Expert System for Automated Design Synthesis

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Barthelemy, Jean-Francois M.

1987-01-01

Expert-system computer program EXADS developed to aid users of Automated Design Synthesis (ADS) general-purpose optimization program. EXADS aids engineer in determining best combination based on knowledge of specific problem and expert knowledge stored in knowledge base. Available in two interactive machine versions. IBM PC version (LAR-13687) written in IQ-LISP. DEC VAX version (LAR-13688) written in Franz-LISP.

Techniques for capturing expert knowledge - An expert systems/hypertext approach

NASA Technical Reports Server (NTRS)

Lafferty, Larry; Taylor, Greg; Schumann, Robin; Evans, Randy; Koller, Albert M., Jr.

1990-01-01

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Using Topdown Conceptual Analysis To Accelerate The Learning Of New Domains For Knowledge Engineers & Domain Experts

NASA Astrophysics Data System (ADS)

Xuan, Albert L.; Shinghal, Rajjan

1989-03-01

As the need for knowledge-based systems increases, an increasing number of domain experts are becoming interested in taking more active part in the building of knowledge-based systems. However, such a domain expert often must deal with a large number of unfamiliar terms concepts, facts, procedures and principles based on different approaches and schools of thought. He (for brevity, we shall use masculine pronouns for both genders) may need the help of a knowledge engineer (KE) in building the knowledge-based system but may encounter a number of problems. For instance, much of the early interaction between him and the knowl edge engineer may be spent in educating each other about their seperate kinds of expertise. Since the knowledge engineer will usually be ignorant of the knowledge domain while the domain expert (DE) will have little knowledge about knowledge-based systems, a great deal of time will be wasted on these issues ad the DE and the KE train each other to the point where a fruitful interaction can occur. In some situations, it may not even be possible for the DE to find a suitable KE to work with because he has no time to train the latter in his domain. This will engender the need for the DE to be more knowledgeable about knowledge-based systems and for the KE to find methods and techniques which will allow them to learn new domains as fast as they can. In any event, it is likely that the process of building knowledge-based systems will be smooth, er and more efficient if the domain expert is knowledgeable about the methods and techniques of knowledge-based systems building.

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: Preliminary ascent knowledge requirements

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

The preliminary version of expert knowledge for the Onboard Navigation (ONAV) Ground Based Expert Trainer Ascent system for the space shuttle is presented. Included is some brief background information along with the information describing the knowledge the system will contain. Information is given on rules and heuristics, telemetry status, landing sites, inertial measurement units, and a high speed trajectory determinator (HSTD) state vector.

Expert systems applied to spacecraft fire safety

NASA Technical Reports Server (NTRS)

Smith, Richard L.; Kashiwagi, Takashi

1989-01-01

Expert systems are problem-solving programs that combine a knowledge base and a reasoning mechanism to simulate a human expert. The development of an expert system to manage fire safety in spacecraft, in particular the NASA Space Station Freedom, is difficult but clearly advantageous in the long-term. Some needs in low-gravity flammability characteristics, ventilating-flow effects, fire detection, fire extinguishment, and decision models, all necessary to establish the knowledge base for an expert system, are discussed.

Expert systems in civil engineering

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

Kostem, C.N.; Maher, M.L.

1986-01-01

This book presents the papers given at a symposium on expert systems in civil engineering. Topics considered at the symposium included problem solving using expert system techniques, construction schedule analysis, decision making and risk analysis, seismic risk analysis systems, an expert system for inactive hazardous waste site characterization, an expert system for site selection, knowledge engineering, and knowledge-based expert systems in seismic analysis.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

PubMed

Liu, Hu-Chen; Liu, Long; Lin, Qing-Lian; Liu, Nan

2013-06-01

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. The parameters in current FPN models could not accurately represent the increasingly complex knowledge-based systems, and the rules in most existing knowledge inference frameworks could not be dynamically adjustable according to propositions' variation as human cognition and thinking. In this paper, we present a knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems mentioned above. As is illustrated by the numerical example, the proposed approach can well capture experts' diversity experience, enhance the knowledge representation power, and reason the rule-based knowledge more intelligently.

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.

Shared Knowledge among Graphic Designers, Instructional Designers and Subject Matter Experts in Designing Multimedia-Based Instructional Media

ERIC Educational Resources Information Center

Razak, Rafiza Abdul

2013-01-01

The research identified and explored the shared knowledge among the instructional multimedia design and development experts comprising of subject matter expert, graphic designer and instructional designer. The knowledge shared by the team was categorized into three groups of multimedia design principles encompasses of basic principles, authoring…

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

Ontology-Based Empirical Knowledge Verification for Professional Virtual Community

ERIC Educational Resources Information Center

Chen, Yuh-Jen

2011-01-01

A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly…

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.

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.

Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1987-01-01

Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed.

A Logical Framework for Service Migration Based Survivability

DTIC Science & Technology

2016-06-24

platforms; Service Migration Strategy Fuzzy Inference System Knowledge Base Fuzzy rules representing domain expert knowledge about implications of...service migration strategy. Our approach uses expert knowledge as linguistic reasoning rules and takes service programs damage assessment, service...programs complexity, and available network capability as input. The fuzzy inference system includes four components as shown in Figure 5: (1) a knowledge

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

NASA Technical Reports Server (NTRS)

Rogers, J. L.; Barthelemy, J.-F. M.

1986-01-01

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

Various perspectives are given of the knowledge currently used in engineering design, specifically dealing with knowledge-based expert systems (KBES). Constructing an expert system often reveals inconsistencies in domain knowledge while formalizing it. The types of domain knowledge (facts, procedures, judgments, and control) differ from the classes of that knowledge (creative, innovative, and routine). The feasible tasks for expert systems can be determined based on these types and classes of knowledge. Interpretive tasks require reasoning about a task in light of the knowledge available, where generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select a knowledge-engineering tool for the domain being considered. The critical features to be weighed after classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations.

Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

NASA Technical Reports Server (NTRS)

Gomez, Fernando

1989-01-01

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

PCLIPS

NASA Technical Reports Server (NTRS)

Krolak, Patrick D.

1990-01-01

CLIPS is an expert system, created specifically to allow rapid implementation of an expert system. CLIPS is written in C, and thus needs a very small amount of memory to run. Parallel CLIPS (PCLIPS) is an extension to CLIPS which is intended to be used in situations where a group of expert systems are expected to run simultaneously and occasionally communicate with each other on an integrated network. PCLIPS is a coarse-grained data distribution system. Its main goal is to take information in one knowledge base and distribute it to other knowledge bases so that all the executing expert systems are able to use that knowledge to solve their disparate problems.

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)

Intelligent systems for human resources.

PubMed

Kline, K B

1988-11-01

An intelligent system contains knowledge about some domain; it has sophisticated decision-making processes and the ability to explain its actions. The most important aspect of an intelligent system is its ability to effectively interact with humans to teach or assist complex information processing. Two intelligent systems are Intelligent Tutoring Systems (ITs) and Expert Systems. The ITSs provide instruction to a student similar to a human tutor. The ITSs capture individual performance and tutor deficiencies. These systems consist of an expert module, which contains the knowledge or material to be taught; the student module, which contains a representation of the knowledge the student knows and does not know about the domain; and the instructional or teaching module, which selects specific knowledge to teach, the instructional strategy, and provides assistance to the student to tutor deficiencies. Expert systems contain an expert's knowledge about some domain and perform specialized tasks or aid a novice in the performance of certain tasks. The most important part of an expert system is the knowledge base. This knowledge base contains all the specialized and technical knowledge an expert possesses. For an expert system to interact effectively with humans, it must have the ability to explain its actions. Use of intelligent systems can have a profound effect on human resources. The ITSs can provide better training by tutoring on an individual basis, and the expert systems can make better use of human resources through job aiding and performing complex tasks. With increasing training requirements and "doing more with less," intelligent systems can have a positive effect on human resources.

Using Ada to implement the operations management system in a community of experts

NASA Technical Reports Server (NTRS)

Frank, M. S.

1986-01-01

An architecture is described for the Space Station Operations Management System (OMS), consisting of a distributed expert system framework implemented in Ada. The motivation for such a scheme is based on the desire to integrate the very diverse elements of the OMS while taking maximum advantage of knowledge based systems technology. Part of the foundation of an Ada based distributed expert system was accomplished in the form of a proof of concept prototype for the KNOMES project (Knowledge-based Maintenance Expert System). This prototype successfully used concurrently active experts to accomplish monitoring and diagnosis for the Remote Manipulator System. The basic concept of this software architecture is named ACTORS for Ada Cognitive Task ORganization Scheme. It is when one considers the overall problem of integrating all of the OMS elements into a cooperative system that the AI solution stands out. By utilizing a distributed knowledge based system as the framework for OMS, it is possible to integrate those components which need to share information in an intelligent manner.

Discovering the knowledge creation process of an expert group in women-friendly policy: The policy case of Seoul City.

PubMed

Oh, Young Sam; Nam, SungHee; Kim, Yuna

2016-01-01

This research explores how expert knowledge is created in the process of women-friendly policy making, based on actor network theory (ANT). To address this purpose, this study uses the "Women's Happiness in the City of Seoul" policy initiated by the local government of Seoul as one example of policy development. Research findings demonstrate that knowledge creation in expert groups followed the four stages suggested by ANT. In addition, this study found that various types of knowledge emerged from individual experts. This research elucidates the process of knowledge creation and its meanings for women-friendly policy.

A Knowledge Navigation Method for the Domain of Customers' Services of Mobile Communication Corporations in China

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

Rapidly increasing amount of mobile phone users and types of services leads to a great accumulation of complaining information. How to use this information to enhance the quality of customers' services is a big issue at present. To handle this kind of problem, the paper presents an approach to construct a domain knowledge map for navigating the explicit and tacit knowledge in two ways: building the Topic Map-based explicit knowledge navigation model, which includes domain TM construction, a semantic topic expansion algorithm and VSM-based similarity calculation; building Social Network Analysis-based tacit knowledge navigation model, which includes a multi-relational expert navigation algorithm and the criterions to evaluate the performance of expert networks. In doing so, both the customer managers and operators in call centers can find the appropriate knowledge and experts quickly and exactly. The experimental results show that the above method is very powerful for knowledge navigation.

Knowledge discovery from data and Monte-Carlo DEA to evaluate technical efficiency of mental health care in small health areas

PubMed Central

García-Alonso, Carlos; Pérez-Naranjo, Leonor

2009-01-01

Introduction Knowledge management, based on information transfer between experts and analysts, is crucial for the validity and usability of data envelopment analysis (DEA). Aim To design and develop a methodology: i) to assess technical efficiency of small health areas (SHA) in an uncertainty environment, and ii) to transfer information between experts and operational models, in both directions, for improving expert’s knowledge. Method A procedure derived from knowledge discovery from data (KDD) is used to select, interpret and weigh DEA inputs and outputs. Based on KDD results, an expert-driven Monte-Carlo DEA model has been designed to assess the technical efficiency of SHA in Andalusia. Results In terms of probability, SHA 29 is the most efficient being, on the contrary, SHA 22 very inefficient. 73% of analysed SHA have a probability of being efficient (Pe) >0.9 and 18% <0.5. Conclusions Expert knowledge is necessary to design and validate any operational model. KDD techniques make the transfer of information from experts to any operational model easy and results obtained from the latter improve expert’s knowledge.

Knowledge Engineering as a Component of the Curriculum for Medical Cybernetists.

PubMed

Karas, Sergey; Konev, Arthur

2017-01-01

According to a new state educational standard, students who have chosen medical cybernetics as their major must develop a knowledge engineering competency. Previously, in the course "Clinical cybernetics" while practicing project-based learning students were designing automated workstations for medical personnel using client-server technology. The purpose of the article is to give insight into the project of a new educational module "Knowledge engineering". Students will acquire expert knowledge by holding interviews and conducting surveys, and then they will formalize it. After that, students will form declarative expert knowledge in a network model and analyze the knowledge graph. Expert decision making methods will be applied in software on the basis of a production model of knowledge. Project implementation will result not only in the development of analytical competencies among students, but also creation of a practically useful expert system based on student models to support medical decisions. Nowadays, this module is being tested in the educational process.

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.

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969-2009.

PubMed

Homan, J Michael

2010-01-01

The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment.

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.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: ONAV entry knowledge requirements specification update

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

A revised version of expert knowledge for the onboard navigation (ONAV) entry system is given. Included is some brief background information together with information describing the knowledge that the system does contain.

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.

Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

NASA Astrophysics Data System (ADS)

Weatherwax Scott, Caroline; Tsareff, Christopher R.

1990-06-01

One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations and the ease of system use.

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.

Desiderata for product labeling of medical expert systems.

PubMed

Geissbühler, A; Miller, R A

1997-12-01

The proliferation and increasing complexity of medical expert systems raise ethical and legal concerns about the ability of practitioners to protect their patients from defective or misused software. Appropriate product labeling of expert systems can help clinical users to understand software indications and limitations. Mechanisms of action and knowledge representation schema should be explained in layperson's terminology. User qualifications and resources available for acquiring the skills necessary to understand and critique the system output should be listed. The processes used for building and maintaining the system's knowledge base are key determinants of the product's quality, and should be carefully documented. To meet these desiderata, a printed label is insufficient. The authors suggest a new, more active, model of product labeling for medical expert systems that involves embedding 'knowledge of the knowledge base', creating user-specific data, and sharing global information using the Internet.

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Evolving Expert Knowledge Bases: Applications of Crowdsourcing and Serious Gaming to Advance Knowledge Development for Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Floryan, Mark

2013-01-01

This dissertation presents a novel effort to develop ITS technologies that adapt by observing student behavior. In particular, we define an evolving expert knowledge base (EEKB) that structures a domain's information as a set of nodes and the relationships that exist between those nodes. The structure of this model is not the particularly novel…

Eyes on the prize: reflections on the impact of the evolving digital ecology on the librarian as expert intermediary and knowledge coach, 1969–2009*

PubMed Central

Homan, J. Michael

2010-01-01

Objective: The 2009 Janet Doe Lecture reflects on the continuing value and increasing return on investment of librarian-mediated services in the constantly evolving digital ecology and complex knowledge environment of the health sciences. Setting: The interrelationship of knowledge, decision making based on knowledge, technology used to access and retrieve knowledge, and the important linkage roles of expert librarian intermediaries is examined. Methodology: Professional experiences from 1969 to 2009, occurring during a time of unprecedented changes in the digital ecology of librarianship, are the base on which the evolving role and value of librarians as knowledge coaches and expert intermediaries are examined. Conclusion: Librarian-mediated services linking knowledge and critical decision making in health care have become more valuable than ever as technology continues to reshape an increasingly complex knowledge environment. PMID:20098655

The nutrition advisor expert system

NASA Technical Reports Server (NTRS)

Huse, Scott M.; Shyne, Scott S.

1991-01-01

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

How much expert knowledge is it worth to put in conceptual hydrological models?

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Zappa, Massimiliano

2017-04-01

Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

Elicitation of neurological knowledge with argument-based machine learning.

PubMed

Groznik, Vida; Guid, Matej; Sadikov, Aleksander; Možina, Martin; Georgiev, Dejan; Kragelj, Veronika; Ribarič, Samo; Pirtošek, Zvezdan; Bratko, Ivan

2013-02-01

The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation process. We are developing a neurological decision support system to help the neurologists differentiate between three types of tremors: Parkinsonian, essential, and mixed tremor (comorbidity). The system is intended to act as a second opinion for the neurologists, and most importantly to help them reduce the number of patients in the "gray area" that require a very costly further examination (DaTSCAN). We strive to elicit comprehensible and medically meaningful knowledge in such a way that it does not come at the cost of diagnostic accuracy. To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used ABML. ABML guides the expert to explain critical special cases which cannot be handled automatically by machine learning. This very efficiently reduces the expert's workload, and combines expert's knowledge with learning data. 122 patients were enrolled into the study. The classification accuracy of the final model was 91%. Equally important, the initial and the final models were also evaluated for their comprehensibility by the neurologists. All 13 rules of the final model were deemed as appropriate to be able to support its decisions with good explanations. The paper demonstrates ABML's advantage in combining machine learning and expert knowledge. The accuracy of the system is very high with respect to the current state-of-the-art in clinical practice, and the system's knowledge base is assessed to be very consistent from a medical point of view. This opens up the possibility to use the system also as a teaching tool. Copyright © 2012 Elsevier B.V. All rights reserved.

An engineering approach to the use of expert systems technology in avionics applications

NASA Technical Reports Server (NTRS)

Duke, E. L.; Regenie, V. A.; Brazee, M.; Brumbaugh, R. W.

1986-01-01

The concept of using a knowledge compiler to transform the knowledge base and inference mechanism of an expert system into a conventional program is presented. The need to accommodate real-time systems requirements in applications such as embedded avionics is outlined. Expert systems and a brief comparison of expert systems and conventional programs are reviewed. Avionics applications of expert systems are discussed before the discussions of applying the proposed concept to example systems using forward and backward chaining.

Reliability and performance evaluation of systems containing embedded rule-based expert systems

NASA Technical Reports Server (NTRS)

Beaton, Robert M.; Adams, Milton B.; Harrison, James V. A.

1989-01-01

A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

Computer Based Expert Systems.

ERIC Educational Resources Information Center

Parry, James D.; Ferrara, Joseph M.

1985-01-01

Claims 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)

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.

A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information

NASA Astrophysics Data System (ADS)

Ozbek, M. M.

2003-12-01

Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ

A knowledge-based support system for mechanical ventilation of the lungs. The KUSIVAR concept and prototype.

PubMed

Rudowski, R; Frostell, C; Gill, H

1989-09-01

The KUSIVAR is an expert system for mechanical ventilation of adult patients suffering from respiratory insufficiency. Its main objective is to provide guidance in respirator management. The knowledge base includes both qualitative, rule-based knowledge and quantitative knowledge expressed in the form of mathematical models (expert control) which is used for prediction of arterial gas tensions and optimization purposes. The system is data driven and uses a forward chaining mechanism for rule invocation. The interaction with the user will be performed in advisory, critiquing, semi-automatic and automatic modes. The system is at present in an advanced prototype stage. Prototyping is performed using KEE (Knowledge Engineering Environment) on a Sperry Explorer workstation. For further development and clinical use the expert system will be downloaded to an advanced PC. The system is intended to support therapy with a Siemens-Elema Servoventilator 900 C.

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…

Do short courses in evidence based medicine improve knowledge and skills? Validation of Berlin questionnaire and before and after study of courses in evidence based medicine

PubMed Central

Fritsche, L; Greenhalgh, T; Falck-Ytter, Y; Neumayer, H-H; Kunz, R

2002-01-01

Objective To develop and validate an instrument for measuring knowledge and skills in evidence based medicine and to investigate whether short courses in evidence based medicine lead to a meaningful increase in knowledge and skills. Design Development and validation of an assessment instrument and before and after study. Setting Various postgraduate short courses in evidence based medicine in Germany. Participants The instrument was validated with experts in evidence based medicine, postgraduate doctors, and medical students. The effect of courses was assessed by postgraduate doctors from medical and surgical backgrounds. Intervention Intensive 3 day courses in evidence based medicine delivered through tutor facilitated small groups. Main outcome measure Increase in knowledge and skills. Results The questionnaire distinguished reliably between groups with different expertise in evidence based medicine. Experts attained a threefold higher average score than students. Postgraduates who had not attended a course performed better than students but significantly worse than experts. Knowledge and skills in evidence based medicine increased after the course by 57% (mean score before course 6.3 (SD 2.9) v 9.9 (SD 2.8), P<0.001). No difference was found among experts or students in absence of an intervention. Conclusions The instrument reliably assessed knowledge and skills in evidence based medicine. An intensive 3 day course in evidence based medicine led to a significant increase in knowledge and skills. What is already known on this topicNumerous observational studies have investigated the impact of teaching evidence based medicine to healthcare professionals, with conflicting resultsMost of the studies were of poor methodological qualityWhat this study addsAn instrument assessing basic knowledge and skills required for practising evidence based medicine was developed and validatedAn intensive 3 day course on evidence based medicine for doctors from various backgrounds and training level led to a clinically meaningful improvement of knowledge and skills PMID:12468485

Novice and expert teachers' conceptions of learners' prior knowledge

NASA Astrophysics Data System (ADS)

Meyer, Helen

2004-11-01

This study presents comparative case studies of preservice and first-year teachers' and expert teachers' conceptions of the concept of prior knowledge. Kelly's (The Psychology of Personal Construct, New York: W.W. Norton, 1955) theory of personal constructs as discussed by Akerson, Flick, and Lederman (Journal of Research in Science Teaching, 2000, 37, 363-385) in relationship to prior knowledge underpins the study. Six teachers were selected to participate in the case studies based upon their level experience teaching science and their willingness to take part. The comparative case studies of the novice and expert teachers provide insights into (a) how novice and expert teachers understand the concept of prior knowledge and (b) how they use this knowledge to make instructional decisions. Data collection consisted of interviews, classroom observations, and document analysis. Findings suggest that novice teachers hold insufficient conceptions of prior knowledge and its role in instruction to effectively implement constructivist teaching practices. While expert teachers hold a complex conception of prior knowledge and make use of their students' prior knowledge in significant ways during instruction. A second finding was an apparent mismatch between the novice teachers' beliefs about their urban students' life experiences and prior knowledge and the wealth of knowledge the expert teachers found to draw upon.

An Expert System for Automating Nuclear Strike Aircraft Replacement, Aircraft Beddown, and Logistics Movement for the Theater Warfare Exercise.

DTIC Science & Technology

1989-12-01

that can be easily understood. (9) Parallelism. Several system components may need to execute in parallel. For example, the processing of sensor data...knowledge base are not accessible for processing by the database. Also in the likely case that the expert system poses a series of related queries, the...hiharken nxpfilcs’Iog - Knowledge base for the automation of loCgistics rr-ovenet T’he Ii rectorY containing the strike aircraft replacement knowledge base

Processes in construction of failure management expert systems from device design information

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

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.

Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

NASA Technical Reports Server (NTRS)

Lee, S. C.; Lollar, Louis F.

1988-01-01

The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

Toward a theory of distributed word expert natural language parsing

NASA Technical Reports Server (NTRS)

Rieger, C.; Small, S.

1981-01-01

An approach to natural language meaning-based parsing in which the unit of linguistic knowledge is the word rather than the rewrite rule is described. In the word expert parser, knowledge about language is distributed across a population of procedural experts, each representing a word of the language, and each an expert at diagnosing that word's intended usage in context. The parser is structured around a coroutine control environment in which the generator-like word experts ask questions and exchange information in coming to collective agreement on sentence meaning. The word expert theory is advanced as a better cognitive model of human language expertise than the traditional rule-based approach. The technical discussion is organized around examples taken from the prototype LISP system which implements parts of the theory.

Collective intelligence in medical diagnosis systems: A case study.

PubMed

Hernández-Chan, Gandhi S; Ceh-Varela, Edgar Eduardo; Sanchez-Cervantes, Jose L; Villanueva-Escalante, Marisol; Rodríguez-González, Alejandro; Pérez-Gallardo, Yuliana

2016-07-01

Diagnosing a patient's condition is one of the most important and challenging tasks in medicine. We present a study of the application of collective intelligence in medical diagnosis by applying consensus methods. We compared the accuracy obtained with this method against the diagnostics accuracy reached through the knowledge of a single expert. We used the ontological structures of ten diseases. Two knowledge bases were created by placing five diseases into each knowledge base. We conducted two experiments, one with an empty knowledge base and the other with a populated knowledge base. For both experiments, five experts added and/or eliminated signs/symptoms and diagnostic tests for each disease. After this process, the individual knowledge bases were built based on the output of the consensus methods. In order to perform the evaluation, we compared the number of items for each disease in the agreed knowledge bases against the number of items in the GS (Gold Standard). We identified that, while the number of items in each knowledge base is higher, the consensus level is lower. In all cases, the lowest level of agreement (20%) exceeded the number of signs that are in the GS. In addition, when all experts agreed, the number of items decreased. The use of collective intelligence can be used to increase the consensus of physicians. This is because, by using consensus, physicians can gather more information and knowledge than when obtaining information and knowledge from knowledge bases fed or populated from the knowledge found in the literature, and, at the same time, they can keep updated and collaborate dynamically. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

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

Expert systems as applied to bridges : knowledge acquisition phase : final report.

DOT National Transportation Integrated Search

1987-01-01

Presented in this report is a detailed description of the procedure to be followed to develop a knowledge-based computerized expert system for determining whether to rehabilitate, improve, replace, abandon, or just to routinely maintain an old highwa...

Knowledge Base Editor (SharpKBE)

NASA Technical Reports Server (NTRS)

Tikidjian, Raffi; James, Mark; Mackey, Ryan

2007-01-01

The SharpKBE software provides a graphical user interface environment for domain experts to build and manage knowledge base systems. Knowledge bases can be exported/translated to various target languages automatically, including customizable target languages.

Knowledge as an Aspect of Scientific Competence for Citizenship: Results of a Delphi Study in Spain

ERIC Educational Resources Information Center

España-Ramos, Enrique; González-García, Francisco José; Blanco-López, Ángel; Franco-Mariscal, Antonio Joaquín

2016-01-01

This article focuses on scientific knowledge as one aspect of the scientific competencies that citizens should ideally possess. The analysis is based on a Delphi study we conducted with Spanish experts from different science-related fields. The results showed that although the experts proposed several examples of scientific knowledge, the degree…

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.

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

SIRE: A Simple Interactive Rule Editor for NICBES

NASA Technical Reports Server (NTRS)

Bykat, Alex

1988-01-01

To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.

Multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

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.

Integrated Knowledge Based Expert System for Disease Diagnosis System

NASA Astrophysics Data System (ADS)

Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

2017-08-01

The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Exploration of Teaching Skills of Pre-Service High School Teachers' through Self-Regulated Learning Based on Learning Style

ERIC Educational Resources Information Center

Habibi; Kuswanto, Heru; Yanti, Fitri April

2017-01-01

An expert in the field of science is often difficult to teach his knowledge to students. Conversely someone who is expert in the field of education is certainly more expert in transferring knowledge. The purpose of this research is to explore the skill of teaching skill preservice of physics teacher of High School. Samples were taken randomly as…

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.

Learning processes in the professional development of mental health counselors: knowledge restructuring and illness script formation.

PubMed

Strasser, Josef; Gruber, Hans

2015-05-01

An important part of learning processes in the professional development of counselors is the integration of declarative knowledge and professional experience. It was investigated in-how-far mental health counselors at different levels of expertise (experts, intermediates, novices) differ in their availability of experience-based knowledge structures. Participants were prompted with 20 client problems. They had to explain those problems, the explanations were analyzed using think-aloud protocols. The results show that experts' knowledge is organized in script-like structures that integrate declarative knowledge and professional experience and help experts in accessing relevant information about cases. Novices revealed less integrated knowledge structures. It is concluded that knowledge restructuring and illness script formation are crucial parts of the professional learning of counselors.

A reusable knowledge acquisition shell: KASH

NASA Technical Reports Server (NTRS)

Westphal, Christopher; Williams, Stephen; Keech, Virginia

1991-01-01

KASH (Knowledge Acquisition SHell) is proposed to assist a knowledge engineer by providing a set of utilities for constructing knowledge acquisition sessions based on interviewing techniques. The information elicited from domain experts during the sessions is guided by a question dependency graph (QDG). The QDG defined by the knowledge engineer, consists of a series of control questions about the domain that are used to organize the knowledge of an expert. The content information supplies by the expert, in response to the questions, is represented in the form of a concept map. These maps can be constructed in a top-down or bottom-up manner by the QDG and used by KASH to generate the rules for a large class of expert system domains. Additionally, the concept maps can support the representation of temporal knowledge. The high degree of reusability encountered in the QDG and concept maps can vastly reduce the development times and costs associated with producing intelligent decision aids, training programs, and process control functions.

Developing Expert System for Tuberculosis Diagnose to Support Knowledge Sharing in the Era of National Health Insurance System

NASA Astrophysics Data System (ADS)

Lidya, L.

2017-03-01

National Health Insurance has been implemented since 1st January 2014. A number of new policies have been established including multilevel referral system. The multilevel referral system classified health care center into three levels, it determined that the flow of patient treatment should be started from first level health care center. There are 144 kind of diseases that must be treat in the first level which mainly consists of general physicians. Unfortunately, competence of the physician in the first level may not fulfil the standard competence yet. To improved the physisians knowledge, government has created many events to accelerate knowledge sharing. However, it still needs times and many resources to give significan results. Expert system is kind of software that provide consulting services to non-expert users in accordance with the area of its expertise. It can improved effectivity and efficiency of knowledge sharing and learning. This research was developed a model of TB diagnose expert system which comply with the standard procedure of TB diagnosis and regulation. The proposed expert system has characteristics as follows provide facility to manage multimedia clinical data, supporting the complexity of TB diagnosis (combine rule-based and case-based expert system), interactive interface, good usability, multi-platform, evolutionary.

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PubMed Central

2016-01-01

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

A machine independent expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark J.

1991-01-01

A new rule-based, machine independent analytical tool for diagnosing spacecraft anomalies, the EnviroNET expert system, was developed. Expert systems provide an effective method for storing knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms which allow approximate reasoning and inference, and the ability to attack problems not rigidly defines. The EviroNET expert system knowledge base currently contains over two hundred rules, and links to databases which include past environmental data, satellite data, and previous known anomalies. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose.

Temporal and contextual knowledge in model-based expert systems

NASA Technical Reports Server (NTRS)

Toth-Fejel, Tihamer; Heher, Dennis

1987-01-01

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.

Expert operator's associate: A knowledge based system for spacecraft control

NASA Technical Reports Server (NTRS)

Nielsen, Mogens; Grue, Klaus; Lecouat, Francois

1991-01-01

The Expert Operator's Associate (EOA) project is presented which studies the applicability of expert systems for day-to-day space operations. A prototype expert system is developed, which operates on-line with an existing spacecraft control system at the European Space Operations Centre, and functions as an 'operator's assistant' in controlling satellites. The prototype is demonstrated using an existing real-time simulation model of the MARECS-B2 telecommunication satellite. By developing a prototype system, the extent to which reliability and effectivens of operations can be enhanced by AI based support is examined. In addition the study examines the questions of acquisition and representation of the 'knowledge' for such systems, and the feasibility of 'migration' of some (currently) ground-based functions into future spaceborne autonomous systems.

Expert system for skin problem consultation in Thai traditional medicine.

PubMed

Nopparatkiat, Pornchai; na Nagara, Byaporn; Chansa-ngavej, Chuvej

2014-01-01

This paper aimed to demonstrate the research and development of a rule-based expert system for skin problem consulting in the areas of acne, melasma, freckle, wrinkle, and uneven skin tone, with recommended treatments from Thai traditional medicine knowledge. The tool selected for developing the expert system is a software program written in the PHP language. MySQL database is used to work together with PHP for building database of the expert system. The system is web-based and can be reached from anywhere with Internet access. The developed expert system gave recommendations on the skin problem treatment with Thai herbal recipes and Thai herbal cosmetics based on 416 rules derived from primary and secondary sources. The system had been tested by 50 users consisting of dermatologists, Thai traditional medicine doctors, and general users. The developed system was considered good for learning and consultation. The present work showed how such a scattered body of traditional knowledge as Thai traditional medicine and herbal recipes could be collected, organised and made accessible to users and interested parties. The expert system developed herein should contribute in a meaningful way towards preserving the knowledge and helping promote the use of Thai traditional medicine as a practical alternative medicine for the treatment of illnesses.

Cognitive task analysis for instruction in single-injection ultrasound guided-regional anesthesia

NASA Astrophysics Data System (ADS)

Gucev, Gligor V.

Cognitive task analysis (CTA) is methodology for eliciting knowledge from subject matter experts. CTA has been used to capture the cognitive processes, decision-making, and judgments that underlie expert behaviors. A review of the literature revealed that CTA has not yet been used to capture the knowledge required to perform ultrasound guided regional anesthesia (UGRA). The purpose of this study was to utilize CTA to extract knowledge from UGRA experts and to determine whether instruction based on CTA of UGRA will produce results superior to the results of traditional training. This study adds to the knowledge base of CTA in being the first one to effectively capture the expert knowledge of UGRA. The derived protocol was used in a randomized, double blinded experiment involving UGRA instruction to 39 novice learners. The results of this study strongly support the hypothesis that CTA-based instruction in UGRA is more effective than conventional clinical instruction, as measured by conceptual pre- and post-tests, performance of a simulated UGRA procedure, and time necessary for the task performance. This study adds to the number of studies that have proven the superiority of CTA-informed instruction. Finally, it produced several validated instruments that can be used in instructing and evaluating UGRA.

