{"product_id":"handbook-of-computational-sciences-a-multi-and-interdisciplinary-approach-hardback-9781119760467","title":"Handbook of Computational Sciences; A Multi and Interdisciplinary Approach (Hardback) 9781119760467","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eHandbook of Computational Sciences\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eA Multi and Interdisciplinary Approach\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eAhmed A. Elngar (Edited by), Elngar (Author), Vigneshwar. M. (Edited by), Vigneshwar. M. (Author), Krishna Kant Singh (Edited by), Krishna Kant Singh (Author), Zdzislaw Polkowski (Edited by), Zdzislaw Polkowski (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781119760467, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 2 August 2023\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e416 pages\u003cbr\u003e22.9 x 15.2 x 2.6 cm, 0.71 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\u003cp\u003e\u003ci\u003e\u003cb\u003eThe Handbook of Computational Sciences \u003c\/b\u003e\u003c\/i\u003eis a comprehensive collection of research chapters that brings together the latest advances and trends in computational sciences and addresses the interdisciplinary nature of computational sciences, which\u003ci\u003e\u003c\/i\u003e \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003erequire expertise from multiple disciplines to solve complex problems.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThis edited volume covers a broad range of topics, including computational physics, chemistry, biology, engineering, finance, and social sciences. Each chapter provides an in-depth discussion of the state-of-the-art techniques and methodologies used in the respective field. The book also highlights the challenges and opportunities for future research in these areas. \u003c\/p\u003e\n\u003cp\u003eThe volume pertains to applications in the areas of imaging, medical imaging, wireless and WS networks, IoT with applied areas, big data for various applicable solutions, etc. This text delves deeply into the core subject and then broadens to encompass the interlinking, interdisciplinary, and cross-disciplinary sections of other relevant areas. Those areas include applied, simulation, modeling, real-time, research applications, and more. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eBecause of the book’s multidisciplinary approach, it will be of value to many researchers and engineers in different fields including computational biologists, computational chemists, and physicists, as well as those in life sciences, neuroscience, mathematics, and software engineering.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 A Sensor-Based Automated Irrigation System for Indian Agricultural Fields 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eI.S. Akila and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Literary Survey 2\u003c\/p\u003e \u003cp\u003e1.3 Proposed System 4\u003c\/p\u003e \u003cp\u003e1.3.1 System Architecture 4\u003c\/p\u003e \u003cp\u003e1.3.2 Flow of Automated Irrigation 5\u003c\/p\u003e \u003cp\u003e1.3.3 Interfacing Sensors 5\u003c\/p\u003e \u003cp\u003e1.3.4 Physical Characteristics Determination Using Image Processing 8\u003c\/p\u003e \u003cp\u003e1.3.4.1 Fractal Dimension Estimation 8\u003c\/p\u003e \u003cp\u003e1.3.4.2 Box-Counting Method 9\u003c\/p\u003e \u003cp\u003e1.3.4.3 Physical Parameters 9\u003c\/p\u003e \u003cp\u003e1.4 Performance Studies 11\u003c\/p\u003e \u003cp\u003e1.4.1 Experimental