.Verdejo, F.1985-01-01The purpose of this article is to introduce readers to the basic principles of rule-based expert systems. Four topics are discussed in subsequent sections: (1) Definition; (2) Structure of an expert system; (3) State of the art and (4) Impact and future research. (orig.).Parry, James D.; Ferrara, Joseph M.1985-01-01Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC).Orwig, Gary; Barron, Ann1992-01-01Provides 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).Ionita, C2014-01-01The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting.
TRICOR Systems, Inc. Is an industrial supplier of 2000 software, 95 software, application software, computer engineering, computer hardware, computer software, custom software, data acquisition software, data management, data visualization software.
At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub- systems. A separate C component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in dierent system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by reg.Ionita, C; Carena, F2014-01-01The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data.
Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub- systems. A separate C component queries certain SMI objects and stores their state as facts in a Prolog knowledge base.
By mining the data stored in different system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by regular shifters during the next data taking period.Renaud-Salis, J.L.1987-01-01The first expert systems prototypes intended for advising physicians on diagnosis or therapy selection have been designed more than ten years ago. However, a few of them are already in use in clinical practice after years of research and development efforts. The capabilities of these systems to reason symbolically and to mimic the hypothetico-deductive processes used by physicians distinguishes them from conventional computer programs.
Their power comes from their knowledge-base which embeds a large quantity of high-level, specialized knowledge captured from medical experts. Common methods for knowledge representation include production rules and frames. These methods also provide a mean for organizing and structuring the knowledge according to hierarchical or causal links. The best expert-systems perform at the level of the experts. They are easy to learn and use, and can communicate with the user in pseudo-natural language.
Moreover they are able to explain their line of reasoning. These capabilities make them potentially useful, usable and acceptable by physicians.
However if the problems related to difficulties and costs in building expert-systems are on the way to be solved within the next few years, forensic and ethical issues should have to be addressed before one can envisage their routine use in clinical practice fr.Tsoukalas, L.; Ikonomopoulos, A.; Uhrig, R.E.1991-01-01This paper presents a methodology that couples rule-based expert systems using fuzzy logic, to pre-trained artificial neutral networks (ANN) for the purpose of transient identification in Nuclear Power Plants (NPP). In order to provide timely concise, and task-specific information about the may aspects of the transient and to determine the state of the system based on the interpretation of potentially noisy data a model-referenced approach is utilized. In it, the expert system performs the basic interpretation and processing of the model data, and pre-trained ANNs provide the model.
Having access to a set of neural networks that typify general categories of transients, the rule based system is able to perform identification functions. Membership functions - condensing information about a transient in a form convenient for a rule-based identification system characterizing a transient - are the output of neural computations. This allows the identification function to be performed with a speed comparable to or faster than that of the temporal evolution of the system. Simulator data form major secondary system pipe rupture is used to demonstrate the methodology.
The results indicate excellent noise-tolerance for ANN's and suggest a new method for transient identification within the framework of Fuzzy Logic.Tobita, Yoshimasa; Yamaguchi, Takashi; Matsumoto, Mitsuo; Ono, Kiyoshi.1990-01-01The computer code system which can evaluate the mass balance and cycle cost in nuclear fuel cycle has been developing a PNC using an artificial intelligence technique. This system is composed of the expert system, data base and analysis codes. The expert system is the most important one in the system and the content of the expert system is explained in this paper. The expert system has the three functions. The first is the function of understanding the meaning of user's questions by natural language, the second is the function of selecting the best way to solve the problem given by the user using the knowledge which is already installed in the system, and the last is the function of answering the questions.
The knowledge of the experts installed in the expert system is represented by the frame-type rules. Therefore, the knowledge will be simply added to the system, and consequently the system will be easily extended. (author).Roysdon, Christine, Ed.; White, Howard D., Ed.1989-01-01Eleven 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.Johanson, Chris-Ellyn; Balster, Robert L.; Henningfield, Jack E.; Schuster, Charles R.; Anthony, James C.; Barthwell, Andrea G.; Coleman, John J.; Dart, Richard C.; Gorodetzky, Charles W.; O’Keeffe, Charles; Sellers, Edward M.; Vocci, Frank; Walsh, Sharon L.2010-01-01The abuse and diversion of medications is a significant public health problem.
This paper is part of a supplemental issue of Drug and Alcohol Dependence focused on the development of risk management plans and post-marketing surveillance related to minimizing this problem. The issue is based on a conference that was held in October, 2008.
An Expert Panel was formed to provide a summary of the conclusions and recommendations that emerged from the meeting involving drug abuse experts, regulators and other government agencies, pharmaceutical companies and professional and other non-governmental organizations. This paper provides a written report of this Expert Panel. Eleven conclusions and eleven recommendations emerged concerning the state of the art of this field of research, the regulatory and public health implications and recommendations for future directions.
It is concluded that special surveillance tools are needed to detect the emergence of medication abuse in a timely manner and that risk management tools can be implemented to increase the benefit to risk ratio. The scientific basis for both the surveillance and risk management tools is in its infancy, yet progress needs to be made. It is also important that the unintended consequences of increased regulation and the imposition of risk management plans be minimized. PMID:19783383.de Monchy, Allan R.; And Others1988-01-01Discusses two computer problem solving programs: rule-based expert systems and decision analysis expert systems. Explores the application of expert systems to automated chemical analyses.
Presents six factors to consider before using expert systems. (MVL).Grider, Daryl A.1994-01-01Discusses expertise, what an expert system is, what an expert system shell is, what expert systems can and cannot do, knowledge engineering and technical communicators, and planning and managing expert system projects. (SR).Winstanley, Trevor; Courvalin, Patrice2011-07-01This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets.