TARGET's role in knowledge acquisition, engineering, validation, and documentation

NASA Technical Reports Server (NTRS)

Levi, Keith R.

1994-01-01

We investigate the use of the TARGET task analysis tool for use in the development of rule-based expert systems. We found TARGET to be very helpful in the knowledge acquisition process. It enabled us to perform knowledge acquisition with one knowledge engineer rather than two. In addition, it improved communication between the domain expert and knowledge engineer. We also found it to be useful for both the rule development and refinement phases of the knowledge engineering process. Using the network in these phases required us to develop guidelines that enabled us to easily translate the network into production rules. A significant requirement for TARGET remaining useful throughout the knowledge engineering process was the need to carefully maintain consistency between the network and the rule representations. Maintaining consistency not only benefited the knowledge engineering process, but also has significant payoffs in the areas of validation of the expert system and documentation of the knowledge in the system.

Decision Support Systems for Launch and Range Operations Using Jess

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar

2007-01-01

The virtual test bed for launch and range operations developed at NASA Ames Research Center consists of various independent expert systems advising on weather effects, toxic gas dispersions and human health risk assessment during space-flight operations. An individual dedicated server supports each expert system and the master system gather information from the dedicated servers to support the launch decision-making process. Since the test bed is based on the web system, reducing network traffic and optimizing the knowledge base is critical to its success of real-time or near real-time operations. Jess, a fast rule engine and powerful scripting environment developed at Sandia National Laboratory has been adopted to build the expert systems providing robustness and scalability. Jess also supports XML representation of knowledge base with forward and backward chaining inference mechanism. Facts added - to working memory during run-time operations facilitates analyses of multiple scenarios. Knowledge base can be distributed with one inference engine performing the inference process. This paper discusses details of the knowledge base and inference engine using Jess for a launch and range virtual test bed.

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.

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.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

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

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

ESKAPE/CF: A Knowledge Acquisition Tool for Expert Systems Using Cognitive Feedback

DTIC Science & Technology

1991-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California AD-A241 815i!1! lit 1i iill 1111 !! I 1111 ST E * ODTIC OCT22 z 99I; THESIS ESKAPE /CF: A KNOWLEDGE...11. TITLE (include Security Classification) ESKAPE /CF: A KNOWLEDGE ACQUISITION TOOL FOR EXPERT SYSTEMS USING COGNITIVE FEEDBACK (U) e PERSOIAL AUTVR(Yl...tool using Cognitive Feedback ( ESKAPE /CF), based on Lens model techniques which have demonstrated effectiveness in cap- turing policy knowledge. The

Adaptation and validation of the REGEN expert system for the Central Appalachians

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system that predicts future species composition at the onset of stem exclusion using preharvest stand conditions. To extend coverage into hardwood stands of the Central Appalachians, we developed REGEN knowledge bases for four site qualities (xeric, subxeric, submesic, mesic) based on relevant literature and expert opinion. Data were collected from...

A spectral-knowledge-based approach for urban land-cover discrimination

NASA Technical Reports Server (NTRS)

Wharton, Stephen W.

1987-01-01

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

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.

Experts' views regarding Australian school-leavers' knowledge of nutrition and food systems.

PubMed

Sadegholvad, Sanaz; Yeatman, Heather; Parrish, Anne-Maree; Worsley, Anthony

2017-10-01

To explore Australian experts' views regarding strengths and gaps in school-leavers' knowledge of nutrition and food systems ( N&FS) and factors that influence that knowledge. Semi-structured interviews were conducted with 21 highly experienced food-related experts in Australia. Qualitative data were analysed thematically using Attride-Stirling's thematic network framework. Two global themes and several organising themes were identified. The first global theme, 'structural curriculum-based problems', emerged from three organising themes of: inconsistencies in provided food education programs at schools in Australia; insufficient coverage of food-related skills and food systems topics in school curricula; and the lack of trained school teachers. The second global theme, 'insufficient levels of school-leavers knowledge of N&FS ', was generated from four organising themes, which together described Australian school-leavers' poor knowledge of N&FS more broadly and knowledge translation problem for everyday practices. Study findings identified key problems relating to current school-based N&FS education programs in Australia and reported knowledge gaps in relation to N&FS among Australian school-leavers. These findings provide important guidance for N&FS curriculum development, to clearly articulate broadly-based N&FS knowledge acquisition in curriculum policy and education documents for Australian schools. © 2017 The Authors.

Concepts of Teacher Knowledge as Social Strategies

ERIC Educational Resources Information Center

Johannesson, Ingolfur Asgeir

2006-01-01

This article reviews didactical and psychologically based research on teachers' work and teacher thinking, narrative educational inquiry and studies of change in teachers' work and places them in the context of sociological theory about expert work and symbolic capital. The work of Abbott on the structure of expert work and knowledge, and Bourdieu…

"Let Your Data Tell a Story:" Climate Change Experts and Students Navigating Disciplinary Argumentation in the Classroom

ERIC Educational Resources Information Center

Walsh, Elizabeth Mary; McGowan, Veronica Cassone

2017-01-01

Science education trends promote student engagement in authentic knowledge in practice to tackle personally consequential problems. This study explored how partnering scientists and students on a social media platform supported students' development of disciplinary practice knowledge through practice-based learning with experts during two pilot…

Planning bioinformatics workflows using an expert system.

PubMed

Chen, Xiaoling; Chang, Jeffrey T

2017-04-15

Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. https://github.com/jefftc/changlab. jeffrey.t.chang@uth.tmc.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Planning bioinformatics workflows using an expert system

PubMed Central

Chen, Xiaoling; Chang, Jeffrey T.

2017-01-01

Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: jeffrey.t.chang@uth.tmc.edu PMID:28052928

Expert Systems: Implications for the Diagnosis and Treatment of Learning Disabilities.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Lubke, Margaret M.

1988-01-01

The article examines characteristics and present or potential applications of expert systems technology for diagnosis and treatment of learning disabilities. Preliminary findings indicate that expert systems can perform as well as humans in specific areas, and that the process of organizing knowledge bases for expert systems helps clarify existing…

An Analysis of the Working Memories of Expert Sport Instructors

ERIC Educational Resources Information Center

McCullick, Bryan; Schempp, Paul; Hsu, Shan-Hui; Jung, Jin Hong; Vickers, Brad; Schuknecht, Greg

2006-01-01

A distinguishing characteristic of expert teachers appears to be an excellent memory (Berliner, 1986; Tan, 1997). Possessing an excellent memory aids experts in building a substantial knowledge base relative to teaching and learning. Despite its importance, the memory skills of expert teachers have yet to be investigated. Therefore, the purpose of…

Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis.

PubMed

Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2009-01-01

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented.

Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron

2009-01-01

The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented. PMID:18971242

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.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

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.

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…

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.

MOORE: A prototype expert system for diagnosing spacecraft problems

NASA Technical Reports Server (NTRS)

Howlin, Katherine; Weissert, Jerry; Krantz, Kerry

1988-01-01

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

NASA Technical Reports Server (NTRS)

Herrin, Stephanie; Iverson, David; Spukovska, Lilly; Souza, Kenneth A. (Technical Monitor)

1994-01-01

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Plant Distribution Data Show Broader Climatic Limits than Expert-Based Climatic Tolerance Estimates

PubMed Central

Curtis, Caroline A.; Bradley, Bethany A.

2016-01-01

Background Although increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance. Methods We compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the ‘plant characteristics’ information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF) and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (ΔCN), and tested whether ΔCN was influenced by growth form or range size. Results Climate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001). The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ΔCN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ΔCN while grasses and trees had larger ΔCN for minimum precipitation. Conclusion Our results show that distribution data are consistently broader than USDA PLANTS experts’ knowledge and likely provide more robust estimates of climatic tolerance, especially for widespread forbs and grasses. These findings suggest that widely available expert-based climatic tolerance estimates underrepresent species’ fundamental niche and likely fail to capture the realized niche. PMID:27870859

Knowledge acquisition and rapid protyping of an expert system: Dealing with real world problems

NASA Technical Reports Server (NTRS)

Bailey, Patrick A.; Doehr, Brett B.

1988-01-01

The knowledge engineering and rapid prototyping phases of an expert system that does fault handling for a Solid Amine, Water Desorbed CO2 removal assembly for the Environmental Control and Life Support System for space based platforms are addressed. The knowledge acquisition phase for this project was interesting because it could not follow the textbook examples. As a result of this, a variety of methods were used during the knowledge acquisition task. The use of rapid prototyping and the need for a flexible prototype suggested certain types of knowledge representation. By combining various techniques, a representative subset of faults and a method for handling those faults was achieved. The experiences should prove useful for developing future fault handling expert systems under similar constraints.

Knowing Who Knows: Laypersons' Capabilities to Judge Experts' Pertinence for Science Topics.

PubMed

Bromme, Rainer; Thomm, Eva

2016-01-01

Because modern societies are built on elaborate divisions of cognitive labor, individuals remain laypersons in most knowledge domains. Hence, they have to rely on others' expertise when deciding on many science-related issues in private and public life. Even children already locate and discern expertise in the minds of others (e.g., Danovitch & Keil, 2004). This study examines how far university students accurately judge experts' pertinence for science topics even when they lack proficient knowledge of the domain. Participants judged the pertinence of experts from diverse disciplines based on the experts' assumed contributions to texts adapted from original articles from Science and Nature. Subjective pertinence judgments were calibrated by comparing them with bibliometrics of the original articles. Furthermore, participants' general science knowledge was controlled. Results showed that participants made well-calibrated pertinence judgments regardless of their level of general science knowledge. Copyright © 2015 Cognitive Science Society, Inc.

A center for commercial development of space: Real-time satellite mapping. Remote sensing-based agricultural information expert system

NASA Technical Reports Server (NTRS)

Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.

1989-01-01

The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

An Ada Based Expert System for the Ada Version of SAtool II. Volume 1 and 2

DTIC Science & Technology

1991-06-06

Integrated Computer-Aided Manufacturing (ICAM) (20). In fact, IDEF 0 stands for ICAM Definition Method Zero . IDEF0 defines a subset of SA that omits...reasoning that has been programmed). An expert’s knowledge is specific to one problem domain as opposed to knowledge about general problem-solving...techniques. General problem domains are medicine, finance, science or engineering and so forth in which an expert can solve specific problems very well

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.

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.

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.

An expert system for diagnostics and estimation of steam turbine components condition

NASA Astrophysics Data System (ADS)

Murmansky, B. E.; Aronson, K. E.; Brodov, Yu. M.

2017-11-01

The report describes an expert system of probability type for diagnostics and state estimation of steam turbine technological subsystems components. The expert system is based on Bayes’ theorem and permits to troubleshoot the equipment components, using expert experience, when there is a lack of baseline information on the indicators of turbine operation. Within a unified approach the expert system solves the problems of diagnosing the flow steam path of the turbine, bearings, thermal expansion system, regulatory system, condensing unit, the systems of regenerative feed-water and hot water heating. The knowledge base of the expert system for turbine unit rotors and bearings contains a description of 34 defects and of 104 related diagnostic features that cause a change in its vibration state. The knowledge base for the condensing unit contains 12 hypotheses and 15 evidence (indications); the procedures are also designated for 20 state parameters estimation. Similar knowledge base containing the diagnostic features and faults hypotheses are formulated for other technological subsystems of turbine unit. With the necessary initial information available a number of problems can be solved within the expert system for various technological subsystems of steam turbine unit: for steam flow path it is the correlation and regression analysis of multifactor relationship between the vibration parameters variations and the regime parameters; for system of thermal expansions it is the evaluation of force acting on the longitudinal keys depending on the temperature state of the turbine cylinder; for condensing unit it is the evaluation of separate effect of the heat exchange surface contamination and of the presence of air in condenser steam space on condenser thermal efficiency performance, as well as the evaluation of term for condenser cleaning and for tube system replacement and so forth. With a lack of initial information the expert system enables to formulate a diagnosis, calculating the probability of faults hypotheses, given the degree of the expert confidence in estimation of turbine components operation parameters.

Improved knowledge diffusion model based on the collaboration hypernetwork

NASA Astrophysics Data System (ADS)

Wang, Jiang-Pan; Guo, Qiang; Yang, Guang-Yong; Liu, Jian-Guo

2015-06-01

The process for absorbing knowledge becomes an essential element for innovation in firms and in adapting to changes in the competitive environment. In this paper, we present an improved knowledge diffusion hypernetwork (IKDH) model based on the idea that knowledge will spread from the target node to all its neighbors in terms of the hyperedge and knowledge stock. We apply the average knowledge stock V(t) , the variable σ2(t) , and the variance coefficient c(t) to evaluate the performance of knowledge diffusion. By analyzing different knowledge diffusion ways, selection ways of the highly knowledgeable nodes, hypernetwork sizes and hypernetwork structures for the performance of knowledge diffusion, results show that the diffusion speed of IKDH model is 3.64 times faster than that of traditional knowledge diffusion (TKDH) model. Besides, it is three times faster to diffuse knowledge by randomly selecting "expert" nodes than that by selecting large-hyperdegree nodes as "expert" nodes. Furthermore, either the closer network structure or smaller network size results in the faster knowledge diffusion.

Structuring expert input for a knowledge-based approach to watershed condition assessment for the Northwest Forest Plan, USA

Treesearch

Sean N. Gordon; Gallo Kirsten

2011-01-01

Assessments of watershed condition for aquatic and riparian species often have to rely on expert opinion because of the complexity of establishing statistical relationships among the many factors involved. Such expert-based assessments can be difficult to document and apply consistently over time and space. We describe and reflect on the process of developing a...

Psychology of developing and designing expert systems

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

Tonn, B.; MacGregor, D.

This paper discusses psychological problems relevant to developing and designing expert systems. With respect to the former, the psychological literature suggests that several cognitive biases may affect the elicitation of a valid knowledge base from the expert. The literature also suggests that common expert system inference engines may be quite inconsistent with reasoning heuristics employed by experts. With respect to expert system user interfaces, care should be taken when eliciting uncertainty estimates from users, presenting system conclusions, and ordering questions.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Utilizing Expert Knowledge in Estimating Future STS Costs

NASA Technical Reports Server (NTRS)

Fortner, David B.; Ruiz-Torres, Alex J.

2004-01-01

A method of estimating the costs of future space transportation systems (STSs) involves classical activity-based cost (ABC) modeling combined with systematic utilization of the knowledge and opinions of experts to extend the process-flow knowledge of existing systems to systems that involve new materials and/or new architectures. The expert knowledge is particularly helpful in filling gaps that arise in computational models of processes because of inconsistencies in historical cost data. Heretofore, the costs of planned STSs have been estimated following a "top-down" approach that tends to force the architectures of new systems to incorporate process flows like those of the space shuttles. In this ABC-based method, one makes assumptions about the processes, but otherwise follows a "bottoms up" approach that does not force the new system architecture to incorporate a space-shuttle-like process flow. Prototype software has been developed to implement this method. Through further development of software, it should be possible to extend the method beyond the space program to almost any setting in which there is a need to estimate the costs of a new system and to extend the applicable knowledge base in order to make the estimate.

Expert system training and control based on the fuzzy relation matrix

NASA Technical Reports Server (NTRS)

Ren, Jie; Sheridan, T. B.

1991-01-01

Fuzzy knowledge, that for which the terms of reference are not crisp but overlapped, seems to characterize human expertise. This can be shown from the fact that an experienced human operator can control some complex plants better than a computer can. Proposed here is fuzzy theory to build a fuzzy expert relation matrix (FERM) from given rules or/and examples, either in linguistic terms or in numerical values to mimic human processes of perception and decision making. The knowledge base is codified in terms of many implicit fuzzy rules. Fuzzy knowledge thus codified may also be compared with explicit rules specified by a human expert. It can also provide a basis for modeling the human operator and allow comparison of what a human operator says to what he does in practice. Two experiments were performed. In the first, control of liquid in a tank, demonstrates how the FERM knowledge base is elicited and trained. The other shows how to use a FERM, build up from linguistic rules, and to control an inverted pendulum without a dynamic model.

A demonstration of expert systems applications in transportation engineering : volume II, TRANZ, a prototype expert system for traffic control in highway work zones.

DOT National Transportation Integrated Search

1988-01-01

The development of a prototype knowledge-based expert system (KBES) for selecting appropriate traffic control strategies and management techniques around highway work zones was initiated. This process was encompassed by the steps that formulate the p...

TARGET: Rapid Capture of Process Knowledge

NASA Technical Reports Server (NTRS)

Ortiz, C. J.; Ly, H. V.; Saito, T.; Loftin, R. B.

1993-01-01

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

A Symbolic Approach Using Feature Construction Capable of Acquiring Information/Knowledge for Building Expert Systems.

ERIC Educational Resources Information Center

Major, Raymond L.

1998-01-01

Presents a technique for developing a knowledge-base of information to use in an expert system. Proposed approach employs a popular machine-learning algorithm along with a method for forming a finite number of features or conjuncts of at most n primitive attributes. Illustrates this procedure by examining qualitative information represented in a…

The Knowledge Base of Subject Matter Experts in Teaching: A Case Study of a Professional Scientist as a Beginning Teacher

ERIC Educational Resources Information Center

Diezmann, Carmel M.; Watters, James J.

2015-01-01

One method of addressing the shortage of science and mathematics teachers is to train scientists and other science-related professionals to become teachers. Advocates argue that as discipline experts these career changers can relate the subject matter knowledge to various contexts and applications in teaching. In this paper, through interviews and…

Approximate Degrees of Similarity between a User's Knowledge and the Tutorial Systems' Knowledge Base

ERIC Educational Resources Information Center

Mogharreban, Namdar

2004-01-01

A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…

PDA: A coupling of knowledge and memory for case-based reasoning

NASA Technical Reports Server (NTRS)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

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.

Autonomously acquiring declarative and procedural knowledge for ICAT systems

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1993-01-01

The construction of Intelligent Computer Aided Training (ICAT) systems is critically dependent on the ability to define and encode knowledge. This knowledge engineering effort can be broadly divided into two categories: domain knowledge and expert or task knowledge. Domain knowledge refers to the physical environment or system with which the expert interacts. Expert knowledge consists of the set of procedures and heuristics employed by the expert in performing their task. Both these areas are a significant bottleneck in the acquisition of knowledge for ICAT systems. This paper presents a research project in the area of autonomous knowledge acquisition using a passive observation concept. The system observes an expert and then generalizes the observations into production rules representing the domain expert's knowledge.

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

NASA Technical Reports Server (NTRS)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

The Shrinkage Model And Expert System Of Plastic Lens Formation

NASA Astrophysics Data System (ADS)

Chang, Rong-Seng

1988-06-01

Shrinkage causes both the appearance & dimension defects of the injected plastic lens. We have built up a model of state equations with the help of finite element analysis program to estimate the volume change (shrinkage and swelling) under the combinations of injection variables such as pressure and temperature etc., then the personal computer expert system has been build up to make that knowledge conveniently available to the user in the model design, process planning, process operation and some other work. The domain knowledge is represented by a R-graph (Relationship-graph) model which states the relationships of variables & equations. This model could be compare with other models in the expert system. If the user has better model to solve the shrinkage problem, the program will evaluate it automatically and a learning file will be trigger by the expert system to teach the user to update their knowledge base and modify the old model by this better model. The Rubin's model and Gilmore's model have been input to the expert system. The conflict has been solved both from the user and the deeper knowledge base. A cube prism and the convex lens examples have been shown in this paper. This program is written by MULISP language in IBM PC-AT. The natural language provides English Explaination of know why and know how and the automatic English translation for the equation rules and the production rules.

DataHub knowledge based assistance for science visualization and analysis using large distributed databases

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Collins, Donald J.; Doyle, Richard J.; Jacobson, Allan S.

1991-01-01

Viewgraphs on DataHub knowledge based assistance for science visualization and analysis using large distributed databases. Topics covered include: DataHub functional architecture; data representation; logical access methods; preliminary software architecture; LinkWinds; data knowledge issues; expert systems; and data management.

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.

An expert system to manage the operation of the Space Shuttle's fuel cell cryogenic reactant tanks

NASA Technical Reports Server (NTRS)

Murphey, Amy Y.

1990-01-01

This paper describes a rule-based expert system to manage the operation of the Space Shuttle's cryogenic fuel system. Rules are based on standard fuel tank operating procedures described in the EECOM Console Handbook. The problem of configuring the operation of the Space Shuttle's fuel tanks is well-bounded and well defined. Moreover, the solution of this problem can be encoded in a knowledge-based system. Therefore, a rule-based expert system is the appropriate paradigm. Furthermore, the expert system could be used in coordination with power system simulation software to design operating procedures for specific missions.

Bridging the Gap between Experts in Designing Multimedia-Based Instructional Media for Learning

ERIC Educational Resources Information Center

Razak, Rafiza Abdul

2013-01-01

The research identified and explored the cognitive knowledge among the instructional multimedia design and development experts comprising of multimedia designer, graphic designer, subject-matter expert and instructional designer. A critical need exists for a solid understanding of the factors that influence team decision making and performance in…

Are Clinicians Better Than Lay Judges at Recalling Case Details? An Evaluation of Expert Memory.

PubMed

Webb, Christopher A; Keeley, Jared W; Eakin, Deborah K

2016-04-01

This study examined the role of expertise in clinicians' memory for case details. Clinicians' diagnostic formulations may afford mechanisms for retaining and retrieving information. Experts (N = 41; 47.6% males, 23.8% females; 28.6% did not report gender; age: mean [M] = 54.69) were members of the American Board of Professional Psychologists. Lay judges (N = 156; 25.4% males, 74.1% females; age: M = 18.85) were undergraduates enrolled in general psychology. Three vignettes were presented to each group, creating a 2 (group: expert, lay judge) x 3 (vignettes: simple, complex-coherent, complex-incoherent) mixed factorial design. Recall accuracy for vignette details was the dependent variable. Data analyses used multivariate analyses of variance to detect group differences among multiple continuous variables. Experts recalled more information than lay judges, overall. However, experts also exhibited more false memories for the complex-incoherent case because of their schema-based knowledge. This study supported clinical expertise as beneficial. Nonetheless, negative influences from experts' schema-based knowledge, as exhibited, could adversely affect clinical practices. © 2016 Wiley Periodicals, Inc.

The Visual Representation and Acquisition of Driving Knowledge for Autonomous Vehicle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxia; Jiang, Qing; Li, Ping; Song, LiangTu; Wang, Rujing; Yu, Biao; Mei, Tao

2017-09-01

In this paper, the driving knowledge base of autonomous vehicle is designed. Based on the driving knowledge modeling system, the driving knowledge of autonomous vehicle is visually acquired, managed, stored, and maintenanced, which has vital significance for creating the development platform of intelligent decision-making systems of automatic driving expert systems for autonomous vehicle.

An integrated knowledge system for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Bangasser, Carl; Fensky, Connie; Cegielski, Eric; Overbey, Glenn

1993-01-01

A computer-based integrated Knowledge-Based System, the Intelligent Hypertext Manual (IHM), was developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at NASA Marshall Space Flight Center (MSFC). The IHM stores HGDS related knowledge and presents it in an interactive and intuitive manner. This manual is a combination of hypertext and an expert system which store experts' knowledge and experience in hazardous gas detection and analysis. The IHM's purpose is to provide HGDS personnel with the capabilities of: locating applicable documentation related to procedures, constraints, and previous fault histories; assisting in the training of personnel; enhancing the interpretation of real time data; and recognizing and identifying possible faults in the Space Shuttle sub-systems related to hazardous gas detection.

Development of an expert system for assessing trumpeter swan breeding habitat in the Northern Rocky Mountains.

USGS Publications Warehouse

Sojda, Richard S.; Cornely, John E.; Howe, Adele E.

2002-01-01

A decision support system for the management of the Rocky Mountain Population of Trumpeter Swans (Cygnus buccinators) is being developed. As part of this, three expert systems are also in development: one for assessing the quality of Trumpeter Swan breeding habitat; one for making water level recommendations in montane, palustrine wetlands; and one for assessing the contribution a particular site can make towards meeting objectives from as flyway perspective. The focus of this paper is the development of the breeding habitat expert system, which currently consists of 157 rules. Out purpose is to provide decision support for issues that appear to be beyond the capability of a single persons to conceptualize and solve. We propose that by involving multiple experts in the development and use of the systems, management will be significantly improved. The knowledge base for the expert system has been developed using standard knowledge engineering techniques with a small team of ecological experts. Knowledge was then coded using production rules organized in decision trees using a commercial expert system development shell. The final system has been deployed on the world wide web.

System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

NASA Technical Reports Server (NTRS)

Nieten, Joseph; Burke, Roger

1993-01-01

Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, 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 knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

Knowledge-based zonal grid generation for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1988-01-01

Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

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)

A real-time navigation monitoring expert system for the Space Shuttle Mission Control Center

NASA Technical Reports Server (NTRS)

Wang, Lui; Fletcher, Malise

1993-01-01

The ONAV (Onboard Navigation) Expert System has been developed as a real time console assistant for use by ONAV flight controllers in the Mission Control Center at the Johnson Space Center. This expert knowledge based system is used to monitor the Space Shuttle onboard navigation system, detect faults, and advise flight operations personnel. This application is the first knowledge-based system to use both telemetry and trajectory data from the Mission Operations Computer (MOC). To arrive at this stage, from a prototype to real world application, the ONAV project has had to deal with not only AI issues but operating environment issues. The AI issues included the maturity of AI languages and the debugging tools, verification, and availability, stability and size of the expert pool. The environmental issues included real time data acquisition, hardware suitability, and how to achieve acceptance by users and management.

Expert system shell to reason on large amounts of data

NASA Technical Reports Server (NTRS)

Giuffrida, Gionanni

1994-01-01

The current data base management systems (DBMS's) do not provide a sophisticated environment to develop rule based expert systems applications. Some of the new DBMS's come with some sort of rule mechanism; these are active and deductive database systems. However, both of these are not featured enough to support full implementation based on rules. On the other hand, current expert system shells do not provide any link with external databases. That is, all the data are kept in the system working memory. Such working memory is maintained in main memory. For some applications the reduced size of the available working memory could represent a constraint for the development. Typically these are applications which require reasoning on huge amounts of data. All these data do not fit into the computer main memory. Moreover, in some cases these data can be already available in some database systems and continuously updated while the expert system is running. This paper proposes an architecture which employs knowledge discovering techniques to reduce the amount of data to be stored in the main memory; in this architecture a standard DBMS is coupled with a rule-based language. The data are stored into the DBMS. An interface between the two systems is responsible for inducing knowledge from the set of relations. Such induced knowledge is then transferred to the rule-based language working memory.

Automatic computation of 2D cardiac measurements from B-mode echocardiography

NASA Astrophysics Data System (ADS)

Park, JinHyeong; Feng, Shaolei; Zhou, S. Kevin

2012-03-01

We propose a robust and fully automatic algorithm which computes the 2D echocardiography measurements recommended by America Society of Echocardiography. The algorithm employs knowledge-based imaging technologies which can learn the expert's knowledge from the training images and expert's annotation. Based on the models constructed from the learning stage, the algorithm searches initial location of the landmark points for the measurements by utilizing heart structure of left ventricle including mitral valve aortic valve. It employs the pseudo anatomic M-mode image generated by accumulating the line images in 2D parasternal long axis view along the time to refine the measurement landmark points. The experiment results with large volume of data show that the algorithm runs fast and is robust comparable to expert.

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.

Knowledge engineering for PACES, the particle accelerator control expert system

NASA Astrophysics Data System (ADS)

Lind, P. C.; Poehlman, W. F. S.; Stark, J. W.; Cousins, T.

1992-04-01

The KN-3000 used at Defense Research Establishment Ottawa is a Van de Graaff particle accelerator employed primarily to produce monoenergetic neutrons for calibrating radiation detectors. To provide training and assistance for new operators, it was decided to develop an expert system for accelerator operation. Knowledge engineering aspects of the expert system are reviewed. Two important issues are involved: the need to encapsulate expert knowledge into the system in a form that facilitates automatic accelerator operation and to partition the system so that time-consuming inferencing is minimized in favor of faster, more algorithmic control. It is seen that accelerator control will require fast, narrowminded decision making for rapid fine tuning, but slower and broader reasoning for machine startup, shutdown, fault diagnosis, and correction. It is also important to render the knowledge base in a form conducive to operator training. A promising form of the expert system involves a hybrid system in which high level reasoning is performed on the host machine that interacts with the user, while an embedded controller employs neural networks for fast but limited adjustment of accelerator performance. This partitioning of duty facilitates a hierarchical chain of command yielding an effective mixture of speed and reasoning ability.

Will You Miss Me when I'm Gone? A Study of the Potential Loss of Company Knowledge and Expertise as Employees Retire

ERIC Educational Resources Information Center

McQuade, Eamonn; Sjoer, Ellen; Fabian, Peter; Nascimento, Jose Carlos; Schroeder, Sanaz

2007-01-01

Purpose--The purpose of this paper is to report on a research project, the aim of which was to identify the potential loss of company knowledge and expertise as experienced and expert employees retire. Design/methodology/approach--The methodology used in this research was based on interviewing experienced and expert people who had retired or were…

Empirical Analysis and Refinement of Expert System Knowledge Bases

DTIC Science & Technology

1988-08-31

refinement. Both a simulated case generation program, and a random rule basher were developed to enhance rule refinement experimentation. *Substantial...the second fiscal year 88 objective was fully met. Rule Refinement System Simulated Rule Basher Case Generator Stored Cases Expert System Knowledge...generated until the rule is satisfied. Cases may be randomly generated for a given rule or hypothesis. Rule Basher Given that one has a correct

Knowledge-Acquisition Tool For Expert System

NASA Technical Reports Server (NTRS)

Disbrow, James D.; Duke, Eugene L.; Regenie, Victoria A.

1988-01-01

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

A Cognitive Architecture for Human Performance Process Model Research

DTIC Science & Technology

1992-11-01

individually defined, updatable world representation which is a description of the world as the operator knows it. It contains rules for decisions, an...operate it), and rules of engagement (knowledge about the operator’s expected behavior). The HPP model works in the following way. Information enters...based models depict the problem-solving processes of experts. The experts’ knowledge is represented in symbol structures, along with rules for

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, Betty M.

1988-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth science. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of US energy and mineral resources.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, B.M.

1987-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth sciences. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of the Nation's energy and mineral resources.

A prototype knowledge-based simulation support system

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

Hill, T.R.; Roberts, S.D.

1987-04-01

As a preliminary step toward the goal of an intelligent automated system for simulation modeling support, we explore the feasibility of the overall concept by generating and testing a prototypical framework. A prototype knowledge-based computer system was developed to support a senior level course in industrial engineering so that the overall feasibility of an expert simulation support system could be studied in a controlled and observable setting. The system behavior mimics the diagnostic (intelligent) process performed by the course instructor and teaching assistants, finding logical errors in INSIGHT simulation models and recommending appropriate corrective measures. The system was programmed inmore » a non-procedural language (PROLOG) and designed to run interactively with students working on course homework and projects. The knowledge-based structure supports intelligent behavior, providing its users with access to an evolving accumulation of expert diagnostic knowledge. The non-procedural approach facilitates the maintenance of the system and helps merge the roles of expert and knowledge engineer by allowing new knowledge to be easily incorporated without regard to the existing flow of control. The background, features and design of the system are describe and preliminary results are reported. Initial success is judged to demonstrate the utility of the reported approach and support the ultimate goal of an intelligent modeling system which can support simulation modelers outside the classroom environment. Finally, future extensions are suggested.« less

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.

Construction of Expert Knowledge Monitoring and Assessment System Based on Integral Method of Knowledge Evaluation

ERIC Educational Resources Information Center

Golovachyova, Viktoriya N.; Menlibekova, Gulbakhyt Zh.; Abayeva, Nella F.; Ten, Tatyana L.; Kogaya, Galina D.

2016-01-01

Using computer-based monitoring systems that rely on tests could be the most effective way of knowledge evaluation. The problem of objective knowledge assessment by means of testing takes on a new dimension in the context of new paradigms in education. The analysis of the existing test methods enabled us to conclude that tests with selected…

Expert Systems for Libraries at SCIL [Small Computers in Libraries]'88.

ERIC Educational Resources Information Center

Kochtanek, Thomas R.; And Others

1988-01-01

Six brief papers on expert systems for libraries cover (1) a knowledge-based approach to database design; (2) getting started in expert systems; (3) using public domain software to develop a business reference system; (4) a music cataloging inquiry system; (5) linguistic analysis of reference transactions; and (6) a model of a reference librarian.…

An expert system that performs a satellite station keepimg maneuver

NASA Technical Reports Server (NTRS)

Linesbrowning, M. Kate; Stone, John L., Jr.