Environment 11\u003c\/p\u003e \u003cp\u003e1.4.2 Accessing Shared Variables from NI Data Dashboard 12\u003c\/p\u003e \u003cp\u003e1.4.2.1 Scenario 1 14\u003c\/p\u003e \u003cp\u003e1.4.2.2 Scenario 2 14\u003c\/p\u003e \u003cp\u003e1.4.2.3 Scenario 3 14\u003c\/p\u003e \u003cp\u003e1.4.2.4 Scenario 4 14\u003c\/p\u003e \u003cp\u003e1.5 Image Processing to Determine Physical Characteristics 15\u003c\/p\u003e \u003cp\u003e1.6 Conclusion and Future Enhancements 20\u003c\/p\u003e \u003cp\u003e1.6.1 Conclusion 20\u003c\/p\u003e \u003cp\u003e1.6.2 Future Scope 20\u003c\/p\u003e \u003cp\u003eReferences 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 An Enhanced Integrated Image Mining Approach to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 23\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSridevy S., Anna Saro Vijendran and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 24\u003c\/p\u003e \u003cp\u003e2.2 Related Work 24\u003c\/p\u003e \u003cp\u003e2.3 Motivation 26\u003c\/p\u003e \u003cp\u003e2.4 Framework of Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 26\u003c\/p\u003e \u003cp\u003e2.5 Algorithm – Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 28\u003c\/p\u003e \u003cp\u003e2.6 Conclusion 34\u003c\/p\u003e \u003cp\u003eReferences 35\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Collaborative Filtering Skyline (CFS) for Enhanced Recommender Systems 37\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShobana G. and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction and Objective 38\u003c\/p\u003e \u003cp\u003e3.1.1 Objective 39\u003c\/p\u003e \u003cp\u003e3.2 Motivation 39\u003c\/p\u003e \u003cp\u003e3.3 Literature Survey 40\u003c\/p\u003e \u003cp\u003e3.4 System Analysis and Existing Systems 43\u003c\/p\u003e \u003cp\u003e3.4.1 Drawbacks 45\u003c\/p\u003e \u003cp\u003e3.5 Proposed System 46\u003c\/p\u003e \u003cp\u003e3.5.1 Feasibility Study 46\u003c\/p\u003e \u003cp\u003e3.5.2 Economic Feasibility 46\u003c\/p\u003e \u003cp\u003e3.5.3 Operational Feasibility 47\u003c\/p\u003e \u003cp\u003e3.5.4 Technical Feasibility 47\u003c\/p\u003e \u003cp\u003e3.5.5 Problem Definition and Project Overview 48\u003c\/p\u003e \u003cp\u003e3.5.6 Overview of the Project 48\u003c\/p\u003e \u003cp\u003e3.5.7 Exact Skyline Computation 51\u003c\/p\u003e \u003cp\u003e3.5.8 Approximate Skyline Computation 52\u003c\/p\u003e \u003cp\u003e3.5.9 Module Description 53\u003c\/p\u003e \u003cp\u003e3.5.9.1 Modules 53\u003c\/p\u003e \u003cp\u003e3.5.10 Data Flow Diagram 54\u003c\/p\u003e \u003cp\u003e3.5.10.1 External Entity (Source\/Sink) 57\u003c\/p\u003e \u003cp\u003e3.5.10.2 Process 57\u003c\/p\u003e \u003cp\u003e3.5.10.3 Data Flow 57\u003c\/p\u003e \u003cp\u003e3.5.10.4 Data Store 58\u003c\/p\u003e \u003cp\u003e3.5.11 Rules Used For Constructing a DFD 58\u003c\/p\u003e \u003cp\u003e3.5.12 Basic DFD Notation 59\u003c\/p\u003e \u003cp\u003e3.5.13 Profiles 59\u003c\/p\u003e \u003cp\u003e3.5.14 Uploaded My Videos 60\u003c\/p\u003e \u003cp\u003e3.5.15 Rating My Videos 60\u003c\/p\u003e \u003cp\u003e3.6 System Implementation 63\u003c\/p\u003e \u003cp\u003e3.6.1 Implementation Procedures 63\u003c\/p\u003e \u003cp\u003e3.6.1.1 User Training 64\u003c\/p\u003e \u003cp\u003e3.6.1.2 User Manual 64\u003c\/p\u003e \u003cp\u003e3.6.1.3 System Maintenance 64\u003c\/p\u003e \u003cp\u003e3.6.1.4 Corrective Maintenance 65\u003c\/p\u003e \u003cp\u003e3.6.1.5 Adaptive Maintenance 65\u003c\/p\u003e \u003cp\u003e3.6.1.6 Perceptive Maintenance 65\u003c\/p\u003e \u003cp\u003e3.6.1.7 Preventive