A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the 'big three': Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.Research Scientist in the. Knowledge Based. Computer Systems Group at NeST.
He is one of the. Expert systems encode human expertise in limited domains. Answers questions the user has and provides an explanation of its reasoning.This page provides an overview Cornell Mixing Zone Expert System water quality modeling and decision support system designed for environmental impact assessment of mixing zones resulting from wastewater discharge from point sources.Barna Iantovics2010-01-01The development of efficient and flexible agent-based medical diagnosis systems represents a recent research direction. Medical multiagent systems may improve the efficiency of traditionally developed medical computational systems, like the medical expert systems. In our previous researches, a novel cooperative medical diagnosis multiagent system called CMDS (Contract Net Based Medical Diagnosis System) was proposed. CMDS system can solve flexibly a large variety of medical diagnosis problems.Jelinek, J.B.; Weidman, S.H.1989-01-01Expert systems technology, one of the branches in the field of computerized artificial intelligence, has existed for 30 yr but only recently has been made available on commercially standard hardware and software platforms. An expert system can be defined as any method of encoding knowledge by representing that knowledge as a collection of facts or objects.
Decisions are made by the expert program by obtaining data about the problem or situation and correlating encoded facts (knowledge) to the data until a conclusion can be reached. Such conclusions can be relayed to the end user as expert advice. Realizing the potential of this technology, General Electric (GE) Nuclear Energy (GENE) has initiated a development program in expert systems applications; this technology offers the potential for packaging, distributing, and preserving nuclear experience in a software form. The paper discusses application fields, effective applications, and knowledge acquisition and knowledge verification.Tsubota, Koji1990-01-01The application of Artificial Intelligence (AI) as a tool for mineral exploration started only a decade ago. The systems that have been reported are in the most cases the expert systems that can simulate the decision of the experts or help numerical calculation for more reasonable and/or fast decision making. PNC started the development of the expert system for uranium exploration in 1983. Since then, KOGITO, a expert system to find the favorability of the target area, has been developed.
Two years ago, the second generation development, Intelligent Research Environment and Support System, IRESS was initiated aiming at the establishment of a total support system for a project evaluation. We will review our effort for development of our system and introduce the application of the Data directed Numerical method as a new tool to Ahnemland area in Australia. (author).Wittig, T.1987-01-01To illustrate where the fundamental difference between expert systems in classical diagnosis and in industrial control lie, the work of process control instrumentation is used as an example for the job of expert systems. Starting from the general process of problem-solving, two classes of expert systems can be defined accordingly. (orig.) de.Gheroghe Popescu2007-05-01Full Text Available Expert systems are built with the help of: specialised programming languages or expert system generators (shell. But this structure was reached after tens of years of work and research, because expert systems are nothing but pragmatic capitalisation of the results of research carried out in artificial intelligence and theory of knowledge.Finlay, Paul N.; And Others1991-01-01Describes a short course to expose managers to expert systems, consisting of (1) introductory lecture; (2) supervised computer tutorial; (3) lecture and discussion about knowledge structuring and modeling; and (4) small group work on a case study using computers.
(SK).Wilson, Harold O.; Burford, Anna Marie1990-01-01Delineates 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).Johnson, Yvette B.; Mccall, Kurt E.1992-01-01The Nickel Cadmium Battery Expert System-2, or 'NICBES-2', which was used by the NASA HST six-battery testbed, was subsequently converted into the Nickel Hydrogen Battery Expert System, or 'NICHES'. Accounts are presently given of this conversion process and future uses being contemplated for NICHES. NICHES will calculate orbital summary data at the end of each orbit, and store these files for trend analyses and rules-generation.Scott, C.K.1989-01-01The feasibility of using expert systems as an aid in regulatory compliance functions has been investigated. A literature review was carried out to identify applications of expert systems to regulatory affairs. A bibliography of the small literature on such applications was prepared. A prototype system, ARIES, was developed to demonstrate the use of an expert system as an aid to a Project Officer in assuring compliance with licence requirements.
The system runs on a personal computer with a graphical interface. Extensive use is made of hypertext to link interrelated rules and requirements as well as to provide an explanation facility.Olmstadt, William J.2000-01-01Discusses 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).Stock, Todd; Stachowitz, Rolf; Chang, Chin-Liang; Combs, Jacqueline1988-01-01An overview of the Expert System Validation Assistant (EVA) is being implemented in Prolog at the Lockheed AI Center. Prolog was chosen to facilitate rapid prototyping of the structure and logic checkers and since February 1987, we have implemented code to check for irrelevance, subsumption, duplication, deadends, unreachability, and cycles. The architecture chosen is extremely flexible and expansible, yet concise and complementary with the normal interactive style of Prolog.
The foundation of the system is in the connection graph representation. Rules and facts are modeled as nodes in the graph and arcs indicate common patterns between rules. The basic activity of the validation system is then a traversal of the connection graph, searching for various patterns the system recognizes as erroneous. To aid in specifying these patterns, a metalanguage is developed, providing the user with the basic facilities required to reason about the expert system. Using the metalanguage, the user can, for example, give the Prolog inference engine the goal of finding inconsistent conclusions among the rules, and Prolog will search the graph intantiations which can match the definition of inconsistency. Examples of code for some of the checkers are provided and the algorithms explained.
Technical highlights include automatic construction of a connection graph, demonstration of the use of metalanguage, the A. algorithm modified to detect all unique cycles, general-purpose stacks in Prolog, and a general-purpose database browser with pattern completion.Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan2017-08-01Heart 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.