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Produktbild: Handbook of Computational Sciences

Handbook of Computational Sciences A Multi and Interdisciplinary Approach

269,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

15.08.2023

Herausgeber

Ahmed A. Elngar + weitere

Verlag

John Wiley & Sons

Seitenzahl

416

Maße (L/B/H)

22,9/15,2/2,6 cm

Gewicht

710 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-76046-7

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

15.08.2023

Herausgeber

Verlag

John Wiley & Sons

Seitenzahl

416

Maße (L/B/H)

22,9/15,2/2,6 cm

Gewicht

710 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-76046-7

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Handbook of Computational Sciences
  • Preface xv
     
    1 A Sensor-Based Automated Irrigation System for Indian Agricultural Fields 1
    I.S. Akila and Ahmed A. Elngar
     
    1.1 Introduction 1
     
    1.2 Literary Survey 2
     
    1.3 Proposed System 4
     
    1.3.1 System Architecture 4
     
    1.3.2 Flow of Automated Irrigation 5
     
    1.3.3 Interfacing Sensors 5
     
    1.3.4 Physical Characteristics Determination Using Image Processing 8
     
    1.3.4.1 Fractal Dimension Estimation 8
     
    1.3.4.2 Box-Counting Method 9
     
    1.3.4.3 Physical Parameters 9
     
    1.4 Performance Studies 11
     
    1.4.1 Experimental Environment 11
     
    1.4.2 Accessing Shared Variables from NI Data Dashboard 12
     
    1.4.2.1 Scenario 1 14
     
    1.4.2.2 Scenario 2 14
     
    1.4.2.3 Scenario 3 14
     
    1.4.2.4 Scenario 4 14
     
    1.5 Image Processing to Determine Physical Characteristics 15
     
    1.6 Conclusion and Future Enhancements 20
     
    1.6.1 Conclusion 20
     
    1.6.2 Future Scope 20
     
    References 20
     
    2 An Enhanced Integrated Image Mining Approach to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 23
    Sridevy S., Anna Saro Vijendran and Ahmed A. Elngar
     
    2.1 Introduction 24
     
    2.2 Related Work 24
     
    2.3 Motivation 26
     
    2.4 Framework of Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 26
     
    2.5 Algorithm - Enhanced Integrated Image Mining Approaches to Address Macro Nutritional Deficiency Problems Limiting Maize Yield 28
     
    2.6 Conclusion 34
     
    References 35
     
    3 Collaborative Filtering Skyline (CFS) for Enhanced Recommender Systems 37
    Shobana G. and Ahmed A. Elngar
     
    3.1 Introduction and Objective 38
     
    3.1.1 Objective 39
     
    3.2 Motivation 39
     
    3.3 Literature Survey 40
     
    3.4 System Analysis and Existing Systems 43
     
    3.4.1 Drawbacks 45
     
    3.5 Proposed System 46
     
    3.5.1 Feasibility Study 46
     
    3.5.2 Economic Feasibility 46
     
    3.5.3 Operational Feasibility 47
     
    3.5.4 Technical Feasibility 47
     
    3.5.5 Problem Definition and Project Overview 48
     
    3.5.6 Overview of the Project 48
     
    3.5.7 Exact Skyline Computation 51
     
    3.5.8 Approximate Skyline Computation 52
     
    3.5.9 Module Description 53
     
    3.5.9.1 Modules 53
     
    3.5.10 Data Flow Diagram 54
     
    3.5.10.1 External Entity (Source/Sink) 57
     
    3.5.10.2 Process 57
     
    3.5.10.3 Data Flow 57
     
    3.5.10.4 Data Store 58
     
    3.5.11 Rules Used For Constructing a DFD 58
     
    3.5.12 Basic DFD Notation 59
     
    3.5.13 Profiles 59
     
    3.5.14 Uploaded My Videos 60
     
    3.5.15 Rating My Videos 60
     
    3.6 System Implementation 63
     
    3.6.1 Implementation Procedures 63
     
    3.6.1.1 User Training 64
     
    3.6.1.2 User Manual 64
     
    3.6.1.3 System Maintenance 64
     
    3.6.1.4 Corrective Maintenance 65
     
    3.6.1.5 Adaptive Maintenance 65
     
    3.6.1.6 Perceptive Maintenance 65
     
    3.6.1.7 Preventive Maintenance 65
     
    3.7 Conclusion and Future Enhancements 65
     
    3.7.1 Conclusion 65
     
    3.7.2 Enhancements 66
     
    References 66
     
    4 Automatic Retinopathic Diabetic Detection: Data Analyses, Approaches and Assessment Measures Using Deep Learning 69
    Rinesh S., Mahdi Ismael Omar, Thamaraiselvi K., V. Karthick and Vigneshwar Manoharan
     
    4.1 Introduction 70
     
    4.2 Related Work 72
     
    4.3 Initial Steps and Experimental Environment 74
     
    4.3.1 Analyzing the Principle Components 74
     
    4.3.2 Firefly Algorithm