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Developments in Natural Intelligence Research and Knowledge Engineering

Book Description

Thought, comprehension, and intelligence are everyday concepts that are so pervasive through the lives of every human being that people scarcely think about them at all. These processes are so complex under the surface, however, that a fully developed scientific discipline is necessary to explore these topics.Developments in Natural Intelligence Research and Knowledge Engineering: Advancing Applications covers the intricate worlds of thought, comprehension, intelligence, and knowledge through the scientific field of Cognitive Science. This groundbreaking reference contains research from global experts, covering topics that have been pivotal at major conferences covering Cognitive Science topics.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. ASSOCIATE EDITORS
    2. INTERNATIONAL EDITORIAL REVIEW BOARD
  5. Preface
    1. SECTION 1. COGNITIVE INFORMATICS
    2. SECTION 2. COGNITIVE COMPUTING
    3. SECTION 3. DENOTATIONAL MATHEMATICS
    4. SECTION 4. COMPUTATIONAL INTELLIGENCE
    5. SECTION 5. APPLICATIONS OF COGNITIVE INFORMATICS AND COGNITIVE COMPUTING
  6. Acknowledgment
  7. Section 1: Cognitive Informatics
    1. Chapter 1: Perspectives on Cognitive Informatics and Cognitive Computing
      1. ABSTRACT
      2. INTRODUCTION
      3. COGNITIVE INFORMATICS AND GLOBAL CONSCIOUSNESS
      4. COGNITIVE INFORMATICS AND COGNITIVE DYNAMICAL SYSTEMS
      5. COGNITIVE COMPUTING AND COMPUTER VISION
      6. COGNITIVE COMPUTING AND MACHINE CONSCIOUSNESS
      7. COGNITIVE INFORMATICS AND WEB INTELLIGENCE
      8. COGNITIVE COMPUTING AND GRAPH INFORMATION PROCESSING
      9. COGNITIVE INFORMATICS AND COMPUTATIONAL LINGUISTICS
      10. COGNITIVE INFORMATICS AND PATTERN THEORY
      11. COGNITIVE INFORMATICS AND KNOWLEDGE REPRESENTATION
      12. COGNITIVE INFORMATICS AND SYMBIOTIC COMPUTING
      13. COGNITIVE INFORMATICS AND GRANULAR MODELING
      14. COGNITIVE COMPUTING AND GRANULAR COMPUTING
      15. COGNITIVE INFORMATICS AND MACHINE LEARNING
      16. COGNITIVE INFORMATICS AND COGNITIVE PENETRABILITY
      17. COGNITIVE INFORMATICS AND ROLE-BASED SOCIAL COMPUTING
      18. CONCLUSION
    2. Chapter 2: The Cognitive Process of Comprehension
      1. ABSTRACT
      2. INTRODUCTION
      3. THE CONCEPTUAL MODEL OF COMPREHENSION
      4. FORMAL DESCRIPTION OF THE COMPREHENSION PROCESS
      5. CONCLUSION
    3. Chapter 3: A Hybrid Genetic Algorithm based Fuzzy Approach for Abnormal Retinal Image Classification
      1. ABSTRACT
      2. INTRODUCTION
      3. MATERIALS AND METHODS
      4. IMAGE PRE-PROCESSING
      5. FEATURE EXTRACTION
      6. FEATURE SELECTION
      7. CLASSIFIER
      8. COMPARATIVE ANALYSIS OF GA BASED FUZZY CLASSIFIER AND CONVENTIONAL FUZZY CLASSIFIER
      9. RESULTS AND DISCUSSIONS
      10. CONCLUSION AND FUTURE WORK
    4. Chapter 4: Logical Connections of Statements at the Ontological Level
      1. ABSTRACT
      2. INTRODUCTION
      3. ONTOLOGIES
      4. LOGICAL CONNECTIONS OF STATEMENTS IN ONTOLOGIES