Maintenance 65\u003c\/p\u003e \u003cp\u003e3.7 Conclusion and Future Enhancements 65\u003c\/p\u003e \u003cp\u003e3.7.1 Conclusion 65\u003c\/p\u003e \u003cp\u003e3.7.2 Enhancements 66\u003c\/p\u003e \u003cp\u003eReferences 66\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Automatic Retinopathic Diabetic Detection: Data Analyses, Approaches and Assessment Measures Using Deep Learning 69\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRinesh S., Mahdi Ismael Omar, Thamaraiselvi K., V. Karthick and Vigneshwar Manoharan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 70\u003c\/p\u003e \u003cp\u003e4.2 Related Work 72\u003c\/p\u003e \u003cp\u003e4.3 Initial Steps and Experimental Environment 74\u003c\/p\u003e \u003cp\u003e4.3.1 Analyzing the Principle Components 74\u003c\/p\u003e \u003cp\u003e4.3.2 Firefly Algorithm 75\u003c\/p\u003e \u003cp\u003e4.4 Experimental Environment 76\u003c\/p\u003e \u003cp\u003e4.5 Data and Knowledge Sources 77\u003c\/p\u003e \u003cp\u003e4.6 Data Preparation 78\u003c\/p\u003e \u003cp\u003e4.7 CNN’s Integrated Design 79\u003c\/p\u003e \u003cp\u003e4.8 Preparing Retinal Image Data 83\u003c\/p\u003e \u003cp\u003e4.9 Performance Evaluation 85\u003c\/p\u003e \u003cp\u003e4.10 Metrics 86\u003c\/p\u003e \u003cp\u003e4.11 Investigation of Tests 90\u003c\/p\u003e \u003cp\u003e4.12 Discussion 90\u003c\/p\u003e \u003cp\u003e4.13 Results and Discussion 92\u003c\/p\u003e \u003cp\u003e4.14 Conclusions 94\u003c\/p\u003e \u003cp\u003eReferences 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Design and Implementation of Smart Parking Management System Based on License Plate Detection 99\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePallavi S. Bangare, Sanjana Naik, Shashwati Behare, Akanksha Swami, Jayesh Gaikwad, Sunil L. Bangare, G. Pradeepini and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 100\u003c\/p\u003e \u003cp\u003e5.2 Literature Survey 101\u003c\/p\u003e \u003cp\u003e5.2.1 Cloud-Based Smart-Parking System Based on Internet-of-Things\/Technologies 101\u003c\/p\u003e \u003cp\u003e5.2.2 A Cloud-Based Intelligent Car Parking System 101\u003c\/p\u003e \u003cp\u003e5.2.3 Research and Implement of the Intelligent Parking Reservation Management System Based on ZigBee Technology 102\u003c\/p\u003e \u003cp\u003e5.2.4 Zigbee and GSM-Based Secure Vehicle Parking Management and Reservation System 102\u003c\/p\u003e \u003cp\u003e5.2.5 Car Park Management with Networked Wireless Sensors and Active RFID 102\u003c\/p\u003e \u003cp\u003e5.2.6 Automated Parking System with Bluetooth Access 103\u003c\/p\u003e \u003cp\u003e5.2.7 Smart Parking: A Secure and Intelligent Parking System 103\u003c\/p\u003e \u003cp\u003e5.3 Proposed System 103\u003c\/p\u003e \u003cp\u003e5.3.1 Methodology 104\u003c\/p\u003e \u003cp\u003e5.3.2 Vehicle Number Plate Recognition Technique 106\u003c\/p\u003e \u003cp\u003e5.4 High Level Design of Proposed System 107\u003c\/p\u003e \u003cp\u003e5.4.1 Data Flow Diagram 107\u003c\/p\u003e \u003cp\u003e5.4.2 UML Diagrams 108\u003c\/p\u003e \u003cp\u003e5.5 Project Requirement Specification 111\u003c\/p\u003e \u003cp\u003e5.5.1 Software Requirements 111\u003c\/p\u003e \u003cp\u003e5.5.2 Hardware Requirements 111\u003c\/p\u003e \u003cp\u003e5.6 Algorithms 111\u003c\/p\u003e \u003cp\u003e5.7 Proposed System Results 113\u003c\/p\u003e \u003cp\u003e5.8 Conclusion 118\u003c\/p\u003e \u003cp\u003eReferences 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 A Novel Algorithm for Stationary Analysis of the Characteristics of the