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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military engineering

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POWER-SYSTEM VOLTAGE CONTROL BY DISTRIBUTED EXPERT systems

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1990年第3期37卷 236-240页

作者： MATSUDA, S OGI, H NISHIMURA, K OKATAKU, Y TAMURA, S Artificial Intelligence Technology Department Computer and Communication Research Center Tokyo Electric Power Company Limited Japan Systems and Software Engineering Laboratory Toshiba Corporation Japan

A case study of the application of a distributed control scheme to a power system control is presented. In addition, an investigation has been conducted into voltage control. Combined injection of VAr-compensating devices controlled by distributed expert systems has been proposed as a measure to maintain voltage stability in a power system under heavy loading conditions. A simulation study has been carried out by using five workstations that represent a power system and four VAr-compensating devices. The results demonstrate the effectiveness of the proposed system for voltage recovery.< >

关键词： Power system control Power systems Voltage control Expert systems Power system stability Power system simulation Distributed control Power system measurements Control systems Power measurement

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Applying Petri net reduction to support Ada-tasking deadlock detection

Applying Petri net reduction to support Ada-tasking deadlock...

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International Conference on Distributed Computing systems

作者： S. Tu S.M. Shatz T. Murata Software Systems Laboratory Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

The application of Petri net reduction to Ada-tasking deadlock detection is investigated. Net reduction can ease reachability analysis by reducing the size of the net while preserving relevant properties. By combining Petri net theory and knowledge of Ada-tasking semantics some specific efficient reduction rules are derived for Petri net models of Ada-tasking. A method by which a useful description of a detected deadlock state can be easily obtained from the reduced net's information is suggested.< >

关键词： System recovery Algorithm design and analysis Petri nets Information analysis software systems Laboratories Reachability analysis Face detection FETs Displays

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EMBEDDING LEARNING IN A GENERAL FRAME-BASED ARCHITECTURE

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International Journal of Pattern Recognition and Artificial Intelligence 1990年第2期4卷 125-145页

作者： TOSHIKAZU TANAKA TOM M. MITCHELL Systems and Software Engineering Laboratory Toshiba Corporation 70 Yanagicho Saiwaiku Kawasaki Kanagawa 210 Japan School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 USA

This research seeks to .incorporate machine learning capabilities within a general-purpose frame-based architecture. We describe CHUNKER, an explanation-based chunking mechanism built on top of THEO, a software framework to support development of self-modifying problem solving systems. CHUNKER forms rules that improve problem solving efficiency, by generalizing and compressing the chains of inference which THEO produces during problem solving. After presenting the learning algorithm used by CHUNKER, we illustrate its application to learning search control knowledge, discuss its relationship to THEO’s other three learning mechanisms, and consider the relationship between architectural features of THEO and the effectiveness of CHUNKER.

关键词： Embedding learning Chunking mechanism Self-modifying problem solving systems Explanation-based learning

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ASSURE: automated design for dependability

ASSURE: automated design for dependability

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Design Automation Conference

作者： P. Edmond A.P. Gupta D.P. Siewiorek A.A. Brennan Silicon and Software Systems Dublin Ireland Electrical and Computer Engineering Department Carnegie Mellon University Pittsburgh PA USA Unisys Corporation Plymouth MI USA

Describes ASSURE, an automated design-for-dependability advisor, which is a part of the MICON system for rapid prototyping of small computer systems. A design-for-dependability methodology and a formal interface between synthesis and dependability analysis are presented. ASSURE's operation includes dependability analysis, evaluation of dependability enhancement techniques using predictive estimation, and selection of a technique. Different kinds of knowledge used in designing for dependability are identified, including an algorithmic approach for dependability analysis and a knowledge-based approach for suggesting dependability enhancement techniques. Examples of designs produced using ASSURE as a dependability advisor are provided and show an order of magnitude dependability improvement.< >

关键词： Redundancy Contracts Design engineering Application software Voting computer errors Prototypes Microwave integrated circuits Buildings Reliability

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THE COMMAND SUPPORT AT-SEA EXPERIMENT

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NAVAL ENGINEERS JOURNAL 1990年第3期102卷 25-36页

作者： BUSCHER, DJ SUNDAY, DM David J. Buscher:is an electrical engineer on the Principal Professional Staff of the Fleet Systems Department of The Johns Hopkins University Applied Physics Laboratory. He earned his BS degree in electrical engineering from Villanova University in 1967 an MSEE degree from the University of Maryland in 1972 and an MS degree in technical management from The Johns Hopkins University in 1985. He was the lead engineer on the Command Support At-Sea Experiment Project. He started his career in 1967 with the U.S. Army Harry Diamond Laboratory working on computer and communications projects. During this time he worked in Vietnam with the United States Army Vietnam Science Advisor Office. Since joining JHU/APL in 1978 he has worked on a variety of projects associated with computer graphics hospital patient information systems computer networks autonomous underwater vehicles and satellite communications. He is currently assistant group supervisor of the Computer Systems Group. Daniel M. Sunday:is a mathematician on the Principal Professional Staff of the Fleet Systems Department of The Johns Hopkins University Applied Physics Laboratory. He earned his Ph.D. in mathematics from the University of Minnesota in 1971 and did postdoctoral research on neural networks at the University of California at Berkeley. Since joining JHU/APL in 1980 Dr. Sunday has worked as a designer and developer of software systems with emphasis on medical imaging interactive graphics natural language interfaces and software standards. He was the network designer for the Headquarters Integrated Office System (HIOS) Network for the Army at the Pentagon. He is currently the lead software engineer on the Command Support At-Sea Experiment Project.