1987-01-01

The development and characteristics of a prototype expert system, Expert System for Satellite Orbit Control (ESSOC), capable of providing real-time spacecraft system analysis and command generation for a geostationary satellite are described. The ESSOC recommends appropriate commands that reflect both the changing spacecraft condition and previous procedural action. An internal knowledge base stores satellite status information and is updated with processed spacecraft telemetry. Procedural structure data are encoded in production rules. Structural methods of knowledge acquisition and the design and performance-enhancing techniques that enable ESSOC to operate in real time are also considered.

EX.MAIN. Expert System Model for Maintenance and Staff Training.

ERIC Educational Resources Information Center

Masturzi, Elio R.

EX.MAIN, a model for maintenance and staff training which combines knowledge based expert systems and computer based training, was developed jointly by the Department of Production Engineering of the University of Naples and CIRCUMVESUVIANA, the largest private railroad in Italy. It is a global model in the maintenance field which contains both…

Debugging expert systems using a dynamically created hypertext network

NASA Technical Reports Server (NTRS)

Boyle, Craig D. B.; Schuette, John F.

1991-01-01

The labor intensive nature of expert system writing and debugging motivated this study. The hypothesis is that a hypertext based debugging tool is easier and faster than one traditional tool, the graphical execution trace. HESDE (Hypertext Expert System Debugging Environment) uses Hypertext nodes and links to represent the objects and their relationships created during the execution of a rule based expert system. HESDE operates transparently on top of the CLIPS (C Language Integrated Production System) rule based system environment and is used during the knowledge base debugging process. During the execution process HESDE builds an execution trace. Use of facts, rules, and their values are automatically stored in a Hypertext network for each execution cycle. After the execution process, the knowledge engineer may access the Hypertext network and browse the network created. The network may be viewed in terms of rules, facts, and values. An experiment was conducted to compare HESDE with a graphical debugging environment. Subjects were given representative tasks. For speed and accuracy, in eight of the eleven tasks given to subjects, HESDE was significantly better.

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;…

A flight expert system for on-board fault monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Ali, Moonis

1990-01-01

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

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…

SigmaCLIPSE = presentation management + NASA CLI PS + SQL

NASA Technical Reports Server (NTRS)

Weiss, Bernard P., Jr.

1990-01-01

SigmaCLIPSE provides an expert systems and 'intelligent' data base development program for diverse systems integration environments that require support for automated reasoning and expert systems technology, presentation management, and access to 'intelligent' SQL data bases. The SigmaCLIPSE technology and and its integrated ability to access 4th generation application development and decision support tools through a portable SQL interface, comprises a sophisticated software development environment for solving knowledge engineering and expert systems development problems in information intensive commercial environments -- financial services, health care, and distributed process control -- where the expert system must be extendable -- a major architectural advantage of NASA CLIPS. SigmaCLIPSE is a research effort intended to test the viability of merging SQL data bases with expert systems technology.

On the acquisition and representation of procedural knowledge

NASA Technical Reports Server (NTRS)

Saito, T.; Ortiz, C.; Loftin, R. B.

1992-01-01

Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.

Psychological tools for knowledge acquisition

NASA Technical Reports Server (NTRS)

Rueter, Henry H.; Olson, Judith Reitman

1988-01-01

Knowledge acquisition is said to be the biggest bottleneck in the development of expert systems. The problem is getting the knowledge out of the expert's head and into a computer. In cognitive psychology, characterizing metal structures and why experts are good at what they do is an important research area. Is there some way that the tools that psychologists have developed to uncover mental structure can be used to benefit knowledge engineers? We think that the way to find out is to browse through the psychologist's toolbox to see what there is in it that might be of use to knowledge engineers. Expert system developers have relied on two standard methods for extracting knowledge from the expert: (1) the knowledge engineer engages in an intense bout of interviews with the expert or experts, or (2) the knowledge engineer becomes an expert himself, relying on introspection to uncover the basis of his own expertise. Unfortunately, these techniques have the difficulty that often the expert himself isn't consciously aware of the basis of his expertise. If the expert himself isn't conscious of how he solves problems, introspection is useless. Cognitive psychology has faced similar problems for many years and has developed exploratory methods that can be used to discover cognitive structure from simple data.

Transformation reborn: A new generation expert system for planning HST operations

NASA Technical Reports Server (NTRS)

Gerb, Andrew

1991-01-01

The Transformation expert system (TRANS) converts proposals for astronomical observations with the Hubble Space Telescope (HST) into detailed observing plans. It encodes expert knowledge to solve problems faced in planning and commanding HST observations to enable their processing by the Science Operations Ground System (SOGS). Among these problems are determining an acceptable order of executing observations, grouping of observations to enhance efficiency and schedulability, inserting extra observations when necessary, and providing parameters for commanding HST instruments. TRANS is currently an operational system and plays a critical role in the HST ground system. It was originally designed using forward-chaining provided by the OPS5 expert system language, but has been reimplemented using a procedural knowledge base. This reimplementation was forced by the explosion in the amount of OPS5 code required to specify the increasingly complicated situations requiring expert-level intervention by the TRANS knowledge base. This problem was compounded by the difficulty of avoiding unintended interaction between rules. To support the TRANS knowledge base, XCL, a small but powerful extension to Commom Lisp was implemented. XCL allows a compact syntax for specifying assignments and references to object attributes. XCL also allows the capability to iterate over objects and perform keyed lookup. The reimplementation of TRANS has greatly diminished the effort needed to maintain and enhance it. As a result of this, its functions have been expanded to include warnings about observations that are difficult or impossible to schedule or command, providing data to aid SPIKE, an intelligent planning system used for HST long-term scheduling, and providing information to the Guide Star Selection System (GSSS) to aid in determination of the long range availability of guide stars.

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.

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

USGS Publications Warehouse

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

Energy literacy of Indiana high school practical arts and vocational teachers

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

Emshousen, F.W. Jr.

The purpose of the study was to develop an energy knowledge examination, investigate the extent high school teachers of home economics, agriculture, and industrial arts differ in their knowledge of energy, and to ascertain the extent their knowledge of energy differs with personal, educational, and geographic characteristics. Based upon literature review, a subject model was structured according to Bloom's (1956) taxonomy category of Knowledge and Hauenstein's (1972) procedure for classifying knowledges. Energy experts critically evaluated this model, which after refinement, was used to develop an Energy Knowledge Examination. The model consisted of six primary elements: sources, uses, costs, conservation, conversion,more » and policy issues. Energy experts reviewed items for accuracy, relevance, reading level, and clarity. The final instrument (65 multiple choice questions), was administered to a stratified random sample of Indiana public high school (IPHS) teachers from selected disciplines. Findings revealed significant biases among energy experts regarding relevance of specific subject content to the needs of teachers and students. Significant differences in the energy knowledge of IPHS teachers existed only in specific areas of the subject.« less

Knowledge-Based Information Retrieval.

ERIC Educational Resources Information Center

Ford, Nigel

1991-01-01

Discussion of information retrieval focuses on theoretical and empirical advances in knowledge-based information retrieval. Topics discussed include the use of natural language for queries; the use of expert systems; intelligent tutoring systems; user modeling; the need for evaluation of system effectiveness; and examples of systems, including…

Representation and matching of knowledge to design digital systems

NASA Technical Reports Server (NTRS)

Jones, J. U.; Shiva, S. G.

1988-01-01

A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described.

[Research & development on computer expert system for forensic bones estimation].

PubMed

Zhao, Jun-ji; Zhang, Jan-zheng; Liu, Nin-guo

2005-08-01

To build an expert system for forensic bones estimation. By using the object oriented method, employing statistical data of forensic anthropology, combining the statistical data frame knowledge representation with productions and also using the fuzzy matching and DS evidence theory method. Software for forensic estimation of sex, age and height with opened knowledge base was designed. This system is reliable and effective, and it would be a good assistant of the forensic technician.

Knowledge base and functionality of concepts of some Filipino biology teachers in five biology topics

NASA Astrophysics Data System (ADS)

Barquilla, Manuel B.

2018-01-01

This mixed research, is a snapshot of some Filipino Biology teachers' knowledge structure and how their concepts of the five topics in Biology (Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics) functions and develops inside a biology classroom. The study focuses on the six biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and the other three (3) are under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilized classroom discourses, concept maps, interpretative case-study method, bracketing method, and concept analysis for qualitative part; the quantitative part uses a nonparametric statistical tool, Kendall's tau Coefficient for determining relationship and congruency while measures of central tendencies and dispersion (mean, and standard deviation) for concept maps scores interpretation. Knowledge Base of Biology teachers were evaluated by experts in field of specialization having a doctorate program (e.g. PhD in Genetics) and PhD Biology candidates. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. The evaluation of teachers' knowledge base by experts indicated that teachers' knowledge of (65%) is lower than the minimum (75%) recommended by ABD-el-Khalick and Boujaoude (1997). Thus, the experts believe that content knowledge of the teachers is hardly adequate for their teaching assignment. Moreover, the teachers in this study do not systematically use reallife situation to apply the concepts they teach. They can identify concepts too abstract for their student; however, they seldom use innovative ways to bring the discussion to their students' level of readiness and capacity to learn. Kendall's Tau Coefficient of agreement indicated that there is an agreement of the rating by experts and PhD (Biology) candidates. As for recommended level for teaching based on the respondent content knowledge structure, the experts and the PhD (Biology) candidates agree that the content knowledge of the teachers is at the borderline (rating of 6) between elementary and high school. These results imply that biology teachers need in-service training to upgrade their content knowledge in the subject. At the same time, the pre-service curriculum for biology teachers needs upgrading.

Graphical explanation in an expert system for Space Station Freedom rack integration

NASA Technical Reports Server (NTRS)

Craig, F. G.; Cutts, D. E.; Fennel, T. R.; Purves, B.

1990-01-01

The rationale and methodology used to incorporate graphics into explanations provided by an expert system for Space Station Freedom rack integration is examined. The rack integration task is typical of a class of constraint satisfaction problems for large programs where expertise from several areas is required. Graphically oriented approaches are used to explain the conclusions made by the system, the knowledge base content, and even at more abstract levels the control strategies employed by the system. The implemented architecture combines hypermedia and inference engine capabilities. The advantages of this architecture include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. The graphical techniques employed range from simple statis presentation of schematics to dynamic creation of a series of pictures presented motion picture style. User models control the type, amount, and order of information presented.

Renewable energy education and industrial arts: linking knowledge producers with knowledge

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

Foley, R.L.

This study introduces renewable energy technology into the industrial arts programs in the State of New Hampshire by providing the following information for decision making: (1) a broad-based perspective on renewable energy technology; (2) the selection of an educational change model; (3) data from a needs analysis; (4) an initial screening of potential teacher-trainers. The Wolf-Welsh Linkage Model was selected as the knowledge production/utilization model for bridging the knowledge gap between renewable energy experts and industrial arts teachers. Ninety-six renewable energy experts were identified by a three-step peer nomination process (92% response rate). The experts stressed the conceptual foundations, economicmore » justifications, and the scientific and quantitative basics of renewable energy technology. The teachers focused on wood-burning technology, educational strategies, and the more popular alternative energy sources such as windpower, hydropower, photovoltaics, and biomass. The most emphatic contribution of the needs analysis was the experts' and teachers' shared perception that residential/commercial building design, retrofitting, and construction is the single most important practical, technical area for the application of renewable energy technology.« less

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.

Techniques and implementation of the embedded rule-based expert system using Ada

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Jones, Robert E.

1991-01-01

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

The development of a knowledge test of depression and its treatment for patients suffering from non-psychotic depression: a psychometric assessment

PubMed Central

Gabriel, Adel; Violato, Claudio

2009-01-01

Background To develop and psychometrically assess a multiple choice question (MCQ) instrument to test knowledge of depression and its treatments in patients suffering from depression. Methods A total of 63 depressed patients and twelve psychiatric experts participated. Based on empirical evidence from an extensive review, theoretical knowledge and in consultations with experts, 27-item MCQ knowledge of depression and its treatment test was constructed. Data collected from the psychiatry experts were used to assess evidence of content validity for the instrument. Results Cronbach's alpha of the instrument was 0.68, and there was an overall 87.8% agreement (items are highly relevant) between experts about the relevance of the MCQs to test patient knowledge on depression and its treatments. There was an overall satisfactory patients' performance on the MCQs with 78.7% correct answers. Results of an item analysis indicated that most items had adequate difficulties and discriminations. Conclusion There was adequate reliability and evidence for content and convergent validity for the instrument. Future research should employ a lager and more heterogeneous sample from both psychiatrist and community samples, than did the present study. Meanwhile, the present study has resulted in psychometrically tested instruments for measuring knowledge of depression and its treatment of depressed patients. PMID:19754944

Knowledge From Pictures (KFP)

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Paterra, Frank; Bailin, Sidney

1993-01-01

The old maxim goes: 'A picture is worth a thousand words'. The objective of the research reported in this paper is to demonstrate this idea as it relates to the knowledge acquisition process and the automated development of an expert system's rule base. A prototype tool, the Knowledge From Pictures (KFP) tool, has been developed which configures an expert system's rule base by an automated analysis of and reasoning about a 'picture', i.e., a graphical representation of some target system to be supported by the diagnostic capabilities of the expert system under development. This rule base, when refined, could then be used by the expert system for target system monitoring and fault analysis in an operational setting. Most people, when faced with the problem of understanding the behavior of a complicated system, resort to the use of some picture or graphical representation of the system as an aid in thinking about it. This depiction provides a means of helping the individual to visualize the bahavior and dynamics of the system under study. An analysis of the picture augmented with the individual's background information, allows the problem solver to codify knowledge about the system. This knowledge can, in turn, be used to develop computer programs to automatically monitor the system's performance. The approach taken is this research was to mimic this knowledge acquisition paradigm. A prototype tool was developed which provides the user: (1) a mechanism for graphically representing sample system-configurations appropriate for the domain, and (2) a linguistic device for annotating the graphical representation with the behaviors and mutual influences of the components depicted in the graphic. The KFP tool, reasoning from the graphical depiction along with user-supplied annotations of component behaviors and inter-component influences, generates a rule base that could be used in automating the fault detection, isolation, and repair of the system.

An AHP-Based Weighted Analysis of Network Knowledge Management Platforms for Elementary School Students

ERIC Educational Resources Information Center

Lee, Chung-Ping; Lou, Shi-Jer; Shih, Ru-Chu; Tseng, Kuo-Hung

2011-01-01

This study uses the analytical hierarchy process (AHP) to quantify important knowledge management behaviors and to analyze the weight scores of elementary school students' behaviors in knowledge transfer, sharing, and creation. Based on the analysis of Expert Choice and tests for validity and reliability, this study identified the weight scores of…

Understanding the Life Cycle of Computer-Based Models: The Role of Expert Contributions in Design, Development and Implementation

ERIC Educational Resources Information Center

Waight, Noemi; Liu, Xiufeng; Gregorius, Roberto Ma.

2015-01-01

This paper examined the nuances of the background process of design and development and follow up classroom implementation of computer-based models for high school chemistry. More specifically, the study examined the knowledge contributions of an interdisciplinary team of experts; points of tensions, negotiations and non-negotiable aspects of…

EXADS - EXPERT SYSTEM FOR AUTOMATED DESIGN SYNTHESIS

NASA Technical Reports Server (NTRS)

Rogers, J. L.

1994-01-01

The expert system called EXADS was developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. Because of the general purpose nature of ADS, it is difficult for a nonexpert to select the best choice of strategy, optimizer, and one-dimensional search options from the one hundred or so combinations that are available. EXADS aids engineers in determining the best combination based on their knowledge of the problem and the expert knowledge previously stored by experts who developed ADS. EXADS is a customized application of the AESOP artificial intelligence program (the general version of AESOP is available separately from COSMIC. The ADS program is also available from COSMIC.) The expert system consists of two main components. The knowledge base contains about 200 rules and is divided into three categories: constrained, unconstrained, and constrained treated as unconstrained. The EXADS inference engine is rule-based and makes decisions about a particular situation using hypotheses (potential solutions), rules, and answers to questions drawn from the rule base. EXADS is backward-chaining, that is, it works from hypothesis to facts. The rule base was compiled from sources such as literature searches, ADS documentation, and engineer surveys. EXADS will accept answers such as yes, no, maybe, likely, and don't know, or a certainty factor ranging from 0 to 10. When any hypothesis reaches a confidence level of 90% or more, it is deemed as the best choice and displayed to the user. If no hypothesis is confirmed, the user can examine explanations of why the hypotheses failed to reach the 90% level. The IBM PC version of EXADS is written in IQ-LISP for execution under DOS 2.0 or higher with a central memory requirement of approximately 512K of 8 bit bytes. This program was developed in 1986.

XBONE: a hybrid expert system for supporting diagnosis of bone diseases.

PubMed

Hatzilygeroudis, I; Vassilakos, P J; Tsakalidis, A

1997-01-01

In this paper, XBONE, a hybrid medical expert system that supports diagnosis of bone diseases is presented. Diagnosis is based on various patient data and is performed in two stages. In the early stage, diagnosis is based on demographic and clinical data of the patient, whereas in the late stage it is mainly based on nuclear medicine image data. Knowledge is represented via an integrated formalism that combines production rules and the Adaline artificial neural unit. Each condition of a rule is assigned a number, called its significance factor, representing its significance in drawing the conclusion of the rule. This results in better representation, reduction of the knowledge base size and gives the system learning capabilities.

A Thermal Expert System (TEXSYS) development overview - AI-based control of a Space Station prototype thermal bus

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hack, E. C.

1990-01-01

A knowledge-based control system for real-time control and fault detection, isolation and recovery (FDIR) of a prototype two-phase Space Station Freedom external thermal control system (TCS) is discussed in this paper. The Thermal Expert System (TEXSYS) has been demonstrated in recent tests to be capable of both fault anticipation and detection and real-time control of the thermal bus. Performance requirements were achieved by using a symbolic control approach, layering model-based expert system software on a conventional numerical data acquisition and control system. The model-based capabilities of TEXSYS were shown to be advantageous during software development and testing. One representative example is given from on-line TCS tests of TEXSYS. The integration and testing of TEXSYS with a live TCS testbed provides some insight on the use of formal software design, development and documentation methodologies to qualify knowledge-based systems for on-line or flight applications.

Ontology based decision system for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

2018-04-01

In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Expert Maintenance Advisor Development for Navy Shipboard Systems

DTIC Science & Technology

1994-01-01

Estoril (EDEN) Chair: Xavier Alaman, Instituto de Ingenieria del Conocimiento, SPAIN "A Model of Handling Uncertainty in Expert Systems," 01 Zhao...for Supervisory Process Control," Xavier Alaman, Instituto de Ingenieria del Conocimiento, SPAIN - (L) INTEGRATED KNOWLEDGE BASED SYSTEMS IN POWER

Expert system for computer-assisted annotation of MS/MS spectra.

PubMed

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-11-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions.

Expert System for Computer-assisted Annotation of MS/MS Spectra*

PubMed Central

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-01-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions. PMID:22888147

A knowledge-based expert system for scheduling of airborne astronomical observations

NASA Technical Reports Server (NTRS)

Nachtsheim, P. R.; Gevarter, W. B.; Stutz, J. C.; Banda, C. P.

1985-01-01

The Kuiper Airborne Observatory Scheduler (KAOS) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

Expert database system for quality control

NASA Astrophysics Data System (ADS)

Wang, Anne J.; Li, Zhi-Cheng

1993-09-01

There are more competitors today. Markets are not homogeneous they are fragmented into increasingly focused niches requiring greater flexibility in the product mix shorter manufacturing production runs and above allhigher quality. In this paper the author identified a real-time expert system as a way to improve plantwide quality management. The quality control expert database system (QCEDS) by integrating knowledge of experts in operations quality management and computer systems use all information relevant to quality managementfacts as well as rulesto determine if a product meets quality standards. Keywords: expert system quality control data base

An on-line expert system for diagnosing environmentally induced spacecraft anomalies using CLIPS

NASA Technical Reports Server (NTRS)

Lauriente, Michael; Rolincik, Mark; Koons, Harry C; Gorney, David

1993-01-01

A new rule-based, expert system for diagnosing spacecraft anomalies is under development. The knowledge base consists of over two-hundred rules and provide links to historical and environmental databases. Environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information (varying degrees of confidence in an answer) or 'unknown' to any question. The expert system not only provides scientists with needed risk analysis and confidence estimates not available in standard numerical models or databases, but it is also an effective learning tool. In addition, the architecture of the expert system allows easy additions to the knowledge base and the database. For example, new frames concerning orbital debris and ionospheric scintillation are being considered. The system currently runs on a MicroVAX and uses the C Language Integrated Production System (CLIPS).

Verification and Validation of KBS with Neural Network Components

NASA Technical Reports Server (NTRS)

Wen, Wu; Callahan, John

1996-01-01

Artificial Neural Network (ANN) play an important role in developing robust Knowledge Based Systems (KBS). The ANN based components used in these systems learn to give appropriate predictions through training with correct input-output data patterns. Unlike traditional KBS that depends on a rule database and a production engine, the ANN based system mimics the decisions of an expert without specifically formulating the if-than type of rules. In fact, the ANNs demonstrate their superiority when such if-then type of rules are hard to generate by human expert. Verification of traditional knowledge based system is based on the proof of consistency and completeness of the rule knowledge base and correctness of the production engine.These techniques, however, can not be directly applied to ANN based components.In this position paper, we propose a verification and validation procedure for KBS with ANN based components. The essence of the procedure is to obtain an accurate system specification through incremental modification of the specifications using an ANN rule extraction algorithm.

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.

Intelligent Tools for Planning Knowledge base Development and Verification

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

Static and Completion Analysis for Planning Knowledge Base Development and Verification

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

PubMed

Fred, A; Filipe, J; Partinen, M; Paiva, T

2000-01-01

This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge- intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.

[Legitimizing and responsibilities of public health reports: public health reports or social court reports?].

PubMed

Borgers, D; Streich, W

1996-11-01

Since 1970 various initiatives have been taken to improve the information bases of health reporting. However, the efforts made up to now by the Länder, the Federal Government and its corporate bodies are characterised by a lack of experience and shortage of resources; moreover, they are viewed with a critical eye by the public and in the political area. In this contribution the authors describe various topics and delimitations of a health reporting system which go far beyond health statistics and health programmes altogether. The chances of a national health reporting system are based on the assumption that an objective judgement based on expert knowledge and science will be possible and that beyond all particularistic interests, expert knowledge can be organised in a democratic process. Public health reporting varies between two extremes: On the one hand, the current reporting in the media on health-related subjects which is characterised by disagreement among experts, particularistic interests and emotions, and on the other hand the national health reporting, which, on the platform of policy marketing and political image shaping, is suspected of degenerating to a kind of "royal court reporting". A health reporting system based on expert knowledge and characterised by topics with relevance to health policy, expert quality of its information and neutrality to particularistic interests, should go beyond these two extremes. Given the political conditions of budgeting and distribution conflicts, health reporting has to deal with two main aspects: effectiveness and efficiency of employed resources and with the problems of a fair distribution of these resources to provide equal chances in the health sector. What cannot be solved, by questions of procedure, however, is the problem of truth and objective knowledge as well as the problem of confidence. If the general public lacks confidence in national expert knowledge, a society discourse will not lead to political results. Additionally, the argument that medicine is of little importance for health is used to categorically reject a rational investigation of needs and thus to reduce the health system to the status of a modern religious doctrine. Proceeding on the assumption that due to systematic thinking and acting in the field of science, effective medicine symbolises one of the paradigms of progress, then health reporting system can be justified despite the precarious objective knowledge, provided such reporting generates the confidence it deserves thanks to its quality standards and seriousness.

An Expert System Shell to Teach Problem Solving.

ERIC Educational Resources Information Center

Lippert, Renate C.

1988-01-01

Discusses the use of expert systems to teach problem-solving skills to students from grade 6 to college level. The role of computer technology in the future of education is considered, and the construction of knowledge bases is described, including an example for physics. (LRW)

Knowledge-based operation and management of communications systems

NASA Technical Reports Server (NTRS)

Heggestad, Harold M.

1988-01-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Knowledge-based operation and management of communications systems

NASA Astrophysics Data System (ADS)

Heggestad, Harold M.

1988-11-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Viewing Knowledge Bases as Qualitative Models.

ERIC Educational Resources Information Center

Clancey, William J.

The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

Genie Inference Engine Rule Writer’s Guide.

DTIC Science & Technology

1987-08-01

33 APPENDIX D. Animal Bootstrap File.............................................................. 39...APPENDIX E. Sample Run of Animal Identification Expert System.......................... 43 APPENDIX F. Numeric Test Knowledge Base...and other data s.tructures stored in the knowledge base (KB), queries the user for input, and draws conclusions. Genie (GENeric Inference Engine) is

Introduction to Radar Signal and Data Processing: The Opportunity

DTIC Science & Technology

2006-09-01

SpA) Director of Analysis of Integrated Systems Group Via Tiburtina Km. 12.400 00131 Rome ITALY e.mail: afarina@selex-si.com Key words: radar...signal processing, data processing, adaptivity, space-time adaptive processing, knowledge based systems , CFAR. 1. SUMMARY This paper introduces to...the lecture series dedicated to the knowledge-based radar signal and data processing. Knowledge-based expert system (KBS) is in the realm of

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

FTDD973: A multimedia knowledge-based system and methodology for operator training and diagnostics

NASA Technical Reports Server (NTRS)

Hekmatpour, Amir; Brown, Gary; Brault, Randy; Bowen, Greg

1993-01-01

FTDD973 (973 Fabricator Training, Documentation, and Diagnostics) is an interactive multimedia knowledge based system and methodology for computer-aided training and certification of operators, as well as tool and process diagnostics in IBM's CMOS SGP fabrication line (building 973). FTDD973 is an example of what can be achieved with modern multimedia workstations. Knowledge-based systems, hypertext, hypergraphics, high resolution images, audio, motion video, and animation are technologies that in synergy can be far more useful than each by itself. FTDD973's modular and object-oriented architecture is also an example of how improvements in software engineering are finally making it possible to combine many software modules into one application. FTDD973 is developed in ExperMedia/2; and OS/2 multimedia expert system shell for domain experts.

Cognition of Experts and Top Managers about the Changes in Innovation Space

ERIC Educational Resources Information Center

Bergman, Jukka-Pekka; Jantunen, Ari; Saksa, Juha-Matti; Hurmelinna-Laukkanen, Pia

2007-01-01

The innovation space has become more complex and knowledge-intensive. As a result, it is increasingly important to see innovations as knowledge that is embodied in learning and technical and organisational knowledge bases. However, in processes such as innovation development, individuals make sense of it and utilise existing knowledge differently…

Exploring ESL/EFL Teachers' Pedagogical Content Knowledge on Reading Strategy Instruction

ERIC Educational Resources Information Center

Xu, Wei

2015-01-01

Any instructional practice must be derived from a teacher's knowledge base for teaching, which can be acquired by training, study, or practice. While much attention has been paid to teachers' practical content knowledge in real educational settings, comprehensive syntheses of expert knowledge on a particular teaching task for a specific group of…

Knowledge-based systems for power management

NASA Technical Reports Server (NTRS)

Lollar, L. F.

1992-01-01

NASA-Marshall's Electrical Power Branch has undertaken the development of expert systems in support of further advancements in electrical power system automation. Attention is given to the features (1) of the Fault Recovery and Management Expert System, (2) a resource scheduler or Master of Automated Expert Scheduling Through Resource Orchestration, and (3) an adaptive load-priority manager, or Load Priority List Management System. The characteristics of an advisory battery manager for the Hubble Space Telescope, designated the 'nickel-hydrogen expert system', are also noted.

Functional specifications for a radioactive waste decision support system

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

Westrom, G.B.; Kurrasch, E.R.; Carlton, R.E.

1989-09-01

It is generally recognized that decisions relative to the treatment, handling, transportation and disposal of low-level wastes produced in nuclear power plants involve a complex array of many inter-related elements or considerations. Complex decision processes can be aided through the use of computer-based expert systems which are based on the knowledge of experts and the inferencing of that knowledge to provide advice to an end-user. To determine the feasibility of developing and applying an expert system in nuclear plant low level waste operations, a Functional Specification for a Radwaste Decision Support System (RDSS) was developed. All areas of radwaste management,more » from the point of waste generation to the disposition of the waste in the final disposal location were considered for inclusion within the scope of the RDSS. 27 figs., 8 tabs.« less

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.

Diagnostics aid for mass spectrometer trouble-shooting

NASA Astrophysics Data System (ADS)

Filby, E. E.; Rankin, R. A.; Webb, G. W.

The MS Expert system provides problem diagnostics for instruments used in the Mass Spectrometry Laboratory (MSL). The most critical results generated on these mass spectrometers are the uranium concentration and isotopic content data used for process control and materials accountability at the Idaho Chemical Processing Plant. The two purposes of the system are: (1) to minimize instrument downtime and thereby provide the best possible support to the Plant, and (2) to improve long-term data quality. This system combines the knowledge of several experts on mass spectrometry to provide a diagnostic tool, and can make these skills available on a more timely basis. It integrates code written in the Pascal language with a knowledge base entered into a commercial expert system shell. The user performs some preliminary status checks, and then selects from among several broad diagnostic categories. These initial steps provide input to the rule base. The overall analysis provides the user with a set of possible solutions to the observed problems, graded as to their probabilities. Besides the trouble-shooting benefits expected from this system, it will also provide structures diagnostic training for lab personnel. In addition, development of the system knowledge base has already produced a better understanding of instrument behavior. Two key findings are that a good user interface is necessary for full acceptance of the tool, and a development system should include standard programming capabilities as well as the expert system shell.

Distributed Knowledge Base Systems for Diagnosis and Information Retrieval.

DTIC Science & Technology

1983-11-01

social system metaphors State University. for distributed problem solving: Introduction to the issue. IEEE Newell. A. and Simon, H. A. (1972) Human...experts and Sriram Mahalingam wha-helped think out the probLema associated with building Auto-Mech. Research on diagnostic expert systemas for the

An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic

NASA Astrophysics Data System (ADS)

Zhu, A.-Xing; Wang, Rongxun; Qiao, Jianping; Qin, Cheng-Zhi; Chen, Yongbo; Liu, Jing; Du, Fei; Lin, Yang; Zhu, Tongxin

2014-06-01

This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the developed approach can be used in large-scale projects. Results from these case studies suggest that the expert knowledge-based approach is effective in mapping landslide susceptibility and that its performance is maintained when it is moved to a new area from the model development area without changes to the knowledge base.

Constructing Knowledge Bases: A Promising Instructional Tool.

ERIC Educational Resources Information Center

Trollip, Stanley R.; Lippert, Renate C.

1987-01-01

Argues that construction of knowledge bases is an instructional tool that encourages students' critical thinking in problem solving situations through metacognitive experiences. A study is described in which college students created expert systems to test the effectiveness of this method of instruction, and benefits for students and teachers are…

Information About a Layperson's Knowledge Supports Experts in Giving Effective and Efficient Online Advice to Laypersons

ERIC Educational Resources Information Center

Nuckles, Matthias; Wittwer, Jorg; Renkl, Alexander

2005-01-01

To give effective and efficient advice to laypersons, experts should adapt their explanations to the layperson's knowledge. However, experts often fail to consider the limited domain knowledge of laypersons. To support adaptation in asynchronous help desk communication, researchers provided computer experts with information about a layperson's…

Expert systems in transmission planning

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

Galiana, F.D.; McGillis, D.T.; Marin, M.A.

1992-05-01

In this paper the state of the field of expert systems and knowledge engineering in transmission planning is reviewed. A detailed analysis of the goals, definition, requirements and methodology of transmission planning is presented. Potential benefits of knowledge-based applications in transmission planning are reviewed. This is followed by a thorough review of the area broken down into subareas or important related topics. The conclusions offer a number of suggestions for possible future research and development. Finally, a detailed bibliography divided into subareas is presented.

Rule groupings: An approach towards verification of expert systems

NASA Technical Reports Server (NTRS)

Mehrotra, Mala

1991-01-01

Knowledge-based expert systems are playing an increasingly important role in NASA space and aircraft systems. However, many of NASA's software applications are life- or mission-critical and knowledge-based systems do not lend themselves to the traditional verification and validation techniques for highly reliable software. Rule-based systems lack the control abstractions found in procedural languages. Hence, it is difficult to verify or maintain such systems. Our goal is to automatically structure a rule-based system into a set of rule-groups having a well-defined interface to other rule-groups. Once a rule base is decomposed into such 'firewalled' units, studying the interactions between rules would become more tractable. Verification-aid tools can then be developed to test the behavior of each such rule-group. Furthermore, the interactions between rule-groups can be studied in a manner similar to integration testing. Such efforts will go a long way towards increasing our confidence in the expert-system software. Our research efforts address the feasibility of automating the identification of rule groups, in order to decompose the rule base into a number of meaningful units.