Queue-Dependent Random Probability for Co-Processor-Shared Memory Using Computational Sciences 121\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNandhini Varadharajan, Vigneshwar Manoharan, Rajadurai and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction - Processor-Shared Service Queue with Independent Service Rate Using Probability Queuing Theory 122\u003c\/p\u003e \u003cp\u003e6.2 The Applications of Queuing Models in Processor-Shared Memory 123\u003c\/p\u003e \u003cp\u003e6.3 The Basic Structure of Queuing Models 123\u003c\/p\u003e \u003cp\u003e6.4 Characteristics of Queuing System 124\u003c\/p\u003e \u003cp\u003e6.5 The Arrival Pattern of Customers 124\u003c\/p\u003e \u003cp\u003e6.6 The Service Pattern of Servers Queue Discipline, System Capacity, and the Number of Servers 124\u003c\/p\u003e \u003cp\u003e6.7 Kendall’s Notation 125\u003c\/p\u003e \u003cp\u003e6.8 The Formation of Retrial Queues as a Solution 126\u003c\/p\u003e \u003cp\u003e6.9 The Stationary Analysis of the Characteristics of the M\/M\/2 Queue with Constant Repeated Attempts 126\u003c\/p\u003e \u003cp\u003e6.10 Computation of the Steady-State Probabilities 128\u003c\/p\u003e \u003cp\u003e6.11 Application of Retrial Queues 134\u003c\/p\u003e \u003cp\u003e6.12 Conclusion 134\u003c\/p\u003e \u003cp\u003eReferences 136\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Smart e-Learning System with IoT-Enabled for Personalized Assessment 137\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVeeramanickam M.R.M., Visalatchi S. and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 137\u003c\/p\u003e \u003cp\u003e7.2 Literature Study 139\u003c\/p\u003e \u003cp\u003e7.3 Architecture Model 140\u003c\/p\u003e \u003cp\u003e7.4 Assessment Technique: CBR Algorithm 143\u003c\/p\u003e \u003cp\u003e7.5 Implementation Modules: Project Outcome 144\u003c\/p\u003e \u003cp\u003e7.5.1 Creating a Web Application 144\u003c\/p\u003e \u003cp\u003e7.5.2 Integrating Raspberry Pi and Scribble Pad 146\u003c\/p\u003e \u003cp\u003e7.5.3 Deploying Web App over Internet\/FTP Server 148\u003c\/p\u003e \u003cp\u003e7.5.4 Assessment Technique – Online Exam 148\u003c\/p\u003e \u003cp\u003e7.6 Conclusion 150\u003c\/p\u003e \u003cp\u003eReferences 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Implementation of File Sharing System Using Li-Fi Based on Internet of Things (IoT) 153\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSunil L. Bangare, Shirin Siddiqui, Ayush Srivastava, Avinash Kumar, Pushkraj Bhagat, G. Pradeepini, S. T. Patil and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 154\u003c\/p\u003e \u003cp\u003e8.1.1 Motivation 154\u003c\/p\u003e \u003cp\u003e8.1.2 Problem Statement 155\u003c\/p\u003e \u003cp\u003e8.1.3 Background 155\u003c\/p\u003e \u003cp\u003e8.2 Existing System\/Related Work 156\u003c\/p\u003e \u003cp\u003e8.2.1 SHARE It 156\u003c\/p\u003e \u003cp\u003e8.2.2 Super Beam 156\u003c\/p\u003e \u003cp\u003e8.2.3 Xender 156\u003c\/p\u003e \u003cp\u003e8.3 Literature Survey 156\u003c\/p\u003e \u003cp\u003e8.4 Proposed System 163\u003c\/p\u003e \u003cp\u003e8.4.1 Input Data 163\u003c\/p\u003e \u003cp\u003e8.4.2 Conversion to Binary Encoded Information 163\u003c\/p\u003e \u003cp\u003e8.4.3 Led Driver 164\u003c\/p\u003e \u003cp\u003e8.4.4 Photo Diode Receiver 164\u003c\/p\u003e \u003cp\u003e8.5 Workflow 165\u003c\/p\u003e \u003cp\u003e8.6 Proposed Solution 171\u003c\/p\u003e \u003cp\u003e8.6.1 Hardware Setup 171\u003c\/p\u003e \u003cp\u003e8.6.2 Transistor-Transistor Logic Serial Communication 