e9.2 Related Work 129\u003c\/p\u003e \u003cp\u003e9.3 Methodology 130\u003c\/p\u003e \u003cp\u003e9.3.1 XGBoost Algorithm 130\u003c\/p\u003e \u003cp\u003e9.3.2 Architecture 131\u003c\/p\u003e \u003cp\u003e9.4 Experimental Results 131\u003c\/p\u003e \u003cp\u003e9.4.1 Exploratory Data Analysis 132\u003c\/p\u003e \u003cp\u003e9.4.1.1 Empirical Cumulative Distribution Function (ECDF) 132\u003c\/p\u003e \u003cp\u003e9.4.1.2 Exploring the Dataset and Making Visualizations between Months and Sales 133\u003c\/p\u003e \u003cp\u003e9.4.1.3 Correlation between each Feature or Attribute 134\u003c\/p\u003e \u003cp\u003e9.4.1.4 Time Series Analysis 134\u003c\/p\u003e \u003cp\u003e9.4.2 Model Prediction 137\u003c\/p\u003e \u003cp\u003e9.5 Conclusion 138\u003c\/p\u003e \u003cp\u003eReferences 139\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Region-Based Convolutional Neural Networks for Selective Search 141\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eR. Kavitha, Srinivasan R, P. Subha and M. Kavitha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 142\u003c\/p\u003e \u003cp\u003e10.2 Literature Review 143\u003c\/p\u003e \u003cp\u003e10.3 Existing Method 145\u003c\/p\u003e \u003cp\u003e10.4 Proposed Methodology 145\u003c\/p\u003e \u003cp\u003e10.5 Implementation and Results 147\u003c\/p\u003e \u003cp\u003e10.6 Conclusion 149\u003c\/p\u003e \u003cp\u003eReferences 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Design and Development of Mobility System for Double Amputees 151\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDr. Saravanan T S, Dr. Sagayaraj R, Dr. Sivaraman P R, Sivamani D, Jaiganesh R and Ragupathy P\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 152\u003c\/p\u003e \u003cp\u003e11.2 Block Diagram 152\u003c\/p\u003e \u003cp\u003e11.3 Working Methodology 153\u003c\/p\u003e \u003cp\u003e11.4 Design Calculation 154\u003c\/p\u003e \u003cp\u003e11.5 Hardware Implementation 156\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 159\u003c\/p\u003e \u003cp\u003eReferences 159\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 A Review: Precision Vehicle Control Using Internet of Things 163\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eR. Srinivasan, Kavitha R, Kavitha M and Sridhar K\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 163\u003c\/p\u003e \u003cp\u003e12.2 Related Works 164\u003c\/p\u003e \u003cp\u003e12.3 Proposed Work 166\u003c\/p\u003e \u003cp\u003e12.4 Existing System 167\u003c\/p\u003e \u003cp\u003e12.4.1 Advantages 167\u003c\/p\u003e \u003cp\u003e12.4.2 Disadvantages 168\u003c\/p\u003e \u003cp\u003e12.4.3 Applications 168\u003c\/p\u003e \u003cp\u003e12.5 Proposed System 169\u003c\/p\u003e \u003cp\u003e12.6 Conclusion and Future Enhancement 170\u003c\/p\u003e \u003cp\u003eReferences 171\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 A Process of Analyzing Soil Moisture with the Integration of Internet of Things and Wireless Sensor Network 173\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eR. Srinivasan, Kavitha R, V. Murugananthan and T. Mylsami\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 174\u003c\/p\u003e \u003cp\u003e13.1.1 Wsn 174\u003c\/p\u003e \u003cp\u003e13.1.2 IoT 174\u003c\/p\u003e \u003cp\u003e13.2 Literature Study 175\u003c\/p\u003e \u003cp\u003e13.3 Proposed Work 176\u003c\/p\u003e \u003cp\u003e13.3.1 Sensing and Transmitter Module 176\u003c\/p\u003e \u003cp\u003e13.3.2 Receiver Unit 178\u003c\/p\u003e \u003cp\u003e13.3.3 IoT Activation 178\u003c\/p\u003e \u003cp\u003e13.3.4 Event Recognition Algorithm 179\u003c\/p\u003e \u003cp\u003e13.4 Result and Discussion 180\u003c\/p\u003e \u003cp\u003e13.5 Conclusion 182\u003c\/p\u003e \u003cp\u003eReferences 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Automatic Angular Position Stabilization of Ambulance Stretcher in Real Time 185\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVedant Joshi, Maheshwari S. and Kathirvelan J.