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Annual IEEE Symposium on computer-Based Medical Systems

作者： D. Krechel R. Bergmann K. Maximini A. von Wangenheim Deutschland GMBH SER Technology Germany Data and Knowledge Management Group University of Hildesheim Hildesheim Germany Department of Computer Science University of Santa Catarina Florianopolis Brazil

The market for health care systems supporting physicians and improving their daily routine is dynamically growing. The development of these systems makes great demands on the handling of medical knowledge, like anatomical and process knowledge. In this paper, a special approach for the radiological domain is presented. Our framework includes mechanisms to store medical knowledge in different knowledge containers, whose importance varies from application to application, and to support the execution of the processes. Three applications are introduced by way of example. We analyze these application scenarios to find the knowledge-intensive tasks that can be supported by an assistant system. The implemented solutions are integrated in the daily work of our radiological partner hospitals.

关键词： Biomedical imaging Medical diagnostic imaging Medical services Humans Hospitals Image analysis knowledge management Image processing Software agents Guidelines

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Preface

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001年 2037卷 V-VI页

作者： Boers, Egbert J. W. Cagnoni, Stefano Gottlieb, Jens Hart, Emma Lanzi, Pier Luca Raidl, Günther R. Smith, Robert E. Tijink, Harald Leiden Institute of Advanced Computer Science Leiden University Niels Bohrweg 1 Leiden Netherlands Dept. of Computer Engineering University of Parma Parco Area delle Scienze 181/a Parma Italy SAP AG Neurottstrasse 16 Walldorf Germany Napier University School of Computing 219 Colinton Road Edinburgh United Kingdom Polytechnic of Milan Piazza Leonardo da Vinci 32 Milan Italy Algorithms and Data Structur es Group Institute of Computer Graphics Vienna University of Technology Favoritenstrasse 9-11/186 Vienna Austria The Intelligent Computer Systems Centre The University of The West of England Coldharbour Lane Frenchay Bristol United Kingdom Data and Knowledge Systems Department National Aerospace Laboratory NLR P.O. Box 153 Emmeloord Netherlands

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Optimal one-to-many disjoint paths in folded hypercubes

Optimal one-to-many disjoint paths in folded hypercubes

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International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN)

作者： Cheng-Nan Lai Gen-Huey Chen Dyi-Rong Duh Operation Management Department Data Communication Business Group Chunghwa Telecom Company Limited Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering National Chi Nan University Nantou Taiwan

ISBN: (纸本)0769509363

Routing functions have been shown to be effective in deriving disjoint paths in the hypercube. In this paper, by the aid of a minimal routing function, k+1 disjoint paths from one node to another k+1 distinct nodes are constructed in the folded hypercube whose maximal length is not greater than [k/2]+1, where k is the dimension and [k/2] is the diameter of the folded hypercube. The maximal length is minimized in the worst case. For the general case, the maximal length is nearly optimal (/spl les/ the maximal distance between the two end nodes of these k+1 paths plus two). The result of this paper also computes the Rabin number of the folded hypercube, which is an open problem raised by Liaw and Chang (1999).

关键词： Hypercubes Routing computer science data engineering Business communication Communication system operations and management engineering management Telecommunications Multiprocessor interconnection networks Multiprocessing systems

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Automatic revision of simulation models

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IEEE Intelligent Systems and Their Applications 1998年第2期13卷 75-81页

作者： Pos, Anita Akkermans, Hans Top, Jan Unilever Res. Lab. Vlaardingen Netherlands Free University Amsterdam Netherlands ATO-DLO Netherlands Systems Engineering Group Unilever Research Netherlands University of Twente Netherlands Unilever Res. Lab. Vlaardingen 3130 AC Vlaardingen PO Box 114 Netherlands Dept. Applic.- Bus.-oriented Info. Free University Amsterdam Netherlands State University Groningen Netherlands Free Univ. Amsterdam Computer Science Dept. NL-1081 HV Amsterdam De Boelelaan 1081a Netherlands AKMC Knowledge Management NL-1831 BV Koedijk Klareweid 19 Netherlands Production Management Department ATO-DLO Netherlands ATO-DLO AA Wageningen PO Box 6700 Netherlands

007, an intelligent modeling assistant, helps users formulate explicit, testable requirements and assess the current model. It then executes generic repair plans and revises the model until requirements are met.