Identifying key conservation threats to Alpine birds through expert knowledge

PubMed Central

Pedrini, Paolo; Brambilla, Mattia; Rolando, Antonio; Girardello, Marco

2016-01-01

Alpine biodiversity is subject to a range of increasing threats, but the scarcity of data for many taxa means that it is difficult to assess the level and likely future impact of a given threat. Expert opinion can be a useful tool to address knowledge gaps in the absence of adequate data. Experts with experience in Alpine ecology were approached to rank threat levels for 69 Alpine bird species over the next 50 years for the whole European Alps in relation to ten categories: land abandonment, climate change, renewable energy, fire, forestry practices, grazing practices, hunting, leisure, mining and urbanization. There was a high degree of concordance in ranking of perceived threats among experts for most threat categories. The major overall perceived threats to Alpine birds identified through expert knowledge were land abandonment, urbanization, leisure and forestry, although other perceived threats were ranked highly for particular species groups (renewable energy and hunting for raptors, hunting for gamebirds). For groups of species defined according to their breeding habitat, open habitat species and treeline species were perceived as the most threatened. A spatial risk assessment tool based on summed scores for the whole community showed threat levels were highest for bird communities of the northern and western Alps. Development of the approaches given in this paper, including addressing biases in the selection of experts and adopting a more detailed ranking procedure, could prove useful in the future in identifying future threats, and in carrying out risk assessments based on levels of threat to the whole bird community. PMID:26966659

An Expert-System Engine With Operative Probabilities

NASA Technical Reports Server (NTRS)

Orlando, N. E.; Palmer, M. T.; Wallace, R. S.

1986-01-01

Program enables proof-of-concepts tests of expert systems under development. AESOP is rule-based inference engine for expert system, which makes decisions about particular situation given user-supplied hypotheses, rules, and answers to questions drawn from rules. If knowledge base containing hypotheses and rules governing environment is available to AESOP, almost any situation within that environment resolved by answering questions asked by AESOP. Questions answered with YES, NO, MAYBE, DON'T KNOW, DON'T CARE, or with probability factor ranging from 0 to 10. AESOP written in Franz LISP for interactive execution.

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).

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...

A Knowledge Based Approach to VLSI CAD

DTIC Science & Technology

1983-09-01

Avail-and/or Dist ISpecial L| OI. SEICURITY CLASIIrCATION OP THIS IPA.lErllm S Daene." A KNOwLEDE BASED APPROACH TO VLSI CAD’ Louis L Steinberg and...major issues lies in building up and managing the knowledge base of oesign expertise. We expect that, as with many recent expert systems, in order to

Teacher leadership in mathematics and science: Subject content knowledge and the improvement of instruction

NASA Astrophysics Data System (ADS)

Manno, Christopher M.

This study explores the role of teacher leader subject content knowledge in the promotion of professional development and instructional reform. Consistent with a distributed leadership perspective, many have asserted that the promotion of school effectiveness can be enhanced through the application of teacher leadership (Frost & Durrant, 2003; Harris, 2002a; Sherrill, 1999; Silva, Gimbert, & Nolan, 2000; York-Barr & Duke, 2004). There has been much discussion in the research about the significance of teachers' subject content knowledge in teaching and learning which has generally asserted a positive relationship with instructional practice and student achievement (Darling-Hammond, 2000; Newton & Newton, 2001; Parker & Heywood, 2000). The role of content knowledge in teacher leader work has been less researched. This study focused on deepening understanding of perceptions regarding teacher leaders' roles in improving instructional practice. Based on a framework of common teacher leader tasks, qualitative methods were used to investigate the relationship between teacher leader subject content knowledge and perceptions of effectiveness in promoting professional development and instructional reform. The study indicates that content experts behave differently than their non-expert counterparts. Content experts recognize deficiencies in colleagues' content knowledge as a primary problem in the implementation of math or science reform. Content experts view their work as advocacy for improved curriculum and instruction for all children, and work within a small set of task categories to promote discussions about teaching, learning, and content. Content experts develop trust and rapport with colleagues by demonstrating expertise, and are respected for their deep knowledge and efforts to help teachers learn the content. They also differ from non-content experts in the professional growth experiences in which they engage. The consideration of content expertise as an influence to teacher leader work helps to refine our conception of teacher leadership. A task-focused model of content expert teacher leadership is presented, and provides guidance for recruitment, selection, and development of future teacher leaders. Content expertise is presented as a form of human capital that promotes task-focused distributed leadership. Practical recommendations for future teacher leadership initiatives and suggestions for future research are presented.

Fuzzy ontologies for semantic interpretation of remotely sensed images

NASA Astrophysics Data System (ADS)

Djerriri, Khelifa; Malki, Mimoun

2015-10-01

Object-based image classification consists in the assignment of object that share similar attributes to object categories. To perform such a task the remote sensing expert uses its personal knowledge, which is rarely formalized. Ontologies have been proposed as solution to represent domain knowledge agreed by domain experts in a formal and machine readable language. Classical ontology languages are not appropriate to deal with imprecision or vagueness in knowledge. Fortunately, Description Logics for the semantic web has been enhanced by various approaches to handle such knowledge. This paper presents the extension of the traditional ontology-based interpretation with fuzzy ontology of main land-cover classes in Landsat8-OLI scenes (vegetation, built-up areas, water bodies, shadow, clouds, forests) objects. A good classification of image objects was obtained and the results highlight the potential of the method to be replicated over time and space in the perspective of transferability of the procedure.

Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

NASA Technical Reports Server (NTRS)

Lambright, Jonathan Paul

1996-01-01

A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of limited well defined rules. The findings indicated that the technique is most effective when used as a design aid and not as a tool to totally automate the composites design process. Other areas of application and implications for future research are discussed.

A framework for teaching medical students and residents about practice-based learning and improvement, synthesized from a literature review.

PubMed

Ogrinc, Greg; Headrick, Linda A; Mutha, Sunita; Coleman, Mary T; O'Donnell, Joseph; Miles, Paul V

2003-07-01

To create a framework for teaching the knowledge and skills of practice-based learning and improvement to medical students and residents based on proven, effective strategies. The authors conducted a Medline search of English-language articles published between 1996 and May 2001, using the term "quality improvement" (QI), and cross-matched it with "medical education" and "health professions education." A thematic-synthesis method of review was used to compile the information from the articles. Based on the literature review, an expert panel recommended educational objectives for practice-based learning and improvement. Twenty-seven articles met the inclusion criteria. The majority of studies were conducted in academic medical centers and medical schools and 40% addressed experiential learning of QI. More than 75% were qualitative case reports capturing educational outcomes, and 7% included an experimental study design. The expert panel integrated data from the literature review with the Dreyfus model of professional skill acquisition, the Institute for Healthcare Improvement's (IHI) knowledge domains for improving health care, and the ACGME competencies and generated a framework of core educational objectives about teaching practice-based learning and improvement to medical students and residents. Teaching the knowledge and skills of practice-based learning and improvement to medical students and residents is a necessary and important foundation for improving patient care. The authors present a framework of learning objectives-informed by the literature and synthesized by the expert panel-to assist educational leaders when integrating these objectives into a curriculum. This framework serves as a blueprint to bridge the gap between current knowledge and future practice needs.

A knowledge creation info-structure to acquire and crystallize the tacit knowledge of health-care experts.

PubMed

Abidi, Syed Sibte Raza; Cheah, Yu-N; Curran, Janet

2005-06-01

Tacit knowledge of health-care experts is an important source of experiential know-how, yet due to various operational and technical reasons, such health-care knowledge is not entirely harnessed and put into professional practice. Emerging knowledge-management (KM) solutions suggest strategies to acquire the seemingly intractable and nonarticulated tacit knowledge of health-care experts. This paper presents a KM methodology, together with its computational implementation, to 1) acquire the tacit knowledge possessed by health-care experts; 2) represent the acquired tacit health-care knowledge in a computational formalism--i.e., clinical scenarios--that allows the reuse of stored knowledge to acquire tacit knowledge; and 3) crystallize the acquired tacit knowledge so that it is validated for health-care decision-support and medical education systems.

Expert System Shells for Rapid Clinical Decision Support Module Development: An ESTA Demonstration of a Simple Rule-Based System for the Diagnosis of Vaginal Discharge

PubMed Central

2012-01-01

Objectives This study demonstrates the feasibility of using expert system shells for rapid clinical decision support module development. Methods A readily available expert system shell was used to build a simple rule-based system for the crude diagnosis of vaginal discharge. Pictures and 'canned text explanations' are extensively used throughout the program to enhance its intuitiveness and educational dimension. All the steps involved in developing the system are documented. Results The system runs under Microsoft Windows and is available as a free download at http://healthcybermap.org/vagdisch.zip (the distribution archive includes both the program's executable and the commented knowledge base source as a text document). The limitations of the demonstration system, such as the lack of provisions for assessing uncertainty or various degrees of severity of a sign or symptom, are discussed in detail. Ways of improving the system, such as porting it to the Web and packaging it as an app for smartphones and tablets, are also presented. Conclusions An easy-to-use expert system shell enables clinicians to rapidly become their own 'knowledge engineers' and develop concise evidence-based decision support modules of simple to moderate complexity, targeting clinical practitioners, medical and nursing students, as well as patients, their lay carers and the general public (where appropriate). In the spirit of the social Web, it is hoped that an online repository can be created to peer review, share and re-use knowledge base modules covering various clinical problems and algorithms, as a service to the clinical community. PMID:23346475

Determining rules for closing customer service centers: A public utility company's fuzzy decision

NASA Technical Reports Server (NTRS)

Dekorvin, Andre; Shipley, Margaret F.; Lea, Robert N.

1992-01-01

In the present work, we consider the general problem of knowledge acquisition under uncertainty. Simply stated, the problem reduces to the following: how can we capture the knowledge of an expert when the expert is unable to clearly formulate how he or she arrives at a decision? A commonly used method is to learn by examples. We observe how the expert solves specific cases and from this infer some rules by which the decision may have been made. Unique to our work is the fuzzy set representation of the conditions or attributes upon which the expert may possibly base his fuzzy decision. From our examples, we infer certain and possible fuzzy rules for closing a customer service center and illustrate the importance of having the decision closely relate to the conditions under consideration.

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.

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.

Fire Effects, Education, and Expert Systems

Treesearch

Robert E. Martin

1987-01-01

Predicting the effects of fires in the year 2000 and beyond will be enhanced by the use of expert systems. Although our predictions may have broad confidence limits, expert systems should help us to improve the predictions and to focus on the areas where improved knowledge is most needed. The knowledge of experts can be incorporated into previously existing knowledge...

Spacelab Life Sciences-1 electrical diagnostic expert system

NASA Technical Reports Server (NTRS)

Kao, C. Y.; Morris, W. S.

1989-01-01

The Spacelab Life Sciences-1 (SLS-1) Electrical Diagnostic (SLED) expert system is a continuous, real time knowledge-based system to monitor and diagnose electrical system problems in the Spacelab. After fault isolation, the SLED system provides corrective procedures and advice to the ground-based console operator. The SLED system updates its knowledge about the status of Spacelab every 3 seconds. The system supports multiprocessing of malfunctions and allows multiple failures to be handled simultaneously. Information which is readily available via a mouse click includes: general information about the system and each component, the electrical schematics, the recovery procedures of each malfunction, and an explanation of the diagnosis.

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.

Application of a rule-based knowledge system using CLIPS for the taxonomy of selected Opuntia species

NASA Technical Reports Server (NTRS)

Heymans, Bart C.; Onema, Joel P.; Kuti, Joseph O.

1991-01-01

A rule based knowledge system was developed in CLIPS (C Language Integrated Production System) for identifying Opuntia species in the family Cactaceae, which contains approx. 1500 different species. This botanist expert tool system is capable of identifying selected Opuntia plants from the family level down to the species level when given some basic characteristics of the plants. Many plants are becoming of increasing importance because of their nutrition and human health potential, especially in the treatment of diabetes mellitus. The expert tool system described can be extremely useful in an unequivocal identification of many useful Opuntia species.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

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

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

[Translation, cultural adaptation and validation of the Salt Knowledge Questionnaire to the Spanish language].

PubMed

Quinteros-Reyes, C; Marcionelli-Sandhaus, T; Mayta-Tristán, P

2017-11-03

In order to reduce salt consumption in Spanish speaking countries it is necessary to know the level of salt knowledge in the population. However, there are no tools in Spanish to measure salt knowledge, but the only valid tool of measurement is the 'Salt Knowledge Questionnaire' (SKQ) developed in Australia, in English. A validation study was conducted in three phases: (Phase1) Translation of the original Australian version into Spanish; (Phase2) Cultural adaptation based on a Spanish-speaking population such as Peru and following criteria used in the development of the original questionnaire which was evaluated by a panel of experts; (Phase3) Construct validity by comparing the scores of three groups (experts, medical students and non-experts) and reliability by performing a test retest. The translation of the SKQ into Spanish maintained a semantic equivalence with the original questionnaire and a panel of experts accepted the cultural adaptation. The SKQ enables discrimination between those who know and those who do not because differences of scores were found between the group of experts, students and non-experts (P<.001). A good overall internal consistency of the instrument was found (KR20=0.69) and a good overall intraclass correlation (0.79) and no test variations in test-retest (P>.05). The SKQ questionnaire in Spanish is valid, reliable and is a suitable first tool to measure knowledge about salt in the Spanish language. It is considered possible to adapt it culturally to the Spanish-speaking country that wishes to use it. Copyright © 2017 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

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.

The use of cognitive task analysis to reveal the instructional limitations of experts in the teaching of procedural skills.

PubMed

Sullivan, Maura E; Yates, Kenneth A; Inaba, Kenji; Lam, Lydia; Clark, Richard E

2014-05-01

Because of the automated nature of knowledge, experts tend to omit information when describing a task. A potential solution is cognitive task analysis (CTA). The authors investigated the percentage of knowledge experts omitted when teaching a cricothyrotomy to determine the percentage of additional knowledge gained during a CTA interview. Three experts were videotaped teaching a cricothyrotomy in 2010 at the University of Southern California. After transcription, they participated in CTA interviews for the same procedure. Three additional surgeons were recruited to perform a CTA for the procedure, and a "gold standard" task list was created. Transcriptions from the teaching sessions were compared with the task list to identify omitted steps (both "what" and "how" to do). Transcripts from the CTA interviews were compared against the task list to determine the percentage of knowledge articulated by each expert during the initial "free recall" (unprompted) phase of the CTA interview versus the amount of knowledge gained by using CTA elicitation techniques (prompted). Experts omitted an average of 71% (10/14) of clinical knowledge steps, 51% (14/27) of action steps, and 73% (3.6/5) of decision steps. For action steps, experts described "how to do it" only 13% (3.6/27) of the time. The average number of steps that were described increased from 44% (20/46) when unprompted to 66% (31/46) when prompted. This study supports previous research that experts unintentionally omit knowledge when describing a procedure. CTA is a useful method to extract automated knowledge and augment expert knowledge recall during teaching.

Knowledge structures and the acquisition of a complex skill.

PubMed

Day, E A; Arthur, W; Gettman, D

2001-10-01

The purpose of this study was to examine the viability of knowledge structures as an operationalization of learning in the context of a task that required a high degree of skill. Over the course of 3 days, 86 men participated in 9 training sessions and learned a complex video game. At the end of acquisition, participants' knowledge structures were assessed. After a 4-day nonpractice interval, trainees completed tests of skill retention and skill transfer. Findings indicated that the similarity of trainees' knowledge structures to an expert structure was correlated with skill acquisition and was predictive of skill retention and skill transfer. However, the magnitude of these effects was dependent on the method used to derive the expert referent structure. Moreover, knowledge structures mediated the relationship between general cognitive ability and skill-based performance.

Understanding the role of knowledge in the practice of expert nephrology nurses in Australia.

PubMed

Bonner, Ann

2007-09-01

This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the role of knowledge in expert practice. Using grounded theory methodology, the study involved 17 registered nurses who were practicing in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participants' observations and interviews. Having extensive nephrology nursing knowledge was a striking characteristic of a nursing expert. Expert nurses clearly relied on and utilized extensive nephrology nursing knowledge to practice. Of importance for nursing, the results of this study indicate that domain-specific knowledge is a crucial feature of expert practice.

The Galileo PPS expert monitoring and diagnostic prototype

NASA Technical Reports Server (NTRS)

Bahrami, Khosrow

1989-01-01

The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text.

An architecture for rule based system explanation

NASA Technical Reports Server (NTRS)

Fennel, T. R.; Johannes, James D.

1990-01-01

A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented.

Implementing a Knowledge-Based Library Information System with Typed Horn Logic.

ERIC Educational Resources Information Center

Ait-Kaci, Hassan; And Others

1990-01-01

Describes a prototype library expert system called BABEL which uses a new programing language, LOGIN, that combines the idea of attribute inheritance with logic programing. Use of hierarchical classification of library objects to build a knowledge base for a library information system is explained, and further research is suggested. (11…

An Ada inference engine for expert systems

NASA Technical Reports Server (NTRS)

Lavallee, David B.

1986-01-01

The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.

Knowledge discovery through games and game theory

NASA Astrophysics Data System (ADS)

Smith, James F., III; Rhyne, Robert D.

2001-03-01

A fuzzy logic based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, robots, land based facilities, etc. Potential foes the platforms deal with can also be general. The initial version of the algorithm was optimized using a genetic algorithm employing fitness functions constructed based on expertise. A new approach is being explored that involves embedding the resource manager in a electronic game environment. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the database as required. The game allows easy evaluation of the information mined in the second step. The measure of effectiveness (MOE) for re-optimization is discussed. The mined information is extremely valuable as shown through demanding scenarios.

A knowledge based expert system for propellant system monitoring at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Jamieson, J. R.; Delaune, C.; Scarl, E.

1985-01-01

The Lox Expert System (LES) is the first attempt to build a realtime expert system capable of simulating the thought processes of NASA system engineers, with regard to fluids systems analysis and troubleshooting. An overview of the hardware and software describes the techniques used, and possible applications to other process control systems. LES is now in the advanced development stage, with a full implementation planned for late 1985.

TES: A modular systems approach to expert system development for real time space applications

NASA Technical Reports Server (NTRS)

England, Brenda; Cacace, Ralph

1987-01-01

A major goal of the space station era is to reduce reliance on support from ground based experts. The TIMES Expert System (TES) is an application that monitors and evaluates real time data to perform fault detection and fault isolation as it would otherwise be carried out by a knowledgeable designer. The development process and primary features of the TES, the modular system and the lessons learned are discussed.

Using XML and XSLT for flexible elicitation of mental-health risk knowledge.

PubMed

Buckingham, C D; Ahmed, A; Adams, A E

2007-03-01

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge.

The Spacecraft Materials Selector: An Artificial Intelligence System for Preliminary Design Trade Studies, Materials Assessments, and Estimates of Environments Present

NASA Technical Reports Server (NTRS)

Pippin, H. G.; Woll, S. L. B.

2000-01-01

Institutions need ways to retain valuable information even as experienced individuals leave an organization. Modern electronic systems have enough capacity to retain large quantities of information that can mitigate the loss of experience. Performance information for long-term space applications is relatively scarce and specific information (typically held by a few individuals within a single project) is often rather narrowly distributed. Spacecraft operate under severe conditions and the consequences of hardware and/or system failures, in terms of cost, loss of information, and time required to replace the loss, are extreme. These risk factors place a premium on appropriate choice of materials and components for space applications. An expert system is a very cost-effective method for sharing valuable and scarce information about spacecraft performance. Boeing has an artificial intelligence software package, called the Boeing Expert System Tool (BEST), to construct and operate knowledge bases to selectively recall and distribute information about specific subjects. A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft has been developed under contract to the NASA SEE program. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described. The knowledge base is a backward-chaining, rule-based system. The user answers a sequence of questions, and the expert system provides estimates of optical and mechanical performance of selected materials under specific environmental conditions. The initial operating capability of the system will include data for Kapton, silverized Teflon, selected paints, silicone-based materials, and certain metals. For situations where a mission profile (launch date, orbital parameters, mission duration, spacecraft orientation) is not precisely defined, the knowledge base still attempts to provide qualitative observations about materials performance and likely exposures. Prior to the NASA contract, a knowledge base, the Spacecraft Environments Assistant (SEA,) was initially developed by Boeing to estimate the environmental factors important for a specific spacecraft mission profile. The NASA SEE program has funded specific enhancements to the capability of this knowledge base. The SEA qualitatively identifies over 25 environmental factors that may influence the performance of a spacecraft during its operational lifetime. For cases where sufficiently detailed answers are provided to questions asked by the knowledge base, atomic oxygen fluence levels, proton and/or electron fluence and dose levels, and solar exposure hours are calculated. The SMS knowledge base incorporates the previously developed SEA knowledge base. A case history for previous flight experiment will be shown as an example, and capabilities and limitations of the system will be discussed.

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

NASA Astrophysics Data System (ADS)

Fredouille, Corinne; Pouchoulin, Gilles; Ghio, Alain; Revis, Joana; Bonastre, Jean-François; Giovanni, Antoine

2009-12-01

This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0-3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Astrophysics Data System (ADS)

Huang, Jen-Kuang; Ho, Ming-Tsang; Ash, Robert L.

1992-08-01

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling.

PubMed

Fischer, Heidi J; Vergara, Ximena P; Yost, Michael; Silva, Michael; Lombardi, David A; Kheifets, Leeka

2017-01-01

Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.

The knowledge of expert nurses and the practical-reflective rationality.

PubMed

Pina Queirós, Paulo Joaquim

2015-01-01

To identify the characteristics of an expert nurse. A group of 49 nurses starting their Master's degree was asked to answer the following question: ''Which characteristics and skills distinguish a novice from an expert nurse?'' The answers were analyzed and classified based on Bardin's content analysis. Through a three-stage classification process, the competences and skills assigned to expert nurses were divided into 17 categories. These nurses showed wide-ranging skills and acquired meta-competencies. Expert nurses are characterized by their leadership, supervision and ability to manage change, as well as their communication and relational skills. They have the ability to act reflectively, plan, systematize and consistently assess; they also show more dexterity. They have more adaptive skills, confidence and achieve a broader view. They are competent while managing conflicts and stress, as well as articulating theory and practice; they create knowledge, make use of research, respond to complex situations and are capable of making decisions. Expert nurses have anticipation skills, insight, use detailed observation, take immediate action and are able to define priorities; they keep context in mind and have a tendency for specialization.

Linking medical records to an expert system

NASA Technical Reports Server (NTRS)

Naeymi-Rad, Frank; Trace, David; Desouzaalmeida, Fabio

1991-01-01

This presentation will be done using the IMR-Entry (Intelligent Medical Record Entry) system. IMR-Entry is a software program developed as a front-end to our diagnostic consultant software MEDAS (Medical Emergency Decision Assistance System). MEDAS (the Medical Emergency Diagnostic Assistance System) is a diagnostic consultant system using a multimembership Bayesian design for its inference engine and relational database technology for its knowledge base maintenance. Research on MEDAS began at the University of Southern California and the Institute of Critical Care in the mid 1970's with support from NASA and NSF. The MEDAS project moved to Chicago in 1982; its current progress is due to collaboration between Illinois Institute of Technology, The Chicago Medical School, Lake Forest College and NASA at KSC. Since the purpose of an expert system is to derive a hypothesis, its communication vocabulary is limited to features used by its knowledge base. The development of a comprehensive problem based medical record entry system which could handshake with an expert system while creating an electronic medical record at the same time was studied. IMR-E is a computer based patient record that serves as a front end to the expert system MEDAS. IMR-E is a graphically oriented comprehensive medical record. The programs major components are demonstrated.

Development of a Knowledge Base for Use in an Expert System Advisor for Aircraft Maintenance Scheduling (ESAAMS)

DTIC Science & Technology

1991-03-01

Cliffs, New Jersey, 1989. Merritt, Dennis, "Forward Chaining in Prolog," Al Expert, v.7 November 1986. Minsky , Marvin ., "A Framework for Representing... Minsky , Marvin , (editor), Semantic Information Processing, MIT Press, 1968. Rychener, M. D., Production Systems as a Programming Language for Artificial

Toward a Knowledge Base for School Learning. Publication Series #93-5a.

ERIC Educational Resources Information Center

Wang, M. C.; And Others

The study explores the relative effects of a wide range of variables that influence learning, and whether three methods--content analysis, expert ratings, and meta-analysis--agree on whether and how strongly these variables influence learning, using the educational research literature and an expert survey. The presence of an emergent knowledge…

Machine Methods for Acquiring, Learning, and Applying Knowledge.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; And Others

A research plan for identifying and acting upon constraints that impede the development of knowledge-based intelligent systems is described. The two primary problems identified are knowledge programming, the task of which is to create an intelligent system that does what an expert says it should, and learning, the problem requiring the criticizing…

Quantitative knowledge acquisition for expert systems

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. While it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a direct task. A statistical method is presented for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development is described of a Navigation Sensor Management (NSM) Expert System from Kalman Filter convariance data. The method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 Algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithms identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. Both are detailed.

The development of expertise in pediatric rehabilitation therapists: changes in approach, self-knowledge, and use of enabling and customizing strategies.

PubMed

King, Gillian; Currie, Melissa; Bartlett, Doreen J; Gilpin, Michelle; Willoughby, Colleen; Tucker, Mary Ann; Strachan, Deborah; Baxter, Donna

2007-01-01

To examine the clinical decision making of novice, intermediate, and expert pediatric rehabilitation therapists from various disciplines. Two qualitative studies were conducted. Thirteen therapists took part in a study using the critical incident interview technique and 11 therapists took part in a study using the 'think aloud' technique. Therapists were classified as novice, intermediate, or expert in developmental level based on a cluster analysis of data collected using a multifaceted battery of assessment tools. Data were analyzed using a grounded theory approach. Expert and intermediate therapists differed from novices with respect to content, self-, and procedural knowledge. With increasing expertise, therapists use a supportive, educational, holistic, functional, and strengths-based approach; have heightened humility yet increased self-confidence; and understand how to facilitate and support client change and adaptation by using principles of engagement, coherence, and manageability. Expert therapists use enabling and customizing strategies to ensure a successful therapeutic session, optimize the child's functioning in the mid-term, and ensure child and family adaptation and accommodation over the longer-term.

Interteaching

ERIC Educational Resources Information Center

Saville, Bryan K.; Zinn, Tracy E.

2011-01-01

In general, people associate college and university teaching with lecture-based methods, in which an expert (the teacher) delivers information to a group of nonexperts (the students), who subsequently show their newfound "knowledge" by answering examination questions. Because of the common notion that knowledge and intelligence are…

The evolution and provision of expert knowledge and its effective utilisation

NASA Astrophysics Data System (ADS)

Sammonds, Peter

2017-04-01

The specific aims of increasing Resilience to Natural Hazards in China programme are (i) to improve hazard forecasting, risk mitigation and preparedness based upon reliable knowledge of the fundamental processes involved and underpinned by basic science and, (ii) to improve the uptake of and responses to scientific advice, by developing risk-based approaches to natural hazards in collaboration with the communities at risk. One of the programme's principal goals is to integrate natural and social science research to increase the benefits for those affected by natural hazards. To that end a co-productive approach to research is expected, involving a framework for sharing knowledge and values between natural and social scientists and consultation with policy makers, civil society and other stakeholders. This paper explore knowledge relationships and reflective learning across disciplines. There is commonly a disjunction between the evolution and provision of expert knowledge and its effective utilisation. Building on experience as Strategic Advisor to the Increasing Resilience to Natural Hazards programme, this paper addresses the research needs to assess how scientific knowledge and risk reduction strategies can be most effectively developed and communicated.

Machine intelligence and autonomy for aerospace systems

NASA Technical Reports Server (NTRS)

Heer, Ewald (Editor); Lum, Henry (Editor)

1988-01-01

The present volume discusses progress toward intelligent robot systems in aerospace applications, NASA Space Program automation and robotics efforts, the supervisory control of telerobotics in space, machine intelligence and crew/vehicle interfaces, expert-system terms and building tools, and knowledge-acquisition for autonomous systems. Also discussed are methods for validation of knowledge-based systems, a design methodology for knowledge-based management systems, knowledge-based simulation for aerospace systems, knowledge-based diagnosis, planning and scheduling methods in AI, the treatment of uncertainty in AI, vision-sensing techniques in aerospace applications, image-understanding techniques, tactile sensing for robots, distributed sensor integration, and the control of articulated and deformable space structures.

An SSME High Pressure Oxidizer Turbopump diagnostic system using G2 real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2 real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for the SSME. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach has been adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

An SSME high pressure oxidizer turbopump diagnostic system using G2(TM) real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2(TM) real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for Space Shuttle Main Engine. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach was adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

An expert system for the evaluation of reinforced concrete structure durability

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

Berra, M.; Bertolini, L.; Briglia, M.C.

1999-11-01

A user-friendly expert system has been developed to evaluate primarily the durability of reinforced concrete structures, either in the design phase or during service life related to reinforcement corrosion. Besides the durability module, the ES has been provided with three other expert modules in order to support the user during the following activities: inspections, corrosion diagnosis and repair strategy (of concrete and reinforcement). Corrosion induced by carbonation and chlorides penetration and caused by concrete degradation such as sulfate attack, freeze/thaw cycles, alkali silica reaction are considered. The knowledge used for the expert system is based both on open literature andmore » international standards as well as on specific experiences and proprietary databases. The paper describes main features of the system, including the modeling of the knowledge, input data, the algorithms, the rules and the outputs for each module.« less

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology

PubMed Central

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y.-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-01-01

Abstract Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy. PMID:29850871

Fuel management optimization using genetic algorithms and expert knowledge

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

DeChaine, M.D.; Feltus, M.A.

1996-09-01

The CIGARO fuel management optimization code based on genetic algorithms is described and tested. The test problem optimized the core lifetime for a pressurized water reactor with a penalty function constraint on the peak normalized power. A bit-string genotype encoded the loading patterns, and genotype bias was reduced with additional bits. Expert knowledge about fuel management was incorporated into the genetic algorithm. Regional crossover exchanged physically adjacent fuel assemblies and improved the optimization slightly. Biasing the initial population toward a known priority table significantly improved the optimization.

Workers' understanding of chemical risks: electroplating case study

PubMed Central

Sadhra, S; Petts, J; McAlpine, S; Pattison, H; MacRae, S

2002-01-01

Background: There is limited research concerning how small companies in particular, respond to health and safety messages. Aims: To understand individuals' knowledge and beliefs about chemical risks and to compare these with those of experts. Methods: The use of chromic acid in particular, and also other chemicals associated with chrome plating were studied. All chromium plating firms were based in the West Midlands. The methodology involved initial face to face interviews (n = 21) with chromium platers, structured questionnaires (n = 84) to test the prevalence of beliefs identified in the interviews, an expert questionnaire, and a workshop to discuss findings. The responses of platers were compared with those of occupational health and safety experts. Results: Although chromium platers appeared to understand the short term adverse effects of the chemicals to which they are exposed, their understanding of long term, or chronic effects appeared to be incomplete. They had good knowledge of acute effects based primarily on experience. Platers were aware of the hazardous nature of the chemicals with which they work, but did not draw distinction between the terms "hazards" and "risks". They had difficulties articulating the effects of the chemicals and how exposure might occur; although it is inappropriate to equate this with lack of knowledge. A significant minority of platers displayed deficiencies in understanding key technical terms used in Safety Data Sheets. Conclusions: This study provides a method which can be used to gain some understanding of workers' knowledge and beliefs about risks that they are exposed to in the workplace. The study also identifies gaps between the platers' knowledge and beliefs and those of experts. New risk information needs to be designed which addresses the information needs of platers using language that they understand. PMID:12356930

Map Reading beyond Information Given: The Expert Orienteers' Internal Knowledge about Terrain.

ERIC Educational Resources Information Center

Murakoshi, Shin

1990-01-01

Compares novice and expert orienteers' map interpretation skills. Subjects asked to judge terrain from maps, including conditions inferable without corresponding map symbols. Experts' interpretation of identical symbols implies use of experiential knowledge. Internal knowledge characteristics discussed in terms of episodic-semantic memory…

Design and implementation of a status at a glance user interface for a power distribution expert system

NASA Technical Reports Server (NTRS)

Liberman, Eugene M.; Manner, David B.; Dolce, James L.; Mellor, Pamela A.

