Advances in Information Systems Science: Volume 9

by Julius T. Tou

Overview

Volume 9 of this series on information systems science presents four timely topics 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 on data structures for scene analysis, database management technology, inductive inference in processing pattern-based information, and logic design of MOS networks. Scene analysis has become a very important aspect in information system design. The process of scene analysis involves sensing, segmentation, recognition, and interpretation. Innovative development of algorithms for these tasks requires the utilization of structural relationship prevalent within the sensed data. In Chapter 1, Thomason and Gonzalez discuss the formula­ tion of data representation techniques and the properties of data structures and databases in scene analysis. In view of the growing importance of database management, Chapter 2 is devoted to an overview of database management technology. In this chapter Kobayashi covers a variety of current topics. The topics discussed include system design methodology, data structure theory, semantic con­ siderations, calculus-based database operations, database management functions, and the issues of integrity, security, concurrency, and recoverabil­ ity. This chapter also discusses the end-user languages and several existing database management systems.

Product Details

ISBN-13:	9781461294498
Publisher:	Springer US
Publication date:	09/27/2011
Edition description:	Softcover reprint of the original 1st ed. 1985
Pages:	340
Product dimensions:	5.98(w) x 9.02(h) x 0.03(d)

Table of Contents

1 Data Structures and Databases in Digital Scene Analysis.- 1. Introduction.- 2. Data Structures.- 3. Databases.- 4. Examples of Existing Systems.- 5. Summary.- 2 An Overview of Database Management Technology.- 1. Introduction.- 2. Motivations.- 3. Database as a New Systems Methodology.- 4. Logical Database Structure.- 5. Database Operations.- 6. Other Requirements.- 7. Physical Representation of the Database.- 8. Database Management Functions.- 9. Database Management Systems.- 10. End-User Languages.- 11. Future Research Directions.- 3 Processing of Pattern-Based Information, Part I: Inductive Inference Methods Suitable for use in Pattern Recognition and Artificial Intelligence.- 1. Introduction.- 2. Representation of Patterns.- 3. Algorithm For Decision Rule Inference.- 4. Structure of the Controls for Systematic Implementation of the Inference Procedure.- 5. A Brief description of the Implementation.- 6. Examples.- 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 Algorithm Represented by an Inductive Inference Transition Network.- 4. Implementation and Illustrative examples.- 5 Automated Logic Design of MOS Networks.- 1. Introduction.- 2. Basic Properties.- 3. Algorithms for Designing Networks with a Minimum Number of Negative Gates.- 4. Synthesis of MOS Cells.- 5. Design of Irredundant MOS Networks.- 6. Interactive design.- 7. Conclusion.