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Handbook of Research on Applied Cybernetics and Systems Science

Book Description

In the digital era, novel applications and techniques in the realm of computer science are increasing constantly. These innovations have led to new techniques and developments in the field of cybernetics. The Handbook of Research on Applied Cybernetics and Systems Science is an authoritative reference publication for the latest scholarly information on complex concepts of more adaptive and self-regulating systems. Featuring exhaustive coverage on a variety of topics such as infectious disease modeling, clinical imaging, and computational modeling, this publication is an ideal source for researchers and students in the field of computer science seeking emerging trends in computer science and computational mathematics.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Dedication
  6. Preface
  7. Section 1: Signal Processing and Communications
    1. Chapter 1: A Survey of Parallel Community Detection Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. EXISTING COMMUNITY DETECTION TAXONOMIES
      4. A NOVEL TAXONOMY OF PARALLEL COMMUNITY DETECTION
      5. PARALLEL COMMUNITY DETECTION ALGORITHMS
      6. MISCELLANEOUS
      7. OPEN PROBLEMS
      8. CONCLUSION
      9. ACKNOWLEDGMENT
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
    2. Chapter 2: Towards Automation of IoT Analytics
      1. ABSTRACT
      2. INTRODUCTION
      3. A MODEL DRIVEN APPROACH IN IoT APPLICATION DEVELOPMENT
      4. USE OF KNOWLEDGE MODELS: AN IoT SCENARIO
      5. CREATION OF SENSOR KNOWLEDGE MODEL
      6. CREATION OF ALGORITHM KNOWLEDGE MODEL
      7. WORKFLOW CREATION USING KNOWLEDGE MODELS
      8. FUTURE WORKS AND CONCLUSION
      9. REFERENCES
    3. Chapter 3: Image Processing for Surveillance and Security
      1. ABSTRACT
      2. INTRODUCTION
      3. IMAGE PROCESSING FOR VISUAL TRACKING
      4. Biometrics authentication
      5. Multimedia Security
      6. CONCLUSION
      7. REFERENCES
    4. Chapter 4: Application of Corona Product of Graphs in Computing Topological Indices of Some Special Chemical Graphs
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN RESULTS
      5. Applications
      6. CONCLUSION
      7. REFERENCES
  8. Section 2: Systems and Computational Biology
    1. Chapter 5: Statistical Analysis of Functional Magnetic Resonance Imaging Data
      1. ABSTRACT
      2. INTRODUCTION
      3. DATA COLLECTION
      4. STATISTICAL ISSUES
      5. OVERVIEW OF APPROACHES TO STATISTICAL ANALYSIS
      6. DISCUSSION
      7. REFERENCES
    2. Chapter 6: Modeling Associations
      1. ABSTRACT
      2. INTRODUCTION
      3. SIGNALING MODELS
      4. SIGNAL DECOMPOSITION AND BAR CODES
      5. SIGNAL GRAMMARS
      6. SIGNAL DECOMPOSITION FROM HOMOLOGY
      7. LAMINAR PROCESSING AND PERSISTENT HOMOLOGY
      8. LAMINAR PROCESSING AS A DECOMPOSITION ALGORITHM IMPLEMENTATION
      9. COMPUTATION IN NEURAL SYSTEMS
      10. CONCLUSION
      11. REFERENCES
  9. Section 3: Machine Learning and Data Sciences
    1. Chapter 7: Graph-Based Semi-Supervised Learning With Big Data
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. STATISTICAL MACHINE LEARNING PROBLEM SETUP
      4. 3. AN OVERVIEW OF SEMI-SUPERVISED LEARNING
      5. 4. ANCHOR GRAPHS IN SEMI-SUPERVISED LEARNING
      6. 5. EMPIRICAL DEMONSTRATIONS
      7. 6. DISCUSSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