1993-01-01

Expert systems are widely used in health monitoring and fault detection applications. One of the key features of an expert system is that it possesses a large body of knowledge about the application for which it was designed. When the user consults this knowledge base, it is essential that the expert system's reasoning process and its conclusions be as concise as possible. If, in addition, an expert system is part of a process monitoring system, the expert system's conclusions must be combined with current events of the process. Under these circumstances, it is difficult for a user to absorb and respond to all the available information. For example, a user can become distracted and confused if two or more unrelated devices in different parts of the system require attention. A human interface designed to integrate expert system diagnoses with process data and to focus the user's attention to the important matters provides a solution to the 'information overload' problem. This paper will discuss a user interface to the power distribution expert system for Space Station Freedom. The importance of features which simplify assessing system status and which minimize navigating through layers of information will be discussed. Design rationale and implementation choices will also be presented.

Use of the Rasch Measurement Model to Explore the Relationship between Content Knowledge and Topic-Specific Pedagogical Content Knowledge for Organic Chemistry

ERIC Educational Resources Information Center

Davidowitz, Bette; Potgieter, Marietjie

2016-01-01

Research has shown that a high level of content knowledge (CK) is necessary but not sufficient to develop the special knowledge base of expert teachers known as pedagogical content knowledge (PCK). This study contributes towards research to quantify the relationship between CK and PCK in science. In order to determine the proportion of the…

Designing Collaborative E-Learning Environments Based upon Semantic Wiki: From Design Models to Application Scenarios

ERIC Educational Resources Information Center

Li, Yanyan; Dong, Mingkai; Huang, Ronghuai

2011-01-01

The knowledge society requires life-long learning and flexible learning environment that enables fast, just-in-time and relevant learning, aiding the development of communities of knowledge, linking learners and practitioners with experts. Based upon semantic wiki, a combination of wiki and Semantic Web technology, this paper designs and develops…

Robot path planning using expert systems and machine vision

NASA Astrophysics Data System (ADS)

Malone, Denis E.; Friedrich, Werner E.

1992-02-01

This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.

An Ontology-Based Conceptual Model For Accumulating And Reusing Knowledge In A DMAIC Process

NASA Astrophysics Data System (ADS)

Nguyen, ThanhDat; Kifor, Claudiu Vasile

2015-09-01

DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

Knowledge acquisition for medical diagnosis using collective intelligence.

PubMed

Hernández-Chan, G; Rodríguez-González, A; Alor-Hernández, G; Gómez-Berbís, J M; Mayer-Pujadas, M A; Posada-Gómez, R

2012-11-01

The wisdom of the crowds (WOC) is the process of taking into account the collective opinion of a group of individuals rather than a single expert to answer a question. Based on this assumption, the use of processes based on WOC techniques to collect new biomedical knowledge represents a challenging and cutting-edge trend on biomedical knowledge acquisition. The work presented in this paper shows a new schema to collect diagnosis information in Diagnosis Decision Support Systems (DDSS) based on collective intelligence and consensus methods.

Knowledge-acquisition tools for medical knowledge-based systems.

PubMed

Lanzola, G; Quaglini, S; Stefanelli, M

1995-03-01

Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.

An Intervention Based on Video Feedback and Questioning to Improve Tactical Knowledge in Expert Female Volleyball Players.

PubMed

Moreno, M Perla; Moreno, Alberto; García-González, Luis; Ureña, Aurelio; Hernández, César; Del Villar, Fernando

2016-06-01

This study applied an intervention program, based on video feedback and questioning, to expert female volleyball players to improve their tactical knowledge. The sample consisted of eight female attackers (26 ± 2.6 years old) from the Spanish National Volleyball Team, who were divided into an experimental group (n = 4) and a control group (n = 4). The video feedback and questioning program applied in the study was developed over eight reflective sessions and consisted of three phases: viewing of the selected actions, self-analysis and reflection by the attacker, and joint player-coach analysis. The attackers were videotaped in an actual game and four clips (situations) of each of the attackers were chosen for each reflective session. Two of the clips showed a correct action by the attacker, and two showed an incorrect decision. Tactical knowledge was measured by problem representation with a verbal protocol. The members of the experimental group showed adaptations in long-term memory, significantly improving their tactical knowledge. With respect to conceptual content, there was an increase in the total number of conditions verbalized by the players; with respect to conceptual sophistication, there was an increase in the indication of appropriate conditions with two or more details; and finally, with respect to conceptual structure, there was an increase in the use of double or triple conceptual structures. The intervention program, based on video feedback and questioning, in addition to on-court training sessions of expert volleyball players, appears to improve the athletes' tactical knowledge. © The Author(s) 2016.

Knowledge Acquisition: A Review of Tools and Ideas.

DTIC Science & Technology

1987-08-01

tools. However, none could be applied directly to solving the problem of acquiring knowledge for the ASPA. RECOMMENDATIONS Develop a tool based on...the social sciences. BACKGROUND Because of the newness and complexity of the knowledge acquisition problem, the background of the knowledge...4. Minimal (does not incorporate any unnecessary complexities ) 5. Expected (experts are not in disagreement over any important aspect) (Grover 1983

A Computer Clone of Human Expert for Mobility Management Scheme (E-MMS): Step toward Green Transportation

NASA Astrophysics Data System (ADS)

Resdiansyah; O. K Rahmat, R. A.; Ismail, A.

2018-03-01

Green transportation refers to a sustainable transport that gives the least impact in terms of social and environmental but at the same time is able to supply energy sources globally that includes non-motorized transport strategies deployment to promote healthy lifestyles, also known as Mobility Management Scheme (MMS). As construction of road infrastructure cannot help solve the problem of congestion, past research has shown that MMS is an effective measure to mitigate congestion and to achieve green transportation. MMS consists of different strategies and policies that subdivided into categories according to how they are able to influence travel behaviour. Appropriate selection of mobility strategies will ensure its effectiveness in mitigating congestion problems. Nevertheless, determining appropriate strategies requires human expert and depends on a number of success factors. This research has successfully developed a computer clone system based on human expert, called E-MMS. The process of knowledge acquisition for MMS strategies and the next following process to selection of strategy has been encode in a knowledge-based system using a shell expert system. The newly developed computer cloning system was successfully verified, validated and evaluated (VV&E) by comparing the result output with the real transportation expert recommendation in which the findings suggested Introduction

Forecasting Doctoral-Level Content in Agricultural Education: Viewpoints of Engaged Scholars in the United States

ERIC Educational Resources Information Center

Shinn, Glen C.; Briers, Gary; Baker, Matt

2008-01-01

In this study, the researchers used a classical Delphi method to re-examine the conceptual framework, definition, and knowledge base of the field. Seventeen engaged scholars, each representing the expert agricultural education community, reached consensus on defining the field of study, 10 knowledge domains, and 67 knowledge objects. The Delphi…

The Knowledge Base and Memory Performance: A Comparison of Academically Successful and Unsuccessful Learners. Paper 5/1987.

ERIC Educational Resources Information Center

Schneider, Wolfgang; And Others

The expert-novice paradigm, which demonstrates the outstanding role of domain-specific knowledge in explaining differences in memory behavior and performance, was examined. Two studies are described which compared memory performance of groups equivalent with regard to domain-specific knowledge but differing in intellectual ability. The hypothesis…

Inflexibility of Experts--Reality or Myth? Quantifying the Einstellung Effect in Chess Masters

ERIC Educational Resources Information Center

Bilalic, Merim; McLeod, Peter; Gobet, Fernand

2008-01-01

How does the knowledge of experts affect their behaviour in situations that require unusual methods of dealing? One possibility, loosely originating in research on creativity and skill acquisition, is that an increase in expertise can lead to inflexibility of thought due to automation of procedures. Yet another possibility, based on expertise…

Physical Activity and Older Adults: Expert Consensus for a New Research Agenda

ERIC Educational Resources Information Center

Hughes, Susan L.; Leith, Katherine H.; Marquez, David X.; Moni, Gwen; Nguyen, Huong Q.; Desai, Pankaja; Jones, Dina L.

2011-01-01

Purpose: This study sought to advance the state of knowledge regarding physical activity and aging by identifying areas of agreement among experts regarding topics that are well understood versus those that are in urgent need of continued research efforts. Design and methods: We used a web-based survey with snowball sampling to identify 348…

Investigating a Metacognitive Strategy for Solving Indefinite Integration Problems in Calculus: An fMRI Study

ERIC Educational Resources Information Center

Schroeder, Larissa Bucchi

2011-01-01

Expertise and expert performance has long been a rich area of research. Experts differ from novices in several ways including the depth of their knowledge base, the ability to detect and recognize salient features of problems, more skilled and accurate performance, and strong self-monitoring skills. Advances in neuroscience methods such as…

Dengue Disease Risk Mental Models in the City of Dhaka, Bangladesh: Juxtapositions and Gaps Between the Public and Experts.

PubMed

Dhar-Chowdhury, Parnali; Haque, C Emdad; Driedger, S Michelle

2016-05-01

Worldwide, more than 50 million cases of dengue fever are reported every year in at least 124 countries, and it is estimated that approximately 2.5 billion people are at risk for dengue infection. In Bangladesh, the recurrence of dengue has become a growing public health threat. Notably, knowledge and perceptions of dengue disease risk, particularly among the public, are not well understood. Recognizing the importance of assessing risk perception, we adopted a comparative approach to examine a generic methodology to assess diverse sets of beliefs related to dengue disease risk. Our study mapped existing knowledge structures regarding the risk associated with dengue virus, its vector (Aedes mosquitoes), water container use, and human activities in the city of Dhaka, Bangladesh. "Public mental models" were developed from interviews and focus group discussions with diverse community groups; "expert mental models" were formulated based on open-ended discussions with experts in the pertinent fields. A comparative assessment of the public's and experts' knowledge and perception of dengue disease risk has revealed significant gaps in the perception of: (a) disease risk indicators and measurements; (b) disease severity; (c) control of disease spread; and (d) the institutions responsible for intervention. This assessment further identifies misconceptions in public perception regarding: (a) causes of dengue disease; (b) dengue disease symptoms; (c) dengue disease severity; (d) dengue vector ecology; and (e) dengue disease transmission. Based on these results, recommendations are put forward for improving communication of dengue risk and practicing local community engagement and knowledge enhancement in Bangladesh. © 2015 Society for Risk Analysis.

Using Pathfinder networks to discover alignment between expert and consumer conceptual knowledge from online vaccine content.

PubMed

Amith, Muhammad; Cunningham, Rachel; Savas, Lara S; Boom, Julie; Schvaneveldt, Roger; Tao, Cui; Cohen, Trevor

2017-10-01

This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience's conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Facilitating Subject Matter Expert (SME)-Built Knowledge Bases (KBS)

DTIC Science & Technology

2004-12-01

exists in the field of economics. Most economics textbooks articulate the desirability of maintaining low inflation, ceteris paribus. However, policy...might say that functional knowledge is what the economic policymakers have and rely on to realize the principles agreed upon in economics textbooks . Note

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.

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.

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.

Evaluation of HardSys/HardDraw, An Expert System for Electromagnetic Interactions Modelling

DTIC Science & Technology

1993-05-01

interactions ir complex systems. This report gives a description of HardSys/HardDraw and reviews the main concepts used in its design. Various aspects of its ...HardDraw, an expert system for the modelling of electromagnetic interactions in complex systems. It consists of two main components: HardSys and HardDraw...HardSys is the advisor part of the expert system. It is knowledge-based, that is it contains a database of models and properties for various types of

An Investigation of Expert Systems Usage for Software Requirements Development in the Strategic Defense Initiative Environment.

DTIC Science & Technology

1986-06-10

the solution of the base could be the solution of the target. If expert systems are to mimic humans , then they should inherently utilize analogy. In the...expert systems environment, the theory of frames for representing knowledge developed partly because humans usually solve problems by first seeing if...Goals," Computer, May 1975, p. 17. 8. A.I. Wasserman, "Some Principles of User Software Engineering for Information Systems ," Digest of Papers, COMPCON

[Clinical treatment of children and adolescents with gender dysphoria from international experts' point of view].

PubMed

Rutzen, Katharina M; Nieder, Timo Ole; Schreier, Herbert; Möller, Birgit

2014-01-01

The clinical treatment of children and adolescents with gender dysphoria is still a controversial issue. The aim of this study was to get an overview of the knowledge and experience of international experts and to highlight shared views as well as differences in theoretical convictions and treatment approaches. Half-structured, guide-line based interviews were carried out with international experts in the field. The interviews were analyzed using qualitative content analysis (Mayring, 2010).

Breakfast barriers and opportunities for children living in a Dutch disadvantaged neighbourhood.

PubMed

van Kleef, Ellen; Vingerhoeds, Monique H; Vrijhof, Milou; van Trijp, Hans C M

2016-12-01

The objective of this study was to explore parents', children's, and experts' beliefs and experiences about breakfast motivation, opportunity, and ability and elicit their thoughts on effective interventions to encourage healthy breakfast consumption. The setting was a disadvantaged neighbourhood in Rotterdam, the Netherlands. Focus groups with mothers and children and semi-structured individual interviews with experts were conducted. Interview guides were developed based on the motivation, opportunity, and ability consumer psychology model. Thirty-two mothers of primary school children participated in five group discussions, eight focus groups were conducted with 44 children, and nine experts participated in interviews. Data from expert interviews and group discussions were coded and thematically analysed. The following themes emerged from the focus groups: (1) generally high motivation to have breakfast, (2) improved performance at school is key motivator, (3) limited time hinders breakfast, and (4) lack of nutritional knowledge about high quality breakfast. Experts mentioned lack of effort, knowledge, and time; financial constraints; and environmental issues (food availability) as barriers to breakfasting healthily. Several ways to encourage healthy breakfasting habits were identified: (1) involvement of both children and parents, (2) role models inspiring change, and (3) interactive educational approaches. Experts perceived more problems and challenges in achieving healthy breakfast habits than did mothers and children. Lack of opportunity (according to the children and experts) and ability (according to the experts) were identified, although the motivation to eat a healthy breakfast was present. Predominant barriers are lack of time and nutritional knowledge. Overall, findings suggest educational and social marketing approaches as interventions to encourage healthy breakfast consumption. Copyright © 2016 Elsevier Ltd. All rights reserved.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

PubMed

Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

2016-06-01

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

The Case for Creative Abrasion: Experts Speak Out on Knowledge Management.

ERIC Educational Resources Information Center

Cowley-Durst, Barbara; Christensen, Hal D.; Degler, Duane; Weidner, Douglas; Feldstein, Michael

2001-01-01

Five knowledge management (KM) experts discuss answers to six fundamental issues of KM that address: a definition of knowledge and KM; relationship between business and KM; whether technology has helped the knowledge worker; relationship between learning, performance, knowledge, and community; the promise of knowledge ecology or ecosystem and…

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

A quality assessment tool for markup-based clinical guidelines.

PubMed

Shalom, Erez; Shahar, Yuval; Taieb-Maimon, Meirav; Lunenfeld, Eitan

2008-11-06

We introduce a tool for quality assessment of procedural and declarative knowledge. We developed this tool for evaluating the specification of mark-up-based clinical GLs. Using this graphical tool, the expert physician and knowledge engineer collaborate to perform scoring, using pre-defined scoring scale, each of the knowledge roles of the mark-ups, comparing it to a gold standard. The tool enables scoring the mark-ups simultaneously at different sites by different users at different locations.

Toward the integration of expert knowledge and instrumental data to control food processes: application to Camembert-type cheese ripening.

PubMed

Sicard, M; Perrot, N; Leclercq-Perlat, M-N; Baudrit, C; Corrieu, G

2011-01-01

Modeling the cheese ripening process remains a challenge because of its complexity. We still lack the knowledge necessary to understand the interactions that take place at different levels of scale during the process. However, information may be gathered from expert knowledge. Combining this expertise with knowledge extracted from experimental databases may allow a better understanding of the entire ripening process. The aim of this study was to elicit expert knowledge and to check its validity to assess the evolution of organoleptic quality during a dynamic food process: Camembert cheese ripening. Experiments on a pilot scale were carried out at different temperatures and relative humidities to obtain contrasting ripening kinetics. During these experiments, macroscopic evolution was evaluated from an expert's point of view and instrumental measurements were carried out to simultaneously monitor microbiological, physicochemical, and biochemical kinetics. A correlation of 76% was established between the microbiological, physicochemical, and biochemical data and the sensory phases measured according to expert knowledge, highlighting the validity of the experts' measurements. In the future, it is hoped that this expert knowledge may be integrated into food process models to build better decision-aid systems that will make it possible to preserve organoleptic qualities by linking them to other phenomena at the microscopic level. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Pedagogical Content Knowledge in Action: Its Impromptu Development by an Expert Practitioner

ERIC Educational Resources Information Center

Saito, Eisuke; Atencio, Matthew

2016-01-01

Research into pedagogical content knowledge (PCK) has advanced over the years. Yet, since most research has developed within specific subject areas, this paper aims to investigate how an expert teacher generates PCK by using various forms of knowledge. This study draws upon the case of an expert Japanese teacher, Mr. T, an educational consultant…

Uncovering clinical knowledge and caring practices.

PubMed

Feldman, M E

1993-06-01

Narrative storytelling is a means by which knowledge embedded in nursing practice is uncovered and examined. Benner uses this method to study and explore skill acquisition and experience-based knowledge in nursing practice. By sharing these stories, knowledge that is unique to the experienced clinician is preserved and extended. The narrative presented here describes the expert coaching, discretionary judgment, and skilled involvement in the care of a patient in the PACU.

Expert Systems: A Challenge for the Reading Profession.

ERIC Educational Resources Information Center

Balajthy, Ernest

The expert systems are designed to imitate the reasoning of a human expert in a content area field. Designed to be advisors, these software systems combine the content area knowledge and decision-making ability of an expert with the user's understanding and knowledge of particular circumstances. The reading diagnosis system, the RD2P System…

Expert-Novice Differences in the Understanding and Explanation of Complex Political Conflicts

ERIC Educational Resources Information Center

Jones, David K.; Read, Stephen J.

2005-01-01

We compare the structure and content of political experts' knowledge with that of novices. We were particularly interested in whether experts would show more causal and historical reasoning in explaining political events, as well as whether their knowledge was structured in the form of a narrative. Eight relative political experts (advanced…

NASA ground terminal communication equipment automated fault isolation expert systems

NASA Technical Reports Server (NTRS)

Tang, Y. K.; Wetzel, C. R.

1990-01-01

The prototype expert systems are described that diagnose the Distribution and Switching System I and II (DSS1 and DSS2), Statistical Multiplexers (SM), and Multiplexer and Demultiplexer systems (MDM) at the NASA Ground Terminal (NGT). A system level fault isolation expert system monitors the activities of a selected data stream, verifies that the fault exists in the NGT and identifies the faulty equipment. Equipment level fault isolation expert systems are invoked to isolate the fault to a Line Replaceable Unit (LRU) level. Input and sometimes output data stream activities for the equipment are available. The system level fault isolation expert system compares the equipment input and output status for a data stream and performs loopback tests (if necessary) to isolate the faulty equipment. The equipment level fault isolation system utilizes the process of elimination and/or the maintenance personnel's fault isolation experience stored in its knowledge base. The DSS1, DSS2 and SM fault isolation systems, using the knowledge of the current equipment configuration and the equipment circuitry issues a set of test connections according to the predefined rules. The faulty component or board can be identified by the expert system by analyzing the test results. The MDM fault isolation system correlates the failure symptoms with the faulty component based on maintenance personnel experience. The faulty component can be determined by knowing the failure symptoms. The DSS1, DSS2, SM, and MDM equipment simulators are implemented in PASCAL. The DSS1 fault isolation expert system was converted to C language from VP-Expert and integrated into the NGT automation software for offline switch diagnoses. Potentially, the NGT fault isolation algorithms can be used for the DSS1, SM, amd MDM located at Goddard Space Flight Center (GSFC).

Will the Oxygen-Phosphorus Paradigm Persist? - Expert Views of the Future of Management and Restoration of Eutrophic Lakes

NASA Astrophysics Data System (ADS)

Nygrén, Nina A.; Tapio, Petri; Horppila, Jukka

2017-11-01

In the age of climate change, the demand and lack of pure water challenges many communities. Substantial amount of effort is put in every year to manage and restore degraded lakes while the long-term effects of those efforts are only poorly known or monitored. Oxygenation, or aeration, is used extensively for the restoration of eutrophic lakes, although many studies question whether this process improves the status of the lakes in the long-term. The desired effect of oxygenation is based on paradigmatic theories that, in the light of recent literature, might not be adequate when long-term improvements are sought. This article canvasses expert views on the feasibility of the `oxygen-phosphorus paradigm' as well as the future of the management and restoration of eutrophic lakes, based on an international, two-rounded, expert panel survey (Delphi study), employing 200 freshwater experts from 33 nationalities, contacted at three conferences on the topic. The conclusion is that the oxygen-phosphorus paradigm seems to be rather persistent. The experts considered oxygenation to be a valid short-term lake restoration method, but not without harmful side-effects. In addition, experts' low level of trust in the adequacy of the scientific knowledge on the effects of restorations and in the use of the scientific knowledge as a basis of choice of restoration methods, could be signs of a paradigm shift towards an outlook emphasizing more effective catchment management over short-term restorations. The expert panel also anticipated that reducing external nutrient loads from both point and diffuse sources will succeed in the future.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts.

PubMed

Kawamoto, Kensaku; Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

2013-01-01

To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care.

Perceptual telerobotics

NASA Technical Reports Server (NTRS)

Ligomenides, Panos A.

1989-01-01

A sensory world modeling system, congruent with a human expert's perception, is proposed. The Experiential Knowledge Base (EKB) system can provide a highly intelligible communication interface for telemonitoring and telecontrol of a real time robotic system operating in space. Paradigmatic acquisition of empirical perceptual knowledge, and real time experiential pattern recognition and knowledge integration are reviewed. The cellular architecture and operation of the EKB system are also examined.

Uncertainty reasoning in expert systems

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik

1993-01-01

Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.

Controlling Real-Time Processes On The Space Station With Expert Systems

NASA Astrophysics Data System (ADS)

Leinweber, David; Perry, John

1987-02-01

Many aspects of space station operations involve continuous control of real-time processes. These processes include electrical power system monitoring, propulsion system health and maintenance, environmental and life support systems, space suit checkout, on-board manufacturing, and servicing of attached vehicles such as satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real-time processes has been done by trained human experts monitoring telemetry data. However, the long duration of space station missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge-based expert control procedures for these space stations. In addition to controlling the normal operations of these processes, the expert systems must also be able to quickly respond to anomalous events, determine their cause and initiate corrective actions in a safe and timely manner. This must be accomplished without excessive diversion of system resources from ongoing control activities and any events beyond the scope of the expert control and diagnosis functions must be recognized and brought to the attention of human operators. Real-time sensor based expert systems (as opposed to off-line, consulting or planning systems receiving data via the keyboard) pose particular problems associated with sensor failures, sensor degradation and data consistency, which must be explicitly handled in an efficient manner. A set of these systems must also be able to work together in a cooperative manner. This paper describes the requirements for real-time expert systems in space station control, and presents prototype implementations of space station expert control procedures in PICON (process intelligent control). PICON is a real-time expert system shell which operates in parallel with distributed data acquisition systems. It incorporates a specialized inference engine with a specialized scheduling portion specifically designed to match the allocation of system resources with the operational requirements of real-time control systems. Innovative knowledge engineering techniques used in PICON to facilitate the development of real-time sensor-based expert systems which use the special features of the inference engine are illustrated in the prototype examples.

Whose Expertise Is It? Evidence for Autistic Adults as Critical Autism Experts

PubMed Central

Gillespie-Lynch, Kristen; Kapp, Steven K.; Brooks, Patricia J.; Pickens, Jonathan; Schwartzman, Ben

2017-01-01

Autistic and non-autistic adults’ agreement with scientific knowledge about autism, how they define autism, and their endorsement of stigmatizing conceptions of autism has not previously been examined. Using an online survey, we assessed autism knowledge and stigma among 636 adults with varied relationships to autism, including autistic people and nuclear family members. Autistic participants exhibited more scientifically based knowledge than others. They were more likely to describe autism experientially or as a neutral difference, and more often opposed the medical model. Autistic participants and family members reported lower stigma. Greater endorsement of the importance of normalizing autistic people was associated with heightened stigma. Findings suggest that autistic adults should be considered autism experts and involved as partners in autism research. PMID:28400742

Engine Data Interpretation System (EDIS), phase 2

NASA Technical Reports Server (NTRS)

Cost, Thomas L.; Hofmann, Martin O.

1991-01-01

A prototype of an expert system was developed which applies qualitative constraint-based reasoning to the task of post-test analysis of data resulting from a rocket engine firing. Data anomalies are detected and corresponding faults are diagnosed. Engine behavior is reconstructed using measured data and knowledge about engine behavior. Knowledge about common faults guides but does not restrict the search for the best explanation in terms of hypothesized faults. The system contains domain knowledge about the behavior of common rocket engine components and was configured for use with the Space Shuttle Main Engine (SSME). A graphical user interface allows an expert user to intimately interact with the system during diagnosis. The system was applied to data taken during actual SSME tests where data anomalies were observed.

Safe and competent opioid prescribing education: Increasing dissemination with a train-the-trainer program.

PubMed

Zisblatt, Lara; Hayes, Sean M; Lazure, Patrice; Hardesty, Ilana; White, Julie L; Alford, Daniel P

2017-01-01

Due to the high prevalence of prescription opioid misuse, the US Food and Drug Administration (FDA) mandated a Risk Evaluation and Mitigation Strategy (REMS) requiring manufacturers of extended-release/long-acting (ER/LA) opioids to fund continuing education based on an FDA curricular Blueprint. This paper describes the Safe and Competent Opioid Prescribing Education (SCOPE of Pain) train-the-trainer program and its impact on (1) disseminating the SCOPE of Pain curriculum and (2) knowledge, confidence, attitudes, and performance of the participants of trainer-led compared with expert-led meetings. SCOPE of Pain is a 3-hour ER/LA opioid REMS education. In addition to expert-led live statewide meetings, a 2-hour train-the-trainer (TTT) workshop was developed to increase dissemination nationally. The trainers were expected to conduct SCOPE of Pain meetings at their institutions. Participants of both the trainer-led and expert-led SCOPE of Pain programs were surveyed immediately post and 2 months post meetings to assess improvements in knowledge, confidence, attitudes, and self-reported safe opioid prescribing practices. During 9 months (May 2013 to February 2014), 89 trainers were trained during 9 TTT workshops in 9 states. Over 24 months (May 2013 to April 2015), 33% of the trainers conducted at least 1 SCOPE of Pain training, with a total of 79 meetings that educated 1419 participants. The average number of meetings of those who conducted at least 1 meeting was 2.8 (range: 1-19). The participants of the trainer-led programs were significantly more likely to be practicing in rural settings than those who participated in the expert-led meetings (39% vs. 26%, P < .001). At 2 months post training, there were no significant differences in improvements in participant knowledge, confidence, attitudes, and performance between expert-led and trainer-led meetings. The SCOPE of Pain TTT program holds promise as an effective dissemination strategy to increase guideline-based safe opioid prescribing knowledge, confidence, attitudes, and self-reported practices.

Influence of tutors' subject-matter expertise on student effort and achievement in problem-based learning.

PubMed

Schmidt, H G; van der Arend, A; Moust, J H; Kokx, I; Boon, L

1993-10-01

To investigate the effects of tutors' subject-matter expertise on students' levels of academic achievement and study effort in a problem-based health sciences curriculum. Also, to study differences in tutors' behaviors and the influences of these differences on students' performances. Data were analyzed from 336 staff-led tutorial groups involving student participants in seven four-year undergraduate programs at the University of Limburg Faculty of Health Sciences in 1989-90. Overall, 1,925 data records were studied, with each student participating in an average of 1.7 groups led by either content experts or non-experts. The basic analyses were of (1) students' achievement scores as a function of tutors' expertise levels and students' curriculum year; (2) students' estimates of self-study time as a function of tutors' expertise levels and students' curriculum year; and (3) the average ratings of the tutors' behaviors as a function of tutors' expertise levels. Statistical methods included analysis of variance and Pearson correlations. The students guided by subject-matter experts were shown to spend more time on self-directed study, and they achieved somewhat better than did the students guided by non-expert tutors. The effect of subject-matter expertise on achievement was strongest in the first curriculum year, suggesting that novice students are more dependent on their tutors' expertise than are more advanced students. Also, the content-expert tutors made more extensive use of their subject-matter knowledge to guide students. However, in addition to the tutors' knowledge-related behaviors, the tutors' process-facilitation skills affected student achievement. Moreover, these two sets of behaviors were correlated, indicating that both are necessary conditions for effective tutoring. The results indicate that, at least for the curriculum studied, the assumption in the literature that tutors do not necessarily need content knowledge so long as they are skilled in the tutoring process is not entirely justified: the students who were guided by content experts achieved somewhat better and spent more time on self-directed learning. More important, tutoring skill and content knowledge seemed to be necessary and closely related conditions for effective tutoring.

Automatic acquisition of domain and procedural knowledge

NASA Technical Reports Server (NTRS)

Ferber, H. J.; Ali, M.

1988-01-01

The design concept and performance of AKAS, an automated knowledge-acquisition system for the development of expert systems, are discussed. AKAS was developed using the FLES knowledge base for the electrical system of the B-737 aircraft and employs a 'learn by being told' strategy. The system comprises four basic modules, a system administration module, a natural-language concept-comprehension module, a knowledge-classification/extraction module, and a knowledge-incorporation module; details of the module architectures are explored.

Testing a Web-Based, Trained-Peer Model to Build Capacity for Evidence-Based Practices in Community Mental Health Systems.

PubMed

German, Ramaris E; Adler, Abby; Frankel, Sarah A; Stirman, Shannon Wiltsey; Pinedo, Paola; Evans, Arthur C; Beck, Aaron T; Creed, Torrey A

2018-03-01

Use of expert-led workshops plus consultation has been established as an effective strategy for training community mental health (CMH) clinicians in evidence-based practices (EBPs). Because of high rates of staff turnover, this strategy inadequately addresses the need to maintain capacity to deliver EBPs. This study examined knowledge, competency, and retention outcomes of a two-phase model developed to build capacity for an EBP in CMH programs. In the first phase, an initial training cohort in each CMH program participated in in-person workshops followed by expert-led consultation (in-person, expert-led [IPEL] phase) (N=214 clinicians). After this cohort completed training, new staff members participated in Web-based training (in place of in-person workshops), followed by peer-led consultation with the initial cohort (Web-based, trained-peer [WBTP] phase) (N=148). Tests of noninferiority assessed whether WBTP was not inferior to IPEL at increasing clinician cognitive-behavioral therapy (CBT) competency, as measured by the Cognitive Therapy Rating Scale. WBTP was not inferior to IPEL at developing clinician competency. Hierarchical linear models showed no significant differences in CBT knowledge acquisition between the two phases. Survival analyses indicated that WBTP trainees were less likely than IPEL trainees to complete training. In terms of time required from experts, WBTP required 8% of the resources of IPEL. After an initial investment to build in-house CBT expertise, CMH programs were able to use a WBTP model to broaden their own capacity for high-fidelity CBT. IPEL followed by WBTP offers an effective alternative to build EBP capacity in CMH programs, rather than reliance on external experts.

A middle man approach to knowledge acquisition in expert systems

NASA Technical Reports Server (NTRS)

Jordan, Janice A.; Lin, Min-Jin; Mayer, Richard J.; Sterle, Mark E.

1990-01-01

The Weed Control Advisor (WCA) is a robust expert system that has been successfully implemented on an IBM AT class microcomputer in CLIPS. The goal of the WCA was to demonstrate the feasibility of providing an economical, efficient, user friendly system through which Texas rice producers could obtain expert level knowledge regarding herbicide application for weed control. During the development phase of the WCA, an improved knowledge acquisition method which we call the Middle Man Approach (MMA) was applied to facilitate the communication process between the domain experts and the knowledge engineer. The MMA served to circumvent the problems associated with the more traditional forms of knowledge acquisition by placing the Middle Man, a semi-expert in the problem domain with some computer expertise, at the site of system development. The middle man was able to contribute to system development in two major ways. First, the Middle Man had experience working in rice production and could assume many of the responsibilities normally performed by the domain experts such as explaining the background of the problem domain and determining the important relations. Second, the Middle Man was familiar with computers and worked closely with the system developers to update the rules after the domain experts reviewed the prototype, contribute to the help menus and explanation portions of the expert system, conduct the testing that is required to insure that the expert system gives the expected results answer questions in a timely way, help the knowledge engineer structure the domain knowledge into a useable form, and provide insight into the end user's profile which helped in the development of the simple user friendly interface. The final results were not only that both time expended and costs were greatly reduced by using the MMA, but the quality of the system was improved. This papa will introduce the WCA system and then discuss traditional knowledge acquisition along with some of the problems often associated with it, the MMA methodology, and its application to the WCA development.

