This volume, the eighth of a continuing series on information systems science, presents five timely topics which are of current interest in this growing field. In each chapter, an attempt is made to familiarize the reader with some basic background information on the advances discussed, so that this volume may be used independently or in conjunction with the previous volumes. The emphasis in this volume is centered upon file or ganization and performance evaluation, computational semantics, digital control, clustering analysis, and geometric modeling. Chapter I presents a comprehensive survey of file organization. In this chapter, Gudes and Ganesh discuss performance evaluation, imple mentation considerations, relationship to database models, and performance tradeoffs of various file organizations. The semantics of programming languages was discussed in Volume 2 of this series. This topic is revisited by Culik II and Farah from a different point of view. Chapter 2 is concerned with linked forest manipulation and models for formal description of a programming language. Linked trees reveal syntactical properties of a programming language and provide data structures for describing com putational semantics.
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1 A Survey of File Organizations and Performance.- 1. Introduction.- 1.1. Basic Concepts.- 1.2. General Performance Measures.- 1.3. Current Literature.- 2. Primary Key File Organizations.- 2.1. Introduction.- 2.2. Sequential Organization.- 2.3. Direct Organization.- 2.4. Indexed Sequential Organization.- 2.5. Index Tree Structures.- 2.5.1. B-trees.- 2.5.2. VSAM.- 2.6. Comparative Evaluation and Simulation.- 2.7. Summary.- 3. Secondary Key File Organizations.- 3.1. Introduction.- 3.2. Organizations.- 3.2.1. Inverted File.- 3.2.2. Multilist.- 3.2.3. Generalized File Structure.- 3.2.4. Cellular Serial Organization.- 3.2.5. Canonical File Structure.- 3.2.6. Combined Indices.- 3.2.7. Multiple Key Hashing Model.- 3.2.8. Superimposed Coding.- 3.2.9. Combinatorial Filing System.- 3.2.10. Consecutive Retrieval Organization.- 3.3. Evaluation.- 3.4. Index Selection.- 3.5. Summary.- 4. Complex File and Data Base Structures.- 4.1. Combinations of File Structures.- 4.2. Database Models and Their Corresponding File Structures.- 4.3. The Effect of New Hardware Technologies.- 5. Summary.- References and Bibliography.- 2 Linked Forest Manipulation Systems—A Tool for Computational Semantics.- 1. Introduction.- 2. Tree and Linked Forest Manipulation Systems.- 2.1. Subtree Replacement Systems.- 2.2. Linked Forest Manipulation Systems.- 3. Describing a Programming Language Formally.- 3.1. The Syntax Part.- 3.2. The Semantics Part.- 4. Formalism for Linked Forest Manipulation Systems.- 4.1. Trees and Forests.- 4.2. Trees and Forests with a Pivotal Node.- 4.3. Operations on Trees and Forests.- 4.3.1. Concatenation and Superposition of Trees.- 4.3.2. Skeletal Operator on Trees.- 4.3.3. Subtree Replacement.- 4.3.4. Substructure Replacement.- 4.3.5. Replacement of Substructures in Forests.- 4.4. Linked Forests; Label, Pointer and Tree Parameters.- 4.4.1. Linked Forests.- 4.4.2. Label, Pointer and Tree Parameters.- 4.4.3. Substitution of Parameters.- 4.4.4. Functional Denotations.- 4.5. Linked Forest Manipulation Systems.- 4.5.1. Informal Description of the System.- 4.5.2. Production Schemas.- 4.5.3. Transformation on Linked Forests.- 5. Model for Formal Description of Programming Languages.- 6. Examples.- 6.1. An ALG Program.- 6.2. Syntax and Semantics of ?-expression.- References.- 3 Software Development for Digital Control.- 1. Introduction.- 1.1. Background.- 1.2. Approach.- 2. Hardware.- 2.1. Computers.- 2.1.1. Single-Component Microcomputers.- 2.1.2. Single-Board Computers.- 2.1.3. High-Performance Microcomputers.- 2.1.4. Development Systems.- 2.2. Interface Equipment.- 2.2.1. Communication.- 2.2.2. Analog I/O.- 2.2.3. Discrete Signals and Power Switching.