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Advances in Abstract Intelligence and Soft Computing

Book Description

Continuous developments in software and intelligence sciences have brought together the studies of both natural and machine intelligence and the relationship between the function of the brain and the abstract soft mind; creating a new multidisciplinary field of study.Advances in Abstract Intelligence and Soft Computing brings together the latest research in computer science: theoretical software engineering, cognitive science and informatics, and also their influence on the processes of natural and machine intelligence. This book is a collection of widespread research in the constant expansions on this emerging discipline. 

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Associate Editors
    2. List of Reviewers
  5. Preface
  6. Acknowledgment
  7. Section 1: Computational Intelligence
    1. Chapter 1: A Formal Knowledge Representation System (FKRS) for the Intelligent Knowledge Base of a Cognitive Learning Engine
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE CONCEPTUAL MODEL OF THE FKRS SYSTEM
      4. 3. THE ARCHITECTURAL MODEL OF THE FKRS SYSTEM
      5. 4. THE BEHAVIORAL MODELS OF THE FKRS SYSTEM
      6. 5. THE IMPLEMENTATION OF THE FKRS SYSTEM
      7. 6. CONCLUSION
    2. Chapter 2: Sparse Based Image Classification With Bag-of-Visual-Words Representations
      1. ABSTRACT
      2. INTRODUCTION
      3. IMAGE FEATURE EXTRACTION
      4. IMAGE CLASSIFICATION BASED ON SPARSE REPRESENTATION
      5. EXPERIMENTS
      6. CONCLUSION
    3. Chapter 3: Quotient Space-Based Boundary Condition for Particle Swarm Optimization Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. THEORY ANALYSIS FOR PSO
      4. STABILITY ANALYSIS
      5. QUOTIENT SPACE-BASED BOUNDARY CONDITION FOR PSO
      6. EXPERIMENTAL PROCEDURE
      7. CONCLUSION
    4. Chapter 4: Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. FEATURE EXTRACTION USING WAVELET TRANSFORM
      4. 3. FEATURE SELECTION ALGORITHMS
      5. 4. SUPPORT VECTOR MACHINE FOR CLASSIFICATION
      6. 5. PERFORMANCE EVALUATION
      7. 6. CONCLUSION
    5. Chapter 5: EEG Feature Extraction and Pattern Classification Based on Motor Imagery in Brain-Computer Interface
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. METHOD
      4. 2. RESULTS
      5. 3. DISCUSSION
      6. 4. CONCLUSION
    6. Chapter 6: Inconsistency-Induced Learning for Perpetual Learners
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. RELATED WORK
      4. 3. PROPOSED FRAMEWORK
      5. 4. INCONSISTENCY CATEGORIES AND MORPHOLOGIES
      6. 5. INCONSISTENCY INDUCED LEARNING
      7. 6. CONCLUSION
    7. Chapter 7: Toward Automatic Answers in User-Interactive Question Answering Systems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. RELATED WORK
      4. 3. THE METHOD
      5. 4. EXPERIMENTS AND EVALUATION
      6. 5. CONCLUSION AND FUTURE WORK
  8. Section 2: Cognitive Computing
    1. Chapter 8: On Cognitive Models of Causal Inferences and Causation Networks
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE TAXONOMY AND NETWORKS OF CAUSATIONS
      4. 3. THE FRAMEWORK AND PROPERTIES OF CAUSAL INFERENCES
      5. 4. UNCERTAIN CAUSAL INFERENCES
      6. 5. FALSE CAUSALITY: A RATIONAL EXPLANATION OF HUMOR AND JOKES
      7. 6. CONCLUSION
    2. Chapter 9: On Localities of Knowledge Inconsistency
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. KNOWLEDGE INCONSISTENCY TYPES
      4. 3. A FIXPOINT CHARACTERIZATION
      5. 4. LOCALITY OF KNOWLEDGE INCONSISTENCY
      6. 5. ALGORITHMS TO CAPTURE LOI
      7. CONCLUSION
    3. Chapter 10: Adaptive Study Design Through Semantic Association Rule Analysis
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. ASSOCIATION MODELING WITH A SEMANTIC NETWORK
      5. 4. SPREADING ACTIVATION METHODS
      6. 5. SEMANTIC ASSOCIATION RULE ANALYSIS
      7. 6. HYPOTHESIS GENERATION
      8. 7. DATA QUALITY ASSESSMENT
      9. 3. A CASE STUDY
      10. 4. RELATED WORK
      11. 5. CONCLUSION
    4. Chapter 11: Qualitative Reasoning Approach to a Driver's Cognitive Mental Load
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. DRIVING MODEL AND FEATURES OF EYE MOVEMENT
      4. 3. QUALITATIVE MODEL OF THE DRIVER COGNITIVE MENTAL LOAD
      5. 4. VERIFICATION OF OUR QUALITATIVE MODEL
      6. 5. CONCLUSION
    5. Chapter 12: Intelligent Fault Recognition and Diagnosis for Rotating Machines using Neural Networks