Computer-Based Training: Will it Replace You?

ERIC Educational Resources Information Center

Hudson, William J.

1982-01-01

Examines myths and fears about computer-based training (displaces trainers, dehumanizes learners), lists what computers cannot do (analyze needs, formulate objectives, act as subject experts), and what they can do effectively (handle knowledge transfer, provide simulation). (SK)

CLIPS: A tool for corn disease diagnostic system and an aid to neural network for automated knowledge acquisition

NASA Technical Reports Server (NTRS)

Wu, Cathy; Taylor, Pam; Whitson, George; Smith, Cathy

1990-01-01

This paper describes the building of a corn disease diagnostic expert system using CLIPS, and the development of a neural expert system using the fact representation method of CLIPS for automated knowledge acquisition. The CLIPS corn expert system diagnoses 21 diseases from 52 symptoms and signs with certainty factors. CLIPS has several unique features. It allows the facts in rules to be broken down to object-attribute-value (OAV) triples, allows rule-grouping, and fires rules based on pattern-matching. These features combined with the chained inference engine result to a natural user query system and speedy execution. In order to develop a method for automated knowledge acquisition, an Artificial Neural Expert System (ANES) is developed by a direct mapping from the CLIPS system. The ANES corn expert system uses the same OAV triples in the CLIPS system for its facts. The LHS and RHS facts of the CLIPS rules are mapped into the input and output layers of the ANES, respectively; and the inference engine of the rules is imbedded in the hidden layer. The fact representation by OAC triples gives a natural grouping of the rules. These features allow the ANES system to automate rule-generation, and make it efficient to execute and easy to expand for a large and complex domain.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

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.

Does Joint Fact-finding work for Water-energy-food Nexus Issues? A Role of Scientific Evidence in Policy Process

NASA Astrophysics Data System (ADS)

Baba, K.

2014-12-01

A quite famous phrase in risk management "How safe is enough safe?" implies there exists a framing gap among experts, the general public and stakeholders. Scientific evidence that experts provide usually contains uncertainty, while the public tends to have the other type of qualitative local knowledge. As there is no zero-risk society, we have to build consensus on acceptable level of risk and trade-offs of risks based on expert knowledge and local knowledge. Therefore having a dialogue among them in the early stage of the policy process such as problem definition and agenda setting is essential to cultivate trust and to integrate their knowledge. To this end, we especially pay attention to Joint Fact-finding (JFF). The tentative definition of JFF is that a promising strategy for experts, decision makers, and key public rights-holders and stakeholders from opposing sides of an issue to work together to resolve or narrow factual disputes over public policy issues. JFF process usually begins with identifying stakeholders and holding interviews with them to determine their interests. We call this step stakeholder analysis. Then we define the scope of the study including the required scientific evidence and the preliminary list of experts. After that, stakeholders jointly select experts to participate in the study, then they work together on what they would like to clear about scientific evidence. They finally get the common understanding and findings through these collaboration. We applied the stakeholder analysis to the issue of groundwater in Obama City and the issues of hot spring water and geothermal power in Beppu City in Japan. We drew conclusions from these case studies to some extent but at the same time we found that the analysis method has a limitation in applying it to multiple nexus issues because the method based on stakeholders' cognition. For example, in Obama case, we identified a lack of cooperation among stakeholders that especially agricultural sector who should have positive relationship with groundwater in nature is not involved in groundwater issue thoroughly. However, we could not enough furnish stakeholders with the framing of trade-offs between resources. Accordingly we need to raise awareness of stakeholders with scientific evidence of experts on the way of the stakeholder analysis.

Symbolic Knowledge Processing for the Acquisition of Expert Behavior: A Study in Medicine.

DTIC Science & Technology

1984-05-01

information . It provides a model for this type of study, suggesting a different approach to the problem of learning and efficiency of knowledge -based...flow of information 2.2. Scope and description of the subsystems Three subsystems perform distinct operations using the preceding knowledge sources...which actually yields a new knowledge rCpresentation Ahere new external information is encoded in the combination and ordering of elements of the

An Embedded Rule-Based Diagnostic Expert System in Ada

NASA Technical Reports Server (NTRS)

Jones, Robert E.; Liberman, Eugene M.

1992-01-01

Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

Knowledge acquisition for temporal abstraction.

PubMed

Stein, A; Musen, M A; Shahar, Y

1996-01-01

Temporal abstraction is the task of detecting relevant patterns in data over time. The knowledge-based temporal-abstraction method uses knowledge about a clinical domain's contexts, external events, and parameters to create meaningful interval-based abstractions from raw time-stamped clinical data. In this paper, we describe the acquisition and maintenance of domain-specific temporal-abstraction knowledge. Using the PROTEGE-II framework, we have designed a graphical tool for acquiring temporal knowledge directly from expert physicians, maintaining the knowledge in a sharable form, and converting the knowledge into a suitable format for use by an appropriate problem-solving method. In initial tests, the tool offered significant gains in our ability to rapidly acquire temporal knowledge and to use that knowledge to perform automated temporal reasoning.

Optics Toolbox: An Intelligent Relational Database System For Optical Designers

NASA Astrophysics Data System (ADS)

Weller, Scott W.; Hopkins, Robert E.

1986-12-01

Optical designers were among the first to use the computer as an engineering tool. Powerful programs have been written to do ray-trace analysis, third-order layout, and optimization. However, newer computing techniques such as database management and expert systems have not been adopted by the optical design community. For the purpose of this discussion we will define a relational database system as a database which allows the user to specify his requirements using logical relations. For example, to search for all lenses in a lens database with a F/number less than two, and a half field of view near 28 degrees, you might enter the following: FNO < 2.0 and FOV of 28 degrees ± 5% Again for the purpose of this discussion, we will define an expert system as a program which contains expert knowledge, can ask intelligent questions, and can form conclusions based on the answers given and the knowledge which it contains. Most expert systems store this knowledge in the form of rules-of-thumb, which are written in an English-like language, and which are easily modified by the user. An example rule is: IF require microscope objective in air and require NA > 0.9 THEN suggest the use of an oil immersion objective The heart of the expert system is the rule interpreter, sometimes called an inference engine, which reads the rules and forms conclusions based on them. The use of a relational database system containing lens prototypes seems to be a viable prospect. However, it is not clear that expert systems have a place in optical design. In domains such as medical diagnosis and petrology, expert systems are flourishing. These domains are quite different from optical design, however, because optical design is a creative process, and the rules are difficult to write down. We do think that an expert system is feasible in the area of first order layout, which is sufficiently diagnostic in nature to permit useful rules to be written. This first-order expert would emulate an expert designer as he interacted with a customer for the first time: asking the right questions, forming conclusions, and making suggestions. With these objectives in mind, we have developed the Optics Toolbox. Optics Toolbox is actually two programs in one: it is a powerful relational database system with twenty-one search parameters, four search modes, and multi-database support, as well as a first-order optical design expert system with a rule interpreter which has full access to the relational database. The system schematic is shown in Figure 1.

Towards a Fuzzy Expert System on Toxicological Data Quality Assessment.

PubMed

Yang, Longzhi; Neagu, Daniel; Cronin, Mark T D; Hewitt, Mark; Enoch, Steven J; Madden, Judith C; Przybylak, Katarzyna

2013-01-01

Quality assessment (QA) requires high levels of domain-specific experience and knowledge. QA tasks for toxicological data are usually performed by human experts manually, although a number of quality evaluation schemes have been proposed in the literature. For instance, the most widely utilised Klimisch scheme1 defines four data quality categories in order to tag data instances with respect to their qualities; ToxRTool2 is an extension of the Klimisch approach aiming to increase the transparency and harmonisation of the approach. Note that the processes of QA in many other areas have been automatised by employing expert systems. Briefly, an expert system is a computer program that uses a knowledge base built upon human expertise, and an inference engine that mimics the reasoning processes of human experts to infer new statements from incoming data. In particular, expert systems have been extended to deal with the uncertainty of information by representing uncertain information (such as linguistic terms) as fuzzy sets under the framework of fuzzy set theory and performing inferences upon fuzzy sets according to fuzzy arithmetic. This paper presents an experimental fuzzy expert system for toxicological data QA which is developed on the basis of the Klimisch approach and the ToxRTool in an effort to illustrate the power of expert systems to toxicologists, and to examine if fuzzy expert systems are a viable solution for QA of toxicological data. Such direction still faces great difficulties due to the well-known common challenge of toxicological data QA that "five toxicologists may have six opinions". In the meantime, this challenge may offer an opportunity for expert systems because the construction and refinement of the knowledge base could be a converging process of different opinions which is of significant importance for regulatory policy making under the regulation of REACH, though a consensus may never be reached. Also, in order to facilitate the implementation of Weight of Evidence approaches and in silico modelling proposed by REACH, there is a higher appeal of numerical quality values than nominal (categorical) ones, where the proposed fuzzy expert system could help. Most importantly, the deriving processes of quality values generated in this way are fully transparent, and thus comprehensible, for final users, which is another vital point for policy making specified in REACH. Case studies have been conducted and this report not only shows the promise of the approach, but also demonstrates the difficulties of the approach and thus indicates areas for future development. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Marking out the clinical expert/clinical leader/clinical scholar: perspectives from nurses in the clinical arena.

PubMed

Mannix, Judy; Wilkes, Lesley; Jackson, Debra

2013-01-01

Clinical scholarship has been conceptualised and theorised in the nursing literature for over 30 years but no research has captured nurses' clinicians' views on how it differs or is the same as clinical expertise and clinical leadership. The aim of this study was to determine clinical nurses' understanding of the differences and similarities between the clinical expert, clinical leader and clinical scholar. A descriptive interpretative qualitative approach using semi-structured interviews with 18 practising nurses from Australia, Canada and England. The audio-taped interviews were transcribed and the text coded for emerging themes. The themes were sorted into categories of clinical expert, clinical leader and clinical scholarship as described by the participants. These themes were then compared and contrasted and the essential elements that characterise the nursing roles of the clinical expert, clinical leader and clinical scholar were identified. Clinical experts were seen as linking knowledge to practice with some displaying clinical leadership and scholarship. Clinical leadership is seen as a positional construct with a management emphasis. For the clinical scholar they linked theory and practice and encouraged research and dissemination of knowledge. There are distinct markers for the roles of clinical expert, clinical leader and clinical scholar. Nurses working in one or more of these roles need to work together to improve patient care. An 'ideal nurse' may be a blending of all three constructs. As nursing is a practice discipline its scholarship should be predominantly based on clinical scholarship. Nurses need to be encouraged to go beyond their roles as clinical leaders and experts to use their position to challenge and change through the propagation of knowledge to their community.

Marking out the clinical expert/clinical leader/clinical scholar: perspectives from nurses in the clinical arena

PubMed Central

2013-01-01

Background Clinical scholarship has been conceptualised and theorised in the nursing literature for over 30 years but no research has captured nurses’ clinicians’ views on how it differs or is the same as clinical expertise and clinical leadership. The aim of this study was to determine clinical nurses’ understanding of the differences and similarities between the clinical expert, clinical leader and clinical scholar. Methods A descriptive interpretative qualitative approach using semi-structured interviews with 18 practising nurses from Australia, Canada and England. The audio-taped interviews were transcribed and the text coded for emerging themes. The themes were sorted into categories of clinical expert, clinical leader and clinical scholarship as described by the participants. These themes were then compared and contrasted and the essential elements that characterise the nursing roles of the clinical expert, clinical leader and clinical scholar were identified. Results Clinical experts were seen as linking knowledge to practice with some displaying clinical leadership and scholarship. Clinical leadership is seen as a positional construct with a management emphasis. For the clinical scholar they linked theory and practice and encouraged research and dissemination of knowledge. Conclusion There are distinct markers for the roles of clinical expert, clinical leader and clinical scholar. Nurses working in one or more of these roles need to work together to improve patient care. An ‘ideal nurse’ may be a blending of all three constructs. As nursing is a practice discipline its scholarship should be predominantly based on clinical scholarship. Nurses need to be encouraged to go beyond their roles as clinical leaders and experts to use their position to challenge and change through the propagation of knowledge to their community. PMID:23587282

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Knowing for Nursing Practice: Patterns of Knowledge and Their Emulation in Expert Systems

PubMed Central

Abraham, Ivo L.; Fitzpatrick, Joyce J.

1987-01-01

This paper addresses the issue of clinical knowledge in nursing, and the feasibility of emulating this knowledge into expert system technology. The perspective on patterns of knowing for nursing practice, advanced by Carper (1978), serves as point of departure. The four patterns of knowing -- empirics, esthetics, ethics, personal knowledge -- are evaluated as to the extent to which they can be emulated in clinical expert systems, given constraints imposed by the current technology of these systems.

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.

Expert elicitation of population-level effects of disturbance

USGS Publications Warehouse

Fleishman, Erica; Burgman, Mark; Runge, Michael C.; Schick, Robert S; Krauss, Scott; Popper, Arthur N.; Hawkins, Anthony

2016-01-01

Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales (Eubalaena glacialis). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.

An Expert System for Environmental Data Management.

ERIC Educational Resources Information Center

Berka, Petr; Jirku, Petr

1995-01-01

Examines the possibility of using expert system tools for environmental data management. Describes the domain-independent expert system shell SAK and Knowledge EXplorer, a system that learns rules from data. Demonstrates the functionality of Knowledge EXplorer on an example of water quality evaluation. (LZ)

Hidden Expert Knowledge: The Knowledge That Counts for the Small School-District Superintendent

ERIC Educational Resources Information Center

Hyle, Adrienne E.; Ivory, Gary; McClellan, Rhonda L.

2010-01-01

Using Bereiter and Scardamalia's (1993) hidden expert knowledge, we explored what knowledge counts from the perspectives of working small school-district superintendents and the ways in which they gain that knowledge. This qualitative study used focus groups as its primary data collection method. Participants were 37 superintendents of districts…

GPs' thoughts on prescribing medication and evidence-based knowledge: the benefit aspect is a strong motivator. A descriptive focus group study.

PubMed

Skoglund, Ingmarie; Segesten, Kerstin; Björkelund, Cecilia

2007-06-01

To describe GPs' thoughts of prescribing medication and evidence-based knowledge (EBM) concerning drug therapy. Tape-recorded focus-group interviews transcribed verbatim and analysed using qualitative methods. GPs from the south-eastern part of Västra Götaland, Sweden. A total of 16 GPs out of 178 from the south-eastern part of the region strategically chosen to represent urban and rural, male and female, long and short GP experience. Transcripts were analysed using a descriptive qualitative method. The categories were: benefits, time and space, and expert knowledge. The benefit was a merge of positive elements, all aspects of the GPs' tasks. Time and space were limitations for GPs' tasks. EBM as a constituent of expert knowledge should be more customer adjusted to be able to be used in practice. Benefit was the most important category, existing in every decision-making situation for the GP. The core category was prompt and pragmatic benefit, which was the utmost benefit. GPs' thoughts on evidence-based medicine and prescribing medication were highly related to reflecting on benefit and results. The interviews indicated that prompt and pragmatic benefit is important for comprehending their thoughts.

GPs’ thoughts on prescribing medication and evidence-based knowledge: The benefit aspect is a strong motivator

PubMed Central

Skoglund, Ingmarie; Segesten, Kerstin; Björkelund, Cecilia

2007-01-01

Objective To describe GPs’ thoughts of prescribing medication and evidence-based knowledge (EBM) concerning drug therapy. Design Tape-recorded focus-group interviews transcribed verbatim and analysed using qualitative methods. Setting GPs from the south-eastern part of Västra Götaland, Sweden. Subjects A total of 16 GPs out of 178 from the south-eastern part of the region strategically chosen to represent urban and rural, male and female, long and short GP experience. Methods Transcripts were analysed using a descriptive qualitative method. Results The categories were: benefits, time and space, and expert knowledge. The benefit was a merge of positive elements, all aspects of the GPs’ tasks. Time and space were limitations for GPs’ tasks. EBM as a constituent of expert knowledge should be more customer adjusted to be able to be used in practice. Benefit was the most important category, existing in every decision-making situation for the GP. The core category was prompt and pragmatic benefit, which was the utmost benefit. Conclusion GPs’ thoughts on evidence-based medicine and prescribing medication were highly related to reflecting on benefit and results. The interviews indicated that prompt and pragmatic benefit is important for comprehending their thoughts. PMID:17497487

Leveraging Event Reporting Through Knowledge Support: A Knowledge-Based Approach to Promoting Patient Fall Prevention.

PubMed

Yao, Bin; Kang, Hong; Miao, Qi; Zhou, Sicheng; Liang, Chen; Gong, Yang

2017-01-01

Patient falls are a common safety event type that impairs the healthcare quality. Strategies including solution tools and reporting systems for preventing patient falls have been developed and implemented in the U.S. However, the current strategies do not include timely knowledge support, which is in great need in bridging the gap between reporting and learning. In this study, we constructed a knowledge base of fall events by combining expert-reviewed fall prevention solutions and then integrating them into a reporting system. The knowledge base enables timely and tailored knowledge support and thus will serve as a prevailing fall prevention tool. This effort holds promise in making knowledge acquisition and management a routine process for enhancing the reporting and understanding of patient safety events.

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems automony demonstration project, volume 1. Overview

NASA Technical Reports Server (NTRS)

Glass, B. J. (Editor)

1992-01-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS test bed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

Thermal Expert System (TEXSYS): Systems autonomy demonstration project, volume 2. Results

NASA Astrophysics Data System (ADS)

Glass, B. J.

1992-10-01

The Systems Autonomy Demonstration Project (SADP) produced a knowledge-based real-time control system for control and fault detection, isolation, and recovery (FDIR) of a prototype two-phase Space Station Freedom external active thermal control system (EATCS). The Thermal Expert System (TEXSYS) was demonstrated in recent tests to be capable of reliable fault anticipation and detection, as well as ordinary control of the thermal bus. Performance requirements were addressed by adopting a hierarchical symbolic control approach-layering model-based expert system software on a conventional, numerical data acquisition and control system. The model-based reasoning capabilities of TEXSYS were shown to be advantageous over typical rule-based expert systems, particularly for detection of unforeseen faults and sensor failures. Volume 1 gives a project overview and testing highlights. Volume 2 provides detail on the EATCS testbed, test operations, and online test results. Appendix A is a test archive, while Appendix B is a compendium of design and user manuals for the TEXSYS software.

A knowledge acquisition process to analyse operational problems in solid waste management facilities.

PubMed

Dokas, Ioannis M; Panagiotakopoulos, Demetrios C

2006-08-01

The available expertise on managing and operating solid waste management (SWM) facilities varies among countries and among types of facilities. Few experts are willing to record their experience, while few researchers systematically investigate the chains of events that could trigger operational failures in a facility; expertise acquisition and dissemination, in SWM, is neither popular nor easy, despite the great need for it. This paper presents a knowledge acquisition process aimed at capturing, codifying and expanding reliable expertise and propagating it to non-experts. The knowledge engineer (KE), the person performing the acquisition, must identify the events (or causes) that could trigger a failure, determine whether a specific event could trigger more than one failure, and establish how various events are related among themselves and how they are linked to specific operational problems. The proposed process, which utilizes logic diagrams (fault trees) widely used in system safety and reliability analyses, was used for the analysis of 24 common landfill operational problems. The acquired knowledge led to the development of a web-based expert system (Landfill Operation Management Advisor, http://loma.civil.duth.gr), which estimates the occurrence possibility of operational problems, provides advice and suggests solutions.

Automated Induction Of Rule-Based Neural Networks

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J.; Goodman, Rodney M.

1994-01-01

Prototype expert systems implemented in software and are functionally equivalent to neural networks set up automatically and placed into operation within minutes following information-theoretic approach to automated acquisition of knowledge from large example data bases. Approach based largely on use of ITRULE computer program.

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

NASA Technical Reports Server (NTRS)

Maslanik, J. A.; Key, J.

1992-01-01

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Knowledge-Based, Interactive, Custom Anatomical Scene Creation for Medical Education: The Biolucida System

PubMed Central

Warren, Wayne; Brinkley, James F.

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity. PMID:16779148

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.

Knowledge-based, interactive, custom anatomical scene creation for medical education: the Biolucida system.

PubMed

Warren, Wayne; Brinkley, James F

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity.

Learning Processes in the Professional Development of Mental Health Counselors: Knowledge Restructuring and Illness Script Formation

ERIC Educational Resources Information Center

Strasser, Josef; Gruber, Hans

2015-01-01

An important part of learning processes in the professional development of counselors is the integration of declarative knowledge and professional experience. It was investigated in-how-far mental health counselors at different levels of expertise (experts, intermediates, novices) differ in their availability of experience-based knowledge…

Developing an Assessment Instrument to Measure Early Elementary Teachers' Mathematical Knowledge for Teaching

ERIC Educational Resources Information Center

Schoen, Robert C.; Bray, Wendy; Wolfe, Christopher; Tazaz, Amanda M.; Nielsen, Lynne

2017-01-01

This study reports on the development and field study of K-TEEM, a web-based assessment instrument designed to measure mathematical knowledge for teaching (MKT) at the early elementary level. The development process involved alignment with early elementary curriculum standards, expert review of items and scoring criteria, cognitive interviews with…

Case-Exercises, Diagnosis, and Explanations in a Knowledge Based Tutoring System for Project Planning.

ERIC Educational Resources Information Center

Pulz, Michael; Lusti, Markus

PROJECTTUTOR is an intelligent tutoring system that enhances conventional classroom instruction by teaching problem solving in project planning. The domain knowledge covered by the expert module is divided into three functions. Structural analysis, identifies the activities that make up the project, time analysis, computes the earliest and latest…

Reusable rocket engine turbopump health monitoring system, part 3

NASA Technical Reports Server (NTRS)

Perry, John G.

1989-01-01

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Automatic Overset Grid Generation with Heuristic Feedback Control

NASA Technical Reports Server (NTRS)

Robinson, Peter I.

2001-01-01

An advancing front grid generation system for structured Overset grids is presented which automatically modifies Overset structured surface grids and control lines until user-specified grid qualities are achieved. The system is demonstrated on two examples: the first refines a space shuttle fuselage control line until global truncation error is achieved; the second advances, from control lines, the space shuttle orbiter fuselage top and fuselage side surface grids until proper overlap is achieved. Surface grids are generated in minutes for complex geometries. The system is implemented as a heuristic feedback control (HFC) expert system which iteratively modifies the input specifications for Overset control line and surface grids. It is developed as an extension of modern control theory, production rules systems and subsumption architectures. The methodology provides benefits over the full knowledge lifecycle of an expert system for knowledge acquisition, knowledge representation, and knowledge execution. The vector/matrix framework of modern control theory systematically acquires and represents expert system knowledge. Missing matrix elements imply missing expert knowledge. The execution of the expert system knowledge is performed through symbolic execution of the matrix algebra equations of modern control theory. The dot product operation of matrix algebra is generalized for heuristic symbolic terms. Constant time execution is guaranteed.

Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning

NASA Astrophysics Data System (ADS)

Khosyi'ah, S.; Irfan, M.; Maylawati, D. S.; Mukhlas, O. S.

2018-01-01

Along with the development of human civilization in Indonesia, the changes and reform of Islamic inheritance law so as to conform to the conditions and culture cannot be denied. The distribution of inheritance in Indonesia can be done automatically by storing the rule of Islamic inheritance law in the expert system. In this study, we analyze the knowledge of experts in Islamic inheritance in Indonesia and represent it in the form of rules using rule-based Forward Chaining (FC) and Davis-Putman-Logemann-Loveland (DPLL) algorithms. By hybridizing FC and DPLL algorithms, the rules of Islamic inheritance law in Indonesia are clearly defined and measured. The rules were conceptually validated by some experts in Islamic laws and informatics. The results revealed that generally all rules were ready for use in an expert system.

Approximate reasoning using terminological models

NASA Technical Reports Server (NTRS)

Yen, John; Vaidya, Nitin

1992-01-01

Term Subsumption Systems (TSS) form a knowledge-representation scheme in AI that can express the defining characteristics of concepts through a formal language that has a well-defined semantics and incorporates a reasoning mechanism that can deduce whether one concept subsumes another. However, TSS's have very limited ability to deal with the issue of uncertainty in knowledge bases. The objective of this research is to address issues in combining approximate reasoning with term subsumption systems. To do this, we have extended an existing AI architecture (CLASP) that is built on the top of a term subsumption system (LOOM). First, the assertional component of LOOM has been extended for asserting and representing uncertain propositions. Second, we have extended the pattern matcher of CLASP for plausible rule-based inferences. Third, an approximate reasoning model has been added to facilitate various kinds of approximate reasoning. And finally, the issue of inconsistency in truth values due to inheritance is addressed using justification of those values. This architecture enhances the reasoning capabilities of expert systems by providing support for reasoning under uncertainty using knowledge captured in TSS. Also, as definitional knowledge is explicit and separate from heuristic knowledge for plausible inferences, the maintainability of expert systems could be improved.

N Reasons Why Production-Rules are Insufficient Models for Expert System Knowledge Representation Schemes

DTIC Science & Technology

1991-02-01

3 2.2 Hybrid Rule/Fact Schemas .............................................................. 3 3 THE LIMITATIONS OF RULE BASED KNOWLEDGE...or hybrid rule/fact schemas. 2 UNCLASSIFIED .WA UNCLASSIFIED ERL-0520-RR 2.1 Propositional Logic The simplest form of production-rules are based upon...requirements which may lead to poor system performance. 2.2 Hybrid Rule/Fact Schemas Hybrid rule/fact relationships (also known as Predicate Calculus ) have

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.

Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

NASA Astrophysics Data System (ADS)

Osipov, Gennady

2013-04-01

We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode includes noncontact registration of eye motion, reconstruction of "attention landscape" fixed by the expert, recording the comments of the expert who is a specialist in the field of images` interpretation, and transfer this information into knowledge base.Creation of base of ophthalmologic images (OI) includes making semantic contacts from great number of OI based on analysis of OI and expert's comments.Processing of OI and making generalized OI (GOI) is realized by inductive logic algorithms and consists in synthesis of structural invariants of OI. The mode of recognition and interpretation of unknown images consists of several stages, which include: comparison of unknown image with the base of structural invariants of OI; revealing of structural invariants in unknown images; ynthesis of interpretive message of the structural invariants base and OI base (the experts` comments stored in it). We want to emphasize that the training mode does not assume special involvement of experts to teach the system - it is realized in the process of regular experts` work on image interpretation and it becomes possible after installation of a special apparatus for non contact registration of experts` attention. Consequently, the technology, which principles is described there, provides fundamentally new effective solution to the problem of exploration of mineral resource deposits based on computer analysis of aerial and satellite image data.

Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts

PubMed Central

Hongsermeier, Tonya; Wright, Adam; Lewis, Janet; Bell, Douglas S; Middleton, Blackford

2013-01-01

Objective To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework. Materials and methods As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework. Results Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model. Discussion Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC's Advancing CDS initiative. Conclusion The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care. PMID:22865671

Relation of Knowledge and Performance in Boys' Tennis: Age and Expertise.

ERIC Educational Resources Information Center

McPherson, Sue L.; Thomas, Jerry R.

1989-01-01

Examined 10- to 13-year-old boys' development of knowledge structure and sport performance in tennis by comparing skills and knowledge of experts and novices. Experts focused on higher concepts and exhibited greater decision-making ability because of their more highly developed knowledge structure. (SAK)

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

The BBN Knowledge Acquisition Project

DTIC Science & Technology

1988-09-01

Optation 17 S . Large-Scale Revisions of Knowledge Bases 19 5.1 The Macro and Structure Editor 19 5.2 Developing Macro Editing Procedre 20 5.2.1 Macro...consistency checking foreach style of representaton easier and mote efficient, so that knowledge engineers and subject matter expert s can work together to... s ~Ta OIM-iJC ~Va Coetnin: MILECSXCT 8.1.3.1 Local Comumand Menus Anytime ICREM ais~laying a view of a particular kind of knowledge , the State Winsdow

An approach to combining heuristic and qualitative reasoning in an expert system

NASA Technical Reports Server (NTRS)

Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

1988-01-01

An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Translation and validation of the Malay version of the Stroke Knowledge Test.

PubMed

Sowtali, Siti Noorkhairina; Yusoff, Dariah Mohd; Harith, Sakinah; Mohamed, Monniaty

2016-04-01

To date, there is a lack of published studies on assessment tools to evaluate the effectiveness of stroke education programs. This study developed and validated the Malay language version of the Stroke Knowledge Test research instrument. This study involved translation, validity, and reliability phases. The instrument underwent backward and forward translation of the English version into the Malay language. Nine experts reviewed the content for consistency, clarity, difficulty, and suitability for inclusion. Perceived usefulness and utilization were obtained from experts' opinions. Later, face validity assessment was conducted with 10 stroke patients to determine appropriateness of sentences and grammar used. A pilot study was conducted with 41 stroke patients to determine the item analysis and reliability of the translated instrument using the Kuder Richardson 20 or Cronbach's alpha. The final Malay version Stroke Knowledge Test included 20 items with good content coverage, acceptable item properties, and positive expert review ratings. Psychometric investigations suggest that Malay version Stroke Knowledge Test had moderate reliability with Kuder Richardson 20 or Cronbach's alpha of 0.58. Improvement is required for Stroke Knowledge Test items with unacceptable difficulty indices. Overall, the average rating of perceived usefulness and perceived utility of the instruments were both 72.7%, suggesting that reviewers were likely to use the instruments in their facilities. Malay version Stroke Knowledge Test was a valid and reliable tool to assess educational needs and to evaluate stroke knowledge among participants of group-based stroke education programs in Malaysia.

Nature-based care opportunities and barriers in oncology contexts: a modified international e-Delphi survey.

PubMed

Blaschke, Sarah; O'Callaghan, Clare C; Schofield, Penelope

2017-10-16

To develop recommendations regarding opportunities and barriers for nature-based care in oncology contexts using a structured knowledge generation process involving relevant healthcare and design experts. Four-round modified electronic Delphi study. Oncology patients' nature-based recommendations, uncovered in preceding qualitative investigation, were included in the first round for the expert participants' consideration. Key items (opportunities and barriers) were developed using data aggregation and synthesis, followed by item prioritisation and 10-point Likert scale ranking (1=not important, 10=very important). Descriptive statistics were calculated to assess items of highest importance representing expert recommendations. Online Delphi process constituting an electronic international survey. A purposive sample of 200 potential panellists (recruitment target n=40) comprising healthcare practitioners, managers, designers, architects and researchers were invited to participate; experts were identified via research networks, snowballing and systematic literature review. 38 experts across seven countries (Australia, USA, UK, New Zealand, Canada, Denmark and Sweden) returned questionnaire 1, which determined consent and acceptance for participation. Initial response rate was 19%, and subsequent response rates were 84%, 82% and 84% for rounds 2, 3 and 4, respectively. The Delphi panel developed recommendations consisting of 10 opportunities and 10 barriers. The following opportunities were rated to be of highest importance: window views from clinical areas onto nature; outdoor settings, gardens and courtyards with easy and effortless access; and nature-based physical exercise adapted to patient requirements. Highest-rated barriers for nature-based oncology care included lack of knowledge and awareness about benefits of nature engagement and inaccessibility, not considering access requirements for the very sick and frail. Experts suggested and agreed on a set of recommendations, which represent critical considerations for the safe adoption of nature-based oncology opportunities. These findings fill a gap in understanding about helpful nature-based oncology care and may translate into oncology design and innovation. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Expert systems for automated maintenance of a Mars oxygen production system

NASA Technical Reports Server (NTRS)

Ash, Robert L.; Huang, Jen-Kuang; Ho, Ming-Tsang

1989-01-01

A prototype expert system was developed for maintaining autonomous operation of a Mars oxygen production system. Normal operation conditions and failure modes according to certain desired criteria are tested and identified. Several schemes for failure detection and isolation using forward chaining, backward chaining, knowledge-based and rule-based are devised to perform several housekeeping functions. These functions include self-health checkout, an emergency shut down program, fault detection and conventional control activities. An effort was made to derive the dynamic model of the system using Bond-Graph technique in order to develop the model-based failure detection and isolation scheme by estimation method. Finally, computer simulations and experimental results demonstrated the feasibility of the expert system and a preliminary reliability analysis for the oxygen production system is also provided.

Computer-assisted knowledge acquisition for hypermedia systems

NASA Technical Reports Server (NTRS)

Steuck, Kurt

1990-01-01

The usage of procedural and declarative knowledge to set up the structure or 'web' of a hypermedia environment is described. An automated knowledge acquisition tool was developed that helps a knowledge engineer elicit and represent an expert's knowledge involved in performing procedural tasks. The tool represents both procedural and prerequisite, declarative knowledge that supports each activity performed by the expert. This knowledge is output and subsequently read by a hypertext scripting language to generate the link between blank, but labeled cards. Each step of the expert's activity and each piece of supporting declarative knowledge is set up as an empty node. An instructional developer can then enter detailed instructional material concerning each step and declarative knowledge into these empty nodes. Other research is also described that facilitates the translation of knowledge from one form into a form more readily useable by computerized systems.