- 2.2.4. Direct Digital Transducers and Actuators.- 2.2.5. Future Trends.- 3. Development of Digital Algorithms.- 3.1. Background.- 3.2. A First-Order System Example.- 3.3. Digital PID.- 3.3.1. The Ideal PID.- 3.3.2. Interactive PID.- 3.3.3. Some PID Variants.- 4. Implementation Considerations.- 4.1. Computational Requirements.- 4.2. Sampling Requirements.- 4.3. Numerical Methods.- 4.3.1. Integration.- 4.3.2. Differentiation.- 4.4. Additional Comments.- 4.4.1. Special Features.- 4.4.2. Other Digital Algorithms.- 5. Software.- 5.1. Overview.- 5.2. Errors and Debugging.- 5.3. Programming Languages.- 5.4. Software Practices.- 5.4.1. Program Development.- 5.4.2. Documentation.- 6. Conclusions.- References.- 4 Clustering Analysis and Its Applications.- 1. Introduction.- 2. Distance Functions.- 2.1. Data Described by Vectors.- 2.2. Distance Functions for Data in Vector Form.- 2.3. Data Described by Picture Description Language.- 2.4. Distance Functions for Data Described by Picture Description Language.- 2.5. The Distance Matrix and the Similarity Matrix.- 3. Clustering Analysis—Graph Theoretical Approach.- 3.1. T-clusters.- 3.2. Minimal Spanning Trees.- 3.3. The Construction of Minimal Spanning Trees.- 3.4. Producing T-clusters from a Minimal Spanning Tree.- 3.5. Minimal Spanning Trees and Hierarchical Clusters.- 3.6. Clustering Analysis through Short Spanning Paths.- 3.7. Cliques—Another Graph-Theoretical Approach.- 4. Visual Clustering Analysis.- 4.1. Introduction.- 4.2. Matrix Reorganization through Short Spanning Paths.- 4.3. Linear Mapping.- 4.4. Nonlinear Mapping I (Trying to Preserve All Distances).- 4.5. Nonlinear Mapping I for a Large Number of Samples.- 4.6. Nonlinear Mapping II (The Triangulation Method: Preserving a Subset of Distances Exactly).- 4.7. Minimal Spanning Trees and the Ordering of Points Being Mapped.- 4.8. Visual Clustering Analysis and Marketing Research.- 5. A Review of Clustering Analysis Techniques Discussed.- 6. Clustering Analysis and Storage Reduction.- 6.1. Introduction.- 6.2. The Selection of the Reference Point.- 6.3. Analysis of the Storage Requirement.- 6.4. Storage Reduction by Spanning Forests.- 7. Clustering Analysis and Nearest Neighbor Searching.- 7.1. Introduction.- 7.2. Using Clustering Analysis to Avoid Exhaustive Searching.- 7.3. Efficient Data Storage and Retrieval for Nearest Neighbor Searching.- 7.4. Hierarchical Clustering and Global Searching.- 7.5. Clustering Analysis by Hashing for Nearest Neighbor Searching.- 7.6. Clustering Analysis for Merging.- 7.7. A Fast Algorithm to Construct Minimal Spanning Trees.- 7.8. Divide and Conquer.- 7.9. Clustering, Nearest Neighbor Searching, and Inductive Question Answering.- 8. Clustering Analysis and Partial Match Searching.- 8.1. Introduction.- 8.2. Multikey Sorting—Clustering Records through the Short Spanning Path Approach.- 8.3. Hashing for Partial Match Queries—Cartesian Product Files.- 8.4. Clustering Analysis and the Data Integrity Problem.- 8.5. Clustering Analysis and Physical Database Design—A Summary.- 9. Clustering Analysis and the Program Restructuring Problem.- 9.1. Introduction.- 9.2. The Assignment Technique.- 9.3. The Symmetrical Assignment Technique.- 10. Concluding Remarks and Directions for Future Research.- References.- 5 An Introduction to Geometric Modeling and Its Applications in Mechanical Design and Production.- 1. Introduction.- 2. Models and Representations for Rigid Solid Objects.- 2.1. Mathematical Models for Rigid Solids.- 2.2. Representation Schemes.- 2.3. Complete Representation Schemes for Rigid Solids.- 3. Properties of Solid Objects.- 3.1. Properties, Functions, and Algorithms.- 3.2. A Case Study: Calculation of Integral Properties.- 4. Object-Modifying Processes.- 4.1. Machining-Process Models and NC Verification.- 4.2. Refinement of the Machining-Process Model.- 4.3. Computational Issues.- 4.4. Remarks.- 5. Conclusions.- References.
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