Sample records for artificial intelligence expert

  1. Artificial Intelligence Information Sources for the Beginner and Expert

    DTIC Science & Technology

    1991-05-01

    SUBPLEETAR TMS T bepbhdi" Artificial Intelligence ApplictionsforMlitar Expertis SystemsWilasbrVA 527Mrh 91 12a. DSCRIBTION C AIITY 6 STAEENRTY CTO SECb.T...DLSIFC ISTR BUMATION OC Apnclassified pu ncrlase; ituied inlsife unlimited. Artificial Intelligence Information Sources for the Beginner and Expert...mgivenfdsac.dia.mil UUCP: {...).osu-cisidsac!mgiven ABSTRACT A tremendous amount of information on artificial intelligence is available via different

  2. [The application and development of artificial intelligence in medical diagnosis systems].

    PubMed

    Chen, Zhencheng; Jiang, Yong; Xu, Mingyu; Wang, Hongyan; Jiang, Dazong

    2002-09-01

    This paper has reviewed the development of artificial intelligence in medical practice and medical diagnostic expert systems, and has summarized the application of artificial neural network. It explains that a source of difficulty in medical diagnostic system is the co-existence of multiple diseases--the potentially inter-related diseases. However, the difficulty of image expert systems is inherent in high-level vision. And it increases the complexity of expert system in medical image. At last, the prospect for the development of artificial intelligence in medical image expert systems is made.

  3. Expert Systems and Special Education.

    ERIC Educational Resources Information Center

    Hofmeister, Alan M.; Ferrara, Joseph M.

    The application of artificial intelligence to the problems of education is examined. One of the most promising areas in artificial intelligence is expert systems technology which engages the user in a problem-solving diaglogue. Some of the characteristics that make expert systems "intelligent" are identified and exemplified. The rise of…

  4. Artificial Intelligence and Expert Systems.

    ERIC Educational Resources Information Center

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  5. Counseling, Artificial Intelligence, and Expert Systems.

    ERIC Educational Resources Information Center

    Illovsky, Michael E.

    1994-01-01

    Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

  6. Artificial Intelligence and Vocational Education: An Impending Confluence.

    ERIC Educational Resources Information Center

    Roth, Gene L.; McEwing, Richard A.

    1986-01-01

    Reports on the relatively new field of artificial intelligence and its relationship to vocational education. Compares human intelligence with artificial intelligence. Discusses expert systems, natural language technology, and current trends. Lists potential applications for vocational education. (CH)

  7. Computational aerodynamics and artificial intelligence

    NASA Technical Reports Server (NTRS)

    Mehta, U. B.; Kutler, P.

    1984-01-01

    The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

  8. Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

    ERIC Educational Resources Information Center

    Borko, Harold

    1985-01-01

    Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

  9. Artificial Intelligence: The Expert Way.

    ERIC Educational Resources Information Center

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  10. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Thornburg, David D.

    1986-01-01

    Overview of the artificial intelligence (AI) field provides a definition; discusses past research and areas of future research; describes the design, functions, and capabilities of expert systems and the "Turing Test" for machine intelligence; and lists additional sources for information on artificial intelligence. Languages of AI are…

  11. Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

    DTIC Science & Technology

    1983-10-28

    Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

  12. What Artificial Intelligence Is Doing for Training.

    ERIC Educational Resources Information Center

    Kirrane, Peter R.; Kirrane, Diane E.

    1989-01-01

    Discusses the three areas of research and application of artificial intelligence: (1) robotics, (2) natural language processing, and (3) knowledge-based or expert systems. Focuses on what expert systems can do, especially in the area of training. (JOW)

  13. Instructional Applications of Artificial Intelligence.

    ERIC Educational Resources Information Center

    Halff, Henry M.

    1986-01-01

    Surveys artificial intelligence and the development of computer-based tutors and speculates on the future of artificial intelligence in education. Includes discussion of the definitions of knowledge, expert systems (computer systems that solve tough technical problems), intelligent tutoring systems (ITS), and specific ITSs such as GUIDON, MYCIN,…

  14. Experiments in Knowledge Refinement for a Large Rule-Based System

    DTIC Science & Technology

    1993-08-01

    empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

  15. Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

    ERIC Educational Resources Information Center

    Davies, Jim

    This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

  16. In Pursuit of Artificial Intelligence.

    ERIC Educational Resources Information Center

    Watstein, Sarah; Kesselman, Martin

    1986-01-01

    Defines artificial intelligence and reviews current research in natural language processing, expert systems, and robotics and sensory systems. Discussion covers current commercial applications of artificial intelligence and projections of uses and limitations in library technical and public services, e.g., in cataloging and online information and…

  17. Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

    NASA Technical Reports Server (NTRS)

    Gilmore, John F. (Editor)

    1987-01-01

    The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

  18. AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Johnson, J.R.; Netrologic, Inc., San Diego, CA)

    1988-01-01

    Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

  19. Conversion of the CALAP (Computer Aided Landform Analysis Program) Program from FORTRAN to DUCK.

    DTIC Science & Technology

    1986-09-01

    J’ DUCK artificial intelligence logic programming 20 AVrACT (Cthm m reerse stabN ameeaaW idelfr by block mbae) An expert advisor program named CALAP...original program was developed in FORTRAN on an HP- 1000, a mirticomputer. CALAP was reprogrammed in an Artificial Intelligence (AI) language called DUCK...the Artificial Intelligence Center, U.S. Army Engineer Topographic Laboratory, Fort Belvoir. Z" I. S. n- Page 1 I. Introduction An expert advisor

  20. Artificial Intelligence: Applications in Education.

    ERIC Educational Resources Information Center

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  1. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    DTIC Science & Technology

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  2. Artificial Intelligence Applications in Special Education: How Feasible? Final Report.

    ERIC Educational Resources Information Center

    Hofmeister, Alan M.; Ferrara, Joseph M.

    The research project investigated whether expert system tools have become sophisticated enough to be applied efficiently to problems in special education. (Expert systems are a development of artificial intelligence that combines the computer's capacity for storing specialized knowledge with a general set of rules intended to replicate the…

  3. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1995-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

  4. Artificial intelligence - New tools for aerospace project managers

    NASA Technical Reports Server (NTRS)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  5. Partial Bibliography of Work on Expert Systems,

    DTIC Science & Technology

    1982-12-01

    Bibliography: AAAI American Association for Artificial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information...Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International...Federation of Information Processing Societies IJCAI International Joint Conferences on Artificial Intelligence SIGPLAN ACM Special Interest Group on

  6. The role of artificial intelligence and expert systems in increasing STS operations productivity

    NASA Technical Reports Server (NTRS)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  7. Utilization of artificial intelligence techniques for the Space Station power system

    NASA Technical Reports Server (NTRS)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  8. Artificial intelligence and space power systems automation

    NASA Technical Reports Server (NTRS)

    Weeks, David J.

    1987-01-01

    Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

  9. Experiments with microcomputer-based artificial intelligence environments

    USGS Publications Warehouse

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  10. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

    PubMed

    Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

    2018-04-01

    Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the clinical utility of the proposed sepsis prediction model.

  11. Artificial intelligence in a mission operations and satellite test environment

    NASA Technical Reports Server (NTRS)

    Busse, Carl

    1988-01-01

    A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

  12. An overview of the artificial intelligence and expert systems component of RICIS

    NASA Technical Reports Server (NTRS)

    Feagin, Terry

    1987-01-01

    Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

  13. Expert Systems: Tutors, Tools, and Tutees.

    ERIC Educational Resources Information Center

    Lippert, Renate C.

    1989-01-01

    Discusses the current status, research, and practical implications of artificial intelligence and expert systems in education. Topics discussed include computer-assisted instruction; intelligent computer-assisted instruction; intelligent tutoring systems; instructional strategies involving the creation of knowledge bases; decision aids;…

  14. Applications of Artificial Intelligence (AI) and Expert Systems for Online Searching.

    ERIC Educational Resources Information Center

    Hawkins, Donald T.

    1988-01-01

    Discussion of the online searching process identifies the formulation of a search strategy as the major problem area for users of online systems. Artificial intelligence is suggested as a solution to this problem, and several expert systems for information retrieval are described. An annotated list of 24 items for further reading is included. (23…

  15. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  16. List of ARI Conference Papers, Journal Articles, Books, and Book Chapters: 1982-1991

    DTIC Science & Technology

    1992-10-01

    and Engineering Applications of Artificial Intelligence and Expert Systems, Tullahoma, TN. Goehring, D.J., & Hart, R.J. (1985, October). Automated...systems: Computkr-based authoring. Proceedings of the 30th annual meeting of the Artificial Intelligence Society, Dayton, OH. Knapp, D.J., & Pliske, R.M...Moses, F.L. (1984-85) Intelligence vehicle integrated displays. Paper presented at the Conference on Applied Artificial Intelligence , the Data Processing

  17. Explanation Generation in Expert Systems (A Literature Review and Implementation)

    DTIC Science & Technology

    1989-01-01

    Rubinoff. Explaining concepts in expert systems: The clear system. In Proceedings of the Second Conference on Aritificial Intelligence Applications. pages... intelligent computer software systems are Heedled. The Expert System (ES) technology of Artificial Intelligence (Al) is ore solution that is (nerging to...Random House College Dictionary defines explanation as: "to make plain, clear, or intelligible something that is not known or understood". [33] While

  18. Bibliography: Artificial Intelligence.

    ERIC Educational Resources Information Center

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  19. Computer Intelligence: Unlimited and Untapped.

    ERIC Educational Resources Information Center

    Staples, Betsy

    1983-01-01

    Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

  20. Small Knowledge-Based Systems in Education and Training: Something New Under the Sun.

    ERIC Educational Resources Information Center

    Wilson, Brent G.; Welsh, Jack R.

    1986-01-01

    Discusses artificial intelligence, robotics, natural language processing, and expert or knowledge-based systems research; examines two large expert systems, MYCIN and XCON; and reviews the resources required to build large expert systems and affordable smaller systems (intelligent job aids) for training. Expert system vendors and products are…

  1. An Expert System for Processing Uncorrelated Satellite Tracks

    DTIC Science & Technology

    1992-12-17

    earthworms with much intellect e\\en though they routinely carry out this same function. One definition given artificial intelligence is "the study of mental...Networks: Benchmarking Studies ," Proceedings from the IEEE International Conference on Neural Networkv. pp. 64-65, 1988. 229 Lyddane, R., "Small...reverse if necessary and rdenqtl_ by block number, Field Group Subgroup Artificial Intelligence, Expert Systems, Neural Networks. Orbital Mechanics

  2. Artificial Intelligence in Education.

    ERIC Educational Resources Information Center

    Ruyle, Kim E.

    Expert systems have made remarkable progress in areas where the knowledge of an expert can be codified and represented, and these systems have many potentially useful applications in education. Expert systems seem "intelligent" because they do not simply repeat a set of predetermined questions during a consultation session, but will have…

  3. Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

    NASA Technical Reports Server (NTRS)

    Kellner, A.

    1987-01-01

    Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

  4. Artificial intelligence in medicine.

    PubMed Central

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  5. Artificial intelligence in medicine.

    PubMed

    Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

    2004-09-01

    Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

  6. Third Conference on Artificial Intelligence for Space Applications, part 1

    NASA Technical Reports Server (NTRS)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1987-01-01

    The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed.

  7. A Spoken English Recognition Expert System.

    DTIC Science & Technology

    1983-09-01

    Davidson. "Representation of Knowledge," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A. Felgenbaum. DTIC document number AD...Regents of the University of CalTorni, 1981. 9. Gardner, Anne. "Search," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A...Felgenbaum, DTIC document number AD A074078, 1979. 10. Gardner, Anne,et al. "Natural Language Understanding," Handbook of Artificial Intelligence, edited

  8. Artificial Intelligence Techniques: Applications for Courseware Development.

    ERIC Educational Resources Information Center

    Dear, Brian L.

    1986-01-01

    Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

  9. Robotic air vehicle. Blending artificial intelligence with conventional software

    NASA Technical Reports Server (NTRS)

    Mcnulty, Christa; Graham, Joyce; Roewer, Paul

    1987-01-01

    The Robotic Air Vehicle (RAV) system is described. The program's objectives were to design, implement, and demonstrate cooperating expert systems for piloting robotic air vehicles. The development of this system merges conventional programming used in passive navigation with Artificial Intelligence techniques such as voice recognition, spatial reasoning, and expert systems. The individual components of the RAV system are discussed as well as their interactions with each other and how they operate as a system.

  10. Artificial Intelligence and Expert Systems: Will They Change the Library? Papers Presented at the Annual Clinic on Library Applications of Data Processing (27th, Urbana, Illinois, March 25-27, 1990). Illinois, March 25-27, 1990).

    ERIC Educational Resources Information Center

    Lancaster, F. W., Ed.; Smith, Linda C., Ed.

    Some of the 12 conference papers presented in this proceedings focus on the present and potential capabilities of artificial intelligence and expert systems as they relate to a wide range of library applications, including descriptive cataloging, technical services, collection development, subject indexing, reference services, database searching,…

  11. Artificial Intelligence in Speech Understanding: Two Applications at C.R.I.N.

    ERIC Educational Resources Information Center

    Carbonell, N.; And Others

    1986-01-01

    This article explains how techniques of artificial intelligence are applied to expert systems for acoustic-phonetic decoding, phonological interpretation, and multi-knowledge sources for man-machine dialogue implementation. The basic ideas are illustrated with short examples. (Author/JDH)

  12. Artificial Intelligence: Underlying Assumptions and Basic Objectives.

    ERIC Educational Resources Information Center

    Cercone, Nick; McCalla, Gordon

    1984-01-01

    Presents perspectives on methodological assumptions underlying research efforts in artificial intelligence (AI) and charts activities, motivations, methods, and current status of research in each of the major AI subareas: natural language understanding; computer vision; expert systems; search, problem solving, planning; theorem proving and logic…

  13. Artificial Intelligence and Expert Systems.

    ERIC Educational Resources Information Center

    Lawlor, Joseph

    Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

  14. ROSIE: A Programming Environment for Expert Systems

    DTIC Science & Technology

    1985-10-01

    ence on Artificial Inteligence , Tbilisi, USSR, 1975. Fain, J., D. Gorlin, F. Hayes-Roth, S. Rosenschein, H. Sowizral, and D. Waterman, The ROSIE Language...gramming environment for artificial intelligence (AI) applications. It provides particular support for designing expert systems, systems that embody

  15. Optical Inference Machines

    DTIC Science & Technology

    1988-06-27

    de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

  16. Artificial Intelligence and CALL.

    ERIC Educational Resources Information Center

    Underwood, John H.

    The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

  17. A Starter's Guide to Artificial Intelligence.

    ERIC Educational Resources Information Center

    McConnell, Barry A.; McConnell, Nancy J.

    1988-01-01

    Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

  18. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

  19. Artificial Intelligence Is for Real: Undergraduate Students Should Know about It.

    ERIC Educational Resources Information Center

    Liebowitz, Jay

    1988-01-01

    Discussion of the possibilities of introducing artificial intelligence (AI) into the undergraduate curriculum highlights the introduction of AI in an introduction to information processing course for business students at George Washington University. Topics discussed include robotics, expert systems prototyping in class, and the interdisciplinary…

  20. Artificial intelligence, expert systems, computer vision, and natural language processing

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  1. Artificial Intelligence and Spacecraft Power Systems

    NASA Technical Reports Server (NTRS)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  2. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    ERIC Educational Resources Information Center

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  3. Artificial Intelligence and School Library Media Centers.

    ERIC Educational Resources Information Center

    Young, Robert J.

    1990-01-01

    Discusses developments in artificial intelligence in terms of their impact on school library media centers and the role of media specialists. Possible uses of expert systems, hypertext, and CD-ROM technologies in school media centers are examined and the challenges presented by these technologies are discussed. Fourteen sources of additional…

  4. Artificial Intelligence and the High School Computer Curriculum.

    ERIC Educational Resources Information Center

    Dillon, Richard W.

    1993-01-01

    Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

  5. Innovative applications of artificial intelligence

    NASA Astrophysics Data System (ADS)

    Schorr, Herbert; Rappaport, Alain

    Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

  6. Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques

    DTIC Science & Technology

    1990-01-01

    Proceedings of the Symposium on Aritificial Intelligence in ~~litary Logistics, Arlington, VA: American Defense Preparedness Assoc. pp. 177-182...dynamic changes, too many variables, and lack pf planning time. The Human Engineeri n ~ Laboratory (HEL) is developing artificial intelligence (AI...first attempt. The field of artificial intelligence includes a variety of knowledge-based approaches. Most widely known are Expert Systems, that are

  7. A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

    DOT National Transportation Integrated Search

    1987-01-01

    Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

  8. Application Of The CSRL Language To The Design Of Diagnostic Expert Systems: The Moodis Experience, A Preliminary Report

    NASA Astrophysics Data System (ADS)

    Bravos, Angelo; Hill, Howard; Choca, James; Bresolin, Linda B.; Bresolin, Michael J.

    1986-03-01

    Computer technology is rapidly becoming an inseparable part of many health science specialties. Recently, a new area of computer technology, namely Artificial Intelligence, has been applied toward assisting the medical experts in their diagnostic and therapeutic decision making process. MOODIS is an experimental diagnostic expert system which assists Psychiatry specialists in diagnosing human Mood Disorders, better known as Affective Disorders. Its diagnostic methodology is patterned after MDX, a diagnostic expert system developed at LAIR (Laboratory for Artificial Intelligence Research) of Ohio State University. MOODIS is implemented in CSRL (Conceptual Structures Representation Language) also developed at LAIR. This paper describes MOODIS in terms of conceptualization and requirements, and discusses why the MDX approach and CSRL were chosen.

  9. Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

    ERIC Educational Resources Information Center

    Hsieh, Cynthia C.; Hall, Wendy

    1989-01-01

    Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

  10. Cataloging Expert Systems: Optimism and Frustrated Reality.

    ERIC Educational Resources Information Center

    Olmstadt, William J.

    2000-01-01

    Discusses artificial intelligence and attempts to catalog expert systems. Topics include the nature of expertise; examples of cataloging expert systems; barriers to implementation; and problems, including total automation, cataloging expertise, priorities, and system design. (LRW)

  11. Framework for Evolutionary Development of an Autonomous Expert System for Acoustically Identifying Classifications of Vessels

    DTIC Science & Technology

    1989-01-01

    completely autonomous system. SOMMIIRE Une exp6rience en intelligence artificielle (IA) en cours au CRDA vise la misc au point 6ventuelle d’un syst~me...identifying vessel classifications from 0aaV Mcute SOAifatwgms is the ultimate goal of Artificial Intelligence (Al) wod ?bhig- eouaduted -*DRAR~ An...Friendly Interface ..................................................................... 4 3 Concepts of Assistant and Autonomous Artificially Intelligent

  12. Artificial intelligence in the diagnosis of low back pain.

    PubMed

    Mann, N H; Brown, M D

    1991-04-01

    Computerized methods are used to recognize the characteristics of patient pain drawings. Artificial neural network (ANN) models are compared with expert predictions and traditional statistical classification methods when placing the pain drawings of low back pain patients into one of five clinically significant categories. A discussion is undertaken outlining the differences in these classifiers and the potential benefits of the ANN model as an artificial intelligence technique.

  13. AAAI (American Association on Artificial Intelligence) Workshop on AI (Artificial Intelligence) Simulation Held in Philadelphia, Pennsylvania on August 11, 1986,

    DTIC Science & Technology

    1986-08-01

    is then applied in i ABSTRCT : ,.:,.vu knowledge acquisition from those multiple sources for a specific design, for example, an expert system for...67. N 181.1 47.U3 a75 269;9.6 % A. %3 3 Genetic Explanations: For the concept of a genetic explanation (see .d -. above) to apply to the Gaither...Simulation Research Unit (Acock,1985; Baker,1983; Baker,1985). -. MD’,EX srves as an inner shell for apPlying Artificial Intelligence and E:pert System

  14. Expert Systems: An Overview for Teacher-Librarians.

    ERIC Educational Resources Information Center

    Orwig, Gary; Barron, Ann

    1992-01-01

    Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

  15. The Paradox of Expertise.

    ERIC Educational Resources Information Center

    Hankins, George.

    1987-01-01

    Describes the novice-to-expert model of human learning and compares it to the recent advances in the areas of artificial intelligence and expert systems. Discusses some of the characteristics of experts, proposing connections between them with expert systems and theories of left-right brain functions. (TW)

  16. Artificial Intelligence In Computational Fluid Dynamics

    NASA Technical Reports Server (NTRS)

    Vogel, Alison Andrews

    1991-01-01

    Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

  17. Applications of artificial intelligence to space station: General purpose intelligent sensor interface

    NASA Technical Reports Server (NTRS)

    Mckee, James W.

    1988-01-01

    This final report describes the accomplishments of the General Purpose Intelligent Sensor Interface task of the Applications of Artificial Intelligence to Space Station grant for the period from October 1, 1987 through September 30, 1988. Portions of the First Biannual Report not revised will not be included but only referenced. The goal is to develop an intelligent sensor system that will simplify the design and development of expert systems using sensors of the physical phenomena as a source of data. This research will concentrate on the integration of image processing sensors and voice processing sensors with a computer designed for expert system development. The result of this research will be the design and documentation of a system in which the user will not need to be an expert in such areas as image processing algorithms, local area networks, image processor hardware selection or interfacing, television camera selection, voice recognition hardware selection, or analog signal processing. The user will be able to access data from video or voice sensors through standard LISP statements without any need to know about the sensor hardware or software.

  18. New directions for Artificial Intelligence (AI) methods in optimum design

    NASA Technical Reports Server (NTRS)

    Hajela, Prabhat

    1989-01-01

    Developments and applications of artificial intelligence (AI) methods in the design of structural systems is reviewed. Principal shortcomings in the current approach are emphasized, and the need for some degree of formalism in the development environment for such design tools is underscored. Emphasis is placed on efforts to integrate algorithmic computations in expert systems.

  19. Developing Applications of Artificial Intelligence Technology To Provide Consultative Support in the Use of Research Methodology by Practitioners.

    ERIC Educational Resources Information Center

    Vitale, Michael R.; Romance, Nancy

    Adopting perspectives based on applications of artificial intelligence proven in industry, this paper discusses methodological strategies and issues that underlie the development of such software environments. The general concept of an expert system is discussed in the context of its relevance to the problem of increasing the accessibility of…

  20. Automated Test Requirement Document Generation

    DTIC Science & Technology

    1987-11-01

    DIAGNOSTICS BASED ON THE PRINCIPLES OF ARTIFICIAL INTELIGENCE ", 1984 International Test Conference, 01Oct84, (A3, 3, Cs D3, E2, G2, H2, 13, J6, K) 425...j0O GLOSSARY OF ACRONYMS 0 ABBREVIATION DEFINITION AFSATCOM Air Force Satellite Communication Al Artificial Intelligence ASIC Application Specific...In-Test Equipment (BITE) and AI ( Artificial Intelligence) - Expert Systems - need to be fully applied before a completely automated process can be

  1. Artificial intelligence costs, benefits, risks for selected spacecraft ground system automation scenarios

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline), (2) standalone expert systems, (3) standardized, reusable knowledge base management systems (KBMS), and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  2. Artificial intelligence costs, benefits, and risks for selected spacecraft ground system automation scenarios

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walter F.; Silverman, Barry G.; Kahn, Martha; Hexmoor, Henry

    1988-01-01

    In response to a number of high-level strategy studies in the early 1980s, expert systems and artificial intelligence (AI/ES) efforts for spacecraft ground systems have proliferated in the past several years primarily as individual small to medium scale applications. It is useful to stop and assess the impact of this technology in view of lessons learned to date, and hopefully, to determine if the overall strategies of some of the earlier studies both are being followed and still seem relevant. To achieve that end four idealized ground system automation scenarios and their attendant AI architecture are postulated and benefits, risks, and lessons learned are examined and compared. These architectures encompass: (1) no AI (baseline); (2) standalone expert systems; (3) standardized, reusable knowledge base management systems (KBMS); and (4) a futuristic unattended automation scenario. The resulting artificial intelligence lessons learned, benefits, and risks for spacecraft ground system automation scenarios are described.

  3. Intelligent Information Retrieval: An Introduction.

    ERIC Educational Resources Information Center

    Gauch, Susan

    1992-01-01

    Discusses the application of artificial intelligence to online information retrieval systems and describes several systems: (1) CANSEARCH, from MEDLINE; (2) Intelligent Interface for Information Retrieval (I3R); (3) Gausch's Query Reformulation; (4) Environmental Pollution Expert (EP-X); (5) PLEXUS (gardening); and (6) SCISOR (corporate…

  4. Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

    NASA Technical Reports Server (NTRS)

    Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

    1993-01-01

    The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

  5. Development of the Diagnostic Expert System for Tea Processing

    NASA Astrophysics Data System (ADS)

    Yoshitomi, Hitoshi; Yamaguchi, Yuichi

    A diagnostic expert system for tea processing which can presume the cause of the defect of the processed tea was developed to contribute to the improvement of tea processing. This system that consists of some programs can be used through the Internet. The inference engine, the core of the system adopts production system which is well used on artificial intelligence, and is coded by Prolog as the artificial intelligence oriented language. At present, 176 rules for inference have been registered on this system. The system will be able to presume better if more rules are added to the system.

  6. Artificial intelligence and expert systems in-flight software testing

    NASA Technical Reports Server (NTRS)

    Demasie, M. P.; Muratore, J. F.

    1991-01-01

    The authors discuss the introduction of advanced information systems technologies such as artificial intelligence, expert systems, and advanced human-computer interfaces directly into Space Shuttle software engineering. The reconfiguration automation project (RAP) was initiated to coordinate this move towards 1990s software technology. The idea behind RAP is to automate several phases of the flight software testing procedure and to introduce AI and ES into space shuttle flight software testing. In the first phase of RAP, conventional tools to automate regression testing have already been developed or acquired. There are currently three tools in use.

  7. Application of artificial intelligence to the management of urological cancer.

    PubMed

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  8. Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

    ERIC Educational Resources Information Center

    Sayre, Scott Alan

    The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

  9. Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

    DTIC Science & Technology

    1984-06-01

    other automatic machinery such as presses, molding machines , and numerically-controlled machine tools, just as people do. A-36...Robotics Technologies 3 B. Relevant AI Technologies 4 1. Expert Systems 4 2. Automatic Planning 4 3. Natural Language 5 4. Machine Vision...building machines that imitate human behavior. Artificial intelligence is concerned with the functions of the brain, whereas robotics include, in

  10. [Artificial intelligence--the knowledge base applied to nephrology].