Prompt comprehension in UNIX command production.

PubMed

Doane, S M; McNamara, D S; Kintsch, W; Polson, P G; Clawson, D M

1992-07-01

We hypothesize that a cognitive analysis based on the construction-integration theory of comprehension (Kintsch, 1988) can predict what is difficult about generating complex composite commands in the UNIX operating system. We provide empirical support for assumptions of the Doane, Kintsch, and Polson (1989, 1990) construction-integration model for generating complex commands in UNIX. We asked users whose UNIX experience varied to produce complex UNIX commands, and then provided help prompts whenever the commands that they produced were erroneous. The help prompts were designed to assist subjects with respect to both the knowledge and the memory processes that our UNIX modeling efforts have suggested are lacking in less expert users. It appears that experts respond to different prompts than do novices. Expert performance is helped by the presentation of abstract information, whereas novice and intermediate performance is modified by presentation of concrete information. Second, while presentation of specific prompts helps less expert subjects, they do not provide sufficient information to obtain correct performance. Our analyses suggest that information about the ordering of commands is required to help the less expert with both knowledge and memory load problems in a manner consistent with skill acquisition theories.

C-Language Integrated Production System, Version 5.1

NASA Technical Reports Server (NTRS)

Riley, Gary; Donnell, Brian; Ly, Huyen-Anh VU; Culbert, Chris; Savely, Robert T.; Mccoy, Daniel J.; Giarratano, Joseph

1992-01-01

CLIPS 5.1 provides cohesive software tool for handling wide variety of knowledge with support for three different programming paradigms: rule-based, object-oriented, and procedural. Rule-based programming provides representation of knowledge by use of heuristics. Object-oriented programming enables modeling of complex systems as modular components. Procedural programming enables CLIPS to represent knowledge in ways similar to those allowed in such languages as C, Pascal, Ada, and LISP. Working with CLIPS 5.1, one can develop expert-system software by use of rule-based programming only, object-oriented programming only, procedural programming only, or combinations of the three.

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

Padalkar, S.; Karsai, G.; Sztipanovits, J.

1988-01-01

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Does expert knowledge improve automatic probabilistic classification of gait joint motion patterns in children with cerebral palsy?

PubMed Central

Papageorgiou, Eirini; Nieuwenhuys, Angela; Desloovere, Kaat

2017-01-01

Background This study aimed to improve the automatic probabilistic classification of joint motion gait patterns in children with cerebral palsy by using the expert knowledge available via a recently developed Delphi-consensus study. To this end, this study applied both Naïve Bayes and Logistic Regression classification with varying degrees of usage of the expert knowledge (expert-defined and discretized features). A database of 356 patients and 1719 gait trials was used to validate the classification performance of eleven joint motions. Hypotheses Two main hypotheses stated that: (1) Joint motion patterns in children with CP, obtained through a Delphi-consensus study, can be automatically classified following a probabilistic approach, with an accuracy similar to clinical expert classification, and (2) The inclusion of clinical expert knowledge in the selection of relevant gait features and the discretization of continuous features increases the performance of automatic probabilistic joint motion classification. Findings This study provided objective evidence supporting the first hypothesis. Automatic probabilistic gait classification using the expert knowledge available from the Delphi-consensus study resulted in accuracy (91%) similar to that obtained with two expert raters (90%), and higher accuracy than that obtained with non-expert raters (78%). Regarding the second hypothesis, this study demonstrated that the use of more advanced machine learning techniques such as automatic feature selection and discretization instead of expert-defined and discretized features can result in slightly higher joint motion classification performance. However, the increase in performance is limited and does not outweigh the additional computational cost and the higher risk of loss of clinical interpretability, which threatens the clinical acceptance and applicability. PMID:28570616

Design of an expert system for the development and formulation of push-pull osmotic pump tablets containing poorly water-soluble drugs.

PubMed

Zhang, Zhi-hong; Dong, Hong-ye; Peng, Bo; Liu, Hong-fei; Li, Chun-lei; Liang, Min; Pan, Wei-san

2011-05-30

The purpose of this article was to build an expert system for the development and formulation of push-pull osmotic pump tablets (PPOP). Hundreds of PPOP formulations were studied according to different poorly water-soluble drugs and pharmaceutical acceptable excipients. The knowledge base including database and rule base was built based on the reported results of hundreds of PPOP formulations containing different poorly water-soluble drugs and pharmaceutical excipients and the experiences available from other researchers. The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function. Formulation design model was established based on the prediction model of release behavior, which was the nucleus of the inference engine. Finally, the expert system program was constructed by VB.NET associating with SQL Server. Expert system is one of the most popular aspects in artificial intelligence. To date there is no expert system available for the formulation of controlled release dosage forms yet. Moreover, osmotic pump technology (OPT) is gradually getting consummate all over the world. It is meaningful to apply expert system on OPT. Famotidine, a water insoluble drug was chosen as the model drug to validate the applicability of the developed expert system. Copyright © 2011 Elsevier B.V. All rights reserved.

Implementation of a frame-based representation in CLIPS

NASA Technical Reports Server (NTRS)

Assal, Hisham; Myers, Leonard

1990-01-01

Knowledge representation is one of the major concerns in expert systems. The representation of domain-specific knowledge should agree with the nature of the domain entities and their use in the real world. For example, architectural applications deal with objects and entities such as spaces, walls, and windows. A natural way of representing these architectural entities is provided by frames. This research explores the potential of using the expert system shell CLIPS, developed by NASA, to implement a frame-based representation that can accommodate architectural knowledge. These frames are similar but quite different from the 'template' construct in version 4.3 of CLIPS. Templates support only the grouping of related information and the assignment of default values to template fields. In addition to these features frames provide other capabilities including definition of classes, inheritance between classes and subclasses, relation of objects of different classes with 'has-a', association of methods (demons) of different types (standard and user-defined) to fields (slots), and creation of new fields at run-time. This frame-based representation is implemented completely in CLIPS. No change to the source code is necessary.

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

Pilat, Joseph F

The application of the methodology developed by the GenIV International Forum's (GIF's) Proliferation Resistance and Physical Protection (PR&PP) Working Group is an expert elicitation. Although the framework of the methodology is structured and systematic, it does not by itself constitute or require a formal elicitation. However, formal elicitation can be utilized in the PR&PP context to provide a systematic, credible and transparent qualitative analysis and develop input for quantitative analyses. This section provides an overview of expert elicitations, a discussion of the role formal expert elicitations can play in the PR&PP methodology, an outline of the formal expert elicitation processmore » and a brief practical guide to conducting formal expert elicitations. Expert elicitation is a process utilizing knowledgeable people in cases, for example, when an assessment is needed but physically based data is absent or open to interpretation. More specifically, it can be used to: (1) predict future events; (2) provide estimates on new, rare, complex or poorly understood phenomena; (3) integrate or interpret existing information; or (4) determine what is currently known, how well it is known or what is worth learning in a field. Expert elicitation can be informal or formal. The informal application of expert judgment is frequently used. Although it can produce good results, it often provides demonstrably biased or otherwise flawed answers to problems. This along with the absence of transparency can result in a loss of confidence when experts speak on issues. More formal expert elicitation is a structured process that makes use of people knowledgeable in certain areas to make assessments. The reason for advocating formal use is that the quality and accuracy of expert judgment comes from the completeness of the expert's understanding of the phenomena and the process used to elicit and analyze the data. The use of a more formal process to obtain, lU1derstand and analyze expert judgment has led to an improved acceptance of expert judgment because of the rigor and transparency of the results.« less

Development of nickel hydrogen battery expert system

NASA Technical Reports Server (NTRS)

Shiva, Sajjan G.

1990-01-01

The Hubble Telescope Battery Testbed employs the nickel-cadmium battery expert system (NICBES-2) which supports the evaluation of performances of Hubble Telescope spacecraft batteries and provides alarm diagnosis and action advice. NICBES-2 also provides a reasoning system along with a battery domain knowledge base to achieve this battery health management function. An effort to modify NICBES-2 to accommodate nickel-hydrogen battery environment in testbed is described.

Expert systems in the process industries

NASA Technical Reports Server (NTRS)

Stanley, G. M.

1992-01-01

This paper gives an overview of industrial applications of real-time knowledge based expert systems (KBES's) in the process industries. After a brief overview of the features of a KBES useful in process applications, the general roles of KBES's are covered. A particular focus is diagnostic applications, one of the major applications areas. Many applications are seen as an expansion of supervisory control. The lessons learned from numerous online applications are summarized.

Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics.

PubMed

Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S

2000-01-01

We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.

Issues on the use of meta-knowledge in expert systems

NASA Technical Reports Server (NTRS)

Facemire, Jon; Chen, Imao

1988-01-01

Meta knowledge is knowledge about knowledge; knowledge that is not domain specific but is concerned instead with its own internal structure. Several past systems have used meta-knowledge to improve the nature of the user interface, to maintain the knowledge base, and to control the inference engine. More extensive use of meta-knowledge is probable for the future as larger scale problems are considered. A proposed system architecture is presented and discussed in terms of meta-knowledge applications. The principle components of this system: the user support subsystem, the control structure, the knowledge base, the inference engine, and a learning facility are all outlined and discussed in light of the use of meta-knowledge. Problems with meta-constructs are also mentioned but it is concluded that the use of meta-knowledge is crucial for increasingly autonomous operations.

Applications of advanced data analysis and expert system technologies in the ATLAS Trigger-DAQ Controls framework

NASA Astrophysics Data System (ADS)

Avolio, G.; Corso Radu, A.; Kazarov, A.; Lehmann Miotto, G.; Magnoni, L.

2012-12-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS experiment is a very complex distributed computing system, composed of more than 20000 applications running on more than 2000 computers. The TDAQ Controls system has to guarantee the smooth and synchronous operations of all the TDAQ components and has to provide the means to minimize the downtime of the system caused by runtime failures. During data taking runs, streams of information messages sent or published by running applications are the main sources of knowledge about correctness of running operations. The huge flow of operational monitoring data produced is constantly monitored by experts in order to detect problems or misbehaviours. Given the scale of the system and the rates of data to be analyzed, the automation of the system functionality in the areas of operational monitoring, system verification, error detection and recovery is a strong requirement. To accomplish its objective, the Controls system includes some high-level components which are based on advanced software technologies, namely the rule-based Expert System and the Complex Event Processing engines. The chosen techniques allow to formalize, store and reuse the knowledge of experts and thus to assist the shifters in the ATLAS control room during the data-taking activities.

Knowledge-based support for the participatory design and implementation of shift systems.

PubMed

Gissel, A; Knauth, P

1998-01-01

This study developed a knowledge-based software system to support the participatory design and implementation of shift systems as a joint planning process including shift workers, the workers' committee, and management. The system was developed using a model-based approach. During the 1st phase, group discussions were repeatedly conducted with 2 experts. Thereafter a structure model of the process was generated and subsequently refined by the experts in additional semistructured interviews. Next, a factual knowledge base of 1713 relevant studies was collected on the effects of shift work. Finally, a prototype of the knowledge-based system was tested on 12 case studies. During the first 2 phases of the system, important basic information about the tasks to be carried out is provided for the user. During the 3rd phase this approach uses the problem-solving method of case-based reasoning to determine a shift rota which has already proved successful in other applications. It can then be modified in the 4th phase according to the shift workers' preferences. The last 2 phases support the final testing and evaluation of the system. The application of this system has shown that it is possible to obtain shift rotas suitable to actual problems and representative of good ergonomic solutions. A knowledge-based approach seems to provide valuable support for the complex task of designing and implementing a new shift system. The separation of the task into several phases, the provision of information at all stages, and the integration of all parties concerned seem to be essential factors for the success of the application.

Knowledge Preservation for Design of Rocket Systems

NASA Technical Reports Server (NTRS)

Moreman, Douglas

2002-01-01

An engineer at NASA Lewis RC presented a challenge to us at Southern University. Our response to that challenge, stated circa 1993, has evolved into the Knowledge Preservation Project which is here reported. The stated problem was to capture some of the knowledge of retiring NASA engineers and make it useful to younger engineers via computers. We evolved that initial challenge to this - design a system of tools such that, with this system, people might efficiently capture and make available via commonplace computers, deep knowledge of retiring NASA engineers. In the process of proving some of the concepts of this system, we would (and did) capture knowledge from some specific engineers and, so, meet the original challenge along the way to meeting the new. Some of the specific knowledge acquired, particularly that on the RL- 10 engine, was directly relevant to design of rocket engines. We considered and rejected some of the techniques popular in the days we began - specifically "expert systems" and "oral histories". We judged that these old methods had too high a cost per sentence preserved. That cost could be measured in hours of labor of a "knowledge professional". We did spend, particularly in the grant preceding this one, some time creating a couple of "concept maps", one of the latest ideas of the day, but judged this also to be costly in time of a specially trained knowledge-professional. We reasoned that the cost in specialized labor could be lowered if less time were spent being selective about sentences from the engineers and in crafting replacements for those sentences. The trade-off would seem to be that our set of sentences would be less dense in information, but we found a computer-based way around this seeming defect. Our plan, details of which we have been carrying out, was to find methods of extracting information from experts which would be capable of gaining cooperation, and interest, of senior engineers and using their time in a way they would find worthy (and, so, they would give more of their time and recruit time of other engineers as well). We studied these four ways of creating text: 1) the old way, via interviews and discussions - one of our team working with one expert, 2) a group-discussion led by one of the experts themselves and on a topic which inspires interaction of the experts, 3) a spoken dissertation by one expert practiced in giving talks, 4) expropriating, and modifying for our system, some existing reports (such as "oral histories" from the Smithsonian Institution).

Knowing the operative game plan: a novel tool for the assessment of surgical procedural knowledge.

PubMed

Balayla, Jacques; Bergman, Simon; Ghitulescu, Gabriela; Feldman, Liane S; Fraser, Shannon A

2012-08-01

What is the source of inadequate performance in the operating room? Is it a lack of technical skills, poor judgment or a lack of procedural knowledge? We created a surgical procedural knowledge (SPK) assessment tool and evaluated its use. We interviewed medical students, residents and training program staff on SPK assessment tools developed for 3 different common general surgery procedures: inguinal hernia repair with mesh in men, laparoscopic cholecystectomy and right hemicolectomy. The tools were developed as a step-wise assessment of specific surgical procedures based on techniques described in a current surgical text. We compared novice (medical student to postgraduate year [PGY]-2) and expert group (PGY-3 to program staff) scores using the Mann-Whitney U test. We calculated the total SPK score and defined a cut-off score using receiver operating characteristic analysis. In all, 5 participants in 7 different training groups (n = 35) underwent an interview. Median scores for each procedure and overall SPK scores increased with experience. The median SPK for novices was 54.9 (95% confidence interval [CI] 21.6-58.8) compared with 98.05 (95% CP 94.1-100.0) for experts (p = 0.012). The SPK cut-off score of 93.1 discriminates between novice and expert surgeons. Surgical procedural knowledge can reliably be assessed using our SPK assessment tool. It can discriminate between novice and expert surgeons for common general surgical procedures. Future studies are planned to evaluate its use for more complex procedures.

Teaching statistics to nursing students: an expert panel consensus.

PubMed

Hayat, Matthew J; Eckardt, Patricia; Higgins, Melinda; Kim, MyoungJin; Schmiege, Sarah J

2013-06-01

Statistics education is a necessary element of nursing education, and its inclusion is recommended in the American Association of Colleges of Nursing guidelines for nurse training at all levels. This article presents a cohesive summary of an expert panel discussion, "Teaching Statistics to Nursing Students," held at the 2012 Joint Statistical Meetings. All panelists were statistics experts, had extensive teaching and consulting experience, and held faculty appointments in a U.S.-based nursing college or school. The panel discussed degree-specific curriculum requirements, course content, how to ensure nursing students understand the relevance of statistics, approaches to integrating statistics consulting knowledge, experience with classroom instruction, use of knowledge from the statistics education research field to make improvements in statistics education for nursing students, and classroom pedagogy and instruction on the use of statistical software. Panelists also discussed the need for evidence to make data-informed decisions about statistics education and training for nurses. Copyright 2013, SLACK Incorporated.

Membership nominations in international scientific assessments

NASA Astrophysics Data System (ADS)

Leifeld, Philip; Fisher, Dana R.

2017-10-01

International scientific assessments are transnational knowledge-based expert networks with a mandate to advise policymakers. A well-known example is the Millennium Ecosystem Assessment (MA), which synthesized research on ecosystem services between 2001 and 2005, utilizing the knowledge of 1,360 expert members. Little, however, is known about the membership composition and the driving forces behind membership nominations in the MA and similar organizations. Here we introduce a survey data set on recruitment in the MA and analyse nomination patterns among experts as a complex network. The results indicate that membership recruitment was governed by prior contacts in other transnational elite organizations and a range of other factors related to personal affinity. Network analysis demonstrates how some core individuals were particularly influential in shaping the overall membership composition of the group. These findings add to recently noted concerns about the lack of diversity of views represented in international scientific assessments.

The Catalonian Expert Patient Programme for Chagas Disease: An Approach to Comprehensive Care Involving Affected Individuals.

PubMed

Claveria Guiu, Isabel; Caro Mendivelso, Johanna; Ouaarab Essadek, Hakima; González Mestre, Maria Asunción; Albajar-Viñas, Pedro; Gómez I Prat, Jordi

2017-02-01

The Catalonian Expert Patient Programme on Chagas disease is a initiative, which is part of the Chronic Disease Programme. It aims to boost responsibility of patients for their own health and to promote self-care. The programme is based on nine sessions conducted by an expert patient. Evaluation was focusing in: habits and lifestyle/self-care, knowledge of disease, perception of health, self-esteem, participant satisfaction, and compliance with medical follow-up visits. Eighteen participants initiated the programme and 15 completed it. The participants were Bolivians. The 66.7 % of them had been diagnosed with chagas disease in Spain. The 100 % mentioned that they would participate in this activity again and would recommend it to family and friends. The knowledge about disease improve after sessions. The method used in the programme could serve as a key strategy in the field of comprehensive care for individuals with this disease.

ACES: Space shuttle flight software analysis expert system

NASA Technical Reports Server (NTRS)

Satterwhite, R. Scott

1990-01-01

The Analysis Criteria Evaluation System (ACES) is a knowledge based expert system that automates the final certification of the Space Shuttle onboard flight software. Guidance, navigation and control of the Space Shuttle through all its flight phases are accomplished by a complex onboard flight software system. This software is reconfigured for each flight to allow thousands of mission-specific parameters to be introduced and must therefore be thoroughly certified prior to each flight. This certification is performed in ground simulations by executing the software in the flight computers. Flight trajectories from liftoff to landing, including abort scenarios, are simulated and the results are stored for analysis. The current methodology of performing this analysis is repetitive and requires many man-hours. The ultimate goals of ACES are to capture the knowledge of the current experts and improve the quality and reduce the manpower required to certify the Space Shuttle onboard flight software.

HERB: A production system for programming with hierarchical expert rule bases: User's manual, HERB Version 1. 0

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

Hummel, K.E.

1987-12-01

Expert systems are artificial intelligence programs that solve problems requiring large amounts of heuristic knowledge, based on years of experience and tradition. Production systems are domain-independent tools that support the development of rule-based expert systems. This document describes a general purpose production system known as HERB. This system was developed to support the programming of expert systems using hierarchically structured rule bases. HERB encourages the partitioning of rules into multiple rule bases and supports the use of multiple conflict resolution strategies. Multiple rule bases can also be placed on a system stack and simultaneously searched during each interpreter cycle. Bothmore » backward and forward chaining rules are supported by HERB. The condition portion of each rule can contain both patterns, which are matched with facts in a data base, and LISP expressions, which are explicitly evaluated in the LISP environment. Properties of objects can also be stored in the HERB data base and referenced within the scope of each rule. This document serves both as an introduction to the principles of LISP-based production systems and as a user's manual for the HERB system. 6 refs., 17 figs.« less

Implementation and assessment of a curriculum for bedside ultrasound training.

PubMed

Turner, Elizabeth E; Fox, J Christian; Rosen, Mark; Allen, Angela; Rosen, Sasha; Anderson, Craig

2015-05-01

This study assessed a curriculum for bedside ultrasound (US) and compared outcomes from 2 common training pathways. The program consisted of e-learning paired with expert-led hands-on training administered to pulmonary/critical care and cardiology fellows with no prior formal training in bedside US. This "simulation-based learner" group completed a survey of attitudes and confidence before and after training, and knowledge and skills were assessed after training. The surveys and scores of the simulation-based learners were compared to the scores of "experts," who were US-trained emergency physicians, and "apprentice learners," who were intensivist physicians informally trained in bedside US on the job during fellowships. There was a significant difference in the self-reported level of prior training between the groups (simulation-based learners, 2.8; apprentice learners, 3.7; experts, 4.1, on a scale of 1-5 [P= .02]) but no difference in the interest level or perceived importance of bedside US. The study curriculum was successful, as shown by scores that exceeded the comparison groups in the cardiac and pulmonary courses (cardiac: simulation-based learners, 80%; apprentice learners, 73%; experts, 62% [P= .001]; pulmonary: 84%, 75%, and 72%, respectively [P =.02]). The simulation-based learners gained confidence in skills, whereas the comparison groups lost confidence after testing (P < .005); however, the simulation-based learners gained confidence in US subject areas that were not taught (abdomen [P <.002] and miscellaneous [P =.005]). The simulation-based learner curriculum resulted in comparable or greater knowledge and confidence in each area of US versus the comparison groups. Findings of overgeneralization of confidence highlight the importance of quality assurance and supervision in bedside US training programs. © 2015 by the American Institute of Ultrasound in Medicine.

A LISP-Ada connection

NASA Technical Reports Server (NTRS)

Jaworski, Allan; Lavallee, David; Zoch, David

1987-01-01

The prototype demonstrates the feasibility of using Ada for expert systems and the implementation of an expert-friendly interface which supports knowledge entry. In the Ford LISP-Ada Connection (FLAC) system LISP and Ada are used in ways which complement their respective capabilities. Future investigation will concentrate on the enhancement of the expert knowledge entry/debugging interface and on the issues associated with multitasking and real-time expert systems implementation in Ada.

A knowledge base for tracking the impact of genomics on population health.

PubMed

Yu, Wei; Gwinn, Marta; Dotson, W David; Green, Ridgely Fisk; Clyne, Mindy; Wulf, Anja; Bowen, Scott; Kolor, Katherine; Khoury, Muin J

2016-12-01

We created an online knowledge base (the Public Health Genomics Knowledge Base (PHGKB)) to provide systematically curated and updated information that bridges population-based research on genomics with clinical and public health applications. Weekly horizon scanning of a wide variety of online resources is used to retrieve relevant scientific publications, guidelines, and commentaries. After curation by domain experts, links are deposited into Web-based databases. PHGKB currently consists of nine component databases. Users can search the entire knowledge base or search one or more component databases directly and choose options for customizing the display of their search results. PHGKB offers researchers, policy makers, practitioners, and the general public a way to find information they need to understand the complicated landscape of genomics and population health.Genet Med 18 12, 1312-1314.

Pedagogical Content Knowledge of Experts and Novices--What Knowledge Do They Activate When Analyzing Science Lessons?

ERIC Educational Resources Information Center

Krepf, Matthias; Plöger, Wilfried; Scholl, Daniel; Seifert, Andreas

2018-01-01

In the current debate on pedagogical content knowledge (PCK), the term is used to refer to the context-specific knowledge that teachers activate when reflecting on practice. Against the background of this debate, we conducted an empirical study and sought to answer the question of which knowledge experts and novices activated in assessing a…

Parasitology tutoring system: a hypermedia computer-based application.

PubMed

Theodoropoulos, G; Loumos, V

1994-02-14

The teaching of parasitology is a basic course in all life sciences curricula, and up to now no computer-assisted tutoring system has been developed for this purpose. By using Knowledge Pro, an object-oriented software development tool, a hypermedia tutoring system for teaching parasitology to college students was developed. Generally, a tutoring system contains a domain expert, a student model, a pedagogical expert and the user interface. In this project, particular emphasis was given to the user interface design and the expert knowledge representation. The system allows access to the educational material through hypermedia and indexing at the pace of the student. The hypermedia access is facilitated through key words defined as hypertext and objects in pictures defined as hyper-areas. The indexing access is based on a list of parameters that refers to various characteristics of the parasites, e.g. taxonomy, host, organ, etc. In addition, this indexing access can be used for testing the student's level of understanding. The advantages of this system are its user-friendliness, graphical interface and ability to incorporate new educational material in the area of parasitology.

Of Pigs and Men: Understanding Students' Reasoning About the Use of Pigs as Donors for Xenotransplantation

NASA Astrophysics Data System (ADS)

Lindahl, Mats Gunnar

2010-09-01

Two important roles of education are to provide students with knowledge for their democratic participation in society and to provide knowledge for a future profession. In science education, students encounter values that may be in conflict with their worldview. Such conflicts may, for example, lead to constructive reflections as well as rejection of scientific knowledge and technology. Students’ ways of reasoning are important starting points for discussing problematic issues and may be crucial for constructive dialogues in the classroom. This study investigates students’ reasoning about conflicting values concerning the human-animal relationship exemplified by the use of genetically modified pigs as organ donors for xenotransplantation. Students’ reasoning is analyzed using Giddens’ concepts of disembedded and embedded practices in parallel with moral philosophical theories in a framework based on human-animal relationships. Thirteen students were interviewed and their stances categorized. Kantian deontological and classical utilitarian ethics were found within the patronage and the partnership models. These students appreciated expert knowledge but those using the partnership model could not accept xenotransplantation if pigs were to be killed. Students using care ethics did not appreciate expert knowledge since it threatened naturalness. The results suggest that stances against the use of scientific knowledge are more problematic than knowledge per se, and that conflicting stances have similarities that present opportunities for understanding and development of students’ argumentation skills for future participation in societal discourse on utilizing expert knowledge. Furthermore it is argued that science education could benefit from a higher awareness of the presence of different morals.

A rule-based expert system applied to moisture durability of building envelopes

DOE PAGES

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.; ...

2018-01-09

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

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.

A rule-based expert system applied to moisture durability of building envelopes

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

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

Applications of Machine Learning and Rule Induction,

DTIC Science & Technology

1995-02-15

An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems. In this paper...we review the major paradigms for machine learning , including neural networks, instance-based methods, genetic learning, rule induction, and analytic

TARGET - TASK ANALYSIS REPORT GENERATION TOOL, VERSION 1.0

NASA Technical Reports Server (NTRS)

Ortiz, C. J.

1994-01-01

The Task Analysis Report Generation Tool, TARGET, is a graphical interface tool used to capture procedural knowledge and translate that knowledge into a hierarchical report. TARGET is based on VISTA, a knowledge acquisition tool developed by the Naval Systems Training Center. TARGET assists a programmer and/or task expert organize and understand the steps involved in accomplishing a task. The user can label individual steps in the task through a dialogue-box and get immediate graphical feedback for analysis. TARGET users can decompose tasks into basic action kernels or minimal steps to provide a clear picture of all basic actions needed to accomplish a job. This method allows the user to go back and critically examine the overall flow and makeup of the process. The user can switch between graphics (box flow diagrams) and text (task hierarchy) versions to more easily study the process being documented. As the practice of decomposition continues, tasks and their subtasks can be continually modified to more accurately reflect the user's procedures and rationale. This program is designed to help a programmer document an expert's task thus allowing the programmer to build an expert system which can help others perform the task. Flexibility is a key element of the system design and of the knowledge acquisition session. If the expert is not able to find time to work on the knowledge acquisition process with the program developer, the developer and subject matter expert may work in iterative sessions. TARGET is easy to use and is tailored to accommodate users ranging from the novice to the experienced expert systems builder. TARGET is written in C-language for IBM PC series and compatible computers running MS-DOS and Microsoft Windows version 3.0 or 3.1. No source code is supplied. The executable also requires 2Mb of RAM, a Microsoft compatible mouse, a VGA display and an 80286, 386 or 486 processor machine. The standard distribution medium for TARGET is one 5.25 inch 360K MS-DOS format diskette. TARGET was developed in 1991.

A methodology for uncertainty quantification in quantitative technology valuation based on expert elicitation

NASA Astrophysics Data System (ADS)

Akram, Muhammad Farooq Bin

The management of technology portfolios is an important element of aerospace system design. New technologies are often applied to new product designs to ensure their competitiveness at the time they are introduced to market. The future performance of yet-to- be designed components is inherently uncertain, necessitating subject matter expert knowledge, statistical methods and financial forecasting. Estimates of the appropriate parameter settings often come from disciplinary experts, who may disagree with each other because of varying experience and background. Due to inherent uncertain nature of expert elicitation in technology valuation process, appropriate uncertainty quantification and propagation is very critical. The uncertainty in defining the impact of an input on performance parameters of a system makes it difficult to use traditional probability theory. Often the available information is not enough to assign the appropriate probability distributions to uncertain inputs. Another problem faced during technology elicitation pertains to technology interactions in a portfolio. When multiple technologies are applied simultaneously on a system, often their cumulative impact is non-linear. Current methods assume that technologies are either incompatible or linearly independent. It is observed that in case of lack of knowledge about the problem, epistemic uncertainty is the most suitable representation of the process. It reduces the number of assumptions during the elicitation process, when experts are forced to assign probability distributions to their opinions without sufficient knowledge. Epistemic uncertainty can be quantified by many techniques. In present research it is proposed that interval analysis and Dempster-Shafer theory of evidence are better suited for quantification of epistemic uncertainty in technology valuation process. Proposed technique seeks to offset some of the problems faced by using deterministic or traditional probabilistic approaches for uncertainty propagation. Non-linear behavior in technology interactions is captured through expert elicitation based technology synergy matrices (TSM). Proposed TSMs increase the fidelity of current technology forecasting methods by including higher order technology interactions. A test case for quantification of epistemic uncertainty on a large scale problem of combined cycle power generation system was selected. A detailed multidisciplinary modeling and simulation environment was adopted for this problem. Results have shown that evidence theory based technique provides more insight on the uncertainties arising from incomplete information or lack of knowledge as compared to deterministic or probability theory methods. Margin analysis was also carried out for both the techniques. A detailed description of TSMs and their usage in conjunction with technology impact matrices and technology compatibility matrices is discussed. Various combination methods are also proposed for higher order interactions, which can be applied according to the expert opinion or historical data. The introduction of technology synergy matrix enabled capturing the higher order technology interactions, and improvement in predicted system performance.

An SQL query generator for CLIPS

NASA Technical Reports Server (NTRS)

Snyder, James; Chirica, Laurian

1990-01-01

As expert systems become more widely used, their access to large amounts of external information becomes increasingly important. This information exists in several forms such as statistical, tabular data, knowledge gained by experts and large databases of information maintained by companies. Because many expert systems, including CLIPS, do not provide access to this external information, much of the usefulness of expert systems is left untapped. The scope of this paper is to describe a database extension for the CLIPS expert system shell. The current industry standard database language is SQL. Due to SQL standardization, large amounts of information stored on various computers, potentially at different locations, will be more easily accessible. Expert systems should be able to directly access these existing databases rather than requiring information to be re-entered into the expert system environment. The ORACLE relational database management system (RDBMS) was used to provide a database connection within the CLIPS environment. To facilitate relational database access a query generation system was developed as a CLIPS user function. The queries are entered in a CLlPS-like syntax and are passed to the query generator, which constructs and submits for execution, an SQL query to the ORACLE RDBMS. The query results are asserted as CLIPS facts. The query generator was developed primarily for use within the ICADS project (Intelligent Computer Aided Design System) currently being developed by the CAD Research Unit in the California Polytechnic State University (Cal Poly). In ICADS, there are several parallel or distributed expert systems accessing a common knowledge base of facts. Expert system has a narrow domain of interest and therefore needs only certain portions of the information. The query generator provides a common method of accessing this information and allows the expert system to specify what data is needed without specifying how to retrieve it.

Simulation Of Combat With An Expert System

NASA Technical Reports Server (NTRS)

Provenzano, J. P.

1989-01-01

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

Integrating knowledge and control into hypermedia-based training environments: Experiments with HyperCLIPS

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.