      5. THE NEGATIONS ONTOLOGIES
      6. CONCLUSION
  8. Section 2: Cognitive Computing
    1. Chapter 5: The Event Search Engine
      1. ABSTRACT
      2. INTRODUCTION
      3. EVENT REPRESENTATION
      4. EVENT SEARCH SYSTEM
      5. EVALUATION
      6. RELATED WORK
      7. CONCLUSION
    2. Chapter 6: Incremental Knowledge Construction for Real-World Event Understanding
      1. ABSTRACT
      2. INTRODUCTION
      3. EVENT DETECTION IN SENSOR NETWORKED ENVIRONMENT
      4. EVENT ONTOLOGY FOR INTERPRETING REAL-WORLD EVENTS
      5. CONSTRUCTION OF REAL-WORLD KNOWLEDGE THROUGH LABELING PRACTICE
      6. LABELING PRACTICE AND EVALUATION
      7. CONCLUSION
    3. Chapter 7: Autonomic Computing for a Complex Problem of Experimental Physics
      1. ABSTRACT
      2. INTRODUCTION
      3. ARTIFICIAL NEURAL NETWORK APPROACH
      4. STANDARD MINIMIZATION APPROACH
      5. NATURAL NEURAL NETWORK APPROACH
      6. DISCUSSION ON THE NNN RESULTS
      7. SUMMARY
    4. Chapter 8: On Hierarchical Content-Based Image Retrieval by Dynamic Indexing and Guided Search
      1. ABSTRACT
      2. INTRODUCTION
      3. IMAGE DATA WAREHOUSE
      4. WAVELET-BASED MULTIPLE IMAGE FEATURE EXTRACTION
      5. DYNAMIC IMAGE FEATURE SELECTION AND INDEXING
      6. HIERARCHICAL SEARCH
      7. CASE STUDIES AND EXPERIMENTAL RESULTS
      8. CONCLUSION
    5. Chapter 9: Robust Feature Vector Set Using Higher Order Autocorrelation Coefficients
      1. ABSTRACT
      2. INTRODUCTION
      3. PROPERTIES OF SHORT-TIME AUTOCORRELATION FUNCTION
      4. FEATURE VECTOR USING HIGHER ORDER AUTOCORRELATION COEFFICIENTS
      5. PROPOSED METHOD
      6. CONCLUSION
  9. Section 3: Denotational Mathematics
    1. Chapter 10: A Web Knowledge Discovery Engine Based on Concept Algebra
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCEPT ALGEBA: A DENOTATIOANL MATHEMATICAL PREPARATION
      4. QUERY FORMULATIONS AND REFINEMENTS
      5. INFORMATION RESTRUCTURING FOR WEB DOCUMENTS
      6. DESIGN OF THE KNOWLEDGE DISCOVERY AND INFORMATION RESTRUCTURING ENGINE
      7. CONCLUSION
    2. Chapter 11: Approximations in Rough Sets vs Granular Computing for Coverings
      1. ABSTRACT
      2. INTRODUCTION
      3. ROUGH SETS BASED ON BINARY RELATIONS
      4. COVERING LOWER APPROXIMATION OPERATIONS
      5. FIRST TYPE OF UPPER APPROXIMATIONS
      6. SECOND TYPE OF UPPER APPROXIMATIONS
      7. THIRD TYPE OF UPPER APPROXIMATIONS
      8. FORTH TYPE OF UPPER APPROXIMATIONS
      9. FIFTH TYPE OF UPPER APPROXIMATIONS
      10. CONCLUSIONS
    3. Chapter 12: Further Considerations of Classification-Oriented and Approximation-Oriented Rough Sets in Generalized Settings
      1. ABSTRACT
      2. INTRODUCTION
      3. THE CLASSICAL ROUGH SETS
      4. CLASSIFICATION-ORIENTED GENERALIZATION
      5. APPROXIMATION-ORIENTED GENERALIZATION
      6. RELATIONSHIPS AMONG CP-, CN-, AU- AND AI-ROUGH SETS
      7. TYPES OF DECISION RULES
      8. A NUMERICAL EXAMPLE
      9. CONCLUDING REMARKS
    4. Chapter 13: Generalized Rough Logics with Rough Algebraic Semantics
      1. ABSTRACT