    PubMed

    Sancipriano, G P

    2005-01-01

    The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

  11. Cardiac risk stratification in renal transplantation using a form of artificial intelligence.

    PubMed

    Heston, T F; Norman, D J; Barry, J M; Bennett, W M; Wilson, R A

    1997-02-15

    The purpose of this study was to determine if an expert network, a form of artificial intelligence, could effectively stratify cardiac risk in candidates for renal transplant. Input into the expert network consisted of clinical risk factors and thallium-201 stress test data. Clinical risk factor screening alone identified 95 of 189 patients as high risk. These 95 patients underwent thallium-201 stress testing, and 53 had either reversible or fixed defects. The other 42 patients were classified as low risk. This algorithm made up the "expert system," and during the 4-year follow-up period had a sensitivity of 82%, specificity of 77%, and accuracy of 78%. An artificial neural network was added to the expert system, creating an expert network. Input into the neural network consisted of both clinical variables and thallium-201 stress test data. There were 5 hidden nodes and the output (end point) was cardiac death. The expert network increased the specificity of the expert system alone from 77% to 90% (p < 0.001), the accuracy from 78% to 89% (p < 0.005), and maintained the overall sensitivity at 88%. An expert network based on clinical risk factor screening and thallium-201 stress testing had an accuracy of 89% in predicting the 4-year cardiac mortality among 189 renal transplant candidates.

  12. Expert Systems in Reference Services.

    ERIC Educational Resources Information Center

    Roysdon, Christine, Ed.; White, Howard D., Ed.

    1989-01-01

    Eleven articles introduce expert systems applications in library and information science, and present design and implementation issues of system development for reference services. Topics covered include knowledge based systems, prototype development, the use of artificial intelligence to remedy current system inadequacies, and an expert system to…

  13. Evaluation of Expert Systems in Decisionmaking Organizations

    DTIC Science & Technology

    1988-07-01

    Abacus Press, Tunbridge Wells. Levis, A. H., 1984. "Information Processing and Decisionmaking Organizations: A Mathematical Description." I Large Scale Systems , Vol. 7, pp. 151-163. hI2 II I, Ie ... intelligence and especially expert systems. This paper presents a procedure for assessing to what extent the measures of performance of an organization are...aids that is receiving attention in the development community is based on artificial intelligence and especially expert systems. This paper presents a

  14. An Expert Systems Approach for PR Campaigns Research.

    ERIC Educational Resources Information Center

    Cameron, Glen T.; Curtin, Patricia A.

    1992-01-01

    Describes an expert system (the artificial intelligence program "Publics") that helps users identify key publics for public relations campaigns. Examines advantages and problems encountered in its use in public relations campaigns classrooms. (SR)

  15. Application of artificial intelligence to pharmacy and medicine.

    PubMed

    Dasta, J F

    1992-04-01

    Artificial intelligence (AI) is a branch of computer science dealing with solving problems using symbolic programming. It has evolved into a problem solving science with applications in business, engineering, and health care. One application of AI is expert system development. An expert system consists of a knowledge base and inference engine, coupled with a user interface. A crucial aspect of expert system development is knowledge acquisition and implementing computable ways to solve problems. There have been several expert systems developed in medicine to assist physicians with medical diagnosis. Recently, several programs focusing on drug therapy have been described. They provide guidance on drug interactions, drug therapy monitoring, and drug formulary selection. There are many aspects of pharmacy that AI can have an impact on and the reader is challenged to consider these possibilities because they may some day become a reality in pharmacy.

  16. A Logic Basis for Information Retrieval.

    ERIC Educational Resources Information Center

    Watters, C. R.; Shepherd, M. A.

    1987-01-01

    Discusses the potential of recent work in artificial intelligence, especially expert systems, for the development of more effective information retrieval systems. Highlights include the role of an expert bibliographic retrieval system and a prototype expert retrieval system, PROBIB-2, that uses MicroProlog to provide deductive reasoning…

  17. Quality assurance paradigms for artificial intelligence in modelling and simulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Oren, T.I.

    1987-04-01

    New classes of quality assurance concepts and techniques are required for the advanced knowledge-processing paradigms (such as artificial intelligence, expert systems, or knowledge-based systems) and the complex problems that only simulative systems can cope with. A systematization of quality assurance problems as well as examples are given to traditional and cognizant quality assurance techniques in traditional and cognizant modelling and simulation.

  18. Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoD

    DTIC Science & Technology

    2017-01-01

    3.2 Generic Network Architecture ........................................................................................ 11 3.3 Neuron Non ...The magnitude of the importance of these technologies is hard to overstate, and we thus feel that technically minded, non -expert readers should be...The result is often billions of weights and biases which need to be calculated. 13 3.3 Neuron Non -Linearity The big, early advance in

  19. Integrating Human and Computer Intelligence. Technical Report No. 32.

    ERIC Educational Resources Information Center

    Pea, Roy D.

    This paper explores the thesis that advances in computer applications and artificial intelligence have important implications for the study of development and learning in psychology. Current approaches to the use of computers as devices for problem solving, reasoning, and thinking--i.e., expert systems and intelligent tutoring systems--are…

  20. Potential application of artificial concepts to aerodynamic simulation

    NASA Technical Reports Server (NTRS)

    Kutler, P.; Mehta, U. B.; Andrews, A.

    1984-01-01

    The concept of artificial intelligence as it applies to computational fluid dynamics simulation is investigated. How expert systems can be adapted to speed the numerical aerodynamic simulation process is also examined. A proposed expert grid generation system is briefly described which, given flow parameters, configuration geometry, and simulation constraints, uses knowledge about the discretization process to determine grid point coordinates, computational surface information, and zonal interface parameters.

  1. Artificial intelligence for turboprop engine maintenance

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    NONE

    1995-01-01

    Long-term maintenance operations, causing the unit to out of action, may seem economical - but they result in reduced operating readiness. Offsetting that concern, careless, hurried maintenance reduces margins of safety and reliability. Any tool that improves maintenance without causing a sharp increase in cost is valuable. Artificial intelligence (AI) is one of the tools. Expert system and neural networks are two different areas of AI that show promise for turboprop engine maintenance.

  2. Quality use of the computer: Computational mechanics, artificial intelligence, robotics, and acoustic sensing; Proceedings of the ASME/JSME Pressure Vessels and Piping Conference, Honolulu, HI, July 23-27, 1989

    NASA Astrophysics Data System (ADS)

    Cory, J. F., Jr.; Gordon, J. L.; Miyoshi, T.; Suzuki, K.

    1989-06-01

    Papers are presented on the use of microcomputers, supercomputers, and workstations in solid and structural mechanics. Artificial intelligence technology, the development and use of expert systems, and research in the area of robotics are discussed. Attention is also given to probabilistic finite element and boundary element methods and acoustic sensing.

  3. Expert Systems the Old Fashioned Way: Person to Person.

    ERIC Educational Resources Information Center

    McCleary, Hunter; Mayer, William J.

    1988-01-01

    Describes the services of Teltech, Inc., which mimic the desirable attributes of artificial intelligence and expert systems via a "database" of 5,000 experts in technical areas and interactive literature searches executed by staff. Advantages and shortcomings of the network are exemplified by sample searches. Several sample menus and…

  4. Toward the Development of Expert Assessment Systems.

    ERIC Educational Resources Information Center

    Hasselbring, Ted S.

    1986-01-01

    The potential application of "expert systems" to the diagnosis and assessment of special-needs children is examined and existing prototype systems are reviewed. The future of this artificial intelligence technology is discussed in relation to emerging development tools designed for the creation of expert systems by the lay public. (Author)

  5. The Potential of Computer-Based Expert Systems for Special Educators in Rural Settings.

    ERIC Educational Resources Information Center

    Parry, James D.; Ferrara, Joseph M.

    Knowledge-based expert computer systems are addressing issues relevant to all special educators, but are particularly relevant in rural settings where human experts are less available because of distance and cost. An expert system is an application of artificial intelligence (AI) that typically engages the user in a dialogue resembling the…

  6. Operation and Structure of an Artificial Intelligence Expert Consultative System for Reading and Learning.

    ERIC Educational Resources Information Center

    Balajthy, Ernest

    1989-01-01

    The article examines decision-making expert systems and discusses their implications for diagnosis and prescription of reading difficulties. A detailed description of how a reading diagnostic expert system might operate to aid classroom teachers is followed by a discussion of advantages and limitations of expert systems for educational use.…

  7. Expert Systems Research.

    ERIC Educational Resources Information Center

    Duda, Richard O.; Shortliffe, Edward H.

    1983-01-01

    Discusses a class of artificial intelligence computer programs (often called "expert systems" because they address problems normally thought to require human specialists for their solution) intended to serve as consultants for decision making. Also discusses accomplishments (including information systematization in medical diagnosis and…

  8. Artificial intelligence, neural network, and Internet tool integration in a pathology workstation to improve information access

    NASA Astrophysics Data System (ADS)

    Sargis, J. C.; Gray, W. A.

    1999-03-01

    The APWS allows user friendly access to several legacy systems which would normally each demand domain expertise for proper utilization. The generalized model, including objects, classes, strategies and patterns is presented. The core components of the APWS are the Microsoft Windows 95 Operating System, Oracle, Oracle Power Objects, Artificial Intelligence tools, a medical hyperlibrary and a web site. The paper includes a discussion of how could be automated by taking advantage of the expert system, object oriented programming and intelligent relational database tools within the APWS.

  9. Tuberculosis control, and the where and why of artificial intelligence

    PubMed Central

    Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

    2017-01-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

  10. Tuberculosis control, and the where and why of artificial intelligence.

    PubMed

    Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

    2017-04-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  11. Intelligent hypertext manual development for the Space Shuttle hazardous gas detection system

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.; Hoyt, W. Andes

    1989-01-01

    This research is designed to utilize artificial intelligence (AI) technology to increase the efficiency of personnel involved with monitoring the space shuttle hazardous gas detection systems at the Marshall Space Flight Center. The objective is to create a computerized service manual in the form of a hypertext and expert system which stores experts' knowledge and experience. The resulting Intelligent Manual will assist the user in interpreting data timely, in identifying possible faults, in locating the applicable documentation efficiently, in training inexperienced personnel effectively, and updating the manual frequently as required.

  12. System of experts for intelligent data management (SEIDAM)

    NASA Technical Reports Server (NTRS)

    Goodenough, David G.; Iisaka, Joji; Fung, KO

    1993-01-01

    A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

  13. System of Experts for Intelligent Data Management (SEIDAM)

    NASA Technical Reports Server (NTRS)

    Goodenough, David G.; Iisaka, Joji; Fung, KO

    1992-01-01

    It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

  14. Embedded expert system for space shuttle main engine maintenance

    NASA Technical Reports Server (NTRS)

    Pooley, J.; Thompson, W.; Homsley, T.; Teoh, W.; Jones, J.; Lewallen, P.

    1987-01-01

    The SPARTA Embedded Expert System (SEES) is an intelligent health monitoring system that directs analysis by placing confidence factors on possible engine status and then recommends a course of action to an engineer or engine controller. The technique can prevent catastropic failures or costly rocket engine down time because of false alarms. Further, the SEES has potential as an on-board flight monitor for reusable rocket engine systems. The SEES methodology synergistically integrates vibration analysis, pattern recognition and communications theory techniques with an artificial intelligence technique - the Embedded Expert System (EES).

  15. Expert System Software

    NASA Technical Reports Server (NTRS)

    1989-01-01

    C Language Integrated Production System (CLIPS) is a software shell for developing expert systems is designed to allow research and development of artificial intelligence on conventional computers. Originally developed by Johnson Space Center, it enables highly efficient pattern matching. A collection of conditions and actions to be taken if the conditions are met is built into a rule network. Additional pertinent facts are matched to the rule network. Using the program, E.I. DuPont de Nemours & Co. is monitoring chemical production machines; California Polytechnic State University is investigating artificial intelligence in computer aided design; Mentor Graphics has built a new Circuit Synthesis system, and Brooke and Brooke, a law firm, can determine which facts from a file are most important.

  16. Rule based artificial intelligence expert system for determination of upper extremity impairment rating.

    PubMed

    Lim, I; Walkup, R K; Vannier, M W

    1993-04-01

    Quantitative evaluation of upper extremity impairment, a percentage rating most often determined using a rule based procedure, has been implemented on a personal computer using an artificial intelligence, rule-based expert system (AI system). In this study, the rules given in Chapter 3 of the AMA Guides to the Evaluation of Permanent Impairment (Third Edition) were used to develop such an AI system for the Apple Macintosh. The program applies the rules from the Guides in a consistent and systematic fashion. It is faster and less error-prone than the manual method, and the results have a higher degree of precision, since intermediate values are not truncated.

  17. Computer Series, 82. The Application of Expert Systems in the General Chemistry Laboratory.

    ERIC Educational Resources Information Center

    Settle, Frank A., Jr.

    1987-01-01

    Describes the construction of expert computer systems using artificial intelligence technology and commercially available software, known as an expert system shell. Provides two applications; a simple one, the identification of seven white substances, and a more complicated one involving the qualitative analysis of six metal ions. (TW)

  18. Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.

    ERIC Educational Resources Information Center

    Fox, Edward A.; Winett, Sheila G.

    1990-01-01

    Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…

  19. Hybrid Architectures and Their Impact on Intelligent Design

    NASA Technical Reports Server (NTRS)

    Kandel, Abe

    1996-01-01

    In this presentation we investigate a novel framework for the design of autonomous fuzzy intelligent systems. The system integrates the following modules into a single autonomous entity: (1) a fuzzy expert system; (2) artificial neural network; (3) genetic algorithm; and (4) case-base reasoning. We describe the integration of these units into one intelligent structure and discuss potential applications.

  20. Blindness in designing intelligent systems

    NASA Technical Reports Server (NTRS)

    Denning, Peter J.

    1988-01-01

    New investigations of the foundations of artificial intelligence are challenging the hypothesis that problem solving is the cornerstone of intelligence. New distinctions among three domains of concern for humans--description, action, and commitment--have revealed that the design process for programmable machines, such as expert systems, is based on descriptions of actions and induces blindness to nonanalytic action and commitment. Design processes focusing in the domain of description are likely to yield programs like burearcracies: rigid, obtuse, impersonal, and unable to adapt to changing circumstances. Systems that learn from their past actions, and systems that organize information for interpretation by human experts, are more likely to be successful in areas where expert systems have failed.

  1. Development of an intelligent hypertext system for wind tunnel testing

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.; Shi, George Z.; Steinle, Frank W.; Wu, Y. C. L. Susan; Hoyt, W. Andes

    1991-01-01

    This paper summarizes the results of a system utilizing artificial intelligence technology to improve the productivity of project engineers who conduct wind tunnel tests. The objective was to create an intelligent hypertext system which integrates a hypertext manual and expert system that stores experts' knowledge and experience. The preliminary (Phase I) effort implemented a prototype IHS module encompassing a portion of the manuals and knowledge used for wind tunnel testing. The effort successfully demonstrated the feasibility of the intelligent hypertext system concept. A module for the internal strain gage balance, implemented on both IBM-PC and Macintosh computers, is presented. A description of the Phase II effort is included.

  2. A/C Interface: Expert Systems: Part II.

    ERIC Educational Resources Information Center

    Dessy, Raymond E., Ed.

    1984-01-01

    Discusses working implementations of artificial intelligence systems for chemical laboratory applications. They include expert systems for liquid chromatography, spectral analysis, instrument control of a totally computerized triple-quadrupole mass spectrometer, and the determination of the mineral constituents of a rock sample given the powder…

  3. Computers Simulate Human Experts.

    ERIC Educational Resources Information Center

    Roberts, Steven K.

    1983-01-01

    Discusses recent progress in artificial intelligence in such narrowly defined areas as medical and electronic diagnosis. Also discusses use of expert systems, man-machine communication problems, novel programing environments (including comments on LISP and LISP machines), and types of knowledge used (factual, heuristic, and meta-knowledge). (JN)

  4. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1989-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

  5. Exodus - Distributed artificial intelligence for Shuttle firing rooms

    NASA Technical Reports Server (NTRS)

    Heard, Astrid E.

    1990-01-01

    This paper describes the Expert System for Operations Distributed Users (EXODUS), a knowledge-based artificial intelligence system developed for the four Firing Rooms at the Kennedy Space Center. EXODUS is used by the Shuttle engineers and test conductors to monitor and control the sequence of tasks required for processing and launching Shuttle vehicles. In this paper, attention is given to the goals and the design of EXODUS, the operational requirements, and the extensibility of the technology.

  6. Demonstrating artificial intelligence for space systems - Integration and project management issues

    NASA Technical Reports Server (NTRS)

    Hack, Edmund C.; Difilippo, Denise M.

    1990-01-01

    As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

  7. Microcomputer-Based Intelligent Tutoring Systems: An Assessment.

    ERIC Educational Resources Information Center

    Schaffer, John William

    Computer-assisted instruction, while familiar to most teachers, has failed to become an effective self-motivating instructional tool. Developments in artificial intelligence, however, have provided new and better tools for exploring human knowledge acquisition and utilization. Expert system technology represents one of the most promising of these…

  8. Intelligent Frameworks for Instructional Design.

    ERIC Educational Resources Information Center

    Spector, J. Michael; And Others

    Many researchers are attempting to develop automated instructional development systems to guide subject matter experts through the lengthy and difficult process of courseware development. Because the targeted users often lack instructional design expertise, a great deal of emphasis has been placed on the use of artificial intelligence (AI) to…

  9. Implementation of artificial intelligence rules in a data base management system

    NASA Technical Reports Server (NTRS)

    Feyock, S.

    1986-01-01

    The intelligent front end prototype was transformed into a RIM-integrated system. A RIM-based expert system was written which demonstrated the developed capability. The use of rules to produce extensibility of the intelligent front end, including the concept of demons and rule manipulation rules were investigated. Innovative approaches such as syntax programming were to be considered.

  10. Space station automation: the role of robotics and artificial intelligence (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Park, W. T.; Firschein, O.

    1985-12-01

    Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.

  11. Space Station Mission Planning System (MPS) development study. Volume 2

    NASA Technical Reports Server (NTRS)

    Klus, W. J.

    1987-01-01

    The process and existing software used for Spacelab payload mission planning were studied. A complete baseline definition of the Spacelab payload mission planning process was established, along with a definition of existing software capabilities for potential extrapolation to the Space Station. This information was used as a basis for defining system requirements to support Space Station mission planning. The Space Station mission planning concept was reviewed for the purpose of identifying areas where artificial intelligence concepts might offer substantially improved capability. Three specific artificial intelligence concepts were to be investigated for applicability: natural language interfaces; expert systems; and automatic programming. The advantages and disadvantages of interfacing an artificial intelligence language with existing FORTRAN programs or of converting totally to a new programming language were identified.

  12. Artificial intelligence in the materials processing laboratory

    NASA Technical Reports Server (NTRS)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys.

  13. Applications of artificial intelligence to scientific research

    NASA Technical Reports Server (NTRS)

    Prince, Mary Ellen

    1986-01-01

    Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

  14. Computer graphics testbed to simulate and test vision systems for space applications

    NASA Technical Reports Server (NTRS)

    Cheatham, John B.

    1991-01-01

    Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.

  15. Knowledge Engineering (Or, Catching Black Cats in Dark Rooms).

    ERIC Educational Resources Information Center

    Ruyle, Kim E.

    1993-01-01

    Discusses knowledge engineering, its relationship to artificial intelligence, and possible applications to developing expert systems, job aids, and technical training. The educational background of knowledge engineers is considered; the role of subject matter experts is described; and examples of flow charts, lists, and pictorial representations…

  16. Development of a Heuristic Knowledge Base for the Selection of Applicable or Relevant and Appropriate Environmental Requirements

    DTIC Science & Technology

    1992-09-01

    David King. Expert Systems: Artificial Intelligence in Bins. New York: John Wiley and Sons Inc., 1985. 10. Hayes-Roth, Frederick, Donald A. Waterman...Technology (AU), Wright-Patterson AFB, OH, July 1992. 26. Simmons, Asa B. and Steven G. Chappel. " Artificial Intelligence - Defini- tion and Practice," IEEE...information on treatment standards is through the publication of the CERCLA Compane With Other Laws Manual and the Co endium of CERCIA ARARs Fact Sheets

  17. Applications of Artificial Intelligence to the Strategic Defense Initiative’s Battle Management/Command and Control Objective.

    DTIC Science & Technology

    1985-09-01

    technology issue is expected to take years of research (20:11). According to Lt Gen James A. Abrahamson, director of the SDI organization heading up...from occurring (14:79). A Wqhite House Panel known as the (Dr. James ) Fletcher Defensive Technologies Study Group has pointed out that, in the past...Handbook of Artificial Intelligence. Volume I. Los Altos CA: WilliamKaufmann Inc., 1981. 5. Basden , Andrew. "On the Application of Expert Systems,N

  18. An Expert System For Tuning Particle-Beam Accelerators

    NASA Astrophysics Data System (ADS)

    Lager, Darrel L.; Brand, Hal R.; Maurer, William J.; Searfus, Robert M.; Hernandez, Jose E.

    1989-03-01

    We have developed a proof-of-concept prototype of an expert system for tuning particle beam accelerators. It is designed to function as an intelligent assistant for an operator. In its present form it implements the strategies and reasoning followed by the operator for steering through the beam transport section of the Advanced Test Accelerator at Lawrence Livermore Laboratory's Site 300. The system is implemented in the language LISP using the Artificial Intelligence concepts of frames, daemons, and a representation we developed called a Monitored Decision Script.

  19. Proceedings of the 1986 IEEE international conference on systems, man and cybernetics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1986-01-01

    This book presents the papers given at a conference on man-machine systems. Topics considered at the conference included neural model-based cognitive theory and engineering, user interfaces, adaptive and learning systems, human interaction with robotics, decision making, the testing and evaluation of expert systems, software development, international conflict resolution, intelligent interfaces, automation in man-machine system design aiding, knowledge acquisition in expert systems, advanced architectures for artificial intelligence, pattern recognition, knowledge bases, and machine vision.

  20. Proceedings of the international conference on cybernetics and societ

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1985-01-01

    This book presents the papers given at a conference on artificial intelligence, expert systems and knowledge bases. Topics considered at the conference included automating expert system development, modeling expert systems, causal maps, data covariances, robot vision, image processing, multiprocessors, parallel processing, VLSI structures, man-machine systems, human factors engineering, cognitive decision analysis, natural language, computerized control systems, and cybernetics.

  1. The Method of Immersion the Problem of Comparing Technical Objects in an Expert Shell in the Class of Artificial Intelligence Algorithms

    NASA Astrophysics Data System (ADS)

    Sergey Vasilievich, Buharin; Aleksandr Vladimirovich, Melnikov; Svetlana Nikolaevna, Chernyaeva; Lyudmila Anatolievna, Korobova

    2017-08-01

    The method of dip of the underlying computational problem of comparing technical object in an expert shell in the class of data mining methods is examined. An example of using the proposed method is given.

  2. A Reference and Referral System Using Expert System Techniques.

    ERIC Educational Resources Information Center

    Vickery, Alina; And Others

    1987-01-01

    Describes PLEXUS, an expert system for information retrieval related to gardening, designed at the University of London for use in public libraries. Focusing on the semantic problems encountered, methods used in artificial intelligence and information science to resolve them are discussed, including classification and facet analysis. (Author/LRW)

  3. Potential applications of expert systems and operations research to space station logistics functions

    NASA Technical Reports Server (NTRS)

    Lippiatt, Thomas F.; Waterman, Donald

    1985-01-01

    The applicability of operations research, artificial intelligence, and expert systems to logistics problems for the space station were assessed. Promising application areas were identified for space station logistics. A needs assessment is presented and a specific course of action in each area is suggested.

  4. The role of automation and artificial intelligence

    NASA Astrophysics Data System (ADS)

    Schappell, R. T.

    1983-07-01

    Consideration is given to emerging technologies that are not currently in common use, yet will be mature enough for implementation in a space station. Artificial intelligence (AI) will permit more autonomous operation and improve the man-machine interfaces. Technology goals include the development of expert systems, a natural language query system, automated planning systems, and AI image understanding systems. Intelligent robots and teleoperators will be needed, together with improved sensory systems for the robotics, housekeeping, vehicle control, and spacecraft housekeeping systems. Finally, NASA is developing the ROBSIM computer program to evaluate level of automation, perform parametric studies and error analyses, optimize trajectories and control systems, and assess AI technology.

  5. DOE Office of Scientific and Technical Information (OSTI.GOV)

    MacAllister, D.J.; Day, R.; McCormack, M.D.

    This paper gives an overview of a major integrated oil company`s experience with artificial intelligence (AI) over the last 5 years, with an emphasis on expert systems. The authors chronicle the development of an AI group, including details on development tool selection, project selection strategies, potential pitfalls, and descriptions of several completed expert systems. Small expert systems produced by teams of petroleum technology experts and experienced expert system developers that are focused in well-defined technical areas have produced substantial benefits and accelerated petroleum technology transfer.

  6. DAWN (Design Assistant Workstation) for advanced physical-chemical life support systems

    NASA Technical Reports Server (NTRS)

    Rudokas, Mary R.; Cantwell, Elizabeth R.; Robinson, Peter I.; Shenk, Timothy W.

    1989-01-01

    This paper reports the results of a project supported by the National Aeronautics and Space Administration, Office of Aeronautics and Space Technology (NASA-OAST) under the Advanced Life Support Development Program. It is an initial attempt to integrate artificial intelligence techniques (via expert systems) with conventional quantitative modeling tools for advanced physical-chemical life support systems. The addition of artificial intelligence techniques will assist the designer in the definition and simulation of loosely/well-defined life support processes/problems as well as assist in the capture of design knowledge, both quantitative and qualitative. Expert system and conventional modeling tools are integrated to provide a design workstation that assists the engineer/scientist in creating, evaluating, documenting and optimizing physical-chemical life support systems for short-term and extended duration missions.

  7. Development of a coupled expert system for the spacecraft attitude control problem

    NASA Technical Reports Server (NTRS)

    Kawamura, K.; Beale, G.; Schaffer, J.; Hsieh, B.-J.; Padalkar, S.; Rodriguezmoscoso, J.; Vinz, F.; Fernandez, K.

    1987-01-01

    A majority of the current expert systems focus on the symbolic-oriented logic and inference mechanisms of artificial intelligence (AI). Common rule-based systems employ empirical associations and are not well suited to deal with problems often arising in engineering. Described is a prototype expert system which combines both symbolic and numeric computing. The expert system's configuration is presented and its application to a spacecraft attitude control problem is discussed.