The Command Support At-Sea Experiment (CS@SE) provides experimental advanced graphics display systems consisting of large screen color displays and operator console color displays in the combat information center (CIC) of an Aegis cruiser and in the tactical flag command center (TFCC) of an aircraft carrier. CS@SE systems are designed to prototype potential command support capabilities in an at-sea environment to validate and refine requirements for planned production system upgrades. These systems use sophisticated color graphics techniques to provide real-time tactical displays that improve the availability of information to an operator by reducing clutter through the use of color, area fill, transparen overlays and intensity coding of track symbols. Interfaces wen developed with the Aegis Display System (ADS), Shipboarc Gridlock System with Auto-correlation (SGS/AC), Flag Dats Display System (FDDS) and Tomahawk Engagement Planning and Exercise Evaluation System (TEPEE) that provided the data for the presentation of a tactical display. Display elements included both real-time and over-the-horizon (OTH) surface track data, velocity leaders, tags, uncertainty ellipses, and history trails. The display also included filled land masses, country boundaries, commercial airways, cities, graphics overlays (i.e., operational areas), weapon system missile performance contours, and engagement plans. This paper describes the experiment, its installation and integration into the shipboard environments of an Aegis cruiser (USS Leyte Gulf ) and an aircraft carrier (USS America , its usage by the ships companies and embarked staffs, and the experiment result! and findings. Key conclusions of the experiment are: 1 Advanced graphics color displays can significantly enhance the ability of the warfighter to assimilate a complex tactical display. 2 Both ships reported a requirement for a correlated OTH and real-time track display with the ability to clearly differentiate the two types

关键词： computer Graphics

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CAD CAM MANUFACTURING OF PROTOTYPE SHIPBOARD COMPONENTS

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NAVAL ENGINEERS JOURNAL 1990年第3期102卷 93-99页

作者： CALVERT, TE RODRIGUEZ, FA SLEBZAK, JS Thomas E. Calvert P.E.: is a senior project engineer with the Propulsion and Auxiliary Systems Department David Taylor Research Center Annapolis Md. His interests include application of computers to all aspects of engineering with particular emphasis on utilization of small computers. Mr. Calvert is a licensed professional engineer in Maryland. He received a BSEE from Drexel University in 1969 and since that time has completed a number of graduate courses related to machinery acoustics. Francisco A. Rodriguez:is an engineer with the Propulsion and Auxiliary Systems Department David Taylor Research Center. He was formerly with the Computer-Aided Design/Interactive Graphics Group of the Division of Engineering and Weapons U.S. Naval Academy. His interests include interfacing the computer aided design to the computer aided manufacturing along with related software and hardware development. Mr. Rodriguez received a BSEEfrom the University of Virginia in 1968. James S. Slebzak:is a mechanical engineering technician with the Propulsion and Auxiliary Systems Department David Taylor Research Center. He received his machinists papers in 1971 after serving his apprenticeship at David Taylor Research Center. He continued his education and became the senior numerical control programmer at the Annapolis Laboratory. He completed his mechanical technology degree from Anne Arundel Community College in 1986. His interests are in the application of numerically controlled manufacturing techniques to prototype machinery components.

The machine shop at the Annapolis Laboratory of the David Taylor Research Center (DTRC) provides model making and prototype support to a large variety of naval ship related engineering projects. In order to meet these challenging requirements, computer aided design/computer aided manufacturing (CAD/CAM) techniques are being used to produce “one of a kind” prototypes or very low volume production parts. The use of computer aides in these cases is to facilitate the accurate manufacture of a difficult part, rather than to improve manufacturing efficiencies. In addition, the approach provides the flexibility required to support research and development projects. Several examples of prototype shipboard components manufactured using CAD/CAM techniques are presented in this paper. The hardware and software that facilitated these projects are discussed. The examples described have met the requirements to produce a wide variety of prototype shipboard machinery components quickly and accurately.