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 185\u003c\/p\u003e \u003cp\u003e14.2 Materials and Methods 187\u003c\/p\u003e \u003cp\u003e14.2.1 Interior and Flaws 187\u003c\/p\u003e \u003cp\u003e14.2.2 Proposed Position of the Stretcher 188\u003c\/p\u003e \u003cp\u003e14.2.3 Hardware and Software 188\u003c\/p\u003e \u003cp\u003e14.2.4 Methodology 189\u003c\/p\u003e \u003cp\u003e14.3 Results and Discussion 192\u003c\/p\u003e \u003cp\u003e14.3.1 Results 192\u003c\/p\u003e \u003cp\u003e14.4 Discussion 194\u003c\/p\u003e \u003cp\u003e14.5 Conclusion 195\u003c\/p\u003e \u003cp\u003eReferences 195\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Automated Ploughing Seeding with Water Management System 199\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnto Sheeba J., Shyam D., Sivamani D., Sangari A., Jayashree K. and Nazar Ali A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 199\u003c\/p\u003e \u003cp\u003e15.2 Block Diagram 200\u003c\/p\u003e \u003cp\u003e15.3 Working Methodology 201\u003c\/p\u003e \u003cp\u003e15.4 Design Calculation 202\u003c\/p\u003e \u003cp\u003e15.5 Simulation 203\u003c\/p\u003e \u003cp\u003e15.6 Hardware Implementation 205\u003c\/p\u003e \u003cp\u003e15.7 Conclusion 208\u003c\/p\u003e \u003cp\u003eReferences 208\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Detecting Fraudulent Data Using Stacked Auto-Encoding: A Three-Layer Approach 211\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eP. Saravanan, V. Indragandhi and V. Subramaniyaswamy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 211\u003c\/p\u003e \u003cp\u003e16.1.1 Deep Learning 212\u003c\/p\u003e \u003cp\u003e16.1.2 Auto-Encoders 212\u003c\/p\u003e \u003cp\u003e16.2 Related Work 214\u003c\/p\u003e \u003cp\u003e16.3 Proposed Methodology 215\u003c\/p\u003e \u003cp\u003e16.4 Results and Discussion 218\u003c\/p\u003e \u003cp\u003e16.5 Conclusion 221\u003c\/p\u003e \u003cp\u003eAcknowledgment 221\u003c\/p\u003e \u003cp\u003eReferences 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Artificial Intelligence-Based Ambulance 223\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDr. R. Sumathi, R.M. Gokul, M. Gokulakrishnan, K. Ganesh Babu and S. Pavithra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 224\u003c\/p\u003e \u003cp\u003e17.1.1 Problem Statement 224\u003c\/p\u003e \u003cp\u003e17.1.2 Field of the Project 224\u003c\/p\u003e \u003cp\u003e17.1.3 Objectives 225\u003c\/p\u003e \u003cp\u003e17.2 Proposed System 225\u003c\/p\u003e \u003cp\u003e17.2.1 Block Diagram of Traffic Signal Control System 225\u003c\/p\u003e \u003cp\u003e17.2.2 Block Diagram of Biometric-Based Medical Records 226\u003c\/p\u003e \u003cp\u003e17.3 Implementation of Traffic Signal Control System 226\u003c\/p\u003e \u003cp\u003e17.3.1 Flowchart of Traffic Signal Control System 226\u003c\/p\u003e \u003cp\u003e17.3.2 Algorithm of Biometric-Based Medical Records System 228\u003c\/p\u003e \u003cp\u003e17.3.3 Methodology of Traffic Signal Control System 228\u003c\/p\u003e \u003cp\u003e17.3.3.1 Normal Mode 229\u003c\/p\u003e \u003cp\u003e17.3.3.2 Emergency Mode 230\u003c\/p\u003e \u003cp\u003e17.3.4 Methodology of Biometric-Based Medical Records System 230\u003c\/p\u003e \u003cp\u003e17.3.4.1 Smpt 230\u003c\/p\u003e \u003cp\u003e17.4 Result and Discussion 231\u003c\/p\u003e \u003cp\u003e17.4.1 Comparison of Results 231\u003c\/p\u003e \u003cp\u003e17.4.2 Hardware Result 231\u003c\/p\u003e \u003cp\u003e17.5 Conclusion 234\u003c\/p\u003e \u003cp\u003e17.6 Future Scope 234\u003c\/p\u003e \u003cp\u003eReferences 235\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 LoRa-Based Flaw Location Detection in HT Line Using GSM 237\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDr. M. Senthilkumar, Abisheck D., Gnana Prakash K., Hari Babu S. and Hariharan R.