  8. Problem representation and variation in the forecasts of ’political experts’

    DTIC Science & Technology

    2001-06-01

    artificial intelligence classification of the themes that were used by the Presidential Commission on Women in Combat. Psychological constraints to...In contrast, controls for expert-novice differences is standard practice in psychology . Cognitive psychologists who have studied how experts and...participant=s Athink aloud@ analysis from Alevel of verbosity.@ By summarizing verbatim statements associated with free-hand cognitive diagrams it

  9. Conference on Space and Military Applications of Automation and Robotics

    NASA Technical Reports Server (NTRS)

    1988-01-01

    Topics addressed include: robotics; deployment strategies; artificial intelligence; expert systems; sensors and image processing; robotic systems; guidance, navigation, and control; aerospace and missile system manufacturing; and telerobotics.

  10. Artificial Intelligence in Sports Biomechanics: New Dawn or False Hope?

    PubMed Central

    Bartlett, Roger

    2006-01-01

    This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements (‘techniques’) and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key Points Expert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis. Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear. Other AI applications, including Evolutionary Computation, have received little attention. PMID:24357939

  11. Artificial intelligence in sports biomechanics: new dawn or false hope?

    PubMed

    Bartlett, Roger

    2006-12-15

    This article reviews developments in the use of Artificial Intelligence (AI) in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques') and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs) in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics. Key PointsExpert Systems remain almost unused in sports biomechanics, unlike in the similar discipline of gait analysis.Artificial Neural Networks, particularly Kohonen Maps, have been used, although their full value remains unclear.Other AI applications, including Evolutionary Computation, have received little attention.

  12. A Simulation of AI Programming Techniques in BASIC.

    ERIC Educational Resources Information Center

    Mandell, Alan

    1986-01-01

    Explains the functions of and the techniques employed in expert systems. Offers the program "The Periodic Table Expert," as a model for using artificial intelligence techniques in BASIC. Includes the program listing and directions for its use on: Tandy 1000, 1200, and 2000; IBM PC; PC Jr; TRS-80; and Apple computers. (ML)

  13. The role of networks and artificial intelligence in nanotechnology design and analysis.

    PubMed

    Hudson, D L; Cohen, M E

    2004-05-01

    Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.

  14. Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

  15. A brief history and technical review of the expert system research

    NASA Astrophysics Data System (ADS)

    Tan, Haocheng

    2017-09-01

    The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge. It is an important branch of artificial intelligence. In this paper, firstly, we briefly introduce the development and basic structure of the expert system. Then, from the perspective of the enabling technology, we classify the current expert systems and elaborate four expert systems: The Rule-Based Expert System, the Framework-Based Expert System, the Fuzzy Logic-Based Expert System and the Expert System Based on Neural Network.

  16. Software Analyzes Complex Systems in Real Time

    NASA Technical Reports Server (NTRS)

    2008-01-01

    Expert system software programs, also known as knowledge-based systems, are computer programs that emulate the knowledge and analytical skills of one or more human experts, related to a specific subject. SHINE (Spacecraft Health Inference Engine) is one such program, a software inference engine (expert system) designed by NASA for the purpose of monitoring, analyzing, and diagnosing both real-time and non-real-time systems. It was developed to meet many of the Agency s demanding and rigorous artificial intelligence goals for current and future needs. NASA developed the sophisticated and reusable software based on the experience and requirements of its Jet Propulsion Laboratory s (JPL) Artificial Intelligence Research Group in developing expert systems for space flight operations specifically, the diagnosis of spacecraft health. It was designed to be efficient enough to operate in demanding real time and in limited hardware environments, and to be utilized by non-expert systems applications written in conventional programming languages. The technology is currently used in several ongoing NASA applications, including the Mars Exploration Rovers and the Spacecraft Health Automatic Reasoning Pilot (SHARP) program for the diagnosis of telecommunication anomalies during the Neptune Voyager Encounter. It is also finding applications outside of the Space Agency.

  17. [Artificial intelligence in sleep analysis (ARTISANA)--modelling visual processes in sleep classification].

    PubMed

    Schwaibold, M; Schöller, B; Penzel, T; Bolz, A

    2001-05-01

    We describe a novel approach to the problem of automated sleep stage recognition. The ARTISANA algorithm mimics the behaviour of a human expert visually scoring sleep stages (Rechtschaffen and Kales classification). It comprises a number of interacting components that imitate the stepwise approach of the human expert, and artificial intelligence components. On the basis of parameters extracted at 1-s intervals from the signal curves, artificial neural networks recognize the incidence of typical patterns, e.g. delta activity or K complexes. This is followed by a rule interpretation stage that identifies the sleep stage with the aid of a neuro-fuzzy system while taking account of the context. Validation studies based on the records of 8 patients with obstructive sleep apnoea have confirmed the potential of this approach. Further features of the system include the transparency of the decision-taking process, and the flexibility of the option for expanding the system to cover new patterns and criteria.

  18. Cooperative analysis expert situation assessment research

    NASA Technical Reports Server (NTRS)

    Mccown, Michael G.

    1987-01-01

    For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described.

  19. AI Tools Bridge Technology Gap.

    ERIC Educational Resources Information Center

    Rauch-Hindin, Wendy

    1985-01-01

    This second part of a report on artificial intelligence focuses on the development of expert systems in a variety of applications, from engineering to science, and details expectations for implementation of these systems. (JN)

  20. Use of artificial intelligence in analytical systems for the clinical laboratory

    PubMed Central

    Truchaud, Alain; Ozawa, Kyoichi; Pardue, Harry; Schnipelsky, Paul

    1995-01-01

    The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system. In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories. It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories. PMID:18924784

  1. Artificial intelligence against breast cancer (A.N.N.E.S-B.C.-Project).

    PubMed

    Parmeggiani, Domenico; Avenia, Nicola; Sanguinetti, Alessandro; Ruggiero, Roberto; Docimo, Giovanni; Siciliano, Mattia; Ambrosino, Pasquale; Madonna, Imma; Peltrini, Roberto; Parmeggiani, Umberto

    2012-01-01

    Our preliminary study examined the development of an advanced innovative technology with the objectives of--developing methodologies and algorithms for a Artificial Neural Network (ANN) system, improving mammography and ultra-sonography images interpretation;--creating autonomous software as a diagnostic tool for the physicians, allowing the possibility for the advanced application of databases using Artificial Intelligence (Expert System). Since 2004 550 F patients over 40 yrs old were divided in two groups: 1) 310 pts underwent echo every 6 months and mammography every year by expert radiologists. 2) 240 pts had the same screening program and were also examined by our diagnosis software, developed with ANN-ES technology by the Engineering Aircraft Research Project team. The information was continually updated and returned to the Expert System, defining the principal rules of automatic diagnosis. In the second group we selected: Expert radiologist decision; ANN-ES decision; Expert radiologists with ANN-ES decision. The second group had significantly better diagnosis for cancer and better specificity for breast lesions risk as well as the highest percentage account when the radiologist's decision was helped by the ANN software. The ANN-ES group was able to select, by anamnestic, diagnostic and genetic means, 8 patients for prophylactic surgery, finding 4 cancers in a very early stage. Although it is only a preliminary study, this innovative diagnostic tool seems to provide better positive and negative predictive value in cancer diagnosis as well as in breast risk lesion identification.

  2. Development and Evaluation of an Adaptive Computerized Training System (ACTS). R&D Report 78-1.

    ERIC Educational Resources Information Center

    Knerr, Bruce W.; Nawrocki, Leon H.

    This report describes the development of a computer based system designed to train electronic troubleshooting procedures. The ACTS uses artificial intelligence techniques to develop models of student and expert troubleshooting behavior as they solve a series of troubleshooting problems on the system. Comparisons of the student and expert models…

  3. Expert systems research

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Duda, R.O.; Shortliffe, E.H.

    1983-04-15

    Artificial intelligence, long a topic of basic computer science research, is now being applied to problems of scientific, technical, and commercial interest. Some consultation programs although limited in versatility, have achieved levels of performance rivaling those of human experts. A collateral benefit of this work is the systematization of previously unformalized knowledge in areas such as medical diagnosis and geology. 30 references.

  4. Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

    PubMed

    Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

    2018-05-01

    A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

  5. Intelligent computer-aided training and tutoring

    NASA Technical Reports Server (NTRS)

    Loftin, R. Bowen; Savely, Robert T.

    1991-01-01

    Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

  6. Computer graphics testbed to simulate and test vision systems for space applications

    NASA Technical Reports Server (NTRS)

    Cheatham, John B.

    1991-01-01

    Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.

  7. DeepStack: Expert-level artificial intelligence in heads-up no-limit poker.

    PubMed

    Moravčík, Matej; Schmid, Martin; Burch, Neil; Lisý, Viliam; Morrill, Dustin; Bard, Nolan; Davis, Trevor; Waugh, Kevin; Johanson, Michael; Bowling, Michael

    2017-05-05

    Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect information. Poker, the quintessential game of imperfect information, is a long-standing challenge problem in artificial intelligence. We introduce DeepStack, an algorithm for imperfect-information settings. It combines recursive reasoning to handle information asymmetry, decomposition to focus computation on the relevant decision, and a form of intuition that is automatically learned from self-play using deep learning. In a study involving 44,000 hands of poker, DeepStack defeated, with statistical significance, professional poker players in heads-up no-limit Texas hold'em. The approach is theoretically sound and is shown to produce strategies that are more difficult to exploit than prior approaches. Copyright © 2017, American Association for the Advancement of Science.

  8. Northeast Artificial Intelligence Consortium annual report. Volume 2. 1988. Discussing, using, and recognizing plans (NLP). Interim report, January-December 1988

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shapiro, S.C.; Woolf, B.

    The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the Office of Scientific Research. Its purpose is to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress that has been made in the fourth year of the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge base maintenance, hardwaremore » architectures for very large systems, knowledge-based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topic for this volume is the recognition of plans expressed in natural language, followed by their discussion and use.« less

  9. Fourth Conference on Artificial Intelligence for Space Applications

    NASA Technical Reports Server (NTRS)

    Odell, Stephen L. (Compiler); Denton, Judith S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

  10. Epistasis analysis using artificial intelligence.

    PubMed

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

  11. An advanced artificial intelligence tool for menu design.

    PubMed

    Khan, Abdus Salam; Hoffmann, Achim

    2003-01-01

    The computer-assisted menu design still remains a difficult task. Usually knowledge that aids in menu design by a computer is hard-coded and because of that a computerised menu planner cannot handle the menu design problem for an unanticipated client. To address this problem we developed a menu design tool, MIKAS (menu construction using incremental knowledge acquisition system), an artificial intelligence system that allows the incremental development of a knowledge-base for menu design. We allow an incremental knowledge acquisition process in which the expert is only required to provide hints to the system in the context of actual problem instances during menu design using menus stored in a so-called Case Base. Our system incorporates Case-Based Reasoning (CBR), an Artificial Intelligence (AI) technique developed to mimic human problem solving behaviour. Ripple Down Rules (RDR) are a proven technique for the acquisition of classification knowledge from expert directly while they are using the system, which complement CBR in a very fruitful way. This combination allows the incremental improvement of the menu design system while it is already in routine use. We believe MIKAS allows better dietary practice by leveraging a dietitian's skills and expertise. As such MIKAS has the potential to be helpful for any institution where dietary advice is practised.

  12. Formal verification of AI software

    NASA Technical Reports Server (NTRS)

    Rushby, John; Whitehurst, R. Alan

    1989-01-01

    The application of formal verification techniques to Artificial Intelligence (AI) software, particularly expert systems, is investigated. Constraint satisfaction and model inversion are identified as two formal specification paradigms for different classes of expert systems. A formal definition of consistency is developed, and the notion of approximate semantics is introduced. Examples are given of how these ideas can be applied in both declarative and imperative forms.

  13. Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

    NASA Astrophysics Data System (ADS)

    Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

    2016-06-01

    With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

  14. PC graphics generation and management tool for real-time applications

    NASA Technical Reports Server (NTRS)

    Truong, Long V.

    1992-01-01

    A graphics tool was designed and developed for easy generation and management of personal computer graphics. It also provides methods and 'run-time' software for many common artificial intelligence (AI) or expert system (ES) applications.

  15. An integrated knowledge system for wind tunnel testing - Project Engineers' Intelligent Assistant

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.; Shi, George Z.; Hoyt, W. A.; Steinle, Frank W., Jr.

    1993-01-01

    The Project Engineers' Intelligent Assistant (PEIA) is an integrated knowledge system developed using artificial intelligence technology, including hypertext, expert systems, and dynamic user interfaces. This system integrates documents, engineering codes, databases, and knowledge from domain experts into an enriched hypermedia environment and was designed to assist project engineers in planning and conducting wind tunnel tests. PEIA is a modular system which consists of an intelligent user-interface, seven modules and an integrated tool facility. Hypermedia technology is discussed and the seven PEIA modules are described. System maintenance and updating is very easy due to the modular structure and the integrated tool facility provides user access to commercial software shells for documentation, reporting, or database updating. PEIA is expected to provide project engineers with technical information, increase efficiency and productivity, and provide a realistic tool for personnel training.

  16. A Collection of Technical Studies Completed for the Computer-Aided Acquisition and Logistic Support (CALS) Program Fiscal Year 1988. Volume 1. Text, Security and Data Management

    DTIC Science & Technology

    1991-03-01

    management methodologies claim to be "expert systems" with security intelligence built into them to I derive a body of both facts and speculative data ... Data Administration considerations . III -21 IV. ARTIFICIAL INTELLIGENCE . .. .. .. . .. IV - 1 A. Description of Technologies . . . . . .. IV - 1 1...as intelligent gateways, wide area networks, and distributed databases for the distribution of logistics products. The integrity of CALS data and the

  17. Object-oriented knowledge representation for expert systems

    NASA Technical Reports Server (NTRS)

    Scott, Stephen L.

    1991-01-01

    Object oriented techniques have generated considerable interest in the Artificial Intelligence (AI) community in recent years. This paper discusses an approach for representing expert system knowledge using classes, objects, and message passing. The implementation is in version 4.3 of NASA's C Language Integrated Production System (CLIPS), an expert system tool that does not provide direct support for object oriented design. The method uses programmer imposed conventions and keywords to structure facts, and rules to provide object oriented capabilities.

  18. An Assessment of Artificial Intelligence and Expert Systems Technology for Application to Management of Cockpit Systems.

    DTIC Science & Technology

    1986-09-01

    expert systems will certainly find management applications a fertile field for research and practice." Elam and Henderson (1983) also discuss concepts ...Shortliffe, E.H. (1983). Expert systems research. Science, 220, 261-268, 15 Apr. * Elam, J.J. and Henderson, J.C. (1983). Knowledge engineering concepts for...Symposium on Aerospace and Electronic Systems, Advanced Concepts and Pioneering Perspectives, Dayton, OH, Sect 4, (pp 1-9), Nov 14-15. Dreyfus, H

  19. A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

    PubMed

    Sokol, R J; Chik, L

    1988-01-01

    Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

  20. Development of expert systems for modeling of technological process of pressure casting on the basis of artificial intelligence

    NASA Astrophysics Data System (ADS)

    Gavarieva, K. N.; Simonova, L. A.; Pankratov, D. L.; Gavariev, R. V.

    2017-09-01

    In article the main component of expert system of process of casting under pressure which consists of algorithms, united in logical models is considered. The characteristics of system showing data on a condition of an object of management are described. A number of logically interconnected steps allowing to increase quality of the received castings is developed

  1. The Effects of Word Processing Software on User Satisfaction: An Empirical Study of Micro, Mini, and Mainframe Computers Using an Interactive Artificial Intelligence Expert-System.

    ERIC Educational Resources Information Center

    Rushinek, Avi; Rushinek, Sara

    1984-01-01

    Describes results of a system rating study in which users responded to WPS (word processing software) questions. Study objectives were data collection and evaluation of variables; statistical quantification of WPS's contribution (along with other variables) to user satisfaction; design of an expert system to evaluate WPS; and database update and…

  2. Expert system technology

    NASA Technical Reports Server (NTRS)

    Prince, Mary Ellen

    1987-01-01

    The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

  3. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  4. Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

    PubMed

    Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

    2012-01-01

    In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

  5. Genie: An Inference Engine with Applications to Vulnerability Analysis.

    DTIC Science & Technology

    1986-06-01

    Stanford Artifcial intelligence Laboratory, 1976. 15 D. A. Waterman and F. Hayes-Roth, eds. Pattern-Directed Inference Systems. Academic Press, Inc...Continue an reverse aide It nlecessary mid Identify by block rnmbor) ; f Expert Systems Artificial Intelligence % Vulnerability Analysis Knowledge...deduction it is used wherever possible in data -driven mode (forward chaining). Production rules - JIM 0 g79OOFMV55@S I INCLASSTpnF SECURITY CLASSIFICATION OF

  6. The ZOG Technology Demonstration Project: A System Evaluation of USS CARL VINSON (CVN 70)

    DTIC Science & Technology

    1984-12-01

    part of a larger project involving development of a wide range of computer technologies, including artifcial intelligence and a long-range computer...shipboard manage- ment, aircraft management, expert systems, menu selection, man- machine interface, artificial intelligence , automation; shipboard It AWM...functions, planning, evaluation, training, hierarchical data bases The objective of this project was to conduct an evaluation of ZOG, a general purpose

  7. Nickel cadmium battery expert system

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The applicability of artificial intelligence methodologies for the automation of energy storage management, in this case, nickel cadmium batteries, is demonstrated. With the Hubble Space Telescope Electrical Power System (HST/EPS) testbed as the application domain, an expert system was developed which incorporates the physical characterization of the EPS, in particular, the nickel cadmium batteries, as well as the human's operational knowledge. The expert system returns not only fault diagnostics but also status and advice along with justifications and explanations in the form of decision support.

  8. An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975

    PubMed Central

    2015-01-01

    Summary The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970’s drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford’s SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975. PMID:26123911

  9. Artificial intelligence-assisted occupational lung disease diagnosis.

    PubMed

    Harber, P; McCoy, J M; Howard, K; Greer, D; Luo, J

    1991-08-01

    An artificial intelligence expert-based system for facilitating the clinical recognition of occupational and environmental factors in lung disease has been developed in a pilot fashion. It utilizes a knowledge representation scheme to capture relevant clinical knowledge into structures about specific objects (jobs, diseases, etc) and pairwise relations between objects. Quantifiers describe both the closeness of association and risk, as well as the degree of belief in the validity of a fact. An independent inference engine utilizes the knowledge, combining likelihoods and uncertainties to achieve estimates of likelihood factors for specific paths from work to illness. The system creates a series of "paths," linking work activities to disease outcomes. One path links a single period of work to a single possible disease outcome. In a preliminary trial, the number of "paths" from job to possible disease averaged 18 per subject in a general population and averaged 25 per subject in an asthmatic population. Artificial intelligence methods hold promise in the future to facilitate diagnosis in pulmonary and occupational medicine.

  10. An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975.

    PubMed

    Kulikowski, C A

    2015-08-13

    The first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970's drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford's SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975.

  11. Recent developments of artificial intelligence in drying of fresh food: A review.

    PubMed

    Sun, Qing; Zhang, Min; Mujumdar, Arun S

    2018-03-01

    Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

  12. Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.

    PubMed

    Senders, Joeky T; Arnaout, Omar; Karhade, Aditya V; Dasenbrock, Hormuzdiyar H; Gormley, William B; Broekman, Marike L; Smith, Timothy R

    2017-09-07

    Machine learning (ML) is a domain of artificial intelligence that allows computer algorithms to learn from experience without being explicitly programmed. To summarize neurosurgical applications of ML where it has been compared to clinical expertise, here referred to as "natural intelligence." A systematic search was performed in the PubMed and Embase databases as of August 2016 to review all studies comparing the performance of various ML approaches with that of clinical experts in neurosurgical literature. Twenty-three studies were identified that used ML algorithms for diagnosis, presurgical planning, or outcome prediction in neurosurgical patients. Compared to clinical experts, ML models demonstrated a median absolute improvement in accuracy and area under the receiver operating curve of 13% (interquartile range 4-21%) and 0.14 (interquartile range 0.07-0.21), respectively. In 29 (58%) of the 50 outcome measures for which a P -value was provided or calculated, ML models outperformed clinical experts ( P < .05). In 18 of 50 (36%), no difference was seen between ML and expert performance ( P > .05), while in 3 of 50 (6%) clinical experts outperformed ML models ( P < .05). All 4 studies that compared clinicians assisted by ML models vs clinicians alone demonstrated a better performance in the first group. We conclude that ML models have the potential to augment the decision-making capacity of clinicians in neurosurgical applications; however, significant hurdles remain associated with creating, validating, and deploying ML models in the clinical setting. Shifting from the preconceptions of a human-vs-machine to a human-and-machine paradigm could be essential to overcome these hurdles. Published by Oxford University Press on behalf of Congress of Neurological Surgeons 2017.

  13. Thoughts on Expertise.

    ERIC Educational Resources Information Center

    Glaser, Robert

    This paper briefly reviews research on tasks in knowledge-rich domains including developmental studies, work in artificial intelligence, studies of expert/novice problem solving, and information processing analysis of aptitude test tasks that have provided increased understanding of the nature of expertise. Particularly evident is the finding that…

  14. Expert Causal Reasoning and Explanation.

    ERIC Educational Resources Information Center

    Kuipers, Benjamin

    The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

  15. Living Design Memory: Framework, Implementation, Lessons Learned.

    ERIC Educational Resources Information Center

    Terveen, Loren G.; And Others

    1995-01-01

    Discusses large-scale software development and describes the development of the Designer Assistant to improve software development effectiveness. Highlights include the knowledge management problem; related work, including artificial intelligence and expert systems, software process modeling research, and other approaches to organizational memory;…

  16. Rocky Mountain High-Tech: LITA's Denver Conference.

    ERIC Educational Resources Information Center

    Flagg, Gordon

    1992-01-01

    Reports on the third national conference of the American Library Association's Library and Information Technology Association, which was held September 13-16, 1992, in Denver, Colorado. Program highlights are summarized, including virtual communities, virtual reality, the electronic library, artificial intelligence and expert-systems, navigating…

  17. The Roles of the Future Library.

    ERIC Educational Resources Information Center

    Murr, Lawrence E.; Williams, James B.

    1987-01-01

    Discusses emerging roles for the library and librarian, including services in the following areas: (1) special collection management and reference; (2) information systems; (3) expert systems; (4) electronic publishing; (5) telecommunications networking; and (6) computer support. The technologies of artificial intelligence, graphic imaging,…

  18. Progress towards autonomous, intelligent systems

    NASA Technical Reports Server (NTRS)

    Lum, Henry; Heer, Ewald

    1987-01-01

    An aggressive program has been initiated to develop, integrate, and implement autonomous systems technologies starting with today's expert systems and evolving to autonomous, intelligent systems by the end of the 1990s. This program includes core technology developments and demonstration projects for technology evaluation and validation. This paper discusses key operational frameworks in the content of systems autonomy applications and then identifies major technological challenges, primarily in artificial intelligence areas. Program content and progress made towards critical technologies and demonstrations that have been initiated to achieve the required future capabilities in the year 2000 era are discussed.

  19. On the use of multi-agent systems for the monitoring of industrial systems

    NASA Astrophysics Data System (ADS)

    Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil

    2016-03-01

    The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

  20. Proceedings of the Air Force Forum for Intelligent Tutoring Systems

    DTIC Science & Technology

    1989-04-01

    interface help the students find facts? I recently developed an expert system that is used at the JFK Airport to help workers assign incoming planes to...of their errors and to make comparisons with optimal solution paths. Chapters 2, and 5 BIP, BIP II: Basic Instructional Program BIP applied knowledge...OFFICE SYMBOL 7a NAME OF MONITORING ORGANIZATION Center for Applied Artificial (If applicable) Training Systems Division Intelligence 1 6. ADDRESS (City

  1. University of Tennessee Center for Space Transportation and Applied Research (CSTAR)

    NASA Astrophysics Data System (ADS)

    1995-10-01

    The Center for Space Transportation and Applied Research had projects with space applications in six major areas: laser materials processing, artificial intelligence/expert systems, space transportation, computational methods, chemical propulsion, and electric propulsion. The closeout status of all these projects is addressed.

  2. First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

    NASA Technical Reports Server (NTRS)

    Griffin, Sandy (Editor)

    1987-01-01

    Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.

  3. University of Tennessee Center for Space Transportation and Applied Research (CSTAR)

    NASA Technical Reports Server (NTRS)

    1995-01-01

    The Center for Space Transportation and Applied Research had projects with space applications in six major areas: laser materials processing, artificial intelligence/expert systems, space transportation, computational methods, chemical propulsion, and electric propulsion. The closeout status of all these projects is addressed.

  4. Knowledge Gateways: The Building Blocks.

    ERIC Educational Resources Information Center

    Hawkins, Donald T.; And Others

    1988-01-01

    Discusses the need for knowledge gateway systems to provide access to scattered information and the use of technologies in gateway building, including artificial intelligence and expert systems, networking, online retrieval systems, optical storage, and natural language processing. The status of four existing gateways is described. (20 references)…

  5. Knowledge Representation: A Brief Review.

    ERIC Educational Resources Information Center

    Vickery, B. C.

    1986-01-01

    Reviews different structures and techniques of knowledge representation: structure of database records and files, data structures in computer programming, syntatic and semantic structure of natural language, knowledge representation in artificial intelligence, and models of human memory. A prototype expert system that makes use of some of these…

  6. The potential of expert systems for remote sensing application

    NASA Technical Reports Server (NTRS)

    Mooneyhan, D. W.

    1983-01-01

    An overview of the status and potential of artificial intelligence-driven expert systems in the role of image data analysis is presented. An expert system is defined and its structure is summarized. Three such systems designed for image interpretation are outlined. The use of an expert system to detect changes on the earth's surface is discussed, and the components of a knowledge-based image interpretation system and their make-up are outlined. An example of how such a system should work for an area in the tropics where deforestation has occurred is presented as a sequence of situation/action decisions.

  7. Using a CLIPS expert system to automatically manage TCP/IP networks and their components

    NASA Technical Reports Server (NTRS)

    Faul, Ben M.

    1991-01-01

    A expert system that can directly manage networks components on a Transmission Control Protocol/Internet Protocol (TCP/IP) network is described. Previous expert systems for managing networks have focused on managing network faults after they occur. However, this proactive expert system can monitor and control network components in near real time. The ability to directly manage network elements from the C Language Integrated Production System (CLIPS) is accomplished by the integration of the Simple Network Management Protocol (SNMP) and a Abstract Syntax Notation (ASN) parser into the CLIPS artificial intelligence language.