172\u003c\/p\u003e \u003cp\u003e8.6.3 Arduino Uno 172\u003c\/p\u003e \u003cp\u003e8.7 Software Implementation 173\u003c\/p\u003e \u003cp\u003e8.7.1 Video Transmission 173\u003c\/p\u003e \u003cp\u003e8.7.2 Text\/Text File Transmission 174\u003c\/p\u003e \u003cp\u003e8.7.3 Audio Transmission 175\u003c\/p\u003e \u003cp\u003e8.7.4 Image Transmission 175\u003c\/p\u003e \u003cp\u003e8.8 Block Diagram – Indoor Navigation System Using Li-Fi 176\u003c\/p\u003e \u003cp\u003e8.9 Implementation 177\u003c\/p\u003e \u003cp\u003e8.10 Unicode Transmission 178\u003c\/p\u003e \u003cp\u003e8.10.1 Receiver – Solar Panel 179\u003c\/p\u003e \u003cp\u003e8.10.2 Text to Speech 179\u003c\/p\u003e \u003cp\u003e8.11 Conclusion 180\u003c\/p\u003e \u003cp\u003eReferences 181\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Survey on Artificial Intelligence Techniques in the Diagnosis of Pleural Mesothelioma 185\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eUshasukhanya S., S.S. Sridhar and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 185\u003c\/p\u003e \u003cp\u003e9.2 Methods 188\u003c\/p\u003e \u003cp\u003e9.3 Analysis 192\u003c\/p\u003e \u003cp\u003e9.4 Conclusion 194\u003c\/p\u003e \u003cp\u003eReferences 194\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Handwritten Character Recognition and Genetic Algorithms 197\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMagesh Kasthuri and Vigneshwar Manoharan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 198\u003c\/p\u003e \u003cp\u003e10.2 Recognition Framework for a Handwritten Character Recognition 199\u003c\/p\u003e \u003cp\u003e10.3 Offline Character Recognition 200\u003c\/p\u003e \u003cp\u003e10.4 Literature Review 201\u003c\/p\u003e \u003cp\u003e10.5 Feature Extraction 206\u003c\/p\u003e \u003cp\u003e10.6 Pattern Recognition 207\u003c\/p\u003e \u003cp\u003e10.7 Noise Reduction 208\u003c\/p\u003e \u003cp\u003e10.8 Segmentation 209\u003c\/p\u003e \u003cp\u003e10.9 Pre-Processing 210\u003c\/p\u003e \u003cp\u003e10.10 Hybrid Recognition 211\u003c\/p\u003e \u003cp\u003e10.11 Applying Genetic Algorithm 211\u003c\/p\u003e \u003cp\u003e10.12 Multilingual Characters 214\u003c\/p\u003e \u003cp\u003e10.12.1 Multilingual Characters – Hindi 214\u003c\/p\u003e \u003cp\u003e10.12.2 Multilingual Characters – Tamil Language 215\u003c\/p\u003e \u003cp\u003e10.12.3 Multilingual Characters – Malayalam Language 215\u003c\/p\u003e \u003cp\u003e10.12.4 Multilingual Characters – Telugu Language 216\u003c\/p\u003e \u003cp\u003e10.12.5 Multilingual Characters – Kannada Language 217\u003c\/p\u003e \u003cp\u003e10.12.6 Multilingual Characters – Egypt Language 218\u003c\/p\u003e \u003cp\u003e10.12.7 Multilingual Characters – Polish Language 219\u003c\/p\u003e \u003cp\u003e10.13 Results 220\u003c\/p\u003e \u003cp\u003eReferences 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 An Intelligent Agent-Based Approach for COVID- 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003ePatient Distribution Management 225\u003cbr\u003e \u003ci\u003eClaudiu-Ionut Popirlan, Adriana Burlea Schiopoiu, Cristina Popirlan and Ahmed A. Elngar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 226\u003c\/p\u003e \u003cp\u003e11.2 Intelligent Agent’s Architecture Proposal for COVID- 19\u003c\/p\u003e \u003cp\u003ePatient Distribution Management 227\u003c\/p\u003e \u003cp\u003e11.2.1 A Clinical Scenario of COVID-19 Patient Distributed Management 231\u003c\/p\u003e \u003cp\u003e11.2.2 Communication Management 232\u003c\/p\u003e \u003cp\u003e11.3 Intelligent Agents