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 238\u003c\/p\u003e \u003cp\u003e18.1.1 Different Types of Transmission Line Fault 238\u003c\/p\u003e \u003cp\u003e18.1.1.1 Single Line-to-Ground Fault 238\u003c\/p\u003e \u003cp\u003e18.1.1.2 Line-to-Line Fault 238\u003c\/p\u003e \u003cp\u003e18.1.1.3 Double Line-to-Ground Fault 239\u003c\/p\u003e \u003cp\u003e18.1.1.4 Balance Three-Phase Fault 239\u003c\/p\u003e \u003cp\u003e18.2 Objective 240\u003c\/p\u003e \u003cp\u003e18.3 Literature Survey 240\u003c\/p\u003e \u003cp\u003e18.4 Proposed System 241\u003c\/p\u003e \u003cp\u003e18.5 Flow Chart 244\u003c\/p\u003e \u003cp\u003e18.6 Result and Discussion 244\u003c\/p\u003e \u003cp\u003e18.7 Novelty of Work 248\u003c\/p\u003e \u003cp\u003e18.8 Conclusion 250\u003c\/p\u003e \u003cp\u003e18.9 Future Enhancement 251\u003c\/p\u003e \u003cp\u003eReferences 252\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Classification Models for Breast Cancer Detection 255\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVarsha B., Sneka P., Tanuja A. and Shana J.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 255\u003c\/p\u003e \u003cp\u003e19.2 Related Work 256\u003c\/p\u003e \u003cp\u003e19.3 Research Objective 257\u003c\/p\u003e \u003cp\u003e19.4 Methodology 257\u003c\/p\u003e \u003cp\u003e19.4.1 Dataset Description 258\u003c\/p\u003e \u003cp\u003e19.4.2 Data Preprocessing 258\u003c\/p\u003e \u003cp\u003e19.4.3 Exploratory Data Analysis 258\u003c\/p\u003e \u003cp\u003e19.5 Model Selection 260\u003c\/p\u003e \u003cp\u003e19.5.1 Logistic Regression 260\u003c\/p\u003e \u003cp\u003e19.5.2 Decision Tree Classifier 261\u003c\/p\u003e \u003cp\u003e19.5.3 Random Forest Classifier 261\u003c\/p\u003e \u003cp\u003e19.6 Results and Discussion 261\u003c\/p\u003e \u003cp\u003e19.6.1 Confusion Matrix 261\u003c\/p\u003e \u003cp\u003e19.6.2 Model Evaluation and Prediction 262\u003c\/p\u003e \u003cp\u003e19.7 Conclusion 263\u003c\/p\u003e \u003cp\u003eReferences 263\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 T-Count Optimized Quantum Comparator Circuit 265\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGayathri S. S., R. Kumar and Samiappan Dhanalakshmi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 265\u003c\/p\u003e \u003cp\u003e20.2 Related Works 268\u003c\/p\u003e \u003cp\u003e20.3 Proposed Quantum Comparator 268\u003c\/p\u003e \u003cp\u003e20.3.1 Multi-Qubit Magnitude Comparator 268\u003c\/p\u003e \u003cp\u003e20.4 Conclusion 270\u003c\/p\u003e \u003cp\u003eReferences 270\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 IoT-Based Heart Rate Monitoring System for Smart Healthcare Applications 273\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJaba Deva Krupa Abel, Samiappan Dhanalakshmi, Sanjana N.L. and R. Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 274\u003c\/p\u003e \u003cp\u003e21.2 Related Work 275\u003c\/p\u003e \u003cp\u003e21.3 Methodology 276\u003c\/p\u003e \u003cp\u003e21.3.1 Fractional Fourier Transform 278\u003c\/p\u003e \u003cp\u003e21.3.2 Amazon Web Services 280\u003c\/p\u003e \u003cp\u003e21.4 Results and Discussion 281\u003c\/p\u003e \u003cp\u003e21.5 Conclusion 283\u003c\/p\u003e \u003cp\u003eReferences 284\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Neural Collaborative Filtering-Based Hybrid Recommender System for Online Movies Recommendation 287\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS. Priyanka, P. Saravanan, V. Indragandhi and V. Subramaniyaswamy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 288\u003c\/p\u003e \u003cp\u003e22.2 Related Works 289\u003c\/p\u003e \u003cp\u003e22.3 Proposed Methodology 290\u003c\/p\u003e \u003cp\u003e22.3.1 Dataset Used for the Proposed System 291\u003c\/p\u003e \u003cp\u003e22.3.2 Architecture Diagram 291\u003c\/p\u003e \u003cp\u003e22.3.3 Sentiment Analysis 292\u003c\/p\u003e \u003cp\u003e22.3.4 Hybrid Recommendation 293\u003c\/p\u003e \u003cp\u003e22.3.4.1 Filtering Based on Content 293\u003c\/p\u003e \u003cp\u003e22.3.4.2 Collaborative Filtering 293\u003c\/p\u003e \u003cp\u003e22.3.5 Neural Collaborative Filtering (NCF) 294\u003c\/p\u003e \u003cp\u003e22.3.6 User-Based Recurrent Neural Networks (RNN) 296\u003c\/p\u003e \u003cp\u003e22.4 Results and Discussion 297\u003c\/p\u003e \u003cp\u003e22.5 Conclusion and Future Work 299\u003c\/p\u003e \u003cp\u003eReferences 300\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 Farmer’s Eye Using CNN 303\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eElam Cheren S., Yuvan Raj Kumar M., Vivek G., Udhayakumar N. and Saravanakumar M. V.