关键词： Automatic Revision Intelligent Modeling Assistant Simulation Models

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Influence of human engineering on manning levels and human performance on ships

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NAVAL ENGINEERS JOURNAL 1997年第5期109卷 67-76页

作者： Anderson, DE Oberman, FR Malone, TB Baker, CC David E. Anderson:has a bachelor of science degree in environmental engineering from Florida Technological University and a master's degree in environmental engineering from the University of Central Florida. He is a graduate of the Naval Sea Systems Command's Engineer-In-Training (EIT) Program. Mr. Anderson was instrumental in introducing the collective protection system (CPS) in the U.S. Navy developing the initial forward-fit package for the USS Gunston Hall and the engineering change proposal (ECP) for the USS Wasp. In 1990 he joined the Human Systems Integration (HSI) Division (SEA 55W5) where he was task leader for auxiliary ships. He is currently the HSI manager for the future technology variant of the SeaLift ship and the future carrier. Association of Scientists and Engineers 33rdAnnual Technical Symposium 26 April 1996. Fred R. Oberman:has B.A. and M.A. degrees from the University of Chicago and Loyola University (experimental psychology) and an M.S. degree in industrial engineering and operations research from Virginia Polytechnic Institute (VPI). He has more than 30 years experience in HSI management planning research analysis design and testing in government and private sector positions. He is currently responsible for NavSea HSI generic research and tool development efforts. He is responsible for Human Engineering Specifications and Standards (Commercial Hypertext) and is the NavSea 03D7 representative on HSI in Performance Specifications and for integration of HSI within Integrated Logistic Support (ILS). He has served as DoD HSI SubTAG chair and member of the Simulation and Modeling Test and Evaluation Display and Control Systems Human Computer Interaction Specifications and Standards and Systems Design Sub Tags as a member of the Society of Naval Architects and Marine Engineers (SNAME) Systems Safety Panel and a member of NATO RSG 14 on man-machine analysis. Thomas B. Malone: CHFEP received a Ph.D. in experimental psychology from Fordham University in 1964. He is president of Carlow

The objectives of Human engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There are other benefits that are thoroughly consistent with the direction of the Navy of the future, chief among these is reduction of required numbers of personnel to operate and maintain Navy ships. The Naval Research Advisory Committee (NRAC) report on Man-Machine Technology in the Navy estimated that one of the benefits from increased application of man-machine technology to Navy ship design is personnel reduction as well as improving system availability, effectiveness, and safety The objective of this paper is to discuss aspects of the human engineering design of ships and systems that affect manning requirements, and impact human-performance and safety The paper will also discuss how the application of human engineering leads to improved performance, and crew safety, and reduced workload, all of which influence manning levels. Finally, the paper presents a discussion of tools and case studies of good human engineering design practices which reduce manning.

关键词： Human engineering

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INTEGRATING knowledge-BASED SYSTEMS AND dataBASES

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CLINICA CHIMICA ACTA 1993年第1-2期222卷 101-115页

作者： GRIMSON, JB Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin 2 Ireland

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. database technology provides efficient and secure management of large amounts of data in a multi-user, multiapplication environment. knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g.'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to coexist as independent systems which can talk to each other by means of standard interfaces.

关键词： dataBASE management knowledge-BASED SYSTEMS EXPERT SYSTEMS

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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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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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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ARCTIC TRAFFICABILITY PROGRAM - A REVIEW

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NAVAL ENGINEERS JOURNAL 1984年第3期96卷 169-175页

作者： VOELKER, R GLEN, IF SEIBOLD, F BAYLY, I Richard Voelker:is Vice President of ARCTEC Incorporated a firm specializing in cold regions technology. He has been responsible for the management of thePolarClass Traffic-ability Program since its inception and annually participates in the field data collection in the Arctic. His prior experience includes positions with the U.S. Coast Guard in the icebreaker design project the Military Sealift Command and at Newport News Shipbuilding. He is a graduate of N. Y.S. Maritime College and has a MS degree from the University of Michigan. I.F. Glen:received his professional degrees in naval architecture from the Royal Naval Engineering College Manadon Plymouth and RN College Greenwich London entering the Royal Corps of Naval Constructors in 1967. After serving as a Constructor Lieutenant in the Royal Navy's Far East Fleet for a short period he joined the Polaris submarine project team in Bath England in 1968. In 1971 he was seconded to the Canadian Department of National Defense in Ottawa as a Constructor Lieutenant Commander under NATO exchange arrangements where he had responsibilities initially for conventional submarines and latterly for computer aided conceptual design. He ventured to Bath England in 1974 and joined Forward Design Group. In 1975 he took a position as a civilian engineer in the Canadian Defense Department and was Head of Hull Systems Engineering from 1977 to 1979. He joined ARCTEC CANADA LIMITED in 1980 and in addition to managing ice model testing projects and full scale trials has specialized in structural response of ships to ice impact. He headed ARCTEC's Kanata Laboratory from 1981 to 1983 when he was promoted to president. Frederick Seibold:is a research program manager with the Maritime Administration's Office of Advanced Ship Development and Technology. He is responsible for the marine science program which includes research in the areas of ship powering structures and propeller performance and Arctic technology. Mr. Seibold has been employed by Mar Ad since 1961 having hel

This paper describes a multiyear program to make an operational assessment on the feasibility of a year-round Arctic marine transportation system to serve Alaska. Specifically, the three objectives were to: collect meteorological and ice data along potential marine routes; instrument the hull and propulsion machinery to improve design critera for ice-worthy ships; and demonstrate that ships can operate in midwinter Alaskan Arctic ice conditions. The U.S. Coast Guard's Polar class icebreakers were used to make the operational assessment by annually extending the route northward and by operating throughout the winter season. This paper reviews some of the operational and technical achievements to date, as well as plans for future Arctic deployments.