  8. An overview of expert systems. [artificial intelligence

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1982-01-01

    An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

  9. Benchmarking expert system tools

    NASA Technical Reports Server (NTRS)

    Riley, Gary

    1988-01-01

    As part of its evaluation of new technologies, the Artificial Intelligence Section of the Mission Planning and Analysis Div. at NASA-Johnson has made timing tests of several expert system building tools. Among the production systems tested were Automated Reasoning Tool, several versions of OPS5, and CLIPS (C Language Integrated Production System), an expert system builder developed by the AI section. Also included in the test were a Zetalisp version of the benchmark along with four versions of the benchmark written in Knowledge Engineering Environment, an object oriented, frame based expert system tool. The benchmarks used for testing are studied.

  10. A Distributed Artificial Intelligence Approach To Object Identification And Classification

    NASA Astrophysics Data System (ADS)

    Sikka, Digvijay I.; Varshney, Pramod K.; Vannicola, Vincent C.

    1989-09-01

    This paper presents an application of Distributed Artificial Intelligence (DAI) tools to the data fusion and classification problem. Our approach is to use a blackboard for information management and hypothe-ses formulation. The blackboard is used by the knowledge sources (KSs) for sharing information and posting their hypotheses on, just as experts sitting around a round table would do. The present simulation performs classification of an Aircraft(AC), after identifying it by its features, into disjoint sets (object classes) comprising of the five commercial ACs; Boeing 747, Boeing 707, DC10, Concord and Boeing 727. A situation data base is characterized by experimental data available from the three levels of expert reasoning. Ohio State University ElectroScience Laboratory provided this experimental data. To validate the architecture presented, we employ two KSs for modeling the sensors, aspect angle polarization feature and the ellipticity data. The system has been implemented on Symbolics 3645, under Genera 7.1, in Common LISP.

  11. Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

    NASA Astrophysics Data System (ADS)

    Szatkowski, Gerard P.; Schultz, Roger

    1988-11-01

    The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

  12. Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

    NASA Technical Reports Server (NTRS)

    Szatkowski, Gerard P.; Schultz, Roger

    1988-01-01

    The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

  13. Artificial intelligence within the chemical laboratory.

    PubMed

    Winkel, P

    1994-01-01

    Various techniques within the area of artificial intelligence such as expert systems and neural networks may play a role during the problem-solving processes within the clinical biochemical laboratory. Neural network analysis provides a non-algorithmic approach to information processing, which results in the ability of the computer to form associations and to recognize patterns or classes among data. It belongs to the machine learning techniques which also include probabilistic techniques such as discriminant function analysis and logistic regression and information theoretical techniques. These techniques may be used to extract knowledge from example patients to optimize decision limits and identify clinically important laboratory quantities. An expert system may be defined as a computer program that can give advice in a well-defined area of expertise and is able to explain its reasoning. Declarative knowledge consists of statements about logical or empirical relationships between things. Expert systems typically separate declarative knowledge residing in a knowledge base from the inference engine: an algorithm that dynamically directs and controls the system when it searches its knowledge base. A tool is an expert system without a knowledge base. The developer of an expert system uses a tool by entering knowledge into the system. Many, if not the majority of problems encountered at the laboratory level are procedural. A problem is procedural if it is possible to write up a step-by-step description of the expert's work or if it can be represented by a decision tree. To solve problems of this type only small expert system tools and/or conventional programming are required.(ABSTRACT TRUNCATED AT 250 WORDS)

  14. [Development and application of a web-based expert system using artificial intelligence for management of mental health by Korean emigrants].

    PubMed

    Bae, Jeongyee

    2013-04-01

    The purpose of this project was to develop an international web-based expert system using principals of artificial intelligence and user-centered design for management of mental health by Korean emigrants. Using this system, anyone can access the system via computer access to the web. Our design process utilized principles of user-centered design with 4 phases: needs assessment, analysis, design/development/testing, and application release. A survey was done with 3,235 Korean emigrants. Focus group interviews were also conducted. Survey and analysis results guided the design of the web-based expert system. With this system, anyone can check their mental health status by themselves using a personal computer. The system analyzes facts based on answers to automated questions, and suggests solutions accordingly. A history tracking mechanism enables monitoring and future analysis. In addition, this system will include intervention programs to promote mental health status. This system is interactive and accessible to anyone in the world. It is expected that this management system will contribute to Korean emigrants' mental health promotion and allow researchers and professionals to share information on mental health.

  15. Accelerating artificial intelligence with reconfigurable computing

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radoslaw

    Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

  16. The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Colombano, Silvano

    2000-01-01

    There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

  17. A scheduling and diagnostic system for scientific satellite GEOTAIL using expert system

    NASA Technical Reports Server (NTRS)

    Nakatani, I; Hashimoto, M.; Mukai, T.; Obara, T.; Nishigori, N.

    1994-01-01

    The Intelligent Satellite Control Software (ISACS) for the geoMagnetic tail observation satellite named GEOTAIL (launched in July 1992) has been successfully developed. ISACS has made it possible by applying Artificial Intelligence (AI) technology including an expert system to autonomously generate a tracking schedule, which originally used to be conducted manually. Using ISACS, a satellite operator can generate a maximum four day period of stored command stream autonomously and can easily confirm its safety. The ISACS system has another function -- to diagnose satellite troubles and to suggest necessary remedies. The workload of satellite operators has drastically been reduced since ISACS has been introduced into the operations of GEOTAIL.

  18. Third Annual Workshop on Space Operations Automation and Robotics (SOAR 1989)

    NASA Technical Reports Server (NTRS)

    Griffin, Sandy (Editor)

    1990-01-01

    Papers presented at the Third Annual Workshop on Space Operations Automation and Robotics (SOAR '89), hosted by the NASA Lyndon B. Johnson Space Center at Houston, Texas, on July 25 to 27, 1989, are given. Approximately 100 technical papers were presented by experts from NASA, the USAF, universities, and technical companies. Also held were panel discussions on Air Force/NASA Artificial Intelligence Overview and Expert System Verification and Validation.

  19. Handbook for Operating the OWLKNEST Technology

    DTIC Science & Technology

    1992-06-01

    D . A. (Ed.). (1988). Expert systems [Special issue]. Human Factors, 30(4), 377-443. Byers, J . C., Hill, S. G., Zaklad, A. L., & Christ, R. E. (1989...Sons. Harmon, P., & King, D . (1985). Expert systems: Artificial intelligence in business. New York, NY: John Wiley & Sons. Hill, S. G., Byers, J . C...Plamondon, B. D ., Linton, P. M., Wierwille, W. W., Zaklad, A. L., Bittner, A. C., Jr., & Wherry, R. J ., Jr. (1989). Operator workload: Comprehensive

  20. Engineering monitoring expert system's developer

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.

    1991-01-01

    This research project is designed to apply artificial intelligence technology including expert systems, dynamic interface of neural networks, and hypertext to construct an expert system developer. The developer environment is specifically suited to building expert systems which monitor the performance of ground support equipment for propulsion systems and testing facilities. The expert system developer, through the use of a graphics interface and a rule network, will be transparent to the user during rule constructing and data scanning of the knowledge base. The project will result in a software system that allows its user to build specific monitoring type expert systems which monitor various equipments used for propulsion systems or ground testing facilities and accrues system performance information in a dynamic knowledge base.

  1. Expert Systems Based Clinical Assessment and Tutorial Project.

    ERIC Educational Resources Information Center

    Papa, Frank; Shores, Jay

    This project at the Texas College of Osteopathic Medicine (Fort Worth) evaluated the use of an artificial-intelligence-derived measure, "Knowledge-Based Inference Tool" (KBIT), as the basis for assessing medical students' diagnostic capabilities and designing instruction to improve diagnostic skills. The instrument was designed to…

  2. Rule-Based Relaxation of Reference Identification Failures. Technical Report No. 396.

    ERIC Educational Resources Information Center

    Goodman, Bradley A.

    In a step toward creating a robust natural language understanding system which detects and avoids miscommunication, this artificial intelligence research report provides a taxonomy of miscommunication problems that arise in expert-apprentice dialogues (including misunderstandings, wrong communication, and bad analogies), and proposes a flexible…

  3. TDAS: The Thermal Expert System (TEXSYS) data acquisition system

    NASA Technical Reports Server (NTRS)

    Hack, Edmund C.; Healey, Kathleen J.

    1987-01-01

    As part of the NASA Systems Autonomy Demonstration Project, a thermal expert system (TEXSYS) is being developed. TEXSYS combines a fast real time control system, a sophisticated human interface for the user and several distinct artificial intelligence techniques in one system. TEXSYS is to provide real time control, operations advice and fault detection, isolation and recovery capabilities for the space station Thermal Test Bed (TTB). TEXSYS will be integrated with the TTB and act as an intelligent assistant to thermal engineers conducting TTB tests and experiments. The results are presented from connecting the real time controller to the knowledge based system thereby creating an integrated system. Special attention will be paid to the problem of filtering and interpreting the raw, real time data and placing the important values into the knowledge base of the expert system.

  4. Empirical Demonstration of Isoperformance Methodology Preparatory of an Interactive Expert Computerized Decision Aid

    DTIC Science & Technology

    1988-11-01

    after modest amounts of 7 practi.ce. Moreover, the advant.ages of display aiding (e.g., Smith & Kennedy, 1976) or artificial intelligence may be largely...team performance in tanks is largely a function of the intelligence of the tank commmander (Wallace, 1932). In summary, individual differences such as...versus small CRT screen), and training on a videogame task which simulated a remotely piloted vehicle. This study was successful as an isoperformance

  5. Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

    PubMed

    Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

    2018-02-01

    Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising approaches for the prescription and monitoring of hemodialysis therapy. Current dialysis machines are continuously improving due to innovative technological developments, but patient safety is still a key challenge. Real-time monitoring systems, coupled with automatic instantaneous biofeedback, will allow changing dialysis prescriptions continuously. The integration of vital sign monitoring with dialysis parameters will produce large data sets that will require the use of data analysis techniques, possibly from the area of machine learning, in order to make better decisions and increase the safety of patients.

  6. An overview of the program to place advanced automation and robotics on the Space Station

    NASA Technical Reports Server (NTRS)

    Heydorn, Richard P.

    1987-01-01

    The preliminary design phase of the Space Station has uncovered a large number of potential uses of automation and robotics, most of which deal with the assembly and operation of the Station. If NASA were to vigorously push automation and robotics concepts in the design, the Station crew would probably be free to spend a substantial portion of time on payload activities. However, at this point NASA has taken a conservative attitude toward automation and robotics. For example, the belief is that robotics should evolve through telerobotics and that uses of artificial intelligence should be initially used in an advisory capacity. This conservativeness is in part due to the new and untested nature of automation and robotics; but, it is also due to emphases plased on designing the Station to the so-called upfront cost without thoroughly understanding the life cycle cost. Presumably automation and robotics has a tendency to increase the initial cost of the Space Station but could substantially reduce the life cycle cost. To insure that NASA will include some form of robotic capability, Congress directed to set aside funding. While this stimulates the development of robotics, it does not necessarily stimulate uses of artificial intelligence. However, since the initial development costs of some forms of artificial intelligence, such as expert systems, are in general lower than they are for robotics one is likely to see several expert systems being used on the Station.

  7. Testing expert systems

    NASA Technical Reports Server (NTRS)

    Chang, C. L.; Stachowitz, R. A.

    1988-01-01

    Software quality is of primary concern in all large-scale expert system development efforts. Building appropriate validation and test tools for ensuring software reliability of expert systems is therefore required. The Expert Systems Validation Associate (EVA) is a validation system under development at the Lockheed Artificial Intelligence Center. EVA provides a wide range of validation and test tools to check correctness, consistency, and completeness of an expert system. Testing a major function of EVA. It means executing an expert system with test cases with the intent of finding errors. In this paper, we describe many different types of testing such as function-based testing, structure-based testing, and data-based testing. We describe how appropriate test cases may be selected in order to perform good and thorough testing of an expert system.

  8. Use of artificial intelligence in supervisory control

    NASA Technical Reports Server (NTRS)

    Cohen, Aaron; Erickson, Jon D.

    1989-01-01

    Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

  9. Communications and control for electric power systems: Power system stability applications of artificial neural networks

    NASA Technical Reports Server (NTRS)

    Toomarian, N.; Kirkham, Harold

    1994-01-01

    This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

  10. Knowledge Engineering: The Interplay between Information and Historical Sciences in the Study of Change.

    ERIC Educational Resources Information Center

    McCrank, Lawrence J.

    1992-01-01

    Discusses trends in the fields of knowledge engineering and historical sciences to speculate about possibilities of converging interests and applications. Topics addressed include artificial intelligence and expert systems; the history of information science; history as a related field; historians as information scientists; multidisciplinary…

  11. Artificial intelligence expert systems with neural network machine learning may assist decision-making for extractions in orthodontic treatment planning.

    PubMed

    Takada, Kenji

    2016-09-01

    New approach for the diagnosis of extractions with neural network machine learning. Seok-Ki Jung and Tae-Woo Kim. Am J Orthod Dentofacial Orthop 2016;149:127-33. Not reported. Mathematical modeling. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

  13. A new intelligent electronic nose system for measuring and analysing livestock and poultry farm odours.

    PubMed

    Pan, Leilei; Yang, Simon X

    2007-12-01

    This paper introduces a new portable intelligent electronic nose system developed especially for measuring and analysing livestock and poultry farm odours. It can be used in both laboratory and field. The sensor array of the proposed electronic nose consists of 14 gas sensors, a humidity sensor, and a temperature sensor. The gas sensors were especially selected for the main compounds from the livestock farm odours. An expert system called "Odour Expert" was developed to support researchers' and farmers' decision making on odour control strategies for livestock and poultry operations. "Odour Expert" utilises several advanced artificial intelligence technologies tailored to livestock and poultry farm odours. It can provide more advanced odour analysis than existing commercially available products. In addition, a rank of odour generation factors is provided, which refines the focus of odour control research. Field experiments were conducted downwind from the barns on 14 livestock and poultry farms. Experimental results show that the predicted odour strengths by the electronic nose yield higher consistency in comparison to the perceived odour intensity by human panel. The "Odour Expert" is a useful tool for assisting farmers' odour management practises.

  14. Progress and challenges in the application of artificial intelligence to computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Andrews, Alison E.

    1987-01-01

    An approach to analyzing CFD knowledge-based systems is proposed which is based, in part, on the concept of knowledge-level analysis. Consideration is given to the expert cooling fan design system, the PAN AIR knowledge system, grid adaptation, and expert zonal grid generation. These AI/CFD systems demonstrate that current AI technology can be successfully applied to well-formulated problems that are solved by means of classification or selection of preenumerated solutions.

  15. Neural network expert system for X-ray analysis of welded joints

    NASA Astrophysics Data System (ADS)

    Kozlov, V. V.; Lapik, N. V.; Popova, N. V.

    2018-03-01

    The use of intelligent technologies for the automated analysis of product quality is one of the main trends in modern machine building. At the same time, rapid development in various spheres of human activity is experienced by methods associated with the use of artificial neural networks, as the basis for building automated intelligent diagnostic systems. Technologies of machine vision allow one to effectively detect the presence of certain regularities in the analyzed designation, including defects of welded joints according to radiography data.

  16. Artificial intelligence applications in space and SDI: A survey

    NASA Technical Reports Server (NTRS)

    Fiala, Harvey E.

    1988-01-01

    The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI.

  17. Representing Learning With Graphical Models

    NASA Technical Reports Server (NTRS)

    Buntine, Wray L.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    Probabilistic graphical models are being used widely in artificial intelligence, for instance, in diagnosis and expert systems, as a unified qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several fields including artificial intelligence, decision theory and statistics, and provides an important bridge between these communities. This paper shows by way of example that these models can be extended to machine learning, neural networks and knowledge discovery by representing the notion of a sample on the graphical model. Not only does this allow a flexible variety of learning problems to be represented, it also provides the means for representing the goal of learning and opens the way for the automatic development of learning algorithms from specifications.

  18. An intercomparison of artificial intelligence approaches for polar scene identification

    NASA Technical Reports Server (NTRS)

    Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

    1993-01-01

    The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

  19. An efficient representation of spatial information for expert reasoning in robotic vehicles

    NASA Technical Reports Server (NTRS)

    Scott, Steven; Interrante, Mark

    1987-01-01

    The previous generation of robotic vehicles and drones was designed for a specific task, with limited flexibility in executing their mission. This limited flexibility arises because the robotic vehicles do not possess the intelligence and knowledge upon which to make significant tactical decisions. Current development of robotic vehicles is toward increased intelligence and capabilities, adapting to a changing environment and altering mission objectives. The latest techniques in artificial intelligence (AI) are being employed to increase the robotic vehicle's intelligent decision-making capabilities. This document describes the design of the SARA spatial database tool, which is composed of request parser, reasoning, computations, and database modules that collectively manage and derive information useful for robotic vehicles.

  20. Fuzzy Expert System for Heart Attack Diagnosis

    NASA Astrophysics Data System (ADS)

    Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

    2017-08-01

    Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

  1. Adaptive neural network/expert system that learns fault diagnosis for different structures

    NASA Astrophysics Data System (ADS)

    Simon, Solomon H.

    1992-08-01

    Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

  2. Mutually Augmented Cognition

    NASA Astrophysics Data System (ADS)

    Friesdorf, Florian; Pangercic, Dejan; Bubb, Heiner; Beetz, Michael

    In mac, an ergonomic dialog-system and algorithms will be developed that enable human experts and companions to be integrated into knowledge gathering and decision making processes of highly complex cognitive systems (e.g. Assistive Household as manifested further in the paper). In this event we propose to join algorithms and methodologies coming from Ergonomics and Artificial Intelligence that: a) make cognitive systems more congenial for non-expert humans, b) facilitate their comprehension by utilizing a high-level expandable control code for human experts and c) augment representation of such cognitive system into “deep representation” obtained through an interaction with human companions.

  3. Neural Networks for the Beginner.

    ERIC Educational Resources Information Center

    Snyder, Robin M.

    Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

  4. Modeling and simulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hanham, R.; Vogt, W.G.; Mickle, M.H.

    1986-01-01

    This book presents the papers given at a conference on computerized simulation. Topics considered at the conference included expert systems, modeling in electric power systems, power systems operating strategies, energy analysis, a linear programming approach to optimum load shedding in transmission systems, econometrics, simulation in natural gas engineering, solar energy studies, artificial intelligence, vision systems, hydrology, multiprocessors, and flow models.

  5. Workshop on Artificial Intelligence Applied to Materials Discovery and Design

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    None

    This workshop report summarizes the presentations, panel discussions, and breakout group discussions that took place at this event. Note that the results presented here are a snapshot of the viewpoints expressed by the experts who attended the workshop and do not necessarily reflect those of the broader materials development community.

  6. Proceedings of the 1984 IEEE international conference on systems, man and cybernetics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1984-01-01

    This conference contains papers on artificial intelligence, pattern recognition, and man-machine systems. Topics considered include concurrent minimization, a robot programming system, system modeling and simulation, camera calibration, thermal power plants, image processing, fault diagnosis, knowledge-based systems, power systems, hydroelectric power plants, expert systems, and electrical transients.

  7. Optimists' Creed: Brave New Cyberlearning, Evolving Utopias (Circa 2041)

    ERIC Educational Resources Information Center

    Burleson, Winslow; Lewis, Armanda

    2016-01-01

    This essay imagines the role that artificial intelligence innovations play in the integrated living, learning and research environments of 2041. Here, in 2041, in the context of increasingly complex wicked challenges, whose solutions by their very nature continue to evade even the most capable experts, society and technology have co-evolved to…

  8. Optimization of knowledge-based systems and expert system building tools

    NASA Technical Reports Server (NTRS)

    Yasuda, Phyllis; Mckellar, Donald

    1993-01-01

    The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

  9. SCAILET - An intelligent assistant for satellite ground terminal operations

    NASA Technical Reports Server (NTRS)

    Shahidi, A. K.; Crapo, J. A.; Schlegelmilch, R. F.; Reinhart, R. C.; Petrik, E. J.; Walters, J. L.; Jones, R. E.

    1992-01-01

    Space communication artificial intelligence for the link evaluation terminal (SCAILET) is an experimenter interface to the link evaluation terminal (LET) developed by NASA through the application of artificial intelligence to an advanced ground terminal. The high-burst-rate (HBR) LET provides the required capabilities for wideband communications experiments with the advanced communications technology satellite (ACTS). The HBR-LET terminal consists of seven major subsystems and is controlled and monitored by a minicomputer through an IEEE-488 or RS-232 interface. Programming scripts configure HBR-LET and allow data acquisition but are difficult to use and therefore the full capabilities of the system are not utilized. An intelligent assistant module was developed as part of the SCAILET module and solves problems encountered during configuration of the HBR-LET system. This assistant is a graphical interface with an expert system running in the background and allows users to configure instrumentation, program sequences and reference documentation. The simplicity of use makes SCAILET a superior interface to the ASCII terminal and continuous monitoring allows nearly flawless configuration and execution of HBR-LET experiments.

  10. Guidelines and rules for automated assembly by robots in space

    NASA Technical Reports Server (NTRS)

    Srivastava, Sadanand

    1992-01-01

    The development of an expert system for a 'Mechanical Design System' is discussed. Two different implementation approaches are described. One is coded in C, and the other is realized by a software package - 'Exsys.' The first method has the advantage of greater flexibility and quicker responses, while the latter one is easier to develop. This report discusses the feasible ways to establish a real mechanical intelligent design system applying artificial intelligence techniques so that the products designed by this system could best meet the requirements for space assembly.

  11. Artificial Intelligence Technology for the Maintainer's Associate. Final Report for the Period October 1983 to December 1985.

    ERIC Educational Resources Information Center

    Richardson, J. Jeffrey; And Others

    In keeping with current Department of Defense policies on integrated diagnostics and a reduced reliance on paper-based documentation, the concept of a portable, expert-system-based job aid and training device was proposed to assist inexperienced electronics maintenance technicians in learning to maintain sophisticated equipment. A prototype was…

  12. Developing Software For Monitoring And Diagnosis

    NASA Technical Reports Server (NTRS)

    Edwards, S. J.; Caglayan, A. K.

    1993-01-01

    Expert-system software shell produces executable code. Report discusses beginning phase of research directed toward development of artificial intelligence for real-time monitoring of, and diagnosis of faults in, complicated systems of equipment. Motivated by need for onboard monitoring and diagnosis of electronic sensing and controlling systems of advanced aircraft. Also applicable to such equipment systems as refineries, factories, and powerplants.

  13. SCAILET: An intelligent assistant for satellite ground terminal operations

    NASA Technical Reports Server (NTRS)

    Shahidi, A. K.; Crapo, J. A.; Schlegelmilch, R. F.; Reinhart, R. C.; Petrik, E. J.; Walters, J. L.; Jones, R. E.

    1993-01-01

    NASA Lewis Research Center has applied artificial intelligence to an advanced ground terminal. This software application is being deployed as an experimenter interface to the link evaluation terminal (LET) and was named Space Communication Artificial Intelligence for the Link Evaluation Terminal (SCAILET). The high-burst-rate (HBR) LET provides 30-GHz-transmitting and 20-GHz-receiving, 220-Mbps capability for wide band communications technology experiments with the Advanced Communication Technology Satellite (ACTS). The HBR-LET terminal consists of seven major subsystems. A minicomputer controls and monitors these subsystems through an IEEE-488 or RS-232 protocol interface. Programming scripts (test procedures defined by design engineers) configure the HBR-LET and permit data acquisition. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. This discourages experimenters from utilizing the full capabilities of the HBR-LET system. An intelligent assistant module was developed as part of the SCAILET software. The intelligent assistant addresses critical experimenter needs by solving and resolving problems that are encountered during the configuring of the HBR-LET system. The intelligent assistant is a graphical user interface with an expert system running in the background. In order to further assist and familiarize an experimenter, an on-line hypertext documentation module was developed and included in the SCAILET software.

  14. The application and development of artificial intelligence in smart clothing

    NASA Astrophysics Data System (ADS)

    Wei, Xiong

    2018-03-01

    This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

  15. Autonomous power expert system

    NASA Technical Reports Server (NTRS)

    Ringer, Mark J.; Quinn, Todd M.

    1990-01-01

    The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.

  16. Autonomous power expert system

    NASA Technical Reports Server (NTRS)

    Ringer, Mark J.; Quinn, Todd M.

    1990-01-01

    The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

  17. Real time AI expert system for robotic applications

    NASA Technical Reports Server (NTRS)

    Follin, John F.

    1987-01-01

    A computer controlled multi-robot process cell to demonstrate advanced technologies for the demilitarization of obsolete chemical munitions was developed. The methods through which the vision system and other sensory inputs were used by the artificial intelligence to provide the information required to direct the robots to complete the desired task are discussed. The mechanisms that the expert system uses to solve problems (goals), the different rule data base, and the methods for adapting this control system to any device that can be controlled or programmed through a high level computer interface are discussed.

  18. Improved Real-Time Monitoring Using Multiple Expert Systems

    NASA Technical Reports Server (NTRS)

    Schwuttke, Ursula M.; Angelino, Robert; Quan, Alan G.; Veregge, John; Childs, Cynthia

    1993-01-01

    Monitor/Analyzer of Real-Time Voyager Engineering Link (MARVEL) computer program implements combination of techniques of both conventional automation and artificial intelligence to improve monitoring of complicated engineering system. Designed to support ground-based operations of Voyager spacecraft, also adapted to other systems. Enables more-accurate monitoring and analysis of telemetry, enhances productivity of monitoring personnel, reduces required number of such personnel by performing routine monitoring tasks, and helps ensure consistency in face of turnover of personnel. Programmed in C language and includes commercial expert-system software shell also written in C.

  19. Automation technology for aerospace power management

    NASA Technical Reports Server (NTRS)

    Larsen, R. L.

    1982-01-01

    The growing size and complexity of spacecraft power systems coupled with limited space/ground communications necessitate increasingly automated onboard control systems. Research in computer science, particularly artificial intelligence has developed methods and techniques for constructing man-machine systems with problem-solving expertise in limited domains which may contribute to the automation of power systems. Since these systems perform tasks which are typically performed by human experts they have become known as Expert Systems. A review of the current state of the art in expert systems technology is presented, and potential applications in power systems management are considered. It is concluded that expert systems appear to have significant potential for improving the productivity of operations personnel in aerospace applications, and in automating the control of many aerospace systems.

