Handbook of Computational Sciences

Ahmed A. Elngar, PhD, is the founder and head of Scientific Innovation Research Group (SIRG) and assistant professor of Computer Science at the Faculty of Computers and Information, Beni-Suef University, Egypt. Vigneshwar. M., is head of R & D and Academic Initiatives, Cybase Technologies, Coimbatore, Tamil Nadu, India. He has around 9 years in industry & research and 8 years in academia. He has an M.E., degree in computer science and engineering, and has published more than 110 international/national conference and journal publications as well as numerous awards. Krishna Kant Singh, PhD, is an associate professor in the Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of machine learning and remote sensing. He has authored more than 50 technical books and research papers in international conferences and SCIE journals. Zdzislaw Polkowski, PhD, is a professor in the Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland. He has published more than 75 research articles in peer-reviewed journals.

• Preface xv1 A Sensor-Based Automated Irrigation System for Indian Agricultural Fields 1I.S. Akila and Ahmed A. Elngar1.1 Introduction 11.2 Literary Survey 21.3 Proposed System 41.3.1 System Architecture 41.3.2 Flow of Automated Irrigation 51.3.3 Interfacing Sensors 51.3.4 Physical Characteristics Determination Using Image Processing 81.3.4.1 Fractal Dimension Estimation 81.3.4.2 Box-Counting Method 91.3.4.3 Physical Parameters 91.4 Performance Studies 111.4.1 Experimental Environment 111.4.2 Accessing Shared Variables from NI Data Dashboard 121.4.2.1 Scenario 1 141.4.2.2 Scenario 2 141.4.2.3 Scenario 3 141.4.2.4 Scenario 4 141.5 Image Processing to Determine Physical Characteristics 151.6 Conclusion and Future Enhancements 201.6.1 Conclusion 201.6.2 Future Scope 20References 202 An Enhanced Integrated Image Mining Approach to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 23Sridevy S., Anna Saro Vijendran and Ahmed A. Elngar2.1 Introduction 242.2 Related Work 242.3 Motivation 262.4 Framework of Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 262.5 Algorithm – Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 282.6 Conclusion 34References 353 Collaborative Filtering Skyline (CFS) for Enhanced Recommender Systems 37Shobana G. and Ahmed A. Elngar3.1 Introduction and Objective 383.1.1 Objective 393.2 Motivation 393.3 Literature Survey 403.4 System Analysis and Existing Systems 433.4.1 Drawbacks 453.5 Proposed System 463.5.1 Feasibility Study 463.5.2 Economic Feasibility 463.5.3 Operational Feasibility 473.5.4 Technical Feasibility 473.5.5 Problem Definition and Project Overview 483.5.6 Overview of the Project 483.5.7 Exact Skyline Computation 513.5.8 Approximate Skyline Computation 523.5.9 Module Description 533.5.9.1 Modules 533.5.10 Data Flow Diagram 543.5.10.1 External Entity (Source/Sink) 573.5.10.2 Process 573.5.10.3 Data Flow 573.5.10.4 Data Store 583.5.11 Rules Used For Constructing a DFD 583.5.12 Basic DFD Notation 593.5.13 Profiles 593.5.14 Uploaded My Videos 603.5.15 Rating My Videos 603.6 System Implementation 633.6.1 Implementation Procedures 633.6.1.1 User Training 643.6.1.2 User Manual 643.6.1.3 System Maintenance 643.6.1.4 Corrective Maintenance 653.6.1.5 Adaptive Maintenance 653.6.1.6 Perceptive Maintenance 653.6.1.7 Preventive Maintenance 653.7 Conclusion and Future Enhancements 653.7.1 Conclusion 653.7.2 Enhancements 66References 664 Automatic Retinopathic Diabetic Detection: Data Analyses, Approaches and Assessment Measures Using Deep Learning 69Rinesh S., Mahdi Ismael Omar, Thamaraiselvi K., V. Karthick and Vigneshwar Manoharan4.1 Introduction 704.2 Related Work 724.3 Initial Steps and Experimental Environment 744.3.1 Analyzing the Principle Components 744.3.2 Firefly Algorithm 754.4 Experimental Environment 764.5 Data and Knowledge Sources 774.6 Data Preparation 784.7 CNN’s Integrated Design 794.8 Preparing Retinal Image Data 834.9 Performance Evaluation 854.10 Metrics 864.11 Investigation of Tests 904.12 Discussion 904.13 Results and Discussion 924.14 Conclusions 94References 955 Design and Implementation of Smart Parking Management System Based on License Plate Detection 99Pallavi S. Bangare, Sanjana Naik, Shashwati Behare, Akanksha Swami, Jayesh Gaikwad, Sunil L. Bangare, G. Pradeepini