关键词： Ship Equipment

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CLEER - AN AI-SYSTEM DEVELOPED TO ASSIST EQUIPMENT ARRANGEMENTS ON WARSHIPS

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NAVAL ENGINEERS JOURNAL 1989年第3期101卷 127-137页

作者： ZHOU, HH SILVERMAN, BG SIMKOL, J Dr. H. Harry Zhou:is a research professor at the Institute for Artificial Intelligence of The George Washington University. Dr. Zhou received his master's degree and Ph.D. in computer science from Vanderbilt University in 1984 and 1987 respectively. He did his dissertation in the fields of artificial intelligence analogical reasoning and machine learning. His research interests include: classifier systems genetic algorithms learning by analogy inductive learning adaptive expert systems automated knowledge acquisition and adaption. He is also interested in data base design programming languages mental modeling and software engineering. Dr. Barry G. Silverman:is director of the Institute for Artificial Intelligence and a professor at the Engineering Administration Department of The George Washington University. He is also president of IntelliTek Inc. an AI consulting firm. Dr. Silverman received the B.S.E. M.S.E. and Ph.D. degrees from the University of Pennsylvania. He has been a principal developer of four generic AI products as well as eight AI applications. Since 1979 he has written over 100 papers and reports on these AI efforts. Joel Simkol:is a research scientist currently engaged in designing expert system architectures to support electronic warfare vulnerability analyses threat assessments shipboard topside antenna arrangements and C3countermeasures employment. Mr. Simkol's work in applying expert systems technology to electromagnetic interference and to spectrum management has generated increased interest and participation from all branches of government agencies.

This paper describes a modularized AI system being built to help improve electromagnetic compatibility (EMC) among shipboard topside equipment and their associated systems. CLEER is intended to act as an easy to use integrator of existing expert knowledge and pre-existing data bases and large scale analytical models. Due to these interfaces; to the need for portability of the software; and to artificial intelligence related design requirements (such as the need for spatial reasoning, expert data base management, model base management, track-based reasoning, and analogical (similar ship) reasoning) it was realized that traditional expert system shells would be inappropriate, although relatively off-the-shelf AI technology could be incorporated. In the same vein, the rapid prototyping approach to expert system design and knowledge engineering was not pursued in favor of a rigorous systems engineering methodology. The critical design decisions affecting CLEER's development are summarized in this paper along with lessons learned to date all in terms of “how,” “why,” and “when” specific features are being developed.

关键词： Artificial Intelligence

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Report: Automating Manual Storeroom Zones in a Factory

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AT&T Technical Journal 1988年第2期67卷 87-94页

作者： Pulat, B. Mustafa Hewett, Alan P. W. B. Mustafa Pulat:is a senior engineer in the Material Handling Engineering Department of AT&T Network Systems at the AT&T Oklahoma City Works in Oklahoma City Oklahoma. Mr. Pulat joined AT&T in 1985 and is involved in system development modeling and just-in-time deliveries. He has a B.Sc. and M.Sc. in industrial engineering from the Middle East Technical University in Ankara Turkey and a Ph.D. in industrial engineering from North Carolina State University.Alan P. W. Hewettis a member of technical staff in the Manufacturing Engineering Systems Development Department of AT&T Bell Laboratories in Columbus Ohio. He joined the company in 1978 and designs and develops software for the Material Operations Velocity System (MOVES) a system that automates material handling in AT&T factories. He has a B.A. in chemistry from Kalamazoo College a Ph.D. in chemistry from Yale University and has done postdoctoral work in both chemistry and computer science at Harvard University.

Moving, storing, and controlling material efficiently is one of the most challenging problems of manufacturing. In the last twenty years, several different technologies were developed for this purpose, including the automated storage and retrieval system (AS/RS), which featured advancements in real‐time control of machines by computers. Today's AS/RS makes total material‐handling system integration a reality. This paper describes the experience of the AT&T Oklahoma City Works with such a system. © 1988 AT&T Technical Journal

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PRACTICAL APPLICATIONS OF ARTIFICIAL-INTELLIGENCE IN NAVAL engineering

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NAVAL ENGINEERS JOURNAL 1988年第6期100卷 32-40页

作者： HARTMAN, PJ PATRICK J. HARTMAN PH.D. P.E.:is head of the Design Engineering Section of the Naval Sea Systems Command (NavSea) Reliability and Maintainability Engineering Branch. He has actively investigated the practical applications of artificial intelligence (AI) for the past half dozen years. He developed the NavSea Computer Supported Design Working Group for Artificial Intelligence (AI) in 1985 to examine hardware and software for NavSea applications. He was educated at Marquette University and the University of Rhode Island where he specialized in mechanical and ocean engineering. Dr. Hartman has 21 years of engineering experience with the Rexnord Corporation the U.S. Coast Guard E.I. du Pont de Nemours and Co. the Gould Chesapeake Instrument Division and NavSea. He is a registered professional engineer and past chairman of the American Society of Mechanical Engineer's Ocean Engineering Division.

This paper examines the historical oscillations of artificial intelligence (AI). It traces the very beginnings from 1956 at the Dartmouth Summer Research Project on Artificial Intelligence, through the depressions of the 1960s and 1970s, to the exponentially increasing number of successful applications in the mid-1980s. It shows how to select problems which can be solved with the aid of expert systems. The paper also identifies areas such as common sense reasoning, automated machine learning, and complex design synthesis which are now beyond the state of the art and will be for years to come. Artificial intelligence programs are able to diagnose faults and classify solutions in narrowly defined specialties even when the data is “fuzzy,” but they have not exhibited autonomous “thinking.” Just as conventional computer programming has alleviated the burden of calculating, AI expert systems will streamline the processing of logical data. Both of these computer techniques are cost effective when they are applied to well defined tasks, since computers are faster than people and error free for routine tasks.

关键词： Artificial Intelligence

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