  20. Artificial Intelligence Controls Tape-Recording Sequence

    NASA Technical Reports Server (NTRS)

    Schwuttke, Ursula M.; Otamura, Roy M.; Zottarelli, Lawrence J.

    1989-01-01

    Developmental expert-system computer program intended to schedule recording of large amounts of data on limited amount of magnetic tape. Schedules recording using two sets of rules. First set incorporates knowledge of locations for recording of new data. Second set incorporates knowledge about issuing commands to recorder. Designed primarily for use on Voyager Spacecraft, also applicable to planning and sequencing in industry.

  1. Development of a Prototype H-46 Helicopter Diagnostic Expert System.

    DTIC Science & Technology

    1987-09-01

    SQUADRON MAINTEN\\NCE: CURRENT PROCESS AND CA D S INTEG R ,ATIO N ........................................ 14 A. MAINTENANCE DATA SYSTEM...increasce the effectiveness of the maintenance process should enhance the ability of achieving :hee objectives. Artificial intelligence techniques offer a...completeiy validated. G. ORGANIZATION OF STUDY Chapter II contains a description of the Naval Aviation Maintenance Program’s Maintenance Data System (MDS

  2. Connections. NECC '89: Proceedings of the National Educational Computing Conference (10th, Boston, Massachusetts, June 20-22, 1989).

    ERIC Educational Resources Information Center

    Ryan, William C., Ed.

    The papers presented at the 1989 National Educational Computing Conference focused on ways of using technology to improve educational quality. Topics of the 50 papers and more than 120 abstracts provided in these proceedings include applications of artificial intelligence and the development of expert systems; authoring systems; using the computer…

  3. Considerations in development of expert systems for real-time space applications

    NASA Technical Reports Server (NTRS)

    Murugesan, S.

    1988-01-01

    Over the years, demand on space systems has increased tremendously and this trend will continue for the near future. Enhanced capabilities of space systems, however, can only be met with increased complexity and sophistication of onboard and ground systems. Artificial Intelligence and expert system techniques have great potential in space applications. Expert systems could facilitate autonomous decision making, improve in-orbit fault diagnosis and repair, enhance performance and reduce reliance on ground support. However, real-time expert systems, unlike conventional off-line consultative systems, have to satisfy certain special stringent requirements before they could be used for onboard space applications. Challenging and interesting new environments are faced while developing expert system space applications. This paper discusses the special characteristics, requirements and typical life cycle issues for onboard expert systems. Further, it also describes considerations in design, development, and implementation which are particularly important to real-time expert systems for space applications.

  4. Diagnosis - Using automatic test equipment and artificial intelligence expert systems

    NASA Astrophysics Data System (ADS)

    Ramsey, J. E., Jr.

    Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

  5. METEOR - an artificial intelligence system for convective storm forecasting

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Elio, R.; De haan, J.; Strong, G.S.

    1987-03-01

    An AI system called METEOR, which uses the meteorologist's heuristics, strategies, and statistical tools to forecast severe hailstorms in Alberta, is described, emphasizing the information and knowledge that METEOR uses to mimic the forecasting procedure of an expert meteorologist. METEOR is then discussed as an AI system, emphasizing the ways in which it is qualitatively different from algorithmic or statistical approaches to prediction. Some features of METEOR's design and the AI techniques for representing meteorological knowledge and for reasoning and inference are presented. Finally, some observations on designing and implementing intelligent consultants for meteorological applications are made. 7 references.

  6. Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

    NASA Technical Reports Server (NTRS)

    Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

    1992-01-01

    A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user.

  7. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    NASA Astrophysics Data System (ADS)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

  8. EMMA: The expert system for munition maintenance

    NASA Technical Reports Server (NTRS)

    Mullins, Barry E.

    1988-01-01

    Expert Missile Maintenance Aid (EMMA) is a first attempt to enhance maintenance of the tactical munition at the field and depot level by using artificial intelligence (AI) techniques. The ultimate goal of EMMA is to help a novice maintenance technician isolate and diagnose electronic, electromechanical, and mechanical equipment faults to the board/chassis level more quickly and consistently than the best human expert using the best currently available automatic test equipment (ATE). To this end, EMMA augments existing ATE with an expert system that captures the knowledge of design and maintenance experts. The EMMA program is described, including the evaluation of field-level expert system prototypes, the description of several study tasks performed during EMMA, and future plans for a follow-on program. This paper will briefly address several study tasks performed during EMMA. The paper concludes with a discussion of future plans for a follow-on program and other areas of concern.

  9. Artificial intelligence. Fears of an AI pioneer.

    PubMed

    Russell, Stuart; Bohannon, John

    2015-07-17

    From the enraged robots in the 1920 play R.U.R. to the homicidal computer H.A.L. in 2001: A Space Odyssey, science fiction writers have embraced the dark side of artificial intelligence (AI) ever since the concept entered our collective imagination. Sluggish progress in AI research, especially during the “AI winter” of the 1970s and 1980s, made such worries seem far-fetched. But recent breakthroughs in machine learning and vast improvements in computational power have brought a flood of research funding— and fresh concerns about where AI may lead us. One researcher now speaking up is Stuart Russell, a computer scientist at the University of California, Berkeley, who with Peter Norvig, director of research at Google, wrote the premier AI textbook, Artificial Intelligence: A Modern Approach, now in its third edition. Last year, Russell joined the Centre for the Study of Existential Risk at Cambridge University in the United Kingdom as an AI expert focusing on “risks that could lead to human extinction.” Among his chief concerns, which he aired at an April meeting in Geneva, Switzerland, run by the United Nations, is the danger of putting military drones and weaponry under the full control of AI systems. This interview has been edited for clarity and brevity.

  10. Intelligent fault-tolerant controllers

    NASA Technical Reports Server (NTRS)

    Huang, Chien Y.

    1987-01-01

    A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

  11. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harber, K.S.

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

  12. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harber, K.S.

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

  13. Northeast Artificial Intelligence Consortium (NAIC) Review of Technical Tasks. Volume 2, Part 1.

    DTIC Science & Technology

    1987-07-01

    34- . 6.2 Transformation Invariant Attributes for S Digitized Object Outlines ................................. 469 6.3 Design of an Inference Engine for an...Attributes for Digital Object Outlines ...................................... 597 7 SPEECH UNDERSTANDING RESEARCH ( Rochester Institute of Technology...versatile maintenance expert system ES) for trouble-shooting--’ digital circuits. +" Some diagnosis systems, such as MYCLN [19] for medical diagnosis and CRIB

  14. Clips as a knowledge based language

    NASA Technical Reports Server (NTRS)

    Harrington, James B.

    1987-01-01

    CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system.

  15. Conference on Automated Decision-Making and Problem Solving, the Third Day: Issues Discussed

    NASA Technical Reports Server (NTRS)

    Hawkins, W. W.; Pennington, J. E.; Baker, L. K.

    1980-01-01

    A conference held at Langley Research Center in May of 1980 brought together university experts from the fields of Control Theory, Operations Research, and Artificial Intelligence to explore current research in automation from both the perspective of their own particular disciplines and from that of interdisciplinary considerations. Informal discussions from the final day of the those day conference are summarized.

  16. Expert System Approach For Generating And Evaluating Engine Design Alternatives

    NASA Astrophysics Data System (ADS)

    Shen, Stewart N. T.; Chew, Meng-Sang; Issa, Ghassan F.

    1989-03-01

    Artificial intelligence is becoming an increasingly important subject of study for computer scientists, engineering designers, as well as professionals in other fields. Even though AI technology is a relatively new discipline, many of its concepts have already found practical applications. Expert systems, in particular, have made significant contributions to technologies in such fields as business, medicine, engineering design, chemistry, and particle physics. This paper describes an expert system developed to aid the mechanical designer with the preliminary design of variable-stroke internal-combustion engines. The expert system accomplished its task by generating and evaluating a large number of design alternatives represented in the form of graphs. Through the application of structural and design rules directly to the graphs, optimal and near optimal preliminary design configurations of engines are deduced.

  17. Deciding alternative left turn signal phases using expert systems

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chang, E.C.P.

    1988-01-01

    The Texas Transportation Institute (TTI) conducted a study to investigate the feasibility of applying artificial intelligence (AI) technology and expert systems (ES) design concepts to a traffic engineering problem. Prototype systems were developed to analyze user input, evaluate various reasoning, and suggest suitable left turn phase treatment. These systems were developed using AI programming tools on IBM PC/XT/AT-compatible microcomputers. Two slightly different systems were designed using AI languages; another was built with a knowledge engineering tool. These systems include the PD PROLOG and TURBO PROLOG AI programs, as well as the INSIGHT Production Rule Language.

  18. System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

    NASA Astrophysics Data System (ADS)

    Nieten, Joseph L.; Burke, Roger

    1993-03-01

    The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

  19. Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

    PubMed

    Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

    2014-09-01

    Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

  20. Translating expert system rules into Ada code with validation and verification

    NASA Technical Reports Server (NTRS)

    Becker, Lee; Duckworth, R. James; Green, Peter; Michalson, Bill; Gosselin, Dave; Nainani, Krishan; Pease, Adam

    1991-01-01

    The purpose of this ongoing research and development program is to develop software tools which enable the rapid development, upgrading, and maintenance of embedded real-time artificial intelligence systems. The goals of this phase of the research were to investigate the feasibility of developing software tools which automatically translate expert system rules into Ada code and develop methods for performing validation and verification testing of the resultant expert system. A prototype system was demonstrated which automatically translated rules from an Air Force expert system was demonstrated which detected errors in the execution of the resultant system. The method and prototype tools for converting AI representations into Ada code by converting the rules into Ada code modules and then linking them with an Activation Framework based run-time environment to form an executable load module are discussed. This method is based upon the use of Evidence Flow Graphs which are a data flow representation for intelligent systems. The development of prototype test generation and evaluation software which was used to test the resultant code is discussed. This testing was performed automatically using Monte-Carlo techniques based upon a constraint based description of the required performance for the system.

  1. Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

    PubMed

    Elkin, Peter L; Schlegel, Daniel R; Anderson, Michael; Komm, Jordan; Ficheur, Gregoire; Bisson, Leslie

    2018-04-01

    Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases. A board-certified orthopedic sports medicine practitioner, L.B., reviewed any disagreements until a gold standard diagnosis was reached. For each case, the patients entered 126 potential answers to 26 questions into a Web interface. These were modeled by an expert sports medicine physician and the answers were reviewed by L.B. For each finding, the clinician specified the sensitivity (term frequency) and both specificity (Sp) and the heuristic evoking strength (ES). Heuristics are methods of reasoning with only partial evidence. An expert system was constructed that reflected the posttest odds of disease-ranked list for each case. We compare the accuracy of using Sp to that of using ES (original model, p  < 0.0008; term importance * disease importance [DItimesTI] model, p  < 0.0001: Wilcoxon ranked sum test). For patient referral assignment, Sp in the DItimesTI model was superior to the use of ES. By the fifth diagnosis, the advantage was lost and so there is no difference between the techniques when serving as a reminder system. Schattauer GmbH Stuttgart.

  2. Intelligent instrumentation applied in environment management

    NASA Astrophysics Data System (ADS)

    Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

    2005-06-01

    The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

  3. Expertise and reasoning with possibility: An explanation of modal logic and expert systems

    NASA Technical Reports Server (NTRS)

    Rochowiak, Daniel

    1988-01-01

    Recently systems of modal reasoning have been brought to the foreground of artificial intelligence studies. The intuitive idea of research efforts in this area is that in addition to the actual world in which sentences have certain truth values there are other worlds in which those sentences have different truth values. Such alternative worlds can be considered as possible worlds, and an agent may or may not have access to some or all of them. This approach to reasoning can be valuable in extending the expert system paradigm. Using the scheme of reasoning proposed by Toulmin, Reike and Janick and the modal system T, a scheme is proposed for expert reasoning that mitigates some of the criticisms raised by Schank and Nickerson.

  4. Artificial intelligence techniques for ground test monitoring of rocket engines

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Gupta, U. K.

    1990-01-01

    An expert system is being developed which can detect anomalies in Space Shuttle Main Engine (SSME) sensor data significantly earlier than the redline algorithm currently in use. The training of such an expert system focuses on two approaches which are based on low frequency and high frequency analyses of sensor data. Both approaches are being tested on data from SSME tests and their results compared with the findings of NASA and Rocketdyne experts. Prototype implementations have detected the presence of anomalies earlier than the redline algorithms that are in use currently. It therefore appears that these approaches have the potential of detecting anomalies early eneough to shut down the engine or take other corrective action before severe damage to the engine occurs.

  5. Development of a knowledge acquisition tool for an expert system flight status monitor

    NASA Technical Reports Server (NTRS)

    Disbrow, J. D.; Duke, E. L.; Regenie, V. A.

    1986-01-01

    Two of the main issues in artificial intelligence today are knowledge acquisition dion and knowledge representation. The Dryden Flight Research Facility of NASA's Ames Research Center is presently involved in the design and implementation of an expert system flight status monitor that will provide expertise and knowledge to aid the flight systems engineer in monitoring today's advanced high-performance aircraft. The flight status monitor can be divided into two sections: the expert system itself and the knowledge acquisition tool. The knowledge acquisition tool, the means it uses to extract knowledge from the domain expert, and how that knowledge is represented for computer use is discussed. An actual aircraft system has been codified by this tool with great success. Future real-time use of the expert system has been facilitated by using the knowledge acquisition tool to easily generate a logically consistent and complete knowledge base.

  6. Development of a knowledge acquisition tool for an expert system flight status monitor

    NASA Technical Reports Server (NTRS)

    Disbrow, J. D.; Duke, E. L.; Regenie, V. A.

    1986-01-01

    Two of the main issues in artificial intelligence today are knowledge acquisition and knowledge representation. The Dryden Flight Research Facility of NASA's Ames Research Center is presently involved in the design and implementation of an expert system flight status monitor that will provide expertise and knowledge to aid the flight systems engineer in monitoring today's advanced high-performance aircraft. The flight status monitor can be divided into two sections: the expert system itself and the knowledge acquisition tool. This paper discusses the knowledge acquisition tool, the means it uses to extract knowledge from the domain expert, and how that knowledge is represented for computer use. An actual aircraft system has been codified by this tool with great success. Future real-time use of the expert system has been facilitated by using the knowledge acquisition tool to easily generate a logically consistent and complete knowledge base.

  7. Logic programming and metadata specifications

    NASA Technical Reports Server (NTRS)

    Lopez, Antonio M., Jr.; Saacks, Marguerite E.

    1992-01-01

    Artificial intelligence (AI) ideas and techniques are critical to the development of intelligent information systems that will be used to collect, manipulate, and retrieve the vast amounts of space data produced by 'Missions to Planet Earth.' Natural language processing, inference, and expert systems are at the core of this space application of AI. This paper presents logic programming as an AI tool that can support inference (the ability to draw conclusions from a set of complicated and interrelated facts). It reports on the use of logic programming in the study of metadata specifications for a small problem domain of airborne sensors, and the dataset characteristics and pointers that are needed for data access.

  8. Shared direct memory access on the Explorer 2-LX

    NASA Technical Reports Server (NTRS)

    Musgrave, Jeffrey L.

    1990-01-01

    Advances in Expert System technology and Artificial Intelligence have provided a framework for applying automated Intelligence to the solution of problems which were generally perceived as intractable using more classical approaches. As a result, hybrid architectures and parallel processing capability have become more common in computing environments. The Texas Instruments Explorer II-LX is an example of a machine which combines a symbolic processing environment, and a computationally oriented environment in a single chassis for integrated problem solutions. This user's manual is an attempt to make these capabilities more accessible to a wider range of engineers and programmers with problems well suited to solution in such an environment.

  9. Artificial Intelligence and Expert Systems

    DTIC Science & Technology

    1986-03-01

    O R R E C T I N G • NOT P R O T E C T E D oEMOTION oFATIGUE oUNAVAILABLE oBIAS olMPERIAL • STABLE (COLD) o lNDEFAT IGABLE eAVAILABLE eLESS... oBIAS olMPERIAL • STABLE (COLD) o lNDEFAT IGABLE eAVAILABLE oLESS BIAS o lMPERSONAL DODCI 1085-.85 THE COMPUTER EVOLUTION I I I • C o m p

  10. Proceedings of GeoTech 85: Personal computers in geology conference

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Not Available

    1985-01-01

    This book presents the papers given at a conference which considered the use of microprocessors in the exploration of petroleum and natural gas deposits. Topics covered at the conference included seismic surveys, geochemistry, expert systems, artificial intelligence, data base management systems, a portable exploration work station, open pit planning on a microcomputer, well logging, fracture analysis, production scheduling of open pit mines, resistivity logging, and coal washability.

  11. The Application of Artificial Intelligence to Human Resource Development. A Case Study in the Development of a Rule-Based Expert System for Performance Analysis and Development Planning.

    ERIC Educational Resources Information Center

    Hummel, Thomas J.; Robinson, Judith A.

    In 1984, the University of Minnesota's College of Education and Wilson Learning Corporation created the Alliance for Learning to support a variety of research projects focused on developing new areas of knowledge about adult learning and new technologies for delivering training and education. This paper describes an Alliance project exploring the…

  12. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    NASA Astrophysics Data System (ADS)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  13. Artificial Intelligence and Information Retrieval.

    ERIC Educational Resources Information Center

    Teodorescu, Ioana

    1987-01-01

    Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)

  14. Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

    NASA Technical Reports Server (NTRS)

    Kawamura, K.; Beale, G. O.; Schaffer, J. D.; Hsieh, B. J.; Padalkar, S.; Rodriguez-Moscoso, J. J.

    1985-01-01

    The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge.

  15. CREATIVE COMPUTATION.

    DTIC Science & Technology

    ARTIFICIAL INTELLIGENCE , RECURSIVE FUNCTIONS), (*RECURSIVE FUNCTIONS, ARTIFICIAL INTELLIGENCE ), (*MATHEMATICAL LOGIC, ARTIFICIAL INTELLIGENCE ), METAMATHEMATICS, AUTOMATA, NUMBER THEORY, INFORMATION THEORY, COMBINATORIAL ANALYSIS

  16. Artificial Intelligence and Its Importance in Education.

    ERIC Educational Resources Information Center

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  17. Northeast Artificial Intelligence Consortium (NAIC) Review of Technical Tasks. Volume 2, Part 2.

    DTIC Science & Technology

    1987-07-01

    A-A19 774 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUN (MIC) 1/5 YVIEN OF TEOICR. T.. (U) NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM SYRACUSE MY J...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM (NAIC) *p,* ~ Review of Technical Tasks ,.. 12 PERSONAL AUTHOR(S) (See reverse) . P VI J.F. Allen, P.B. Berra...See reverse) /" I ABSTRACT (Coninue on ’.wrse if necessary and identify by block number) % .. *. -. ’ The Northeast Artificial Intelligence Consortium

  18. Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

    NASA Technical Reports Server (NTRS)

    Shewhart, Mark

    1991-01-01

    Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

  19. Building validation tools for knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

    1987-01-01

    The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

  20. The Reliability Estimation for the Open Function of Cabin Door Affected by the Imprecise Judgment Corresponding to Distribution Hypothesis

    NASA Astrophysics Data System (ADS)

    Yu, Z. P.; Yue, Z. F.; Liu, W.

    2018-05-01

    With the development of artificial intelligence, more and more reliability experts have noticed the roles of subjective information in the reliability design of complex system. Therefore, based on the certain numbers of experiment data and expert judgments, we have divided the reliability estimation based on distribution hypothesis into cognition process and reliability calculation. Consequently, for an illustration of this modification, we have taken the information fusion based on intuitional fuzzy belief functions as the diagnosis model of cognition process, and finished the reliability estimation for the open function of cabin door affected by the imprecise judgment corresponding to distribution hypothesis.

  1. Blowout Monitor

    NASA Technical Reports Server (NTRS)

    1994-01-01

    C Language Integrated Production System (CLIPS), a NASA-developed software shell for developing expert systems, has been embedded in a PC-based expert system for training oil rig personnel in monitoring oil drilling. Oil drilling rigs if not properly maintained for possible blowouts pose hazards to human life, property and the environment may be destroyed. CLIPS is designed to permit the delivery of artificial intelligence on computer. A collection of rules is set up and, as facts become known, these rules are applied. In the Well Site Advisor, CLIPS provides the capability to accurately process, predict and interpret well data in a real time mode. CLIPS was provided to INTEQ by COSMIC.

  2. Vision Guided Intelligent Robot Design And Experiments

    NASA Astrophysics Data System (ADS)

    Slutzky, G. D.; Hall, E. L.

    1988-02-01

    The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

  3. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  4. Detection of Terrorist Preparations by an Artificial Intelligence Expert System Employing Fuzzy Signal Detection Theory

    DTIC Science & Technology

    2004-10-25

    FUSEDOT does not require facial recognition , or video surveillance of public areas, both of which are apparently a component of TIA ([26], pp...does not use fuzzy signal detection. Involves facial recognition and video surveillance of public areas. Involves monitoring the content of voice...fuzzy signal detection, which TIA does not. Second, FUSEDOT would be easier to develop, because it does not require the development of facial

  5. Accomplishments of Naturalistic Decision Making Research and Applications to Emerging Defense Challenges

    DTIC Science & Technology

    2015-07-27

    studying an expert physician. In Proceedings of the 8th International Conference on Artificial Intelligence (pp. ###-###). Los Altos, CA: Morgan...incidentally on analogy lo particular past cases (e.g., a fire involving a billboard on a rooftop brought to mind a past case involving a billboard). Rather...Action. Los Angeles, CA: Sage CQ Press. Bums, K. (2005). Mental models and normal errors. In H, Montgomery, R, Lipshitz & B, Brehmer (Eds.), How

  6. Rule-Based Expert Systems in the Command Estimate: An Operational Perspective

    DTIC Science & Technology

    1990-06-01

    control measures. 5. Prepare COA statement(s) and sketch(es). The key inputs for developing courses of action are the DFD process of IPB, data stores...mission, or a change of information provides new direction to this process for that particular operation." Formal scientific analysis of the command...30 5. Delivery of outside news . This feature contributes to the commanders insatiable need for current information. Artificial intelligence ana rule

  7. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Floyd, Stephen; Ford, Donnie

    1988-01-01

    The role that artificial intelligence/expert systems technologies play in the development and implementation of effective decision support systems is illustrated. A recently developed prototype system for supporting the scheduling of subsystems and payloads/experiments for NASA's Space Station program is presented and serves to highlight various concepts. The potential integration of knowledge based systems and decision support systems which has been proposed in several recent articles and presentations is illustrated.

  8. Automated Decision Making and Problem Solving. Volume 1: Executive Summary

    NASA Technical Reports Server (NTRS)

    Heer, E.

    1981-01-01

    The May 1980 conference is summarized. Related topics in artificial intelligence, operations research, and control theory were explored. Existing techniques were assessed, trends of development determined, and potential for application in NASA automation technology programs were identified. Formal presentations were made by experts in the three disciplines nd a workshop was held in which current technology in automation and possible NASA interfaces with the academic community to advance this technology were discussed.

  9. Center for Space Transportation and Applied Research Fifth Annual Technical Symposium Proceedings

    NASA Technical Reports Server (NTRS)

    1993-01-01

    This Fifth Annual Technical Symposium, sponsored by the UT-Calspan Center for Space Transportation and Applied Research (CSTAR), is organized to provide an overview of the technical accomplishments of the Center's five Research and Technology focus areas during the past year. These areas include chemical propulsion, electric propulsion, commerical space transportation, computational methods, and laser materials processing. Papers in the area of artificial intelligence/expert systems are also presented.

  10. A Preliminary Investigation on the Application of Robotics to Missile Fire Control.

    DTIC Science & Technology

    1983-11-01

    application. Even this is a broad area, but it is one in which Okhe general theories and concepts of robo - tics and/or artificial intelligence can be...K::. 3. Expert Advisors .J1. %4. Data Assimilation and Access Aids 5. Handling Support Systems 6. Support Systems 7...appears, therefore, that a robo - tic forward observer can be manufactured in quantities for a reasonable cost when compared to the cost of training

  11. Artificial Intelligence Project

    DTIC Science & Technology

    1990-01-01

    Artifcial Intelligence Project at The University of Texas at Austin, University of Texas at Austin, Artificial Intelligence Laboratory AITR84-01. Novak...Texas at Austin, Artificial Intelligence Laboratory A187-52, April 1987. Novak, G. "GLISP: A Lisp-Based Programming System with Data Abstraction...of Texas at Austin, Artificial Intelligence Laboratory AITR85-14.) Rim, Hae-Chang, and Simmons, R. F. "Extracting Data Base Knowledge from Medical

  12. A Knowledge-Based System Developer for aerospace applications

    NASA Technical Reports Server (NTRS)

    Shi, George Z.; Wu, Kewei; Fensky, Connie S.; Lo, Ching F.

    1993-01-01

    A prototype Knowledge-Based System Developer (KBSD) has been developed for aerospace applications by utilizing artificial intelligence technology. The KBSD directly acquires knowledge from domain experts through a graphical interface then builds expert systems from that knowledge. This raises the state of the art of knowledge acquisition/expert system technology to a new level by lessening the need for skilled knowledge engineers. The feasibility, applicability , and efficiency of the proposed concept was established, making a continuation which would develop the prototype to a full-scale general-purpose knowledge-based system developer justifiable. The KBSD has great commercial potential. It will provide a marketable software shell which alleviates the need for knowledge engineers and increase productivity in the workplace. The KBSD will therefore make knowledge-based systems available to a large portion of industry.

  13. Computer finds ore

    NASA Astrophysics Data System (ADS)

    Bell, Peter M.

    Artificial intelligence techniques are being used for the first time to evaluate geophysical, geochemical, and geologic data and theory in order to locate ore deposits. After several years of development, an intelligent computer code has been formulated and applied to the Mount Tolman area in Washington state. In a project funded by the United States Geological Survey and the National Science Foundation a set of computer programs, under the general title Prospector, was used successfully to locate a previously unknown ore-grade porphyry molybdenum deposit in the vicinity of Mount Tolman (Science, Sept. 3, 1982).The general area of the deposit had been known to contain exposures of porphyry mineralization. Between 1964 and 1978, exploration surveys had been run by the Bear Creek Mining Company, and later exploration was done in the area by the Amax Corporation. Some of the geophysical data and geochemical and other prospecting surveys were incorporated into the programs, and mine exploration specialists contributed to a set of rules for Prospector. The rules were encoded as ‘inference networks’ to form the ‘expert system’ on which the artificial intelligence codes were based. The molybdenum ore deposit discovered by the test is large, located subsurface, and has an areal extent of more than 18 km2.

