Advances in Information Systems Science: Volume 9

'1 Data Structures and Databases in Digital Scene Analysis.- 1. Introduction.- 2. Data Structures.- 2.1. Definitions and Basic Concepts.- 2.2. Use of Lists for Scene Representation and Processing.- 2.3. Use of Quad Trees for Image representation and Processing.- 3. Databases.- 3.1. Definitions and Basic Concepts.- 3.2. Hierarchical and Relational Models for Scene Representation and Processing.- 3.3. Use of Relational Tables for Three-Dimensional Object Location.- 4. Examples of Existing Systems.- 4.1. Multisensor Image Database System (MIDAS).- 4.2. Relational Pictorial Database System.- 5. Summary.- References.- 2 An Overview of Database Management Technology.- 1. Introduction.- 2. Motivations.- 2.1. Large Shared Files.- 2.2. Rapid Social Change.- 2.3. Man-Computer Cooperation.- 3. Database as a New Systems Methodology.- 3.1. Output-Oriented Approach.- 3.2. Database-Oriented Approach.- 4. Logical Database Structure.- 4.1. Relational View of the Real World.- 4.2. Geometric Representation of Relations.- 4.3. Semantic Constraints.- 4.4. Tuple Constraints.- 4.5. Dependencies.- 4.6. Interrelation Constraints.- 4.7. Other Static Constraints.- 4.8. Definition of Logical Database Structure.- 5. Database Operations.- 5.1. Functions of Tuples.- 5.2. Alpha Operation.- 5.3. Relational Algebra.- 5.5. Information Algebra.- 5.6. Imaginary Tuples.- 5.7. Navigations.- 5.8. Disadvantages of Set Operations.- 5.9. Tuple-by-Tuple Operations.- 5.10. Data Manipulation Requirements.- 6. Other Requirements.- 6.1. Integrity.- 6.2. Security.- 6.3. Concurrency.- 6.4. Recoverability.- 6.5. Database Distribution.- 6.6. Environmental Requirements.- 7. Physical Representation of the Database.- 7.1. Data Associations in Computer Storage.- 7.2. Basic File Organizations.- 7.3. Representation of Entity Relations.- 7.4. Representation of Relationship Relations.- 7.5. Localization.- 8. Database Management Functions.- 8.1. Data Description.- 8.2. Data Manipulation.- 8.3. Binding.- 8.4. Functions for Database Administrators.- 8.5. Database Management Languages.- 9. Database Management Systems.- 9.1. Selection Criteria for Database Management Systems.- 9.2. Directory-Type Classification of Database Management Systems.- 9.3. Database Operations.- 9.4. Environmental Requirements.- 9.5. Physical Representation.- 9.6. Host Language Interfaces.- 9.7. Other Criteria.- 10. End-User Languages.- 10.1. Application Routines.- 10.2. Language for Real-Time Users.- 10.3. Languages for Casual Users.- 10.4. Languages for Parameter Users.- 10.5. Self-Contained Systems.- 10.6. High-Level Languages on the Host Language Systems.- 10.7. Language Extensibility.- 11. Future Research Directions.- 11.1. Database Machines.- 11.2. Deductive Processes.- 11.3. Neutral-Language Query Processing.- References.- 3 Processing of Pattern-Based Information, Part I: Inductive Inference Methods Suitable for use in Pattern Recognition and Artificial Intelligence.- 1. Introduction.- 1.1. Preamble.- 1.2. The Decision Rule Inference Problem in Pattern Recognition.- 1.3. Inference in Artificial Intelligence.- 1.4. Basic Tenets of the Present Approach to Inductive Inference of Decision Rules.- 2. Representation of Patterns.- 3. Algorithm For Decision Rule Inference.- 3.1. The Nature of the Task.- 3.2. Some Concepts and Definitions Used in the Algorithms.- 3.3. Hypotheses Generation and Test.- 3.4. Problem Reduction in the "CD" Hypothesis Generation.- 3.5. Sentential Form of the Decision Rules.- 3.6. An Illustration of Suggested Algorithm.- 4. Structure of the Controls for Systematic Implementation of the Inference Procedure.- 5. A Brief description of the Implementation.- 6. Examples.- References.- 4 Processing of Pattern-Based Information, Part II: Description of Inductive Inference in Terms of Transition Networks.- 1. Introduction.- 2. Description of the Inductive Inference Transition Network.- 3. An Inference