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE OVERALL STRUCTURE OF THE MELVIN I SYSTEM
      4. 3. THE NEURAL NETWORK FOR FAULT RECOGNITION IN MELVIN I
      5. 5. CONCLUSION
  9. Section 3: Software Science
    1. Chapter 13: Empirical Studies on the Functional Complexity of Software in Large-Scale Software Systems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THEORETICAL FOUNDATIONS OF SOFTWARE FUNCTIONAL COMPLEXITY
      4. 4. FUNDAMENTAL FINDINGS ON SOFTWARE FUNCTIONAL COMPLEXITY
      5. 5. CONCLUSION
    2. Chapter 14: The Formal Design Model of a File Management System (FMS)
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE CONCEPTUAL MODELS OF FILES AND FMS
      4. 3. THE ARCHITECTURAL MODELS OF THE FILE ADT AND FMS
      5. 4. THE BEHAVIORAL PROCESS MODELS OF THE FILE ADT
      6. 5. THE BEHAVIORAL PROCESS MODELS OF FMS
      7. 6. THE DYNAMIC BEHAVIORAL MODELS OF THE FILE ADT AND FMS
      8. CONCLUSION
    3. Chapter 15: The Formal Design Model of Doubly-Linked-Circular Lists (DLC-Lists)
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE CONCEPTUAL MODEL OF DLC-LISTS
      4. 3. THE ARCHITECTURAL MODELS OF DLC-LISTS
      5. 4. THE BEHAVIORAL PROCESS MODELS OF DLC-LISTS
      6. 5. THE DYNAMIC BEHAVIORAL MODEL OF DLC-LISTS
      7. 6. CONCLUSION
    4. Chapter 16: Petri Nets and Discrete Events Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. PETRI NETS MODELING DISCRETE-EVENTS PROCESSES
      4. PETRI NETS AS DISCRETE DYNAMICAL SYSTEMS
      5. DEFINITION OF THE DDS
      6. A METRIC FOR THE DDS ASSOCIATED TO A 1-SAFE PETRI NET
      7. METRICS FOR NON-BOUNDED PETRI NETS
      8. CONCLUSIONS AND FURTHER RESEARCH DIRECTIONS
    5. Chapter 17: The Formal Design Models of a Universal Array (UA) and its Implementation
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE CONCEPTUAL AND MATHEMATICAL MODELS OF UA
      4. 3. THE ARCHITECTURAL MODEL OF UA
      5. 4. THE STATIC BEHAVIORAL MODEL OF UA
      6. 5. THE DYNAMIC BEHAVIORAL MODEL OF THE UA
      7. 6. IMPLEMENTATION OF THE UA MODELS IN JAVA
      8. 6. CONCLUSION
    6. Chapter 18: The Formal Design Models of Tree Architectures and Behaviors
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE CONCEPTUAL MODEL OF B-TREES
      4. 3. THE ARCHITECTURAL MODELS OF B-TREES
      5. 4. THE BEHAVIORAL PROCESS MODELS OF B-TREES
      6. 5. THE DYNAMIC BEHAVIOR MODELS OF B-TREES
      7. 6. CONCLUSION
  10. Section 4: Applications of Computational Intelligence and Cognitive Computing
    1. Chapter 19: Four-Channel Control Architectures for Bilateral and Multilateral Teleoperation
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. PASSIVE FOUR-CHANNEL ARCHITECTURE
      4. 3. DUAL-MASTER MULTILATERAL SHARED CONTROL ARCHITECTURE
      5. 4. DUAL-SLAVE MULTILATERAL SHARED CONTROL ARCHITECTURE
      6. 5. SIMULATIONS
      7. 6. CONCLUSION
    2. Chapter 20: Entropy Quad-Trees for High Complexity Regions Detection
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. PARTITIONS, ENTROPY, AND TREES
      4. 2. AN ALGORITHM FOR DETECTION OF HIGH COMPLEXITY REGIONS
      5. 3. AN ALGORITHM FOR CRATER DETECTION USING ENTROPY QUAD-TREES
      6. 4. CONCLUSION
    3. Chapter 21: Sitting Posture Recognition and Location Estimation for Human-Aware Environment
      1. ABSTRACT
      2. INTRODUCTION
      3. HUMAN-AWARE ENVIRONMENT AND TWO PROPOSED PERCEPTUAL FUNCTIONS
      4. EXPERIMENT II
      5. CONCLUSION
    4. Chapter 22: Generic Cabling of Intelligent Buildings Based on Ant Colony Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. GENERIC CABLING SYSTEM
      4. SYSTEM ANALYSIS
      5. MATHEMATICAL MODELING
      6. CONCLUSION
    5. Chapter 23: Potentials of Quadratic Neural Unit for Applications
      1. ABSTRACT
      2. INTRODUCTION
      3. STRUCTURE AND LEARNING OF QNU
      4. APPLICATIONS AND ASPECTS OF QNUS
      5. DISCUSSION
      6. PAPER SUMMARY
    6. Chapter 24: A Value-Based Framework for Software Evolutionary Testing
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. MACHINE LEARNING APPLICATION TO VALUE-NEUTRAL SOFTWARE TEST DATA GENERATION
      4. 3. SOME DEFINITIONS
      5. 4. A VALUE-BASED FRAMEWORK
      6. 5. AN ILLUSTRATIVE EXAMPLE
      7. 6. CONCLUSION
    7. Chapter 25: Comparison of Promoter Sequences Based on Inter Motif Distance
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. METHODOLOGY
      4. 2A. MOTIF IDENTIFICATION
      5. 2B. DISTANCE MEASURE
      6. 3. RESULTS
      7. 4. DISCUSSION AND CONCLUSION
  11. Compilation of References
  12. About the Contributors