Task Management 234\u003c\/p\u003e \u003cp\u003e11.3.1 Intelligent Agents Cooperation Management 236\u003c\/p\u003e \u003cp\u003e11.3.1.1 Establishing Commitments 236\u003c\/p\u003e \u003cp\u003e11.3.1.2 Adaptive Management of Commitment Changes 237\u003c\/p\u003e \u003cp\u003e11.4 Java Agent Development Framework 237\u003c\/p\u003e \u003cp\u003e11.4.1 Software Implementation 239\u003c\/p\u003e \u003cp\u003e11.4.2 Results Comparison 241\u003c\/p\u003e \u003cp\u003e11.5 Conclusions 242\u003c\/p\u003e \u003cp\u003eReferences 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Computational Science Role in Medical and Healthcare- Related Approach 245\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePawan Whig, Arun Velu, Rahul Reddy Nadikattu and Yusuf Jibrin Alkali\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 246\u003c\/p\u003e \u003cp\u003e12.2 Background 251\u003c\/p\u003e \u003cp\u003e12.3 Healthcare Nowadays 253\u003c\/p\u003e \u003cp\u003e12.4 Healthcare Activities and Processes 253\u003c\/p\u003e \u003cp\u003e12.5 Organization and Financial Aspects of Healthcare 254\u003c\/p\u003e \u003cp\u003e12.6 Health Information Technology is Currently Being Used 255\u003c\/p\u003e \u003cp\u003e12.7 Future Healthcare 256\u003c\/p\u003e \u003cp\u003e12.8 Research Challenges 257\u003c\/p\u003e \u003cp\u003e12.9 Modeling 259\u003c\/p\u003e \u003cp\u003e12.10 Automation 260\u003c\/p\u003e \u003cp\u003e12.11 Teamwork and Data Exchange 260\u003c\/p\u003e \u003cp\u003e12.12 Scaled Data Management 260\u003c\/p\u003e \u003cp\u003e12.13 Comprehensive Automated Recording of Exchanges Between Doctors and Patients 260\u003c\/p\u003e \u003cp\u003e12.14 Johns Hopkins University: A Case Study 261\u003c\/p\u003e \u003cp\u003e12.15 Case Study: Managing Patient Flow 263\u003c\/p\u003e \u003cp\u003e12.16 Case Study: Using Electronic Health Records and Human Factors Engineering 263\u003c\/p\u003e \u003cp\u003e12.17 Technology, Leadership, Culture, and Increased Learning are Necessary for the Spread of Systems Approaches 265\u003c\/p\u003e \u003cp\u003e12.18 Conclusion 267\u003c\/p\u003e \u003cp\u003eReferences 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Impact of e-Business Services on Product Management 273\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSanchit Sarhadi and Priyadarshini Adyasha Pattanaik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 274\u003c\/p\u003e \u003cp\u003e13.2 Literature Review 275\u003c\/p\u003e \u003cp\u003e13.3 Data Collection and Method Details 283\u003c\/p\u003e \u003cp\u003e13.4 Results 294\u003c\/p\u003e \u003cp\u003e13.5 Conclusion 295\u003c\/p\u003e \u003cp\u003eReferences 295\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Analysis of Lakeshore Images Obtained from Unmanned Aerial Vehicles 299\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eIvana Čermáková and Roman Danel\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 299\u003c\/p\u003e \u003cp\u003e14.2 Possibilities of Processing Images Acquired from Unmanned Aerial Vehicles 302\u003c\/p\u003e \u003cp\u003e14.3 Defining Purpose, Location and Users of the Study 302\u003c\/p\u003e \u003cp\u003e14.4 Suitable and Available Data and Vehicle 303\u003c\/p\u003e \u003cp\u003e14.5 Usable Image Processing Methods 304\u003c\/p\u003e \u003cp\u003e14.6 Invasive-Plant Detection 309\u003c\/p\u003e \u003cp\u003e14.7 Evaluation and Interpretation of the Results 311\u003c\/p\u003e \u003cp\u003e14.8 Analysis of Lakeshore – Koblov Lake 313\u003c\/p\u003e \u003cp\u003e14.9 Area of Interest 