      2. INTRODUCTION
      3. SEQUENT CALCULUS FOR ROUGH STONE ALGEBRA
  10. Section 4: Computational Intelligence
    1. Chapter 14: Feature Reduction with Inconsistency
      1. ABSTRACT
      2. 1. RELATED DEFFINITIONS AND CONCEPTS
      3. 2. REDUCTION ALGORITHMS BASED ON THE INCONSISTENCY
      4. 3. “MINI-SATURATION” BIAS FOR REDUCTION SELECTION
      5. 4. CONCLUSION
    2. Chapter 15: Learning Hierarchical Lexical Hyponymy
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. TERMINOLOGY
      4. 3. LEARNING FRAMEWORK
      5. 4. COMMON SUFFIX TREE CLUSTERING
      6. 5. SUFFIX ANALYSIS
      7. 6. CLASS CONCEPT VERIFICATION
      8. 7. PREFIX CLUSTERING
      9. 8. ACQUIRING HIERARCHICAL LEXICAL HYPONYMY
      10. 9. EXPERIMENTAL RESULT
      11. 10. CONCLUSION
    3. Chapter 16: A New Quantum Evolutionary Algorithm with Sifting Strategy for Binary Decision Diagram Ordering Problem
      1. ABSTRACT
      2. INTRODUCTION
      3. BINARY DECISION DIAGRAM
      4. QUANTUM COMPUTING
      5. THE PROPOSED APPROACH
      6. IMPLEMENTATION AND EVALUATION
      7. CONCLUSION
    4. Chapter 17: A Robust Facial Feature Tracking Method Based on Optical Flow and Prior Measurement
      1. ABSTRACT
      2. INTRODUCTION
      3. OPTICAL FLOW-BASED FACIAL FEATURE TRACKING
      4. KLT OPTICAL FLOW
      5. PRIOR MEASUREMENT
      6. ERROR ACCUMULATION
      7. OPTICAL FLOW-BASED ROBUST FACIAL FEATURE TRACKING ALGORITHM
      8. DISCUSSION
      9. CONCLUSION
  11. Section 5: Applications of Cognitive Informatics and Cognitive Computing
    1. Chapter 18: Modeling a Secure Sensor Network Using an Extended Elementary Object System
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. FORMAL MODEL FOR SENSOR NETWORKS
      4. 3. SECURITY MECHANISMS
      5. 4. SIMULATION AND ANALYSIS
      6. 5. CONCLUSION AND FUTURE WORK
    2. Chapter 19: Amplification of Signal Features Using Variance Fractal Dimension Trajectory
      1. ABSTRACT
      2. INTRODUCTION
      3. VARIANCE FRACTAL DIMENSION TRAJECTORY ALGORITHM
      4. THE TIME INCREMENT SELECTION IN VFD ALGORITHM
      5. REDUCING ERROR IN Dσ DUE TO SIGNAL CORRELATION
      6. EXPERIMENTS AND RESULTS
      7. DISCUSSION
    3. Chapter 20: Some Remarks on the Concept of Approximations from the View of Knowledge Engineering
      1. ABSTRACT
      2. INTRODUCTION
      3. RS-APPROXIMATIONS IN (INFINITE) UNIVERSE
      4. COUNTER INTUITIVE PHENOMENA
      5. KNOWLEDGE THEORY ON GrC
      6. CONCLUSIONS
      7. APPENDIX- COUNTER INTUITIVE APPROXIMATIONS IN CLASSICAL RS
    4. Chapter 21: Giving Personal Assistant Agents a Case-Based Memory
      1. ABSTRACT
      2. INTRODUCTION
      3. CONTEXT
      4. THE MEMORY FORMALISM
      5. IMPLEMENTATION
      6. TESTS
      7. DISCUSSION
      8. CONCLUSION AND FUTURE WORK
    5. Chapter 22: An Evaluation Method of Relative Reducts Based on Roughness of Partitions
      1. ABSTRACT
      2. INTRODUCTION
      3. ROUGH SET
      4. EVALUATION OF RELATIVE REDUCTS USING PARTITIONS
      5. EXAMPLE
      6. CONCLUSION
  12. Compilation of References
  13. About the Contributors