  14. Artificial Intelligence and Information Management

    NASA Astrophysics Data System (ADS)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  15. a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

    NASA Astrophysics Data System (ADS)

    Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

    1997-06-01

    Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

  16. Predicate calculus, artificial intelligence, and workers' compensation.

    PubMed

    Harber, P; McCoy, J M

    1989-05-01

    Application of principles of predicate calculus (PC) and artificial intelligence (AI) search methods to occupational medicine can meet several goals. First, they can improve understanding of the diagnostic process and recognition of the sources of uncertainty in knowledge and in case specific information. Second, PC provides a rational means of resolving differences in conclusion based upon the same premises. Third, understanding of these principles allows separation of knowledge (facts) from the process by which they are used and therefore facilitates development of AI-based expert systems. Application of PC to recognizing causation of pulmonary fibrosis is demonstrated in this paper, providing a method that can be generalized to other problems in occupational medicine. Application of PC and understanding of AI search routines may be particularly applicable to workers' compensation where explicit statement of rational and inferential process is necessary. This approach is useful in the diagnosis of occupational lung disease and may be particularly valuable in workers' compensation considerations, wherein explicit statement of rationale is needed.

  17. Processing and representation of meta-data for sleep apnea diagnosis with an artificial intelligence approach.

    PubMed

    Nettleton, D; Muñiz, J

    2001-09-01

    In this article, we revise and try to resolve some of the problems inherent in questionnaire screening of sleep apnea cases and apnea diagnosis based on attributes which are relevant and reliable. We present a way of learning information about the relevance of the data, comparing this with the definition of the information by the medical expert. We generate a predictive data model using a data aggregation operator which takes relevance and reliability information about the data into account to produce a diagnosis for each case. We also introduce a grade of membership for each question response which allows the patient to indicate a level of confidence or doubt in their own judgement. The method is tested with data collected from patients in a Sleep Clinic using questionnaires specially designed for the study. Other artificial intelligence predictive modeling algorithms are also tested on the same data and their predictive accuracy compared to that of the aggregation operator.

  18. Artificial intelligence in the service of system administrators

    NASA Astrophysics Data System (ADS)

    Haen, C.; Barra, V.; Bonaccorsi, E.; Neufeld, N.

    2012-12-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  19. An artificial intelligence approach to lithostratigraphic correlation using geophysical well logs

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Olea, R.A.; Davis, J.C.

    1986-01-01

    Computer programs for lithostratigraphic correlation of well logs have achieved limited success. Their algorithms are based on an oversimplified view of the manual process used by analysts to establish geologically correct correlations. The programs experience difficulties if the correlated rocks deviate from an ideal geometry of perfectly homogeneous, parallel layers of infinite extent. Artificial intelligence provides a conceptual basis for formulating the task of lithostratigraphic correlation, leading to more realistic procedures. A prototype system using the ''production rule'' approach of expert systems successfully correlates well logs in areas of stratigraphic complexity. Two digitized logs are used per well, one formore » curve matching and the other for lithologic comparison. The software has been successfully used to correlate more than 100,000 ft (30 480 m) of section, through clastic sequences in Louisiana and through carbonate sequences in Kansas. Correlations have been achieved even in the presence of faults, unconformities, facies changes, and lateral variations in bed thickness.« less

  20. Artificial Intelligence in Medical Practice: The Question to the Answer?

    PubMed

    Miller, D Douglas; Brown, Eric W

    2018-02-01

    Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice remains an unanswered question. Machines (computers) learn to detect patterns not decipherable using biostatistics by processing massive datasets (big data) through layered mathematical models (algorithms). Correcting algorithm mistakes (training) adds to AI predictive model confidence. AI is being successfully applied for image analysis in radiology, pathology, and dermatology, with diagnostic speed exceeding, and accuracy paralleling, medical experts. While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. Cognitive programs are impacting medical practice by applying natural language processing to read the rapidly expanding scientific literature and collate years of diverse electronic medical records. In this and other ways, AI may optimize the care trajectory of chronic disease patients, suggest precision therapies for complex illnesses, reduce medical errors, and improve subject enrollment into clinical trials. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Web-based expert system for foundry pollution prevention

    NASA Astrophysics Data System (ADS)

    Moynihan, Gary P.

    2004-02-01

    Pollution prevention is a complex task. Many small foundries lack the in-house expertise to perform these tasks. Expert systems are a type of computer information system that incorporates artificial intelligence. As noted in the literature, they provide a means of automating specialized expertise. This approach may be further leveraged by implementing the expert system on the internet (or world-wide web). This will allow distribution of the expertise to a variety of geographically-dispersed foundries. The purpose of this research is to develop a prototype web-based expert system to support pollution prevention for the foundry industry. The prototype system identifies potential emissions for a specified process, and also provides recommendations for the prevention of these contaminants. The system is viewed as an initial step toward assisting the foundry industry in better meeting government pollution regulations, as well as improving operating efficiencies within these companies.

  2. Weather forecasting expert system study

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

  3. A framework for building real-time expert systems

    NASA Technical Reports Server (NTRS)

    Lee, S. Daniel

    1991-01-01

    The Space Station Freedom is an example of complex systems that require both traditional and artificial intelligence (AI) real-time methodologies. It was mandated that Ada should be used for all new software development projects. The station also requires distributed processing. Catastrophic failures on the station can cause the transmission system to malfunction for a long period of time, during which ground-based expert systems cannot provide any assistance to the crisis situation on the station. This is even more critical for other NASA projects that would have longer transmission delays (e.g., the lunar base, Mars missions, etc.). To address these issues, a distributed agent architecture (DAA) is proposed that can support a variety of paradigms based on both traditional real-time computing and AI. The proposed testbed for DAA is an autonomous power expert (APEX) which is a real-time monitoring and diagnosis expert system for the electrical power distribution system of the space station.

  4. Web Intelligence and Artificial Intelligence in Education

    ERIC Educational Resources Information Center

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  5. Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

    DTIC Science & Technology

    1989-10-01

    Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

  6. Intelligence: Real or artificial?

    PubMed Central

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

  7. Artificial Intelligence: Expert Systems for Corps Tactical Planning and Other Applications.

    DTIC Science & Technology

    1987-03-23

    territory; and prepares to continue the attack into East Germany to secure Magdeburg and crossing sites on the Elbe River.. 3. EXECUTION. a. Concept of...14th Armored Cavalry Regiment, and the 22d Aviation Brigade to West Germany . The theater commander assigned the 1 Ith Corps and attached units to the...newly formed Middle Army Group (MIDAG), which had been given responsibility for a sector in the vicinity of Hannover, West Germany . Prior to issuing

  8. Autonomous power expert fault diagnostic system for Space Station Freedom electrical power system testbed

    NASA Technical Reports Server (NTRS)

    Truong, Long V.; Walters, Jerry L.; Roth, Mary Ellen; Quinn, Todd M.; Krawczonek, Walter M.

    1990-01-01

    The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.

  9. Prerequisites for Deriving Formal Specifications from Natural Language Requirements.

    DTIC Science & Technology

    1983-04-01

    International Joint Conference on Artificial Intell1ence, American Association for Artificial Intelligence, Mento Park, CA, 1981, 385-387. Mann, William C...Centering". Proceedings of the Seventh International Joint Conference on Artificial Intelligence, American Association for Artificial Intelligence, Mento

  10. Artificial Intelligence--Applications in Education.

    ERIC Educational Resources Information Center

    Poirot, James L.; Norris, Cathleen A.

    1987-01-01

    This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

  11. Innovation on Energy Power Technology (22)Challenge to Development of Expert System stored Knowledge of Expert Power Network Operators

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Hideharu

    Do you remember an expert system? I think there are various impressions about the system. For example, some might say “It reminds me of old days”. On the other hand, some might say “It was really troublesome”. About 25 years ago, from late 1980s to the middle of 1990s, when the Showa era was about to change into the Heisei Era, artificial intelligence boomed. Research and development for an expert system which was equipped with expertise and worked as smart as expert, was advanced in various fields. Our company also picked up the system as the new system which covered weak point of conventional computer technology. We started research and development in 1984, and installed an expert system in a SCADA system, which started operating in March 1990 in the Fukuoka Integrated Control Center. In this essay, as an electric power engineer who involved in development at that time, I introduce the situation and travail story about developing an expert system which support restorative actions from the outage and overload condition of power networks.

  12. AIonAI: a humanitarian law of artificial intelligence and robotics.

    PubMed

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

  13. ABCluster: the artificial bee colony algorithm for cluster global optimization.

    PubMed

    Zhang, Jun; Dolg, Michael

    2015-10-07

    Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

  14. Model authoring system for fail safe analysis

    NASA Technical Reports Server (NTRS)

    Sikora, Scott E.

    1990-01-01

    The Model Authoring System is a prototype software application for generating fault tree analyses and failure mode and effects analyses for circuit designs. Utilizing established artificial intelligence and expert system techniques, the circuits are modeled as a frame-based knowledge base in an expert system shell, which allows the use of object oriented programming and an inference engine. The behavior of the circuit is then captured through IF-THEN rules, which then are searched to generate either a graphical fault tree analysis or failure modes and effects analysis. Sophisticated authoring techniques allow the circuit to be easily modeled, permit its behavior to be quickly defined, and provide abstraction features to deal with complexity.

  15. Space applications of artificial intelligence; Proceedings of the Annual Goddard Conference, Greenbelt, MD, May 16, 17, 1989

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor); Dent, Carolyn P. (Editor)

    1989-01-01

    Theoretical and implementation aspects of AI systems for space applications are discussed in reviews and reports. Sections are devoted to planning and scheduling, fault isolation and diagnosis, data management, modeling and simulation, and development tools and methods. Particular attention is given to a situated reasoning architecture for space repair and replace tasks, parallel plan execution with self-processing networks, the electrical diagnostics expert system for Spacelab life-sciences experiments, diagnostic tolerance for missing sensor data, the integration of perception and reasoning in fast neural modules, a connectionist model for dynamic control, and applications of fuzzy sets to the development of rule-based expert systems.

  16. Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

    PubMed

    Ashrafian, Hutan

    2017-04-01

    The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

  17. Capital Expert System

    NASA Astrophysics Data System (ADS)

    Dowell, Laurie; Gary, Jack; Illingworth, Bill; Sargent, Tom

    1987-05-01

    Gathering information, necessary forms, and financial calculations needed to generate a "capital investment proposal" is an extremely complex and difficult process. The intent of the capital investment proposal is to ensure management that the proposed investment has been thoroughly investigated and will have a positive impact on corporate goals. Meeting this requirement typically takes four or five experts a total of 12 hours to generate a "Capital Package." A Capital Expert System was therefore developed using "Personal Consultant." The completed system is hybrid and as such does not depend solely on rules but incorporates several different software packages that communicate through variables and functions passed from one to another. This paper describes the use of expert system techniques, methodology in building the knowledge base, contexts, LISP functions, data base, and special challenges that had to be overcome to create this system. The Capital Expert System is the successful result of a unique integration of artificial intelligence with business accounting, financial forms generation, and investment proposal expertise.

  18. Artificial Intelligence and Autonomy: Opportunities and Challenges

    DTIC Science & Technology

    2017-10-01

    Cleared for Public Release Artificial Intelligence & Autonomy Opportunities and Challenges Andrew Ilachinski October 2017 Copyright © 2017 CNA... Artificial Intelligence & Autonomy Opportunities and 5a. CONTRACT NUMBER N00014-16-D-5003 Challenges 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0605154N...conducted by unmanned and increasingly autonomous weapon systems. This exploratory study considers the state-of-the-art of artificial intelligence (AI

  19. Intelligent Learning System using cognitive science theory and artificial intelligence methods

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cristensen, D.L.

    1986-01-01

    This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic ismore » used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.« less

  20. The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities

    NASA Astrophysics Data System (ADS)

    Muzyka, Kamil

    2013-12-01

    On the verge of technological breakthroughs, which define and revolutionize our understanding of intelligence, cognition, and personhood, especially when speaking of artificial intelligences and mind uploads, one must consider the legal implications of granting personhood rights to artificial intelligences or emulated human entities

  1. Evaluating neural networks and artificial intelligence systems

    NASA Astrophysics Data System (ADS)

    Alberts, David S.

    1994-02-01

    Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.

  2. An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

    NASA Astrophysics Data System (ADS)

    Rodionov, S. N.; Martin, J. H.

    1999-07-01

    A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

  3. Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

    PubMed

    Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

    2009-09-01

    Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.

  4. Expert systems built by the Expert: An evaluation of OPS5

    NASA Technical Reports Server (NTRS)

    Jackson, Robert

    1987-01-01

    Two expert systems were written in OPS5 by the expert, a Ph.D. astronomer with no prior experience in artificial intelligence or expert systems, without the use of a knowledge engineer. The first system was built from scratch and uses 146 rules to check for duplication of scientific information within a pool of prospective observations. The second system was grafted onto another expert system and uses 149 additional rules to estimate the spacecraft and ground resources consumed by a set of prospective observations. The small vocabulary, the IF this occurs THEN do that logical structure of OPS5, and the ability to follow program execution allowed the expert to design and implement these systems with only the data structures and rules of another OPS5 system as an example. The modularity of the rules in OPS5 allowed the second system to modify the rulebase of the system onto which it was grafted without changing the code or the operation of that system. These experiences show that experts are able to develop their own expert systems due to the ease of programming and code reusability in OPS5.

  5. Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

    USGS Publications Warehouse

    Albert, T.M.

    1988-01-01

    In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

  6. Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.

    PubMed

    Ye, Jay J

    2015-07-01

    Pathologists' daily tasks consist of both the professional interpretation of slides and the secretarial tasks of translating these interpretations into final pathology reports, the latter of which is a time-consuming endeavor for most pathologists. To describe an artificial intelligence that performs secretarial tasks, designated as Secretary-Mimicking Artificial Intelligence (SMILE). The underling implementation of SMILE is a collection of computer programs that work in concert to "listen to" the voice commands and to "watch for" the changes of windows caused by slide bar code scanning; SMILE responds to these inputs by acting upon PowerPath Client windows (Sunquest Information Systems, Tucson, Arizona) and its Microsoft Word (Microsoft, Redmond, Washington) Add-In window, eventuating in the reports being typed and finalized. Secretary-Mimicking Artificial Intelligence also communicates relevant information to the pathologist via the computer speakers and message box on the screen. Secretary-Mimicking Artificial Intelligence performs many secretarial tasks intelligently and semiautonomously, with rapidity and consistency, thus enabling pathologists to focus on slide interpretation, which results in a marked increase in productivity, decrease in errors, and reduction of stress in daily practice. Secretary-Mimicking Artificial Intelligence undergoes encounter-based learning continually, resulting in a continuous improvement in its knowledge-based intelligence. Artificial intelligence for pathologists is both feasible and powerful. The future widespread use of artificial intelligence in our profession is certainly going to transform how we practice pathology.

  7. Second Annual Workshop on Space Operations Automation and Robotics (SOAR 1988)

    NASA Technical Reports Server (NTRS)

    Griffin, Sandy (Editor)

    1988-01-01

    Papers presented at the Second Annual Workshop on Space Operation Automation and Robotics (SOAR '88), hosted by Wright State University at Dayton, Ohio, on July 20, 21, 22, and 23, 1988, are documented herein. During the 4 days, approximately 100 technical papers were presented by experts from NASA, the USAF, universities, and technical companies. Panel discussions on Human Factors, Artificial Intelligence, Robotics, and Space Systems were held but are not documented herein. Technical topics addressed included knowledge-based systems, human factors, and robotics.

  8. Planning Complex Projects Automatically

    NASA Technical Reports Server (NTRS)

    Henke, Andrea L.; Stottler, Richard H.; Maher, Timothy P.

    1995-01-01

    Automated Manifest Planner (AMP) computer program applies combination of artificial-intelligence techniques to assist both expert and novice planners, reducing planning time by orders of magnitude. Gives planners flexibility to modify plans and constraints easily, without need for programming expertise. Developed specifically for planning space shuttle missions 5 to 10 years ahead, with modifications, applicable in general to planning other complex projects requiring scheduling of activities depending on other activities and/or timely allocation of resources. Adaptable to variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction.

  9. Living Color Frame System: PC graphics tool for data visualization

    NASA Technical Reports Server (NTRS)

    Truong, Long V.

    1993-01-01

    Living Color Frame System (LCFS) is a personal computer software tool for generating real-time graphics applications. It is highly applicable for a wide range of data visualization in virtual environment applications. Engineers often use computer graphics to enhance the interpretation of data under observation. These graphics become more complicated when 'run time' animations are required, such as found in many typical modern artificial intelligence and expert systems. Living Color Frame System solves many of these real-time graphics problems.

  10. Production Systems as a Programming Language for Artificial Intelligence Applications. Volume III.

    DTIC Science & Technology

    1976-12-01

    that the reader has some familiarity with Volume I of this report, which discusses the goals and conclusions of the thesis as a whole, and which...probably a suitable domain only for chess experts (which I am not), it will still be useful for the present thesis for the following reasons. As Berliner...chapters of this thesis do focus on such storage problems. Three other representational and low-level PS issues can be mentioned. Words are

  11. International Symposium on Spacecraft Ground Control and Flight Dynamics, SCD1, Sao Jose dos Campos, Brazil, Feb. 7-11, 1994

    NASA Astrophysics Data System (ADS)

    Rozenfeld, Pawel; Kuga, Helio Koiti; Orlando, Valcir

    An international symposium on spacecraft flight dynamics and ground control systems produced 85 papers in the areas of attitude determination and control, orbit control, satellite constellation strategies, stationkeeping, spacecraft maneuvering, orbit determination, astrodynamics, ground command and control systems, and mission operations. Several papers included discussions on the application of artificial intelligence, neural networks, expert systems, and ion propulsion. For individual titles, see A95-89098 through A95-89182.

  12. The Calculus of Uncertainty in Artificial Intelligence and Expert Systems. Proceedings of a Conference Held on December 28-29, 1984.

    DTIC Science & Technology

    1986-01-15

    within that - group , has led naturally to the study of the possible role of belief functions in medicine (Gordon & Shortliffe, 1984). Much attention is...Street ,- Washington, DC 20052 Arlington, VA 22217 HENRY SOLOMON BEN P. WISE Graduate School of Arts & Carnegie-Mellon University Sciences Robotics...Bayesian methods and place the theory of belief functions in this iii--’ historical context. Sections 3 studies some strands of the development within

  13. Combining real-time monitoring and knowledge-based analysis in MARVEL

    NASA Technical Reports Server (NTRS)

    Schwuttke, Ursula M.; Quan, A. G.; Angelino, R.; Veregge, J. R.

    1993-01-01

    Real-time artificial intelligence is gaining increasing attention for applications in which conventional software methods are unable to meet technology needs. One such application area is the monitoring and analysis of complex systems. MARVEL, a distributed monitoring and analysis tool with multiple expert systems, was developed and successfully applied to the automation of interplanetary spacecraft operations at NASA's Jet Propulsion Laboratory. MARVEL implementation and verification approaches, the MARVEL architecture, and the specific benefits that were realized by using MARVEL in operations are described.

  14. Northeast Artificial Intelligence Consortium (NAIC). Volume 3. The Versatile Maintenance Expert System (VMES)

    DTIC Science & Technology

    1990-12-01

    expected values. However, because the same good /bad output pattern of a device always gives rise to the same initial ordering, the method has its limitation...For any device and good /bad output pattern, it is easy to come up with an example on which the method does poorly in the sense that the actual...submodule is hss likely to be faulty if it is connec d to more good primary outputs. Initially, candidates are ordered according to their relat -nships with

  15. AiGERM: A logic programming front end for GERM

    NASA Technical Reports Server (NTRS)

    Hashim, Safaa H.

    1990-01-01

    AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ.

  16. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    DOT National Transportation Integrated Search

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  17. Toward a computational theory for motion understanding: The expert animators model

    NASA Technical Reports Server (NTRS)

    Mohamed, Ahmed S.; Armstrong, William W.

    1988-01-01

    Artificial intelligence researchers claim to understand some aspect of human intelligence when their model is able to emulate it. In the context of computer graphics, the ability to go from motion representation to convincing animation should accordingly be treated not simply as a trick for computer graphics programmers but as important epistemological and methodological goal. In this paper we investigate a unifying model for animating a group of articulated bodies such as humans and robots in a three-dimensional environment. The proposed model is considered in the framework of knowledge representation and processing, with special reference to motion knowledge. The model is meant to help setting the basis for a computational theory for motion understanding applied to articulated bodies.

  18. A knowledge-based system for controlling automobile traffic

    NASA Technical Reports Server (NTRS)

    Maravas, Alexander; Stengel, Robert F.

    1994-01-01

    Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

  19. Users manual for an expert system (HSPEXP) for calibration of the hydrological simulation program; Fortran

    USGS Publications Warehouse

    Lumb, A.M.; McCammon, R.B.; Kittle, J.L.

    1994-01-01

    Expert system software was developed to assist less experienced modelers with calibration of a watershed model and to facilitate the interaction between the modeler and the modeling process not provided by mathematical optimization. A prototype was developed with artificial intelligence software tools, a knowledge engineer, and two domain experts. The manual procedures used by the domain experts were identified and the prototype was then coded by the knowledge engineer. The expert system consists of a set of hierarchical rules designed to guide the calibration of the model through a systematic evaluation of model parameters. When the prototype was completed and tested, it was rewritten for portability and operational use and was named HSPEXP. The watershed model Hydrological Simulation Program--Fortran (HSPF) is used in the expert system. This report is the users manual for HSPEXP and contains a discussion of the concepts and detailed steps and examples for using the software. The system has been tested on watersheds in the States of Washington and Maryland, and the system correctly identified the model parameters to be adjusted and the adjustments led to improved calibration.

  20. Expert system application education project

    NASA Technical Reports Server (NTRS)

    Gonzelez, Avelino J.; Ragusa, James M.

    1988-01-01

    Artificial intelligence (AI) technology, and in particular expert systems, has shown potential applicability in many areas of operation at the Kennedy Space Center (KSC). In an era of limited resources, the early identification of good expert system applications, and their segregation from inappropriate ones can result in a more efficient use of available NASA resources. On the other hand, the education of students in a highly technical area such as AI requires an extensive hands-on effort. The nature of expert systems is such that proper sample applications for the educational process are difficult to find. A pilot project between NASA-KSC and the University of Central Florida which was designed to simultaneously address the needs of both institutions at a minimum cost. This project, referred to as Expert Systems Prototype Training Project (ESPTP), provided NASA with relatively inexpensive development of initial prototype versions of certain applications. University students likewise benefit by having expertise on a non-trivial problem accessible to them at no cost. Such expertise is indispensible in a hands-on training approach to developing expert systems.

  1. Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

    NASA Technical Reports Server (NTRS)

    Stephan, Amy; Erikson, Carol A.

    1991-01-01

    As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

  2. Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

    ERIC Educational Resources Information Center

    Elsom-Cook, Mark

    The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

  3. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part C: Basic AI topics

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1983-01-01

    Readily understandable overviews of search oriented problem solving, knowledge representation, and computational logic are provided. Mechanization, automation and artificial intelligence are discussed as well as how they interrelate.

  4. A Primer for Problem Solving Using Artificial Intelligence.

    ERIC Educational Resources Information Center

    Schell, George P.

    1988-01-01

    Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)

  5. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    NASA Technical Reports Server (NTRS)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

  6. A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems

    DTIC Science & Technology

    1990-11-01

    Intelligence Systems," in Distributed Artifcial Intelligence , vol. II, L. Gasser and M. Huhns (eds), Pitman, London, 1989, pp. 413-430. Shaw, M. Harrow, B...IDTIC FILE COPY A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems N Michael I. Shaw...SUBTITLE 5. FUNDING NUMBERS A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems 6

  7. Diagnosis of diabetes diseases using an Artificial Immune Recognition System2 (AIRS2) with fuzzy K-nearest neighbor.

    PubMed

    Chikh, Mohamed Amine; Saidi, Meryem; Settouti, Nesma

    2012-10-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disease dataset used in our work is retrieved from UCI machine learning repository. The performances of the AIRS2 and MAIRS2 are evaluated regarding classification accuracy, sensitivity and specificity values. The highest classification accuracy obtained when applying the AIRS2 and MAIRS2 using 10-fold cross-validation was, respectively 82.69% and 89.10%.

  8. 2017 Cybersecurity Workshop: Readouts from Working Groups - Video Text

    Science.gov Websites

    applicability of artificial intelligence to search for cybersecurity gaps in our existing SKATA networks. Second primarily renewable that all back each other up; that are all highly intelligent, artificial intelligence we have in cyber security, digital technologies, artificial intelligence. We think that that would

  9. An intelligent interface for satellite operations: Your Orbit Determination Assistant (YODA)

    NASA Technical Reports Server (NTRS)

    Schur, Anne

    1988-01-01

    An intelligent interface is often characterized by the ability to adapt evaluation criteria as the environment and user goals change. Some factors that impact these adaptations are redefinition of task goals and, hence, user requirements; time criticality; and system status. To implement adaptations affected by these factors, a new set of capabilities must be incorporated into the human-computer interface design. These capabilities include: (1) dynamic update and removal of control states based on user inputs, (2) generation and removal of logical dependencies as change occurs, (3) uniform and smooth interfacing to numerous processes, databases, and expert systems, and (4) unobtrusive on-line assistance to users of concepts were applied and incorporated into a human-computer interface using artificial intelligence techniques to create a prototype expert system, Your Orbit Determination Assistant (YODA). YODA is a smart interface that supports, in real teime, orbit analysts who must determine the location of a satellite during the station acquisition phase of a mission. Also described is the integration of four knowledge sources required to support the orbit determination assistant: orbital mechanics, spacecraft specifications, characteristics of the mission support software, and orbit analyst experience. This initial effort is continuing with expansion of YODA's capabilities, including evaluation of results of the orbit determination task.

  10. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    PubMed

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

  11. Statistical Software and Artificial Intelligence: A Watershed in Applications Programming.

    ERIC Educational Resources Information Center

    Pickett, John C.

    1984-01-01

    AUTOBJ and AUTOBOX are revolutionary software programs which contain the first application of artificial intelligence to statistical procedures used in analysis of time series data. The artificial intelligence included in the programs and program features are discussed. (JN)

  12. Artificial intelligence in astronomy - a forecast.

    NASA Astrophysics Data System (ADS)

    Adorf, H. M.

    Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

  13. Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems.