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Abstracts

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Environmental management 1977年第1期1卷 67-96页

作者： Frankenfeld, John W. Schulz, Wolfgang McMurty, George J. Petersen, Gary W. May, G. A. Hering, F. S. Schwartz, J. I. Heywood, J. B. Chigier, N. A. Grohse, E. W. Walker, J. D. Colwell, R. R. Petrakis, L. Pergament, H. S. Thorpe, R. D. Schoepf, Richard W. Krzyczkowski, Roman Henneman, Suzanne S. Hudson, Charles L. Putnam, Evelyn S. Thiesen, Donna J. Parks, G. A. McCarty, Perry L. Leckie, J. O. Schrumpf, Barry J. Simonson, G. H. Paine, D. P. Lawrence, R. D. Pyott, W. T. Leh, M. Elders, W. Combs, J. Caplen, T. Harrison, F. L. Wong, K. M. Heft., R. E. Charnell, Robert L. Lehmann, Edward J. Mallon, Lawrence G. Hatfield, Cecile Adams, Gerald H. Johanning, James Talvitie, Antti Noll, Kenneth E. Miller, Terry Smiarowski, Joseph F. Willis, Cleve E. Foster, John H. Schlesinger, Benjamin Daetz, Douglas Lear, Donald U. Smith, Mona F. Hundemann, Audrey S. Crockett, Pernell W. Werner, Kirk G. Carroll, Thomas E. Maase, David L. Genco, Joseph E. Ifeadi, Christopher N. Lowman, F. G. Christensen, S. W. Van Winkle, W. Mattice, J. S. Harrison, Elizabeth A. Barker, James C. Chesness, Jerry L. Smith, Ralph E. Shaheeen, Donald G. Raney, R. Keith Borton, T. Wezernak, C. T. Raney, R. K. Sherwani, Jabbor K. Moreau, David H. Eisenberg, Norman A. Lynch, Cornelius J. Breeding, Roger J. Johnson, J. D. Foster, K. E. Mouat, D. A. Clark, R. Hyden, John William Owen, Wilfred Bayfield, Neil G. Barrow, Graham C. Stolz, Stephanie B. Wienckowski, Louis A. Brown, Betram S. Keyfitz, Nathan Wilson, W. L. Newman, Peter W. G. Bammi, Deepak Bammi, Dalip Goddard, James E. Chisholm, Tony Walsh, Cliff Brennan, Geoffrey Thompson, K. S. Richardson, R. Jensen, Clayton E. Brown, Dail W. Mirabito, John A. Cowing, Thomas G. Binghamton, Suny Siehl, George H. Albrecht, O. W. Alexander, Ariel Barde, Jean -Philippe Darby, William P. McMichael, Francis Clay Dunlap, Robert W. Muckleston, Keith W. Frankenhoff, Charles A. Giulini, Lorenzo T. Wyatt, T. Black, Peter E. Keating, William Thomas Leonard, M. E. Fisher, E. L. Brunelle, M. F. Dickinson, J. E. Pethig, Rudiger Clapham Exxon Research & Engineering Co. Linden Government Research Lab Coast Guard Washington D.C. Department of Transportation Washington D.C. Office For Remote Sensing of Earth Resources. NASA Earth Resources Survey Program Pennsylvania State University Washington D.C. Department of the Navy Washington D.C. Cambridge. Dept. of Mechanical Engineering Massachusetts Inst. of Technology USA Huntsville. School of Graduate Studies and Research Alabama Univ. USA Dept. of Microbiology. Office of Naval Research Maryland Univ. Arlington Research and Development Co. Pittsburgh AeroChem Research Labs. Inc. Princeton Dept. of the Interior Office of Library Services. Bibliographic Series (Final) Washington D.C. Interplan Corp. Santa Barbara Urban Mass Transportation Adm. Washington D.C. Naval Underwater Systems Center Newport Calif. Mercury Project. National Science Found Stanford Univ Washington D.C. Div. of Advanced Environmental Research & Tech. USA Corvallis. NASA Earth Resources Survey Program Oregon State Univ. Washington D.C. Riverside. Inst. of Geophysics and Planetary Physics National Science Foundation California Univ. Washington D.C. Livermore Lawrence Livermore Lab. California Univ. USA Atlantic Oceanographic and Meteorological Labs. National Oceanic and Atmospheric Administration Miami National Technical Information Service Springfield Miami Univ. Coral Gables School of Law National Oceanic and Atmospheric Administration Rockville National Academy of Sciences Office of Sea Grant Washington D. C. School of Law National Oceanic and Atmospheric Administration Office of Sea Grant. Rockville Norman. Dept. of Civil Engineering and Environmental Science. Urban Mass Transportation Administration Oklahoma Univ. Washington D. C. Knoxville.Dept. of Civil Engineering. Federal Highway Administration Tennessee Univ. Washington D. C. Amherst.Water Resources Research Center. Office of Water Research and Technology Massachusetts Univ. Washington D. C. Calif. Dept. of Industria

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