313\u003c\/p\u003e \u003cp\u003e14.10 Data Acquisition 314\u003c\/p\u003e \u003cp\u003e14.11 Data Pre-Processing 315\u003c\/p\u003e \u003cp\u003e14.12 Data Processing and Evaluation 316\u003c\/p\u003e \u003cp\u003e14.13 Evaluation and Interpretation of the Results 318\u003c\/p\u003e \u003cp\u003e14.14 Conclusion 321\u003c\/p\u003e \u003cp\u003eReferences 321\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Robotic Arm: Impact on Industrial and Domestic Applications 323\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNidhi Chahal, Ruchi Bisht, Arun Kumar Rana and Aryan Srivastava\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 324\u003c\/p\u003e \u003cp\u003e15.2 Circuit Diagram 326\u003c\/p\u003e \u003cp\u003e15.3 Literature Survey 327\u003c\/p\u003e \u003cp\u003e15.4 Operation of Robot 329\u003c\/p\u003e \u003cp\u003e15.5 The Benefits of Industrial Robotic Arms 330\u003c\/p\u003e \u003cp\u003e15.6 Component Details 330\u003c\/p\u003e \u003cp\u003e15.7 Working of Robotic Arm 332\u003c\/p\u003e \u003cp\u003e15.8 Intel Takes Robotic Arms to The Next Level 334\u003c\/p\u003e \u003cp\u003e15.9 Robotic Arm Applications 334\u003c\/p\u003e \u003cp\u003e15.10 Conclusion 335\u003c\/p\u003e \u003cp\u003eReferences 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Effects of Using VR on Computer Science Students’ Learning Behavior in Indonesia: An Experimental Study for TEFL 341\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMuthmainnah, Ahmad Al Yakin, Luís Cardoso, Ahmed A. Elngar, Ibrahim Oteir and Abdullah Nijr Al-Otaibi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 342\u003c\/p\u003e \u003cp\u003e16.2 VR as FUTELA 344\u003c\/p\u003e \u003cp\u003e16.3 Using the Internet to Study and Learning Behavior 346\u003c\/p\u003e \u003cp\u003e16.4 Methods 347\u003c\/p\u003e \u003cp\u003e16.5 Research Participants 348\u003c\/p\u003e \u003cp\u003e16.6 Techniques for Analyzing Data 349\u003c\/p\u003e \u003cp\u003e16.7 The Indicator of Efficiency 350\u003c\/p\u003e \u003cp\u003e16.8 Results and Discussion 350\u003c\/p\u003e \u003cp\u003e16.9 Discussion 357\u003c\/p\u003e \u003cp\u003e16.10 Conclusion 360\u003c\/p\u003e \u003cp\u003eReferences 361\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Satisfaction of Students Toward Media and Technology Innovation Amidst COVID- 19 365\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMuthmainnah, Ahmad Al Yakin, Saikat Gochhait, Andi Asrifan, Ahmed A. Elngar and Luís Cardoso\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 366\u003c\/p\u003e \u003cp\u003e17.2 Literature Review 370\u003c\/p\u003e \u003cp\u003e17.2.1 Accelerating Digital Transformation in the Education Sector 370\u003c\/p\u003e \u003cp\u003e17.2.2 Digital Media and Technology in English as a Foreign Language (EFL) 371\u003c\/p\u003e \u003cp\u003e17.3 Methods 378\u003c\/p\u003e \u003cp\u003e17.4 Results and Findings 379\u003c\/p\u003e \u003cp\u003e17.5 Discussion 383\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 386\u003c\/p\u003e \u003cp\u003eReferences 386\u003c\/p\u003e \u003cp\u003eIndex 391\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\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":52430915567896,"sku":"9781119760467","price":172.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781119760467.jpg?v=1784765405","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/handbook-of-computational-sciences-a-multi-and-interdisciplinary-approach-hardback-9781119760467","provider":"Freshly Printed Books","version":"1.0","type":"link"}