    PubMed

    Fiuzy, Mohammad; Haddadnia, Javad; Mollania, Nasrin; Hashemian, Maryam; Hassanpour, Kazem

    2012-01-01

    Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA", which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA). We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%" on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples.

  14. Development of the Spacecraft Materials Selector Expert System

    NASA Technical Reports Server (NTRS)

    Pippin, H. G.

    2000-01-01

    A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft is being developed under contract to the NASA SEE program. An artificial intelligence software package, the Boeing Expert System Tool (BEST), contains an inference engine used to operate knowledge bases constructed to selectively recall and distribute information about materials performance in space applications. This same system is used to make estimates of the environmental exposures expected for a given space flight. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described in this paper. A case history for a planned flight experiment on ISS is shown as an example of the use of the SMS, and capabilities and limitations of the knowledge base are discussed.

  15. Structure of the knowledge base for an expert labeling system

    NASA Technical Reports Server (NTRS)

    Rajaram, N. S.

    1981-01-01

    One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.

  16. Knowledge-based diagnosis for aerospace systems

    NASA Technical Reports Server (NTRS)

    Atkinson, David J.

    1988-01-01

    The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

  17. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

    PubMed Central

    Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

    2016-01-01

    Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

  18. Galen-In-Use: using artificial intelligence terminology tools to improve the linguistic coherence of a national coding system for surgical procedures.

    PubMed

    Rodrigues, J M; Trombert-Paviot, B; Baud, R; Wagner, J; Meusnier-Carriot, F

    1998-01-01

    GALEN has developed a language independent common reference model based on a medically oriented ontology and practical tools and techniques for managing healthcare terminology including natural language processing. GALEN-IN-USE is the current phase which applied the modelling and the tools to the development or the updating of coding systems for surgical procedures in different national coding centers co-operating within the European Federation of Coding Centre (EFCC) to create a language independent knowledge repository for multicultural Europe. We used an integrated set of artificial intelligence terminology tools named CLAssification Manager workbench to process French professional medical language rubrics into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation we generate controlled French natural language. The French national coding centre is then able to retrieve the initial professional rubrics with different categories of concepts, to compare the professional language proposed by expert clinicians to the French generated controlled vocabulary and to finalize the linguistic labels of the coding system in relation with the meanings of the conceptual system structure.

  19. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

    PubMed Central

    Popovič, Aleš

    2016-01-01

    Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge. PMID:27313604

  20. An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.

    PubMed

    Castelli, Mauro; Manzoni, Luca; Popovič, Aleš

    2016-01-01

    Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.

  1. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

    PubMed

    Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

    2016-01-14

    Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

  2. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    NASA Astrophysics Data System (ADS)

    Krishnan, Govindarajapuram Subramaniam

    1997-12-01

    The National Aeronautics & Space Administration (NASA), the European Space Agency (ESA), and the Canadian Space Agency (CSA) missions involve the performance of scientific experiments in Space. Instruments used in such experiments are fabricated using electronic parts such as microcircuits, inductors, capacitors, diodes, transistors, etc. For instruments to perform reliably the selection of commercial parts must be monitored and strictly controlled. The process used to achieve this goal is by a manual review and approval of every part used to build the instrument. The present system to select and approve parts for space applications is manual, inefficient, inconsistent, slow and tedious, and very costly. In this dissertation a computer based decision support model is developed for implementing this process using artificial intelligence concepts based on the current information (expert sources). Such a model would result in a greater consistency, accuracy, and timeliness of evaluation. This study presents the methodology of development and features of the model, and the analysis of the data pertaining to the performance of the model in the field. The model was evaluated for three different part types by experts from three different space agencies. The results show that the model was more consistent than the manual evaluation for all part types considered. The study concludes with the cost and benefits analysis of implementing the models and shows that implementation of the model will result in significant cost savings. Other implementation details are highlighted.

  3. The blackboard model - A framework for integrating multiple cooperating expert systems

    NASA Technical Reports Server (NTRS)

    Erickson, W. K.

    1985-01-01

    The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.

  4. [Advances in the research of application of artificial intelligence in burn field].

    PubMed

    Li, H H; Bao, Z X; Liu, X B; Zhu, S H

    2018-04-20

    Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

  5. Raising the AIQ of the Space Station

    NASA Technical Reports Server (NTRS)

    Lum, Henry; Heer, Ewald

    1987-01-01

    Expert systems and robotics technologies are to be significantly advanced during the Space Station program. Artificial intelligence systems (AI) on the Station will include 'scars', which will permit upgrading the AI capabilities as the Station evolves to autonomy. NASA-Ames is managing the development of the AI systems through a series of demonstrations, the first, controlling a single subsystem, to be performed in 1988. The capabilities being integrated into the first demonstration are described; however, machine learning and goal-driven natural language understanding will not reach a prototype stage until the mid-1990s. Steps which will be taken to endow the computer systems with the ability to move from heuristic reasoning to factual knowledge, i.e., learning from experience, are explored. It is noted that the development of Space Station expert systems depends on the development of experts in Station operations, which will not happen until the Station has been used extensively by crew members.

  6. Development of an expert data reduction assistant

    NASA Technical Reports Server (NTRS)

    Miller, Glenn E.; Johnston, Mark D.; Hanisch, Robert J.

    1993-01-01

    We propose the development of an expert system tool for the management and reduction of complex datasets. the proposed work is an extension of a successful prototype system for the calibration of CCD (charge coupled device) images developed by Dr. Johnston in 1987. (ref.: Proceedings of the Goddard Conference on Space Applications of Artificial Intelligence). The reduction of complex multi-parameter data sets presents severe challenges to a scientist. Not only must a particular data analysis system be mastered, (e.g. IRAF/SDAS/MIDAS), large amounts of data can require many days of tedious work and supervision by the scientist for even the most straightforward reductions. The proposed Expert Data Reduction Assistant will help the scientist overcome these obstacles by developing a reduction plan based on the data at hand and producing a script for the reduction of the data in a target common language.

  7. Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

    PubMed

    Brasil, L M; de Azevedo, F M; Barreto, J M

    2001-09-01

    This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

  8. Validation of an expert system intended for research in distributed artificial intelligence

    NASA Technical Reports Server (NTRS)

    Grossner, C.; Lyons, J.; Radhakrishnan, T.

    1991-01-01

    The expert system discussed in this paper is designed to function as a testbed for research on cooperating expert systems. Cooperating expert systems are members of an organization which dictates the manner in which the expert systems will interact when solving a problem. The Blackbox Expert described in this paper has been constructed using the C Language Integrated Production System (CLIPS), C++, and X windowing environment. CLIPS is embedded in a C++ program which provides objects that are used to maintain the state of the Blackbox puzzle. These objects are accessed by CLIPS rules through user-defined functions calls. The performance of the Blackbox Expert is validated by experimentation. A group of people are asked to solve a set of test cases for the Blackbox puzzle. A metric has been devised which evaluates the 'correctness' of a solution proposed for a test case of Blackbox. Using this metric and the solutions proposed by the humans, each person receives a rating for their ability to solve the Blackbox puzzle. The Blackbox Expert solves the same set of test cases and is assigned a rating for its ability. Then the rating obtained by the Blackbox Expert is compared with the ratings of the people, thus establishing the skill level of our expert system.

  9. Analysis and Implementation of Robust Grasping Behaviors

    DTIC Science & Technology

    1990-05-01

    34 Technical Report 992, MIT Artificial Intelligence Laboratory, Cambridge, MA, May, 1987. 2. Brooks, R. A. "Achieving Artifci &l Intelligence Through...DTIu FILE COPY Technical Report 1237 ’Analysis and Implementation of NRobust Grasping Behaviors Camille Z. Chammas MIT Artificial Intelligence ...describes research conducted at the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the laboratory’s

  10. An Approach to Object Recognition: Aligning Pictorial Descriptions.

    DTIC Science & Technology

    1986-12-01

    PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

  11. Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,

    DTIC Science & Technology

    1981-05-08

    STATEMENT ........................ 8 Artificial Intellegence Versus Supervisory Control ....... 8 Computer Generation of Operator Feedback...operator. Artificial Intelligence Versus Supervisory Control The use of computers to aid human operators can be divided into two catagories: artificial ...operator. Artificial intelligence ( A. I. ) attempts to give the computer maximum intelligence and to replace all operator functions by the computer

  12. Artificial Intelligence in Astronomy

    NASA Astrophysics Data System (ADS)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  13. The Artificial Intelligence Applications to Learning Programme.

    ERIC Educational Resources Information Center

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  14. Artificial Intelligence and Language Comprehension.

    ERIC Educational Resources Information Center

    National Inst. of Education (DHEW), Washington, DC. Basic Skills Group. Learning Div.

    The three papers in this volume concerning artificial intelligence and language comprehension were commissioned by the National Institute of Education to further the understanding of the cognitive processes that enable people to comprehend what they read. The first paper, "Artificial Intelligence and Language Comprehension," by Terry Winograd,…

  15. A Research Program on Artificial Intelligence in Process Engineering.

    ERIC Educational Resources Information Center

    Stephanopoulos, George

    1986-01-01

    Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…

  16. Transforming Systems Engineering through Model-Centric Engineering

    DTIC Science & Technology

    2018-02-28

    intelligence (e.g., Artificial Intelligence , etc.), because they provide a means for representing knowledge. We see these capabilities coming to use in both...level, including:  Performance is measured by degree of success of a mission  Artificial Intelligence (AI) is applied to counterparties so that they...Modeling, Artificial Intelligence , Simulation and Modeling, 1989. [140] SAE ARP4761. Guidelines and Methods for Conducting the Safety Assessment Process

  17. An expert system based on principal component analysis, artificial immune system and fuzzy k-NN for diagnosis of valvular heart diseases.

    PubMed

    Sengur, Abdulkadir

    2008-03-01

    In the last two decades, the use of artificial intelligence methods in medical analysis is increasing. This is mainly because the effectiveness of classification and detection systems have improved a great deal to help the medical experts in diagnosing. In this work, we investigate the use of principal component analysis (PCA), artificial immune system (AIS) and fuzzy k-NN to determine the normal and abnormal heart valves from the Doppler heart sounds. The proposed heart valve disorder detection system is composed of three stages. The first stage is the pre-processing stage. Filtering, normalization and white de-noising are the processes that were used in this stage. The feature extraction is the second stage. During feature extraction stage, wavelet packet decomposition was used. As a next step, wavelet entropy was considered as features. For reducing the complexity of the system, PCA was used for feature reduction. In the classification stage, AIS and fuzzy k-NN were used. To evaluate the performance of the proposed methodology, a comparative study is realized by using a data set containing 215 samples. The validation of the proposed method is measured by using the sensitivity and specificity parameters; 95.9% sensitivity and 96% specificity rate was obtained.

  18. A self-taught artificial agent for multi-physics computational model personalization.

    PubMed

    Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

    2016-12-01

    Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

  19. Dynamical Systems and Motion Vision.

    DTIC Science & Technology

    1988-04-01

    TASK Artificial Inteligence Laboratory AREA I WORK UNIT NUMBERS 545 Technology Square . Cambridge, MA 02139 C\\ II. CONTROLLING OFFICE NAME ANO0 ADDRESS...INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I.Memo No. 1037 April, 1988 Dynamical Systems and Motion Vision Joachim Heel Abstract: In this... Artificial Intelligence L3 Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory’s [1 Artificial Intelligence Research is

  20. Northeast Artificial Intelligence Consortium (NAIC). Volume 2. Discussing, Using, and Recognizing Plans

    DTIC Science & Technology

    1990-12-01

    knowledge and meta-reasoning. In Proceedings of EP14-85 ("Encontro Portugues de Inteligencia Artificial "), pages 138-154, Oporto, Portugal, 1985. [19] N, J...See reverse) 7. PERFORMING ORGANIZATION NAME(S) AND ADORESS(ES) 8. PERFORMING ORGANIZATION Northeast Artificial Intelligence...ABSTRACTM-2.,-- The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and

  1. Artificial Intelligence Study (AIS).

    DTIC Science & Technology

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  2. An analysis of the application of AI to the development of intelligent aids for flight crew tasks

    NASA Technical Reports Server (NTRS)

    Baron, S.; Feehrer, C.

    1985-01-01

    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

  3. Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

    ERIC Educational Resources Information Center

    Buckland, Michael K.; Florian, Doris

    1991-01-01

    Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

  4. The Case for Artificial Intelligence in Medicine

    PubMed Central

    Reggia, James A.

    1983-01-01

    Current artificial intelligence (AI) technology can be viewed as producing “systematic artifacts” onto which we project an interpretation of intelligent behavior. One major benefit this technology could bring to medicine is help with handling the tremendous and growing volume of medical knowledge. The reader is led to a vision of the medical library of tomorrow, an interactive, artificially intelligent knowledge source that is fully and directly integrated with daily patient care.

  5. Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

    DTIC Science & Technology

    1988-03-01

    logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

  6. Knowledge-Based Software Development Tools

    DTIC Science & Technology

    1993-09-01

    GREEN, C., AND WESTFOLD, S. Knowledge-based programming self-applied. In Machine Intelligence 10, J. E. Hayes, D. Mitchie, and Y. Pao, Eds., Wiley...Technical Report KES.U.84.2, Kestrel Institute, April 1984. [181 KORF, R. E. Toward a model of representation changes. Artificial Intelligence 14, 1...Artificial Intelligence 27, 1 (February 1985), 43-96. Replinted in Readings in Artificial Intelligence and Software Engineering, C. Rich •ad R. Waters

  7. Actors: A Model of Concurrent Computation in Distributed Systems.

    DTIC Science & Technology

    1985-06-01

    Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SY𔃿TEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI

  8. Spatial information technologies for remote sensing today and tomorrow; Proceedings of the Ninth Pecora Symposium, Sioux Falls, SD, October 2-4, 1984

    NASA Technical Reports Server (NTRS)

    1984-01-01

    Topics discussed at the symposium include hardware, geographic information system (GIS) implementation, processing remotely sensed data, spatial data structures, and NASA programs in remote sensing information systems. Attention is also given GIS applications, advanced techniques, artificial intelligence, graphics, spatial navigation, and classification. Papers are included on the design of computer software for geographic image processing, concepts for a global resource information system, algorithm development for spatial operators, and an application of expert systems technology to remotely sensed image analysis.

  9. Use of artificial intelligence in severe accident diagnosis for PWRs

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wu, Zheng; Okrent, D.; Kastenberg, W.E.

    1995-12-31

    A combination approach of an expert system and neural networks is used to implement a prototype severe accident diagnostic system which would monitor the progression of the severe accident and provide necessary plant status information to assist the plant staff in accident management during the accident. The station blackout accident in a pressurized water reactor (PWR) is used as the study case. The current phase of research focus is on distinguishing different primary system failure modes and following the accident transient before and up to vessel breach.

  10. Power to the People: Addressing Big Data Challenges in Neuroscience by Creating a New Cadre of Citizen Neuroscientists.

    PubMed

    Roskams, Jane; Popović, Zoran

    2016-11-02

    Global neuroscience projects are producing big data at an unprecedented rate that informatic and artificial intelligence (AI) analytics simply cannot handle. Online games, like Foldit, Eterna, and Eyewire-and now a new neuroscience game, Mozak-are fueling a people-powered research science (PPRS) revolution, creating a global community of "new experts" that over time synergize with computational efforts to accelerate scientific progress, empowering us to use our collective cerebral talents to drive our understanding of our brain. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. The use of artificially intelligent agents with bounded rationality in the study of economic markets

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rajan, V.; Slagle, J.R.

    The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

  12. What Is Artificial Intelligence Anyway?

    ERIC Educational Resources Information Center

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  13. Visiting Scholars Program

    DTIC Science & Technology

    2016-09-01

    other associated grants. 15. SUBJECT TERMS SUNY Poly, STEM, Artificial Intelligence , Command and Control 16. SECURITY CLASSIFICATION OF: 17...neuromorphic system has the potential to be widely used in a high-efficiency artificial intelligence system. Simulation results have indicated that the...novel multiresolution fusion and advanced fusion performance evaluation tool for an Artificial Intelligence based natural language annotation engine for

  14. The Joint Tactical Aerial Resupply Vehicle Impact on Sustainment Operations

    DTIC Science & Technology

    2017-06-09

    Artificial Intelligence , Sustainment Operations, Rifle Company, Autonomous Aerial Resupply, Joint Tactical Autonomous Aerial Resupply System 16...Integrations and Development System AI Artificial Intelligence ARCIC Army Capabilities Integration Center ARDEC Armament Research, Development and...semi- autonomous systems, and fully autonomous systems. Autonomy of machines depends on sophisticated software, including Artificial Intelligence

  15. Artificial Intelligence Measurement System, Overview and Lessons Learned. Final Project Report.

    ERIC Educational Resources Information Center

    Baker, Eva L.; Butler, Frances A.

    This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…

  16. The Potential of Artificial Intelligence in Aids for the Disabled.

    ERIC Educational Resources Information Center

    Boyer, John J.

    The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

  17. Computer science, artificial intelligence, and cybernetics: Applied artificial intelligence in Japan

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rubinger, B.

    1988-01-01

    This sourcebook provides information on the developments in artificial intelligence originating in Japan. Spanning such innovations as software productivity, natural language processing, CAD, and parallel inference machines, this volume lists leading organizations conducting research or implementing AI systems, describes AI applications being pursued, illustrates current results achieved, and highlights sources reporting progress.

  18. Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants

    NASA Astrophysics Data System (ADS)

    Masri Husam Fayiz, Al

    2017-01-01

    The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms.

  19. The importance of motivation and emotion for explaining human cognition.

    PubMed

    Güss, C Dominik; Dörner, Dietrich

    2017-01-01

    Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

  20. Tools and technologies for expert systems: A human factors perspective

    NASA Technical Reports Server (NTRS)

    Rajaram, Navaratna S.

    1987-01-01

    It is widely recognized that technologies based on artificial intelligence (AI), especially expert systems, can make significant contributions to the productivity and effectiveness of operations of information and knowledge intensive organizations such as NASA. At the same time, these being relatively new technologies, there is the problem of transfering technology to key personnel of such organizations. The problems of examining the potential of expert systems and of technology transfer is addressed in the context of human factors applications. One of the topics of interest was the investigation of the potential use of expert system building tools, particularly NEXPERT as a technology transfer medium. Two basic conclusions were reached in this regard. First, NEXPERT is an excellent tool for rapid prototyping of experimental expert systems, but not ideal as a delivery vehicle. Therefore, it is not a substitute for general purpose system implementation languages such a LISP or C. This assertion probably holds for nearly all such tools on the market today. Second, an effective technology transfer mechanism is to formulate and implement expert systems for problems which members of the organization in question can relate to. For this purpose, the LIghting EnGineering Expert (LIEGE) was implemented using NEXPERT as the tool for technology transfer and to illustrate the value of expert systems to the activities of the Man-System Division.

  1. Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

    DTIC Science & Technology

    1989-10-01

    Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

  2. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  3. Integration of perception and reasoning in fast neural modules

    NASA Technical Reports Server (NTRS)

    Fritz, David G.

    1989-01-01

    Artificial neural systems promise to integrate symbolic and sub-symbolic processing to achieve real time control of physical systems. Two potential alternatives exist. In one, neural nets can be used to front-end expert systems. The expert systems, in turn, are developed with varying degrees of parallelism, including their implementation in neural nets. In the other, rule-based reasoning and sensor data can be integrated within a single hybrid neural system. The hybrid system reacts as a unit to provide decisions (problem solutions) based on the simultaneous evaluation of data and rules. Discussed here is a model hybrid system based on the fuzzy cognitive map (FCM). The operation of the model is illustrated with the control of a hypothetical satellite that intelligently alters its attitude in space in response to an intersecting micrometeorite shower.

  4. Knowledge based systems: A preliminary survey of selected issues and techniques

    NASA Technical Reports Server (NTRS)

    Dominick, Wayne D. (Editor); Kavi, Srinu

    1984-01-01

    It is only recently that research in Artificial Intelligence (AI) is accomplishing practical results. Most of these results can be attributed to the design and use of expert systems (or Knowledge-Based Systems, KBS) - problem-solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. But many computer systems designed to see images, hear sounds, and recognize speech are still in a fairly early stage of development. In this report, a preliminary survey of recent work in the KBS is reported, explaining KBS concepts and issues and techniques used to construct them. Application considerations to construct the KBS and potential KBS research areas are identified. A case study (MYCIN) of a KBS is also provided.

  5. Intelligent data management

    NASA Technical Reports Server (NTRS)

    Campbell, William J.

    1985-01-01

    Intelligent data management is the concept of interfacing a user to a database management system with a value added service that will allow a full range of data management operations at a high level of abstraction using human written language. The development of such a system will be based on expert systems and related artificial intelligence technologies, and will allow the capturing of procedural and relational knowledge about data management operations and the support of a user with such knowledge in an on-line, interactive manner. Such a system will have the following capabilities: (1) the ability to construct a model of the users view of the database, based on the query syntax; (2) the ability to transform English queries and commands into database instructions and processes; (3) the ability to use heuristic knowledge to rapidly prune the data space in search processes; and (4) the ability to use an on-line explanation system to allow the user to understand what the system is doing and why it is doing it. Additional information is given in outline form.

  6. Behavioral personal digital assistants: The seventh generation of computing

    PubMed Central

    Stephens, Kenneth R.; Hutchison, William R.

    1992-01-01

    Skinner (1985) described two divergent approaches to developing computer systems that would behave with some approximation to intelligence. The first approach, which corresponds to the mainstream of artificial intelligence and expert systems, models intelligence as a set of production rules that incorporate knowledge and a set of heuristics for inference and symbol manipulation. The alternative is a system that models the behavioral repertoire as a network of associations between antecedent stimuli and operants, and adapts when supplied with reinforcement. The latter approach is consistent with developments in the field of “neural networks.” The authors describe how an existing adaptive network software system, based on behavior analysis and developed since 1983, can be extended to provide a new generation of software systems capable of acquiring verbal behavior. This effort will require the collaboration of the academic and commercial sectors of the behavioral community, but the end result will enable a generational change in computer systems and support for behavior analytic concepts. PMID:22477053

  7. Sniffing out the truth: clinical diagnosis using the electronic nose.

    PubMed

    Pavlou, A K; Turner, A P

    2000-02-01

    Recently the use of smell in clinical diagnosis has been rediscovered due to major advances in odour sensing technology and artificial intelligence (AI). It was well known in the past that a number of infectious or metabolic diseases could liberate specific odours characteristic of the disease stage. Later chromatographic techniques identified an enormous number of volatiles in human clinical specimens that might serve as potential disease markers. "Artificial nose" technology has been employed in several areas of medical diagnosis, including rapid detection of tuberculosis (TB), Helicobacter pylori (HP) and urinary tract infections (UTI). Preliminary results have demonstrated the possibility of identifying and characterising microbial pathogens in clinical specimens. A hybrid intelligent model of four interdependent "tools", odour generation "kits", rapid volatile delivery and recovery systems, consistent low drift sensor performance and a hybrid intelligent system of parallel neural networks (NN) and expert systems, have been applied in gastric, pulmonary and urine diagnosis. Initial clinical tests have shown that it may be possible in the near future to use electronic nose technology not only for the rapid detection of diseases such as peptic ulceration, UTI, and TB but also for the continuous dynamic monitoring of disease stages. Major advances in information and gas sensor technology could enhance the diagnostic power of future bio-electronic noses and facilitate global surveillance models of disease control and management.

  8. Artificial Intelligence Applications to High-Technology Training.

    ERIC Educational Resources Information Center

    Dede, Christopher

    1987-01-01

    Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

  9. Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

    PubMed

    Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

    2017-12-01

    To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

  10. Artificial intelligence and synthetic biology: A tri-temporal contribution.

    PubMed

    Bianchini, Francesco

    2016-10-01

    Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Protecting Networks Via Automated Defense of Cyber Systems

    DTIC Science & Technology

    2016-09-01

    autonomics, and artificial intelligence . Our conclusion is that automation is the future of cyber defense, and that advances are being made in each of...SUBJECT TERMS Internet of Things, autonomics, sensors, artificial intelligence , cyber defense, active cyber defense, automated indicator sharing...called Automated Defense of Cyber Systems, built upon three core technological components: sensors, autonomics, and artificial intelligence . Our

  12. Automated Knowledge Generation with Persistent Surveillance Video

    DTIC Science & Technology

    2008-03-26

    5 2.1 Artificial Intelligence . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Formal Logic . . . . . . . . . . . . . . . . . . . 6 2.1.2...background of Artificial Intelligence and the reasoning engines that will be applied to generate knowledge from data. Section 2.2 discusses background on...generation from persistent video. 4 II. Background In this chapter, we will discuss the background of Artificial Intelligence, Semantic Web, image

  13. Finding Edges and Lines in Images.

    DTIC Science & Technology

    1983-06-01

    34 UNCLASSI FlED , SECURITY CLASSIFICATION OF THIS PAGE ("osen Data Entered) READ INSTRUCTIONSREPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM I. REPORT...PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA&WORKUNITNUMBERS 545 Technology Square...in the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory’s artificial intelligence research

  14. Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

    DTIC Science & Technology

    1986-10-01

    rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

  15. Planning and Scheduling of Software Manufacturing Projects

    DTIC Science & Technology

    1991-03-01

    based on the previous results in social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing...planning and scheduling, and the traditional approaches to planning in artificial intelligence, and extends the techniques that have been developed by them...social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing planning and scheduling, and the

  16. Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

    DTIC Science & Technology

    1987-10-01

    include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

  17. Real Rules of Inference

    DTIC Science & Technology

    1986-01-01

    the AAAI Workshop on Uncertainty and Probability in Artificial Intelligence , 1985. [McC771 McCarthy, J. "Epistemological Problems of Aritificial ...NUMBER OF PAGES Artificial Intelligence , Data Fusion, Inference, Probability, 30 Philosophy, Inheritance Hierachies, Default Reasoning ia.PRCECODE I...prominent philosophers Glymour and Thomason even applaud the uninhibited steps: Artificial Intelligence has done us the service not only of reminding us

  18. Current Uses of Artificial Intelligence in Special Education. Abstract XI: Research & Resources on Special Education.

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

    Summarized are two reports of a federally funded project on the use of artificial intelligence in special education. The first report, "Artificial Intelligence Applications in Special Education: How Feasible?," by Alan Hofmeister and Joseph Ferrara, provides information on the development and evaluation of a series of prototype systems in special…

  19. Cultural Modelling: Literature review

    DTIC Science & Technology

    2006-09-01

    of mood and/or emotions. Our review did show some evidence that artificial intelligence research has tended to depict human decision making as...pp. 72-79). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB). Halfill, T., Sundstrom, E., Nielsen, T. M...M. & Thagard, P. (2005). Changing personalities: Towards realistic virtual characters. Journal of Experimental & Theoretical Artificial Intelligence

  20. "It's Going to Kill Us!" and Other Myths about the Future of Artificial Intelligence

    ERIC Educational Resources Information Center

    Atkinson, Robert D.