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 303\u003c\/p\u003e \u003cp\u003e23.2 Related Works 304\u003c\/p\u003e \u003cp\u003e23.3 PV Module 305\u003c\/p\u003e \u003cp\u003e23.4 Hardware Description 306\u003c\/p\u003e \u003cp\u003e23.5 Software Implementation 309\u003c\/p\u003e \u003cp\u003e23.6 Hardware Implementation 311\u003c\/p\u003e \u003cp\u003e23.7 Conclusion 313\u003c\/p\u003e \u003cp\u003eReferences 313\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 Solar Powered Density and Emergency-Based Traffic Control System Using NI LabVIEW 315\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eM. Devika Rani, G. Bhavani, K. Kartheek, A. Sindhura and D. Nikhila\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24.1 Introduction 315\u003c\/p\u003e \u003cp\u003e24.2 Literature Review 316\u003c\/p\u003e \u003cp\u003e24.3 Methodology 317\u003c\/p\u003e \u003cp\u003e24.3.1 Block Diagram 317\u003c\/p\u003e \u003cp\u003e24.3.2 LabVIEW 319\u003c\/p\u003e \u003cp\u003e24.4 Components 322\u003c\/p\u003e \u003cp\u003e24.4.1 Main Components 322\u003c\/p\u003e \u003cp\u003e24.4.1.1 Solar Panel 322\u003c\/p\u003e \u003cp\u003e24.4.1.2 Battery 323\u003c\/p\u003e \u003cp\u003e24.4.1.3 Buck Converter 323\u003c\/p\u003e \u003cp\u003e24.4.1.4 IR Sensor 323\u003c\/p\u003e \u003cp\u003e24.4.1.5 NI my RIO 324\u003c\/p\u003e \u003cp\u003e24.4.1.6 NPN Transistor 324\u003c\/p\u003e \u003cp\u003e24.4.1.7 Glue Sticks 324\u003c\/p\u003e \u003cp\u003e24.4.1.8 Heat Sink Slive Tubes 325\u003c\/p\u003e \u003cp\u003e24.4.1.9 Toggle Switch 325\u003c\/p\u003e \u003cp\u003e24.4.2 Supporting Components 326\u003c\/p\u003e \u003cp\u003e24.4.2.1 Connecting Pins 326\u003c\/p\u003e \u003cp\u003e24.4.2.2 Leds 326\u003c\/p\u003e \u003cp\u003e24.5 Result 328\u003c\/p\u003e \u003cp\u003e24.5.1 SIM View 328\u003c\/p\u003e \u003cp\u003e24.6 Implementation of Hardware Components 330\u003c\/p\u003e \u003cp\u003e24.7 Conclusion 332\u003c\/p\u003e \u003cp\u003eApplications 332\u003c\/p\u003e \u003cp\u003eReferences 332\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 Observation of TCSU: Travel Cold Storage Unit Operated by SPV Technology 335\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDevesh Umesh Sarkar, Tapan Prakash, Madhur Zadegaonkar, Ritu Bhimgade, Abhijeeta Gupta and Nidhi Ambekar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25.1 Introduction 335\u003c\/p\u003e \u003cp\u003e25.2 Working Methodology 336\u003c\/p\u003e \u003cp\u003e25.3 Tools \u0026amp; Platform 338\u003c\/p\u003e \u003cp\u003e25.4 Design \u0026amp; Implementation 338\u003c\/p\u003e \u003cp\u003e25.5 Advantages \u0026amp; Application 341\u003c\/p\u003e \u003cp\u003e25.6 Conclusion 341\u003c\/p\u003e \u003cp\u003eReferences 342\u003c\/p\u003e \u003cp\u003eIndex 345\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Electronics \u0026amp; communications engineering [\u003ca title=\"See our other books on Electronics \u0026amp; communications engineering\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Electronics%20\u0026amp;%20communications%20engineering%20%5BTJ%5D%22\"\u003eTJ\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52431054504216,"sku":"9781394166374","price":133.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394166374.jpg?v=1784770133","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/intelligent-and-soft-computing-systems-for-green-energy-hardback-9781394166374","provider":"Freshly Printed Books","version":"1.0","type":"link"}