and Ahmed A. Elngar5.1 Introduction 1005.2 Literature Survey 1015.2.1 Cloud-Based Smart-Parking System Based on Internet-of-Things/Technologies 1015.2.2 A Cloud-Based Intelligent Car Parking System 1015.2.3 Research and Implement of the Intelligent Parking Reservation Management System Based on ZigBee Technology 1025.2.4 Zigbee and GSM-Based Secure Vehicle Parking Management and Reservation System 1025.2.5 Car Park Management with Networked Wireless Sensors and Active RFID 1025.2.6 Automated Parking System with Bluetooth Access 1035.2.7 Smart Parking: A Secure and Intelligent Parking System 1035.3 Proposed System 1035.3.1 Methodology 1045.3.2 Vehicle Number Plate Recognition Technique 1065.4 High Level Design of Proposed System 1075.4.1 Data Flow Diagram 1075.4.2 UML Diagrams 1085.5 Project Requirement Specification 1115.5.1 Software Requirements 1115.5.2 Hardware Requirements 1115.6 Algorithms 1115.7 Proposed System Results 1135.8 Conclusion 118References 1186 A Novel Algorithm for Stationary Analysis of the Characteristics of the Queue-Dependent Random Probability for Co-Processor-Shared Memory Using Computational Sciences 121Nandhini Varadharajan, Vigneshwar Manoharan, Rajadurai and Ahmed A. Elngar6.1 Introduction - Processor-Shared Service Queue with Independent Service Rate Using Probability Queuing Theory 1226.2 The Applications of Queuing Models in Processor-Shared Memory 1236.3 The Basic Structure of Queuing Models 1236.4 Characteristics of Queuing System 1246.5 The Arrival Pattern of Customers 1246.6 The Service Pattern of Servers Queue Discipline, System Capacity, and the Number of Servers 1246.7 Kendall’s Notation 1256.8 The Formation of Retrial Queues as a Solution 1266.9 The Stationary Analysis of the Characteristics of the M/M/2 Queue with Constant Repeated Attempts 1266.10 Computation of the Steady-State Probabilities 1286.11 Application of Retrial Queues 1346.12 Conclusion 134References 1367 Smart e-Learning System with IoT-Enabled for Personalized Assessment 137Veeramanickam M.R.M., Visalatchi S. and Ahmed A. Elngar7.1 Introduction 1377.2 Literature Study 1397.3 Architecture Model 1407.4 Assessment Technique: CBR Algorithm 1437.5 Implementation Modules: Project Outcome 1447.5.1 Creating a Web Application 1447.5.2 Integrating Raspberry Pi and Scribble Pad 1467.5.3 Deploying Web App over Internet/FTP Server 1487.5.4 Assessment Technique – Online Exam 1487.6 Conclusion 150References 1508 Implementation of File Sharing System Using Li-Fi Based on Internet of Things (IoT) 153Sunil L. Bangare, Shirin Siddiqui, Ayush Srivastava, Avinash Kumar, Pushkraj Bhagat, G. Pradeepini, S. T. Patil and Ahmed A. Elngar8.1 Introduction 1548.1.1 Motivation 1548.1.2 Problem Statement 1558.1.3 Background 1558.2 Existing System/Related Work 1568.2.1 SHARE It 1568.2.2 Super Beam 1568.2.3 Xender 1568.3 Literature Survey 1568.4 Proposed System 1638.4.1 Input Data 1638.4.2 Conversion to Binary Encoded Information 1638.4.3 Led Driver 1648.4.4 Photo Diode Receiver 1648.5 Workflow 1658.6 Proposed Solution 1718.6.1 Hardware Setup 1718.6.2 Transistor-Transistor Logic Serial Communication 1728.6.3 Arduino Uno 1728.7 Software Implementation 1738.7.1 Video Transmission 1738.7.2 Text/Text File Transmission 1748.7.3 Audio Transmission 1758.7.4 Image Transmission 1758.8 Block Diagram – Indoor Navigation System Using Li-Fi 1768.9 Implementation 1778.10 Unicode Transmission 1788.10.1 Receiver – Solar Panel 1798.10.2 Text to Speech 1798.11 Conclusion 180References 1819 Survey on Artificial Intelligence Techniques in the Diagnosis of Pleural Mesothelioma 185Ushasukhanya S., S.S. Sridhar and Ahmed A. Elngar9.1 Introduction 1859.2 Methods 1889.3 Analysis 1929.4 Conclusion 194References 19410 Handwritten Character Recognition and Genetic Algorithms 197Magesh Kasthuri and Vigneshwar Manoharan10.1 Introduction 19810.2 Recognition Framework for a Handwritten Character Recognition 19910.3 Offline Character Recognition 20010.4 Literature Review 20110.5 Feature Extraction 20610.6 Pattern Recognition 20710.7 Noise Reduction 20810.8 Segmentation 20910.9 Pre-Processing 21010.10 Hybrid Recognition 21110.11 Applying Genetic Algorithm 21110.12 Multilingual Characters 21410.12.1 Multilingual Characters – Hindi 21410.12.2 Multilingual Characters – Tamil Language 21510.12.3 Multilingual Characters – Malayalam Language 21510.12.4 Multilingual Characters – Telugu Language 21610.12.5 Multilingual Characters – Kannada Language 21710.12.6 Multilingual Characters – Egypt Language 21810.12.7 Multilingual Characters – Polish Language 21910.13 Results 220References 22111 An Intelligent Agent-Based Approach for COVID- 19Patient Distribution Management 225Claudiu-Ionut Popirlan, Adriana Burlea Schiopoiu, Cristina Popirlan and Ahmed A. Elngar11.1 Introduction 22611.2 Intelligent Agent’s Architecture Proposal for COVID- 19Patient Distribution Management 22711.2.1 A Clinical Scenario of COVID-19 Patient Distributed Management 23111.2.2 Communication Management 23211.3 Intelligent Agents Task Management 23411.3.1 Intelligent Agents Cooperation Management 23611.3.1.1 Establishing Commitments 23611.3.1.2 Adaptive Management of Commitment Changes 23711.4 Java Agent Development Framework 23711.4.1 Software Implementation 23911.4.2 Results Comparison 24111.5 Conclusions 242References 24312 Computational Science Role in Medical and Healthcare- Related Approach 245Pawan Whig, Arun Velu, Rahul Reddy Nadikattu and Yusuf Jibrin Alkali12.1 Introduction 24612.2 Background 25112.3 Healthcare Nowadays 25312.4 Healthcare Activities and Processes 25312.5 Organization and Financial Aspects of Healthcare 25412.6 Health Information Technology is Currently Being Used 25512.7 Future Healthcare 25612.8 Research Challenges 25712.9 Modeling 25912.10 Automation 26012.11 Teamwork and Data Exchange 26012.12 Scaled Data Management 26012.13 Comprehensive Automated Recording of Exchanges Between Doctors and Patients 26012.14 Johns Hopkins University: A Case Study 26112.15 Case Study: Managing Patient Flow 26312.16 Case Study: Using Electronic Health Records and Human Factors Engineering 26312.17 Technology, Leadership, Culture, and Increased Learning are Necessary for the Spread of Systems Approaches 26512.18 Conclusion 267References 26713 Impact of e-Business Services on Product Management 273Sanchit Sarhadi and Priyadarshini Adyasha Pattanaik13.1 Introduction 27413.2 Literature Review 27513.3 Data Collection and Method Details 28313.4 Results 29413.5 Conclusion 295References 29514 Analysis of Lakeshore Images Obtained from Unmanned Aerial Vehicles 299Ivana Čermáková and Roman Danel14.1 Introduction 29914.2 Possibilities of Processing Images Acquired from Unmanned Aerial Vehicles 30214.3 Defining Purpose, Location and Users of the Study 30214.4 Suitable and Available Data and Vehicle 30314.5 Usable Image Processing Methods 30414.6 Invasive-Plant Detection 30914.7 Evaluation and Interpretation of the Results 31114.8 Analysis of Lakeshore – Koblov Lake 31314.9 Area of Interest 31314.10 Data Acquisition 31414.11 Data Pre-Processing 31514.12 Data Processing and Evaluation 31614.13 Evaluation and Interpretation of the Results 31814.14 Conclusion 321References 32115 Robotic Arm: Impact on Industrial and Domestic Applications 323Nidhi Chahal, Ruchi Bisht, Arun Kumar Rana and Aryan Srivastava15.1 Introduction 32415.2 Circuit Diagram 32615.3 Literature Survey 32715.4 Operation of Robot 32915.5 The Benefits of Industrial Robotic Arms 33015.6 Component Details 33015.7 Working of Robotic Arm 33215.8 Intel Takes Robotic Arms to The Next Level 33415.9 Robotic Arm Applications 33415.10 Conclusion 335References 33616 Effects of Using VR on Computer Science Students’ Learning Behavior in Indonesia: An Experimental Study for TEFL 341Muthmainnah, Ahmad Al Yakin, Luís Cardoso, Ahmed A. Elngar, Ibrahim Oteir and Abdullah Nijr Al-Otaibi16.1 Introduction 34216.2 VR as FUTELA 34416.3 Using the Internet to Study and Learning Behavior 34616.4 Methods 34716.5 Research Participants 34816.6 Techniques for Analyzing Data 34916.7 The Indicator of Efficiency 35016.8 Results and Discussion 35016.9 Discussion 35716.10 Conclusion 360References 36117 Satisfaction of Students Toward Media and Technology Innovation Amidst COVID- 19 365Muthmainnah, Ahmad Al Yakin, Saikat Gochhait, Andi Asrifan, Ahmed A. Elngar and Luís Cardoso17.1 Introduction 36617.2 Literature Review 37017.2.1 Accelerating Digital Transformation in the Education Sector 37017.2.2 Digital Media and Technology in English as a Foreign Language (EFL) 37117.3 Methods 37817.4 Results and Findings 37917.5 Discussion 38317.6 Conclusion 386References 386Index 391