    2. Chapter 8: Machine Learning Methods as a Test Bed for EEG Analysis in BCI Paradigms
      1. ABSTRACT
      2. INTRODUCTION
      3. METHODS
      4. EXPERIMENT RESULTS
      5. DISCUSSION
      6. REFERENCES
    3. Chapter 9: Machine Learning Approaches for Supernovae Classification
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. CATEGORIZATION OF SUPERNOVA
      5. MACHINE LEARNING TECHNIQUES
      6. SUPERNOVAE DATA SOURCE AND CLASSIFICATION
      7. RESULTS AND ANALYSIS
      8. FUTURE RESEARCH DIRECTIONS
      9. CONCLUSION
      10. REFERENCES
    4. Chapter 10: Supervised Learning in Absence of Accurate Class Labels
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. METHODOLOGY
      5. 4. EMPIRICAL VALIDATION
      6. CONCLUSION AND DIRECTIONS FOR FUTURE WORK
      7. REFERENCES
    5. Chapter 11: Patient Data De-Identification
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND SIGNIFICANCE
      4. LITERATURE SURVEY
      5. METHODS
      6. DATASET AND EXPERIMENTS
      7. CONCLUSION
      8. FUTURE WORK
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    6. Chapter 12: Support Vector Machines and Applications
      1. ABSTRACT
      2. INTRODUCTION TO PATTERN RECOGNITION
      3. WHY SUPPORT VECTOR MACHINES
      4. HARD MARGIN SVM
      5. KERNEL METHODS
      6. CONCLUSION
      7. KEY TERMS AND DEFINITIONS
  10. Section 4: Statistical Models and Designs in Computing
    1. Chapter 13: Design and Analysis of Computer Experiments
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 EXPERIMENTAL DESIGNS FOR COMPUTER EXPERIMENTS
      4. 3 MODELING OF COMPUTER EXPERIMENTS
      5. 4 CONCLUSION
      6. ACKNOWLEDGMENT
      7. REFERENCES
    2. Chapter 14: Effective Statistical Methods for Big Data Analytics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. STATISTICAL FORMULATION OF BID DATA PROBLEM
      4. 3. LEVERAGE-BASED SAMPLING METHOD
      5. 4. NOVEL LEVERAGING-BASED SAMPLING METHOD
      6. 5. SOFTWARE IMPLEMENTATION
      7. 6. DEMONSTRATION: TWO CASE STUDIES
      8. 7. SUMMARY
      9. ACKNOWLEDGMENT
      10. REFERENCES
  11. Section 5: Scientometrics and Cybernetics
    1. Chapter 15: Measuring Complexity of Chaotic Systems With Cybernetics Applications
      1. ABSTRACT
      2. INTRODUCTION
      3. COMPLEX SYSTEMS
      4. INFORMATION AND COMPLEXITY
      5. MEASURING COMPLEXITY OF CHAOTIC SYSTEMS
      6. PRACTICAL APPLICATIONS IN CYBERNETICS
      7. SUMMARY AND FUTURE RESEARCH DIRECTIONS
      8. ACKNOWLEDGMENT
      9. REFERENCES
    2. Chapter 16: Cyber-Physical Systems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. CYBER-PHYSICAL SYSTEMS: A BRIEF OVERVIEW
      4. 3. APPLICATIONS OF CYBER-PHYSICAL SYSTEMS
      5. 4. THE DESIGN PROCESS
      6. 5. SECURITY OF CYBER-PHYSICAL SYSTEMS
      7. 6. SUMMARY
      8. REFERENCES
    3. Chapter 17: Scientometrics
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. “INFLUENCE” AS A METRIC: JOURNAL LEVEL
      5. CASE STUDY
      6. INTERNATIONALITY: AT JOURNAL LEVEL
      7. COBB DOUGLAS MODEL
      8. SCHOLASTIC MEASURES
      9. INTERNATIONAL COLLABORATION
      10. OTHER CITATIONS QUOTIENT: MEASURING DIVERSITY OF AN AUTHOR
      11. CONCLUSION
      12. REFERENCES
    4. Chapter 18: Design of Assistive Speller Machine Based on Brain Computer Interfacing
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BCI DESIGN PRINCIPLES
      4. 3. METHODOLOGY
      5. 4. FUTURE RESEARCH DIRECTIONS
      6. 5. CONCLUSION
      7. REFERENCES
  12. Compilation of References
  13. About the Contributors