    2016-01-01

    Given the promise that artificial intelligence (AI) holds for economic growth and societal advancement, it is critical that policymakers not only avoid retarding the progress of AI innovation, but also actively support its further development and use. This report provides a primer on artificial intelligence and debunks five prevailing myths that,…

  1. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    ERIC Educational Resources Information Center

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  2. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    ERIC Educational Resources Information Center

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  3. ESD/MITRE Software Acquisition Symposium Proceedings; an ESD/Industry Dialogue held in Bedford, Massachusetts on May 6-7, 1986

    DTIC Science & Technology

    1986-05-07

    Cycle? Moderator: Christine M. Anderson Dennis D. Doe Manager of Engineering Software and Artificial Intelligence Boeing Aerospace Company In... intelligence systems development pro- cess affect the life cycle? Artificial intelligence developers seem to be the last haven for people who don’t...of Engineering Software and Artificial Intelligence at the Boeing Aerospace Company. In this capacity, Mr. Doe is the focal point for software

  4. Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

    DTIC Science & Technology

    1988-04-13

    Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

  5. The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

    PubMed

    Collado-Mesa, Fernando; Alvarez, Edilberto; Arheart, Kris

    2018-02-21

    Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program. An anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ 2 analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used. The overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401). Radiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  6. Expert systems for C3I. Volume 1. A user's introduction

    NASA Astrophysics Data System (ADS)

    Clapp, J. A.; Hockett, S. M.; Prelle, M. J.; Tallant, A. M.; Triant, D. D.

    1985-10-01

    There has been a tremendous burgeoning of interest in artificial intelligence (AI) over the last few years. Investments of commercial and government sponsors reflect a widespread belief that AI is now ready for practical applications. The area of AI currently receiving the greatest attention and investment is expert system technology. Most major high tech corporations have begun to develop expert systems, and many software houses specializing in expert system tools and applications have recently appeared. The defense community is one of the heaviest investors in expert system technology, and within this community one of the application areas receiving greatest attention is C3I. Many ESD programs are now beginning to ask whether expert system applications for C3I are ready for incorporation into ESD-developed systems, and, if so, what are the potential benefits and risks of doing so. This report was prepared to help ESD and MITRE personnel working on acquisition programs to address these issues and to gain a better understanding of what expert systems are all about. The primary intention of this report is to investigate what expert systems are and the advances that are being made in expert system technology for C3I applications. The report begins with a brief tutorial on expert systems, emphasizing how they differ from conventional software systems and what they are best at doing.

  7. Using artificial intelligence to predict the risk for posterior capsule opacification after phacoemulsification.

    PubMed

    Mohammadi, Seyed-Farzad; Sabbaghi, Mostafa; Z-Mehrjardi, Hadi; Hashemi, Hassan; Alizadeh, Somayeh; Majdi, Mercede; Taee, Farough

    2012-03-01

    To apply artificial intelligence models to predict the occurrence of posterior capsule opacification (PCO) after phacoemulsification. Farabi Eye Hospital, Tehran, Iran. Clinical-based cross-sectional study. The posterior capsule status of eyes operated on for age-related cataract and the need for laser capsulotomy were determined. After a literature review, data polishing, and expert consultation, 10 input variables were selected. The QUEST algorithm was used to develop a decision tree. Three back-propagation artificial neural networks were constructed with 4, 20, and 40 neurons in 2 hidden layers and trained with the same transfer functions (log-sigmoid and linear transfer) and training protocol with randomly selected eyes. They were then tested on the remaining eyes and the networks compared for their performance. Performance indices were used to compare resultant models with the results of logistic regression analysis. The models were trained using 282 randomly selected eyes and then tested using 70 eyes. Laser capsulotomy for clinically significant PCO was indicated or had been performed 2 years postoperatively in 40 eyes. A sample decision tree was produced with accuracy of 50% (likelihood ratio 0.8). The best artificial neural network, which showed 87% accuracy and a positive likelihood ratio of 8, was achieved with 40 neurons. The area under the receiver-operating-characteristic curve was 0.71. In comparison, logistic regression reached accuracy of 80%; however, the likelihood ratio was not measurable because the sensitivity was zero. A prototype artificial neural network was developed that predicted posterior capsule status (requiring capsulotomy) with reasonable accuracy. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

  8. Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

    DTIC Science & Technology

    1983-09-01

    AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

  9. Computer network defense through radial wave functions

    NASA Astrophysics Data System (ADS)

    Malloy, Ian J.

    The purpose of this research is to synthesize basic and fundamental findings in quantum computing, as applied to the attack and defense of conventional computer networks. The concept focuses on uses of radio waves as a shield for, and attack against traditional computers. A logic bomb is analogous to a landmine in a computer network, and if one was to implement it as non-trivial mitigation, it will aid computer network defense. As has been seen in kinetic warfare, the use of landmines has been devastating to geopolitical regions in that they are severely difficult for a civilian to avoid triggering given the unknown position of a landmine. Thus, the importance of understanding a logic bomb is relevant and has corollaries to quantum mechanics as well. The research synthesizes quantum logic phase shifts in certain respects using the Dynamic Data Exchange protocol in software written for this work, as well as a C-NOT gate applied to a virtual quantum circuit environment by implementing a Quantum Fourier Transform. The research focus applies the principles of coherence and entanglement from quantum physics, the concept of expert systems in artificial intelligence, principles of prime number based cryptography with trapdoor functions, and modeling radio wave propagation against an event from unknown parameters. This comes as a program relying on the artificial intelligence concept of an expert system in conjunction with trigger events for a trapdoor function relying on infinite recursion, as well as system mechanics for elliptic curve cryptography along orbital angular momenta. Here trapdoor both denotes the form of cipher, as well as the implied relationship to logic bombs.

  10. A Challenge to Watson

    ERIC Educational Resources Information Center

    Detterman, Douglas K.

    2011-01-01

    Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same…

  11. Cockpit automation - In need of a philosophy

    NASA Technical Reports Server (NTRS)

    Wiener, E. L.

    1985-01-01

    Concern has been expressed over the rapid development and deployment of automatic devices in transport aircraft, due mainly to the human interface and particularly the role of automation in inducing human error. The paper discusses the need for coherent philosophies of automation, and proposes several approaches: (1) flight management by exception, which states that as long as a crew stays within the bounds of regulations, air traffic control and flight safety, it may fly as it sees fit; (2) exceptions by forecasting, where the use of forecasting models would predict boundary penetration, rather than waiting for it to happen; (3) goal-sharing, where a computer is informed of overall goals, and subsequently has the capability of checking inputs and aircraft position for consistency with the overall goal or intentions; and (4) artificial intelligence and expert systems, where intelligent machines could mimic human reason.

  12. AI in medicine on its way from knowledge-intensive to data-intensive systems.

    PubMed

    Horn, W

    2001-08-01

    The last 20 years of research and development in the field of artificial intelligence in medicine (AIM) show a path from knowledge-intensive systems, which try to capture the essential knowledge of experts in a knowledge-based system, to data-intensive systems available today. Nowadays enormous amounts of information is accessible electronically. Large datasets are collected continuously monitoring physiological parameters of patients. Knowledge-based systems are needed to make use of all these data available and to help us to cope with the information explosion. In addition, temporal data analysis and intelligent information visualization can help us to get a summarized view of the change over time of clinical parameters. Integrating AIM modules into the daily-routine software environment of our care providers gives us a great chance for maintaining and improving quality of care.

  13. Development of a software tool using deterministic logic for the optimization of cochlear implant processor programming.

    PubMed

    Govaerts, Paul J; Vaerenberg, Bart; De Ceulaer, Geert; Daemers, Kristin; De Beukelaer, Carina; Schauwers, Karen

    2010-08-01

    An intelligent agent, Fitting to Outcomes eXpert, was developed to optimize and automate Cochlear implant (CI) programming. The current article describes the rationale, development, and features of this tool. Cochlear implant fitting is a time-consuming procedure to define the value of a subset of the available electric parameters based primarily on behavioral responses. It is comfort-driven with high intraindividual and interindividual variability both with respect to the patient and to the clinician. Its validity in terms of process control can be questioned. Good clinical practice would require an outcome-driven approach. An intelligent agent may help solve the complexity of addressing more electric parameters based on a range of outcome measures. A software application was developed that consists of deterministic rules that analyze the map settings in the processor together with psychoacoustic test results (audiogram, A(section sign)E phoneme discrimination, A(section sign)E loudness scaling, speech audiogram) obtained with that map. The rules were based on the daily clinical practice and the expertise of the CI programmers. The data transfer to and from this agent is either manual or through seamless digital communication with the CI fitting database and the psychoacoustic test suite. It recommends and executes modifications to the map settings to improve the outcome. Fitting to Outcomes eXpert is an operational intelligent agent, the principles of which are described. Its development and modes of operation are outlined, and a case example is given. Fitting to Outcomes eXpert is in use for more than a year now and seems to be capable to improve the measured outcome. It is argued that this novel tool allows a systematic approach focusing on outcome, reducing the fitting time, and improving the quality of fitting. It introduces principles of artificial intelligence in the process of CI fitting.

  14. Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  15. Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

    DTIC Science & Technology

    1984-12-01

    system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD

  16. A Cyber Situational Awareness Model for Network Administrators

    DTIC Science & Technology

    2017-03-01

    environments, the Internet of Things, artificial intelligence , and so on. As users’ data requirements grow more complex, they demand information...security of systems of interest. Further, artificial intelligence is a powerful concept in information technology. Therefore, new research should...look into how to use artificial intelligence to develop CSA. Human interaction with cyber systems is not making networks and their components safer

  17. Operations Monitoring Assistant System Design

    DTIC Science & Technology

    1986-07-01

    Logic. Artificial Inteligence 25(1)::75-94. January.18. 41 -Nils J. Nilsson. Problem-Solving Methods In Artificli Intelligence. .klcG raw-Hill B3ook...operations monitoring assistant (OMA) system is designed that combines operations research, artificial intelligence, and human reasoning techniques and...KnowledgeCraft (from Carnegie Group), and 5.1 (from Teknowledze). These tools incorporate the best methods of applied artificial intelligence, and

  18. The 1994 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Hostetter, Carl F. (Editor)

    1994-01-01

    This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  19. Artificial Intelligence and Its Potential as an Aid to Vocational Training and Education.

    ERIC Educational Resources Information Center

    Aleksander, I.; And Others

    This document contains a series of papers which attempt to de-mystify the subject of artificial intelligence and to show how some countries in the European Community (EC) are approaching the promotion of development and application of artificial intelligence systems that can be used as an aid in vocational training programs, as well as to…

  20. The Classification, Detection and Handling of Imperfect Theory Problems.

    DTIC Science & Technology

    1987-04-20

    Explanation-Based Learning: Failure-Driven Schema Refinement." Proceedings of the Third IEEE Conference on Artificial Intelligence Applications . Orlando...A. Rajamoney. Gerald F. DeJong Artificial Intelligence Research Group " . Coordinated Science Laboratory " University of Illinois at Urbana-Champaign...Urbana. IL 61801 . April 1987 ABSTRACT This paper also appears in the Proceedings of the Tenth International Conference on Artificial Intelligence

  1. Interdisciplinary Study on Artificial Intelligence.

    DTIC Science & Technology

    1983-07-01

    systems, uiophysics of information processing, cognitive science, and traditional artificial intelligence. The objective behi d this objective was to...information processing, cognitive science, and traditional * artificial intelligence. The objective behind this objective was to provide a vehicle for reviewing...Another departure from ’classical’ neurodynamics must be sought in the strong coupling between the micro and macroscopic scales. No other physical mechanism

  2. The 1993 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Hostetter, Carl F. (Editor)

    1993-01-01

    This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  3. Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

    DTIC Science & Technology

    2006-07-01

    4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

  4. Patient behavior and the benefits of artificial intelligence: the perils of "dangerous" literacy and illusory patient empowerment.

    PubMed

    Schulz, Peter J; Nakamoto, Kent

    2013-08-01

    Artificial intelligence can provide important support of patient health. However, limits to realized benefits can arise as patients assume an active role in their health decisions. Distinguishing the concepts of health literacy and patient empowerment, we analyze conditions that bias patient use of the Internet and limit access to and impact of artificial intelligence. Improving health literacy in the face of the Internet requires significant guidance. Patients must be directed toward the appropriate tools and also provided with key background knowledge enabling them to use the tools and capitalize on the artificial intelligence technology. Benefits of tools employing artificial intelligence to promote health cannot be realized without recognizing and addressing the patients' desires, expectations, and limitations that impact their Internet behavior. In order to benefit from artificial intelligence, patients need a substantial level of background knowledge and skill in information use-i.e., health literacy. It is critical that health professionals respond to patient search for information on the Internet, first by guiding their search to relevant, authoritative, and responsive sources, and second by educating patients about how to interpret the information they are likely to encounter. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    ERIC Educational Resources Information Center

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  6. Predicting IVF Outcome: A Proposed Web-based System Using Artificial Intelligence.

    PubMed

    Siristatidis, Charalampos; Vogiatzi, Paraskevi; Pouliakis, Abraham; Trivella, Marialenna; Papantoniou, Nikolaos; Bettocchi, Stefano

    2016-01-01

    To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome. Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network expert in an IVF setting. The system is capable to act as a routine information technology platform for the IVF unit and is capable of recalling and evaluating a vast amount of information in a rapid and automated manner to provide an objective indication on the outcome of an artificial reproductive cycle. ANNs are an exceptional candidate in providing the fertility specialist with numerical estimates to promote personalization of healthcare and adaptation of the course of treatment according to the indications. Copyright © 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  7. Integrating artificial and human intelligence into tablet production process.

    PubMed

    Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

    2014-12-01

    We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

  8. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    DTIC Science & Technology

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  9. Artificial intelligence in hematology.

    PubMed

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

  10. An expert system for integrated structural analysis and design optimization for aerospace structures

    NASA Technical Reports Server (NTRS)

    1992-01-01

    The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

  11. An expert system for integrated structural analysis and design optimization for aerospace structures

    NASA Astrophysics Data System (ADS)

    1992-04-01

    The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

  12. Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

    NASA Astrophysics Data System (ADS)

    Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

    2002-07-01

    The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

  13. AI's Philosophical Underpinnings: A Thinking Person's Walk through the Twists and Turns of Artificial Intelligence's Meandering Path

    NASA Technical Reports Server (NTRS)

    Colombano, Silvano; Norvig, Peter (Technical Monitor)

    2000-01-01

    Few human endeavors can be viewed both as extremely successful and unsuccessful at the same time. This is typically the case when goals have not been well defined or have been shifting in time. This has certainly been true of Artificial Intelligence (AI). The nature of intelligence has been the object of much thought and speculation throughout the history of philosophy. It is in the nature of philosophy that real headway is sometimes made only when appropriate tools become available. Similarly the computer, coupled with the ability to program (at least in principle) any function, appeared to be the tool that could tackle the notion of intelligence. To suit the tool, the problem of the nature of intelligence was soon sidestepped in favor of this notion: If a probing conversation with a computer could not be distinguished from a conversation with a human, then AI had been achieved. This notion became known as the Turing test, after the mathematician Alan Turing who proposed it in 1950. Conceptually rich and interesting, these early efforts gave rise to a large portion of the field's framework. Key to AI, rather than the 'number crunching' typical of computers until then, was viewed as the ability to manipulate symbols and make logical inferences. To facilitate these tasks, AI languages such as LISP and Prolog were invented and used widely in the field. One idea that emerged and enabled some success with real world problems was the notion that 'most intelligence' really resided in knowledge. A phrase attributed to Feigenbaum, one of the pioneers, was 'knowledge is the power.' With this premise, the problem is shifted from 'how do we solve problems' to 'how do we represent knowledge.' A good knowledge representation scheme could allow one to draw conclusions from given premises. Such schemes took forms such as rules,frames and scripts. It allowed the building of what became known as expert systems or knowledge based systems (KBS).

  14. Special Issue on Expert Systems for Department of Defense Training.

    ERIC Educational Resources Information Center

    Ahlers, Robert H., Ed.; And Others

    1986-01-01

    Features articles on topics related to use of expert systems for training: machine intelligence effectiveness in military systems applications; automated maneuvering board training system; intelligent tutoring system for electronic troubleshooting; technology development for intelligent maintenance advisors; design of intelligent computer assisted…

  15. Spontaneous Analogy by Piggybacking on a Perceptual System

    DTIC Science & Technology

    2013-08-01

    1992). High-level Perception, Representation, and Analogy: A Critique of Artificial Intelligence Methodology. J. Exp. Theor. Artif . Intell., 4(3...nrl.navy.mil David W. Aha Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory (Code 5510); Washington, DC 20375 david.aha...Research Laboratory,Center for Applied Research in Artificial Intelligence (Code 5510),4555 Overlook Ave., SW,Washington,DC,20375 8. PERFORMING ORGANIZATION

  16. Circumscribing Circumscription. A Guide to Relevance and Incompleteness,

    DTIC Science & Technology

    1985-10-01

    other rules of conjecture, to account for resource limitations. P "- h’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo...of conjecture, to account for resource limitations. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts...Institute of Technology. Support for the laboratory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency

  17. Why the United States Must Adopt Lethal Autonomous Weapon Systems

    DTIC Science & Technology

    2017-05-25

    2017. http://www.designboom.com/ technology /designboom-tech-predictions-robotics-12-26- 2016/. Egan, Matt. "Robots Write Thousands Of News Stories A...views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture sees artificial intelligence as an economic savior...Army, 37 pages. The East and West have differing views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture

  18. Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

    ERIC Educational Resources Information Center

    Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

    2014-01-01

    In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

  19. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    NASA Technical Reports Server (NTRS)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

  20. An American knowledge base in England - Alternate implementations of an expert system flight status monitor

    NASA Technical Reports Server (NTRS)

    Butler, G. F.; Graves, A. T.; Disbrow, J. D.; Duke, E. L.

    1989-01-01

    A joint activity between the Dryden Flight Research Facility of the NASA Ames Research Center (Ames-Dryden) and the Royal Aerospace Establishment (RAE) on knowledge-based systems has been agreed. Under the agreement, a flight status monitor knowledge base developed at Ames-Dryden has been implemented using the real-time AI (artificial intelligence) toolkit MUSE, which was developed in the UK. Here, the background to the cooperation is described and the details of the flight status monitor and a prototype MUSE implementation are presented. It is noted that the capabilities of the expert-system flight status monitor to monitor data downlinked from the flight test aircraft and to generate information on the state and health of the system for the test engineers provides increased safety during flight testing of new systems. Furthermore, the expert-system flight status monitor provides the systems engineers with ready access to the large amount of information required to describe a complex aircraft system.

  1. THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

    DTIC Science & Technology

    COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

  2. An evaluation of Ada for Al applications

    NASA Technical Reports Server (NTRS)

    Wallace, David R.

    1986-01-01

    Expert system technology seems to be the most promising type of Artificial Intelligence (AI) application for Ada. An expert system implemented with an expert system shell provides a highly structured approach that fits well with the structured approach found in Ada systems. The current commercial expert system shells use Lisp. In this highly structured situation a shell could be built that used Ada just as well. On the other hand, if it is necessary to deal with some AI problems that are not suited to expert systems, the use of Ada becomes more problematical. Ada was not designed as an AI development language, and is not suited to that. It is possible that an application developed in say, Common Lisp could be translated to Ada for actual use in a particular application, but this could be difficult. Some standard Ada packages could be developed to make such a translation easier. If the most general AI programs need to be dealt with, a Common Lisp system integrated with the Ada Environment is probably necessary. Aside from problems with language features, Ada, by itself, is not well suited to the prototyping and incremental development that is well supported by Lisp.

  3. An expert system based software sizing tool, phase 2

    NASA Technical Reports Server (NTRS)

    Friedlander, David

    1990-01-01

    A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

  4. Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems

    PubMed Central

    Fiuzy, Mohammad; Haddadnia, Javad; Mollania, Nasrin; Hashemian, Maryam; Hassanpour, Kazem

    2012-01-01

    Background Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA”, which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA). Methods We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. Results According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%” on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Conclusion Such a smart, economical, non-invasive, rapid and accurate system can be introduced as a useful diagnostic system for comprehensive treatment of breast cancer. Another advantage of this method is the possibility of diagnosing breast abnormalities. If done by experts, FNA can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. PMID:25352966

  5. The Use of CK-LOG Formalism for Knowledge Representation and Problem Solving in OPPLAN-CONSULTANT: An Expert System for Naval Operational Planning.

    DTIC Science & Technology

    1985-09-30

    further discussed in Sections 4 and 5. "=:.’. 1 ":210 NRL REPORT 8902 Notice that I have used the plural form, OBJECTS, in Fig. 2.1 to indicate that there...Washington, DC. Artificial Intelligence Center, SRI International , Menlo Park, CA, 1978. i 8. G. Gentzen, "Investigations into Logical Deduction," The...one of the form ( relatio -sm term-i term-Z) or (tuple-name term-I ... term-a) with or without the negation operator oT, and atm-exp denotes a timed

  6. A data analysis expert system for large established distributed databases

    NASA Technical Reports Server (NTRS)

    Gnacek, Anne-Marie; An, Y. Kim; Ryan, J. Patrick

    1987-01-01

    A design for a natural language database interface system, called the Deductively Augmented NASA Management Decision support System (DANMDS), is presented. The DANMDS system components have been chosen on the basis of the following considerations: maximal employment of the existing NASA IBM-PC computers and supporting software; local structuring and storing of external data via the entity-relationship model; a natural easy-to-use error-free database query language; user ability to alter query language vocabulary and data analysis heuristic; and significant artificial intelligence data analysis heuristic techniques that allow the system to become progressively and automatically more useful.

  7. Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results

    NASA Technical Reports Server (NTRS)

    Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

    1982-01-01

    A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.

  8. Automation and robotics - Key to productivity. [in industry and space

    NASA Technical Reports Server (NTRS)

    Cohen, A.

    1985-01-01

    The automated and robotic systems requirements of the NASA Space Station are prompted by maintenance, repair, servicing and assembly requirements. Trend analyses, fault diagnoses, and subsystem status assessments for the Station's electrical power, guidance, navigation, control, data management and environmental control subsystems will be undertaken by cybernetic expert systems; this will reduce or eliminate on-board or ground facility activities that would otherwise be essential, enhancing system productivity. Additional capabilities may also be obtained through the incorporation of even a limited amount of artificial intelligence in the controllers of the various Space Station systems.

  9. Structure-biodegradability study and computer-automated prediction of aerobic biodegradation of chemicals

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Klopman, G.; Tu, M.

    1997-09-01

    It is shown that a combination of two programs, MultiCASE and META, can help assess the biodegradability of industrial organic materials in the ecosystem. MultiCASE is an artificial intelligence computer program that had been trained to identify molecular substructures believed to cause or inhibit biodegradation and META is an expert system trained to predict the aerobic biodegradation products of organic molecules. These two programs can be used to help evaluate the fate of disposed chemicals by estimating their biodegradability and the nature of their biodegradation products under conditions that may model the environment.

  10. Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 2. Part A. The Versatile Maintenance Expert System (VMES) Research Project

    DTIC Science & Technology

    1989-03-01

    DI _1.3)))an also the wire connecting m419 (id (3))( (tp (P-PORT))(port-of rDim) (m88 ( l l ) (type (P-PORT)) (port-of ( DI -1.1))) (m428 (id (2)) (type (P...research on this project had two dis - tinct but overlapping phases: consolidation of work done during the previous two years and developing new...diagnosis when VMES notices a diagnostic short-cut from the dual device model is present; this will be dis - cussed in the section of "Dual Device Model

  11. Machine learning research 1989-90

    NASA Technical Reports Server (NTRS)

    Porter, Bruce W.; Souther, Arthur

    1990-01-01

    Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base.

  12. Tropical Timber Identification using Backpropagation Neural Network

    NASA Astrophysics Data System (ADS)

    Siregar, B.; Andayani, U.; Fatihah, N.; Hakim, L.; Fahmi, F.

    2017-01-01

    Each and every type of wood has different characteristics. Identifying the type of wood properly is important, especially for industries that need to know the type of timber specifically. However, it requires expertise in identifying the type of wood and only limited experts available. In addition, the manual identification even by experts is rather inefficient because it requires a lot of time and possibility of human errors. To overcome these problems, a digital image based method to identify the type of timber automatically is needed. In this study, backpropagation neural network is used as artificial intelligence component. Several stages were developed: a microscope image acquisition, pre-processing, feature extraction using gray level co-occurrence matrix and normalization of data extraction using decimal scaling features. The results showed that the proposed method was able to identify the timber with an accuracy of 94%.

  13. Acute asthma severity identification of expert system flow in emergency department

    NASA Astrophysics Data System (ADS)

    Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

    2017-11-01

    Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

  14. Artificial intelligence applications of fast optical memory access

    NASA Astrophysics Data System (ADS)

    Henshaw, P. D.; Todtenkopf, A. B.

    The operating principles and performance of rapid laser beam-steering (LBS) techniques are reviewed and illustrated with diagrams; their applicability to fast optical-memory (disk) access is evaluated; and the implications of fast access for the design of expert systems are discussed. LBS methods examined include analog deflection (source motion, wavefront tilt, and phased arrays), digital deflection (polarization modulation, reflectivity modulation, interferometric switching, and waveguide deflection), and photorefractive LBS. The disk-access problem is considered, and typical LBS requirements are listed as 38,000 beam positions, rotational latency 25 ms, one-sector rotation time 1.5 ms, and intersector space 87 microsec. The value of rapid access for increasing the power of expert systems (by permitting better organization of blocks of information) is illustrated by summarizing the learning process of the MVP-FORTH system (Park, 1983).

  15. Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

    PubMed

    Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

    2009-01-01

    In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

  16. Launching AI in NASA ground systems

    NASA Technical Reports Server (NTRS)

    Perkins, Dorothy C.; Truszkowski, Walter F.

    1990-01-01

    This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.

  17. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    DOT National Transportation Integrated Search

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  18. Artificial intelligence in robot control systems

    NASA Astrophysics Data System (ADS)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  19. A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

    PubMed Central

    Brenkus, Lawrence M.

    1984-01-01

    Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

  20. Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

    DTIC Science & Technology

    1987-04-20

    Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Top