1990-01-01

The issues of knowledge representation and control in hypermedia-based training environments are discussed. The main objective is to integrate the flexible presentation capability of hypermedia with a knowledge-based approach to lesson discourse management. The instructional goals and their associated concepts are represented in a knowledge representation structure called a 'concept network'. Its functional usages are many: it is used to control the navigation through a presentation space, generate tests for student evaluation, and model the student. This architecture was implemented in HyperCLIPS, a hybrid system that creates a bridge between HyperCard, a popular hypertext-like system used for building user interfaces to data bases and other applications, and CLIPS, a highly portable government-owned expert system shell.

Bridging Research and Environmental Regulatory Processes: The Role of Knowledge Brokers

PubMed Central

Pennell, Kelly G.; Thompson, Marcella; Rice, James W.; Senier, Laura; Brown, Phil; Suuberg, Eric

2013-01-01

Federal funding agencies increasingly require research investigators to ensure that federally-sponsored research demonstrates broader societal impact. Specifically, the National Institutes of Environmental Health Sciences (NIEHS) Superfund Research Program (SRP) requires research centers to include research translation and community engagement cores to achieve broader impacts, with special emphasis on improving environmental health policies through better scientific understanding. This paper draws on theoretical insights from the social sciences to show how incorporating knowledge brokers in research centers can facilitate translation of scientific expertise to influence regulatory processes and thus promote public health. Knowledge brokers connect academic researchers with decision-makers, to facilitate the translation of research findings into policies and programs. In this article, we describe the stages of the regulatory process and highlight the role of the knowledge broker and scientific expert at each stage. We illustrate the cooperation of knowledge brokers, scientific experts and policymakers using a case from the Brown University (Brown) SRP. We show how the Brown SRP incorporated knowledge brokers to engage scientific experts with regulatory officials around the emerging public health problem of vapor intrusion. In the Brown SRP, the knowledge broker brought regulatory officials into the research process, to help scientific experts understand the critical nature of this emerging public health threat, and helped scientific experts develop a research agenda that would inform the development of timely measures to protect public health. Our experience shows that knowledge brokers can enhance the impact of environmental research on public health by connecting policy decision-makers with scientific experts at critical points throughout the regulatory process. PMID:24083557

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.

Enlargement Futures Project: Expert Panel on Technology, Knowledge and Learning. Final Report.

ERIC Educational Resources Information Center

Gourova, Elissaveta; Ducatel, Ken; Gavigan, James; Scapolo, Fabiana; Di Pietrogiacomo, Paola

The next 10 years provide an opportunity for the European Union (EU) to renew the science and technology (S&T) base and build necessary knowledge-society capacities and capabilities in Pre-Accession Countries (PACs). Applied research has faced a major downsize; redressing the balance in the research and development systems is urgently needed.…

Automated Session-Quality Assessment for Human Tutoring Based on Expert Ratings of Tutoring Success

ERIC Educational Resources Information Center

Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan

2015-01-01

Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…

The Role of Knowledge Base and Declarative Metamemory in the Acquisition of a Reading Strategy.

ERIC Educational Resources Information Center

Gaultney, Jane F.; Hack-Weiner, Nancy

A study examined whether previous knowledge facilitates the acquisition of a reading comprehension strategy by children who are poor readers. Subjects, 54 fourth- and fifth-grade boys in Palm Beach County, Florida, who were poor readers and baseball experts, were trained in the use of a reading strategy (asking "why" questions), with…

How Do Physicians Become Medical Experts? A Test of Three Competing Theories: Distinct Domains, Independent Influence and Encapsulation Models

ERIC Educational Resources Information Center

Violato, Claudio; Gao, Hong; O'Brien, Mary Claire; Grier, David; Shen, E.

2018-01-01

The distinction between basic sciences and clinical knowledge which has led to a theoretical debate on how medical expertise is developed has implications for medical school and lifelong medical education. This longitudinal, population based observational study was conducted to test the fit of three theories--knowledge encapsulation, independent…

Developing an Assessment Instrument to Measure Early Elementary Teachers' Mathematical Knowledge for Teaching

ERIC Educational Resources Information Center

Schoen, Robert C.; Bray, Wendy; Wolfe, Christopher; Tazaz, Amanda M.; Nielsen, Lynne

2017-01-01

This study reports on the development and field study of K-TEEM, a web-based assessment instrument designed to measure mathematical knowledge for teaching (MKT) at the early elementary level. The development process involved alignment with early elementary curriculum standards, expert review of items and scoring criteria, cognitive interviews with…

A knowledge authoring tool for clinical decision support.

PubMed

Dunsmuir, Dustin; Daniels, Jeremy; Brouse, Christopher; Ford, Simon; Ansermino, J Mark

2008-06-01

Anesthesiologists in the operating room are unable to constantly monitor all data generated by physiological monitors. They are further distracted by clinical and educational tasks. An expert system would ideally provide assistance to the anesthesiologist in this data-rich environment. Clinical monitoring expert systems have not been widely adopted, as traditional methods of knowledge encoding require both expert medical and programming skills, making knowledge acquisition difficult. A software application was developed for use as a knowledge authoring tool for physiological monitoring. This application enables clinicians to create knowledge rules without the need of a knowledge engineer or programmer. These rules are designed to provide clinical diagnosis, explanations and treatment advice for optimal patient care to the clinician in real time. By intelligently combining data from physiological monitors and demographical data sources the expert system can use these rules to assist in monitoring the patient. The knowledge authoring process is simplified by limiting connective relationships between rules. The application is designed to allow open collaboration between communities of clinicians to build a library of rules for clinical use. This design provides clinicians with a system for parameter surveillance and expert advice with a transparent pathway of reasoning. A usability evaluation demonstrated that anesthesiologists can rapidly develop useful rules for use in a predefined clinical scenario.

Expert systems for automated correlation and interpretation of wireline logs

USGS Publications Warehouse

Olea, R.A.

1994-01-01

CORRELATOR is an interactive computer program for lithostratigraphic correlation of wireline logs able to store correlations in a data base with a consistency, accuracy, speed, and resolution that are difficult to obtain manually. The automatic determination of correlations is based on the maximization of a weighted correlation coefficient using two wireline logs per well. CORRELATOR has an expert system to scan and flag incongruous correlations in the data base. The user has the option to accept or disregard the advice offered by the system. The expert system represents knowledge through production rules. The inference system is goal-driven and uses backward chaining to scan through the rules. Work in progress is used to illustrate the potential that a second expert system with a similar architecture for interpreting dip diagrams could have to identify episodes-as those of interest in sequence stratigraphy and fault detection- and annotate them in the stratigraphic column. Several examples illustrate the presentation. ?? 1994 International Association for Mathematical Geology.

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Walters, Jerry L.; Petrik, Edward J.; Roth, Mary Ellen; Truong, Long Van; Quinn, Todd; Krawczonek, Walter M.

1990-01-01

The Autonomous Power Expert (APEX) system was designed to monitor and diagnose fault conditions that occur within the Space Station Freedom Electrical Power System (SSF/EPS) Testbed. APEX is designed to interface with SSF/EPS testbed power management controllers to provide enhanced autonomous operation and control capability. The APEX architecture consists of three components: (1) a rule-based expert system, (2) a testbed data acquisition interface, and (3) a power scheduler interface. Fault detection, fault isolation, justification of probable causes, recommended actions, and incipient fault analysis are the main functions of the expert system component. The data acquisition component requests and receives pertinent parametric values from the EPS testbed and asserts the values into a knowledge base. Power load profile information is obtained from a remote scheduler through the power scheduler interface component. The current APEX design and development work is discussed. Operation and use of APEX by way of the user interface screens is also covered.

Knowledge acquisition for a simple expert controller

NASA Technical Reports Server (NTRS)

Bieker, B.

1987-01-01

A method is presented for process control which has the properties of being incremental, cyclic and top-down. It is described on the basis of the development of an expert controller for a simple, but nonlinear control route. A quality comparison between expert controller and process operator shows the ability of the method for knowledge acquisition.

An Expert System for Designing Fire Prescriptions

Treesearch

Elizabeth Reinhardt

1987-01-01

Managers use prescribed fire to accomplish a variety of resource objectives. The knowledge needed to design successful prescriptions is both quantitative and qualitative. Some of it is available through publications and computer programs, but much of the knowledge of expert practitioners has never been collected or published. An expert system being developed at the,...

On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph

NASA Astrophysics Data System (ADS)

Hao, Ruizhe; Huang, Jian

2017-08-01

Knowledge graph construction in military intelligence domain is sprouting but technically immature. This paper presents a method to construct the heterogeneous knowledge graph in the field of shipborne and airborne radar and equipment. Based on the expert knowledge and the up-to-date Internet open source information, we construct the knowledge graph of radar characteristic information and the equipment respectively, and establish relationships between two graphs, providing the pipeline and method for the intelligence organization and management in the context of the crowding battlefields big data.

TES: A modular systems approach to expert system development for real-time space applications

NASA Technical Reports Server (NTRS)

Cacace, Ralph; England, Brenda

1988-01-01

A major goal of the Space Station era is to reduce reliance on support from ground based experts. The development of software programs using expert systems technology is one means of reaching this goal without requiring crew members to become intimately familiar with the many complex spacecraft subsystems. Development of an expert systems program requires a validation of the software with actual flight hardware. By combining accurate hardware and software modelling techniques with a modular systems approach to expert systems development, the validation of these software programs can be successfully completed with minimum risk and effort. The TIMES Expert System (TES) is an application that monitors and evaluates real time data to perform fault detection and fault isolation tasks as they would otherwise be carried out by a knowledgeable designer. The development process and primary features of TES, a modular systems approach, and the lessons learned are discussed.

An Approach for Externalization of Expert Tacit Knowledge Using a Query Management System in an E-Learning Environment

ERIC Educational Resources Information Center

Khan, Abdul Azeez; Khader, Sheik Abdul

2014-01-01

E-learning or electronic learning platforms facilitate delivery of the knowledge spectrum to the learning community through information and communication technologies. The transfer of knowledge takes place from experts to learners, and externalization of the knowledge transfer is significant. In the e-learning environment, the learners seek…

Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research.

PubMed

Girardi, Dominic; Küng, Josef; Kleiser, Raimund; Sonnberger, Michael; Csillag, Doris; Trenkler, Johannes; Holzinger, Andreas

2016-09-01

Established process models for knowledge discovery find the domain-expert in a customer-like and supervising role. In the field of biomedical research, it is necessary to move the domain-experts into the center of this process with far-reaching consequences for both their research output and the process itself. In this paper, we revise the established process models for knowledge discovery and propose a new process model for domain-expert-driven interactive knowledge discovery. Furthermore, we present a research infrastructure which is adapted to this new process model and demonstrate how the domain-expert can be deeply integrated even into the highly complex data-mining process and data-exploration tasks. We evaluated this approach in the medical domain for the case of cerebral aneurysms research.

Expert system verification and validation study. Phase 2: Requirements Identification. Delivery 2: Current requirements applicability

NASA Technical Reports Server (NTRS)

1991-01-01

The second phase of a task is described which has the ultimate purpose of ensuring that adequate Expert Systems (ESs) Verification and Validation (V and V) tools and techniques are available for Space Station Freedom Program Knowledge Based Systems development. The purpose of this phase is to recommend modifications to current software V and V requirements which will extend the applicability of the requirements to NASA ESs.

Expert systems for MSFC power systems

NASA Technical Reports Server (NTRS)

Weeks, David J.

1988-01-01

Future space vehicles and platforms including Space Station will possess complex power systems. These systems will require a high level of autonomous operation to allow the crew to concentrate on mission activities and to limit the number of ground support personnel to a reasonable number. The Electrical Power Branch at NASA-Marshall is developing advanced automation approaches which will enable the necessary levels of autonomy. These approaches include the utilization of knowledge based or expert systems.

From the EBM pyramid to the Greek temple: a new conceptual approach to Guidelines as implementation tools in mental health.

PubMed

Salvador-Carulla, L; Lukersmith, S; Sullivan, W

2017-04-01

Guideline methods to develop recommendations dedicate most effort around organising discovery and corroboration knowledge following the evidence-based medicine (EBM) framework. Guidelines typically use a single dimension of information, and generally discard contextual evidence and formal expert knowledge and consumer's experiences in the process. In recognition of the limitations of guidelines in complex cases, complex interventions and systems research, there has been significant effort to develop new tools, guides, resources and structures to use alongside EBM methods of guideline development. In addition to these advances, a new framework based on the philosophy of science is required. Guidelines should be defined as implementation decision support tools for improving the decision-making process in real-world practice and not only as a procedure to optimise the knowledge base of scientific discovery and corroboration. A shift from the model of the EBM pyramid of corroboration of evidence to the use of broader multi-domain perspective graphically depicted as 'Greek temple' could be considered. This model takes into account the different stages of scientific knowledge (discovery, corroboration and implementation), the sources of knowledge relevant to guideline development (experimental, observational, contextual, expert-based and experiential); their underlying inference mechanisms (deduction, induction, abduction, means-end inferences) and a more precise definition of evidence and related terms. The applicability of this broader approach is presented for the development of the Canadian Consensus Guidelines for the Primary Care of People with Developmental Disabilities.

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.

Improvement of sand filter and constructed wetland design using an environmental decision support system.

PubMed

Turon, Clàudia; Comas, Joaquim; Torrens, Antonina; Molle, Pascal; Poch, Manel

2008-01-01

With the aim of improving effluent quality of waste stabilization ponds, different designs of vertical flow constructed wetlands and intermittent sand filters were tested on an experimental full-scale plant within the framework of a European project. The information extracted from this study was completed and updated with heuristic and bibliographic knowledge. The data and knowledge acquired were difficult to integrate into mathematical models because they involve qualitative information and expert reasoning. Therefore, it was decided to develop an environmental decision support system (EDSS-Filter-Design) as a tool to integrate mathematical models and knowledge-based techniques. This paper describes the development of this support tool, emphasizing the collection of data and knowledge and representation of this information by means of mathematical equations and a rule-based system. The developed support tool provides the main design characteristics of filters: (i) required surface, (ii) media type, and (iii) media depth. These design recommendations are based on wastewater characteristics, applied load, and required treatment level data provided by the user. The results of the EDSS-Filter-Design provide appropriate and useful information and guidelines on how to design filters, according to the expert criteria. The encapsulation of the information into a decision support system reduces the design period and provides a feasible, reasoned, and positively evaluated proposal.

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…

Factors influencing analysis of complex cognitive tasks: a framework and example from industrial process control.

PubMed

Prietula, M J; Feltovich, P J; Marchak, F

2000-01-01

We propose that considering four categories of task factors can facilitate knowledge elicitation efforts in the analysis of complex cognitive tasks: materials, strategies, knowledge characteristics, and goals. A study was conducted to examine the effects of altering aspects of two of these task categories on problem-solving behavior across skill levels: materials and goals. Two versions of an applied engineering problem were presented to expert, intermediate, and novice participants. Participants were to minimize the cost of running a steam generation facility by adjusting steam generation levels and flows. One version was cast in the form of a dynamic, computer-based simulation that provided immediate feedback on flows, costs, and constraint violations, thus incorporating key variable dynamics of the problem context. The other version was cast as a static computer-based model, with no dynamic components, cost feedback, or constraint checking. Experts performed better than the other groups across material conditions, and, when required, the presentation of the goal assisted the experts more than the other groups. The static group generated richer protocols than the dynamic group, but the dynamic group solved the problem in significantly less time. Little effect of feedback was found for intermediates, and none for novices. We conclude that demonstrating differences in performance in this task requires different materials than explicating underlying knowledge that leads to performance. We also conclude that substantial knowledge is required to exploit the information yielded by the dynamic form of the task or the explicit solution goal. This simple model can help to identify the contextual factors that influence elicitation and specification of knowledge, which is essential in the engineering of joint cognitive systems.

Design of a Knowledge Driven HIS

PubMed Central

Pryor, T. Allan; Clayton, Paul D.; Haug, Peter J.; Wigertz, Ove

1987-01-01

Design of the software architecture for a knowledge driven HIS is presented. In our design the frame has been used as the basic unit of knowledge representation. The structure of the frame is being designed to be sufficiently universal to contain knowledge required to implement not only expert systems, but almost all traditional HIS functions including ADT, order entry and results review. The design incorporates a two level format for the knowledge. The first level as ASCII records is used to maintain the knowledge base while the second level converted by special knowledge compilers to standard computer languages is used for efficient implementation of the knowledge applications.

Expert knowledge elicitation using computer simulation: the organization of frail elderly case management as an illustration.

PubMed

Chiêm, Jean-Christophe; Van Durme, Thérèse; Vandendorpe, Florence; Schmitz, Olivier; Speybroeck, Niko; Cès, Sophie; Macq, Jean

2014-08-01

Various elderly case management projects have been implemented in Belgium. This type of long-term health care intervention involves contextual factors and human interactions. These underlying complex mechanisms can be usefully informed with field experts' knowledge, which are hard to make explicit. However, computer simulation has been suggested as one possible method of overcoming the difficulty of articulating such elicited qualitative views. A simulation model of case management was designed using an agent-based methodology, based on the initial qualitative research material. Variables and rules of interaction were formulated into a simple conceptual framework. This model has been implemented and was used as a support for a structured discussion with experts in case management. The rigorous formulation provided by the agent-based methodology clarified the descriptions of the interventions and the problems encountered regarding: the diverse network topologies of health care actors in the project; the adaptation time required by the intervention; the communication between the health care actors; the institutional context; the organization of the care; and the role of the case manager and his or hers personal ability to interpret the informal demands of the frail older person. The simulation model should be seen primarily as a tool for thinking and learning. A number of insights were gained as part of a valuable cognitive process. Computer simulation supporting field experts' elicitation can lead to better-informed decisions in the organization of complex health care interventions. © 2013 John Wiley & Sons, Ltd.

Automated eddy current analysis of materials

NASA Technical Reports Server (NTRS)

Workman, Gary L.

1990-01-01

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

Development and Psychometric Evaluation of a Questionnaire Based on the Nursing Outcomes Classification to Determine the Knowledge of Parents on Breast-Feeding: Research Protocol.

PubMed

Paloma-Castro, Olga; Romero-Sánchez, José Manuel; Paramio-Cuevas, Juan Carlos; Pastor-Montero, Sonia María; Del Carmen Sánchez-Dalda, María; Rozadillas-Sanmiguel, Elena; Moreno-Corral, Luis Javier

2017-04-01

To develop and psychometrically evaluate a questionnaire based on the outcome "Knowledge: Breast-feeding" of the Nursing Outcomes Classification (NOC) to determine the knowledge of parents on breast-feeding. The NOC outcome "Knowledge: Breast-feeding" allows for nurses/midwives to assess the efficacy of interventions aimed to improve the knowledge on breast-feeding in parents thought the clinical interview/observation. However, the use of self-administered questionnaires by patients could facilitate its evaluation. Two-phased study: (1) Development of the questionnaire based on experts' opinions; (2) Methodological design to assess its psychometric properties. The availability of tools that enable the determination of the knowledge of patients would facilitate nurses/midwives to set objectives, individualize interventions, and measure their effectiveness. © 2015 NANDA International, Inc.

Bridging the gap: simulations meet knowledge bases

NASA Astrophysics Data System (ADS)

King, Gary W.; Morrison, Clayton T.; Westbrook, David L.; Cohen, Paul R.

2003-09-01

Tapir and Krill are declarative languages for specifying actions and agents, respectively, that can be executed in simulation. As such, they bridge the gap between strictly declarative knowledge bases and strictly executable code. Tapir and Krill components can be combined to produce models of activity which can answer questions about mechanisms and processes using conventional inference methods and simulation. Tapir was used in DARPA's Rapid Knowledge Formation (RKF) project to construct models of military tactics from the Army Field Manual FM3-90. These were then used to build Courses of Actions (COAs) which could be critiqued by declarative reasoning or via Monte Carlo simulation. Tapir and Krill can be read and written by non-knowledge engineers making it an excellent vehicle for Subject Matter Experts to build and critique knowledge bases.

Research and knowledge in Ontario tobacco control networks.

PubMed

Bickford, Julia J; Kothari, Anita R

2008-01-01

This study sought to better understand the role of research knowledge in Ontario tobacco control networks by asking: 1) How is research managed; 2) How is research evaluated; and 3) How is research utilized? This is a secondary analysis of a qualitative study based on individual semistructured interviews with 29 participants between January and May 2006. These participants were purposefully sampled from across four Ministries in the provincial government (n = 7), non-government (n = 15), and public health organizations (n = 7). Interviews were transcribed verbatim and coded and analyzed using QSR N7 qualitative software. This study received ethics approval from The University of Western Ontario Health Research Ethics Board. There exists a dissonance between the preference for peer-reviewed, unbiased, non-partisan knowledge to support claims and the need for fast, "real-time" information on which to base tobacco-related policy decisions. Second, there is a great deal of tacit knowledge held by experts within the Ontario tobacco control community. The networks among government, non-government, and public health organizations are the structures through which tacit knowledge is exchanged. These networks are dynamic, fluid and shifting. There exists a gap in the production and utilization of research knowledge for tobacco control policy. Tacit knowledge held by experts in Ontario tobacco control networks is an integral means of managing and evaluating research knowledge. Finally, this study builds on Weiss's concept of tactical model of evidence use by highlighting the utilization of research to enhance one's credibility.

How far we are from the complete knowledge: Complexity of knowledge acquisition in Dempster-Shafer approach

NASA Technical Reports Server (NTRS)

Chokr, Bassam A.; Kreinovich, Vladik YA.

1991-01-01

When a knowledge base represents the experts' uncertainty, then it is reasonable to ask how far we are from the complete knowledge, that is, how many more questions do we have to ask (to these experts, to nature by means of experimenting, etc) in order to attain the complete knowledge. Of course, since we do not know what the real world is, we cannot get the precise number of questions from the very beginning: it is quite possible, for example, that we ask the right question first and thus guess the real state of the world after the first question. So we have to estimate this number and use this estimate as a natural measure of completeness for a given knowledge base. We give such estimates for Dempster-Shafer formalism. Namely, we show that this average number of questions can be obtained by solving a simple mathematical optimization problem. In principle this characteristic is not always sufficient to express the fact that sometimes we have more knowledge. For example, it has the same value if we have an event with two possible outcomes and nothing else is known, and if there is an additional knowledge that the probability of every outcome is 0.5. We'll show that from the practical viewpoint this is not a problem, because the difference between the necessary number of questions in both cases is practically negligible.

Design and implementation of expert decision system in Yellow River Irrigation

NASA Astrophysics Data System (ADS)

Fuping, Wang; Bingbing, Lei; Jie, Pan

2018-03-01

How to make full use of water resources in the Yellow River irrigation is a problem needed to be solved urgently. On account of the different irrigation strategies in various growth stages of wheat, this paper proposes a novel irrigation expert decision system basing on fuzzy control technique. According to the control experience, expert knowledge and MATLAB simulation optimization, we obtain the irrigation fuzzy control table stored in the computer memory. The controlling irrigation is accomplished by reading the data from fuzzy control table. The experimental results show that the expert system can be used in the production of wheat to achieve timely and appropriate irrigation, and ensure that wheat growth cycle is always in the best growth environment.

ICADS: A cooperative decision making model with CLIPS experts

NASA Technical Reports Server (NTRS)

Pohl, Jens; Myers, Leonard

1991-01-01

A cooperative decision making model is described which is comprised of six concurrently executing domain experts coordinated by a blackboard control expert. The focus application field is architectural design, and the domain experts represent consultants in the area of daylighting, noise control, structural support, cost estimating, space planning, and climate responsiveness. Both the domain experts and the blackboard were implemented as production systems, using an enhanced version of the basic CLIPS package. Acting in unison as an Expert Design Advisor, the domain and control experts react to the evolving design solution progressively developed by the user in a 2-D CAD drawing environment. A Geometry Interpreter maps each drawing action taken by the user to real world objects, such as spaces, walls, windows, and doors. These objects, endowed with geometric and nongeometric attributes, are stored as frames in a semantic network. Object descriptions are derived partly from the geometry of the drawing environment and partly from knowledge bases containing prototypical, generalized information about the building type and site conditions under consideration.

Knowledge and Social Relationships in Teacher Education.

ERIC Educational Resources Information Center

Bell, Adrian

1981-01-01

Based on Max Weber's three ideal types of education (charismatic education, education of the cultivated man, and specialized expert training), the article analyzes interpersonal interaction and students' educational identities in teacher training institutions in Britain. (DB)

Development of the Paris definition of early Crohn's disease for disease-modification trials: results of an international expert opinion process.

PubMed

Peyrin-Biroulet, Laurent; Billioud, Vincent; D'Haens, Geert; Panaccione, Remo; Feagan, Brian; Panés, Julian; Danese, Silvio; Schreiber, Stefan; Ogata, Haruhiko; Hibi, Toshifumi; Higgins, Peter D R; Beaugerie, Laurent; Chowers, Yehuda; Louis, Edouard; Steinwurz, Flávio; Reinisch, Walter; Rutgeerts, Paul; Colombel, Jean-Frédéric; Travis, Simon; Sandborn, William J

2012-12-01

We report the findings and outputs of an international expert opinion process to develop a definition of early Crohn's disease (CD) that could be used in future disease-modification trials. Nineteen experts on inflammatory bowel diseases held an international expert opinion meeting to discuss and agree on a definition for early CD to be used in disease-modification trials. The process included literature searches for the relevant basic-science and clinical evidence. A published preliminary definition of early CD was used as the basis for development of a proposed definition that was discussed at the expert opinion meeting. The participants then derived a final definition, based on best current knowledge, that it is hoped will be of practical use in disease-modification trials in CD.

Validation and verification of expert systems

NASA Technical Reports Server (NTRS)

Gilstrap, Lewey

1991-01-01

Validation and verification (V&V) are procedures used to evaluate system structure or behavior with respect to a set of requirements. Although expert systems are often developed as a series of prototypes without requirements, it is not possible to perform V&V on any system for which requirements have not been prepared. In addition, there are special problems associated with the evaluation of expert systems that do not arise in the evaluation of conventional systems, such as verification of the completeness and accuracy of the knowledge base. The criticality of most NASA missions make it important to be able to certify the performance of the expert systems used to support these mission. Recommendations for the most appropriate method for integrating V&V into the Expert System Development Methodology (ESDM) and suggestions for the most suitable approaches for each stage of ESDM development are presented.

Expert system verification concerns in an operations environment

NASA Technical Reports Server (NTRS)

Goodwin, Mary Ann; Robertson, Charles C.

1987-01-01

The Space Shuttle community is currently developing a number of knowledge-based tools, primarily expert systems, to support Space Shuttle operations. It is proposed that anticipating and responding to the requirements of the operations environment will contribute to a rapid and smooth transition of expert systems from development to operations, and that the requirements for verification are critical to this transition. The paper identifies the requirements of expert systems to be used for flight planning and support and compares them to those of existing procedural software used for flight planning and support. It then explores software engineering concepts and methodology that can be used to satisfy these requirements, to aid the transition from development to operations and to support the operations environment during the lifetime of expert systems. Many of these are similar to those used for procedural hardware.

KAM (Knowledge Acquisition Module): A tool to simplify the knowledge acquisition process

NASA Technical Reports Server (NTRS)

Gettig, Gary A.

1988-01-01

Analysts, knowledge engineers and information specialists are faced with increasing volumes of time-sensitive data in text form, either as free text or highly structured text records. Rapid access to the relevant data in these sources is essential. However, due to the volume and organization of the contents, and limitations of human memory and association, frequently: (1) important information is not located in time; (2) reams of irrelevant data are searched; and (3) interesting or critical associations are missed due to physical or temporal gaps involved in working with large files. The Knowledge Acquisition Module (KAM) is a microcomputer-based expert system designed to assist knowledge engineers, analysts, and other specialists in extracting useful knowledge from large volumes of digitized text and text-based files. KAM formulates non-explicit, ambiguous, or vague relations, rules, and facts into a manageable and consistent formal code. A library of system rules or heuristics is maintained to control the extraction of rules, relations, assertions, and other patterns from the text. These heuristics can be added, deleted or customized by the user. The user can further control the extraction process with optional topic specifications. This allows the user to cluster extracts based on specific topics. Because KAM formalizes diverse knowledge, it can be used by a variety of expert systems and automated reasoning applications. KAM can also perform important roles in computer-assisted training and skill development. Current research efforts include the applicability of neural networks to aid in the extraction process and the conversion of these extracts into standard formats.

Qpais: A Web-Based Expert System for Assistedidentification of Quarantine Stored Insect Pests

NASA Astrophysics Data System (ADS)

Huang, Han; Rajotte, Edwin G.; Li, Zhihong; Chen, Ke; Zhang, Shengfang

Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.

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…

[Recommendations in neonatal resuscitation].

PubMed

2004-01-01

The recommendations for neonatal resuscitation are not always based on sufficient scientific evidence and thus expert consensus based on current research, knowledge, and experience are useful for formulating practical protocols that are easy to follow. The latest recommendations, in 2000, modified previously published recommendations and are included in the present text.

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

Research and development for Onboard Navigation (ONAV) ground based expert/trainer system: ONAV entry expert system code

NASA Technical Reports Server (NTRS)

Bochsler, Daniel C.

1988-01-01

A complete listing is given of the expert system rules for the Entry phase of the Onboard Navigation (ONAV) Ground Based Expert Trainer System for aircraft/space shuttle navigation. These source listings appear in the same format as utilized and required by the C Language Integrated Production System (CLIPS) expert system shell which is the basis for the ONAV entry system. A schematic overview is given of how the rules are organized. These groups result from a partitioning of the rules according to the overall function which a given set of rules performs. This partitioning was established and maintained according to that established in the knowledge specification document. In addition, four other groups of rules are specified. The four groups (control flow, operator inputs, output management, and data tables) perform functions that affect all the other functional rule groups. As the name implies, control flow ensures that the rule groups are executed in the order required for proper operation; operator input rules control the introduction into the CLIPS fact base of various kinds of data required by the expert system; output management rules control the updating of the ONAV expert system user display screen during execution of the system; and data tables are static information utilized by many different rule sets gathered in one convenient place.

Hemispheric Activation Differences in Novice and Expert Clinicians during Clinical Decision Making

ERIC Educational Resources Information Center

Hruska, Pam; Hecker, Kent G.; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav

2016-01-01

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…

The Advantages of Abstract Control Knowledge in Expert System Design. Technical Report #7.

ERIC Educational Resources Information Center

Clancey, William J.

This paper argues that an important design principle for building expert systems is to represent all control knowledge abstractly and separately from the domain knowledge upon which it operates. Abstract control knowledge is defined as the specifications of when and how a program is to carry out its operations, such as pursuing a goal, focusing,…

Improving conservation outcomes with insights from local experts and bureaucracies.

PubMed

Haenn, Nora; Schmook, Birgit; Reyes, Yol; Calmé, Sophie

2014-08-01

We describe conservation built on local expertise such that it constitutes a hybrid form of traditional and bureaucratic knowledge. Researchers regularly ask how local knowledge might be applied to programs linked to protected areas. By examining the production of conservation knowledge in southern Mexico, we assert local expertise is already central to conservation. However, bureaucratic norms and social identity differences between lay experts and conservation practitioners prevent the public valuing of traditional knowledge. We make this point by contrasting 2 examples. The first is a master's thesis survey of local experts regarding the biology of the King Vulture (Sarcoramphus papa) in which data collection took place in communities adjacent to the Calakmul Biosphere Reserve. The second is a workshop sponsored by the same reserve that instructed farmers on how to monitor endangered species, including the King Vulture. In both examples, conservation knowledge would not have existed without traditional knowledge. In both examples, this traditional knowledge is absent from scientific reporting. On the basis of these findings, we suggest conservation outcomes may be improved by recognizing the knowledge contributions local experts already make to conservation programming. © 2014 Society for Conservation Biology.

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Evidence based library and information practice in Australia: defining skills and knowledge.

PubMed

Lewis, Suzanne

2011-06-01

This guest feature from Suzanne Lewis, a long-time advocate of evidence based library and information practice (EBLIP) in Australia, discusses a current trend within the movement that focuses on the skills, knowledge and competencies of health librarians. In particular, the feature describes three specific Australia-based research projects, on expert searching, indigenous health and future skills requirements for the health library workforce respectively, that exemplify this trend. These projects illustrate how the evidence base can be strengthened around the skills and knowledge required to deliver services that continue to meet the changing needs of health library and information users. © 2011 The authors. Health Information and Libraries Journal © 2011 Health Libraries Group.

Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

2016-05-01

Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert elicitation methodology is developed and applied to the real-world test case in order to provide a road map for the use of fuzzy Bayesian inference in groundwater modeling applications.

Common sense of experts: Social representations of justice amongst professionals.

PubMed

Rochira, Alessia

2014-09-01

The dialectics between different modes of knowledge is at the very core of social sciences. In particular, the theory of social representations looks at expert and lay modes as they were not peculiar of specific domains but rather as they were mutually interdependent. Based on the conceptual distinction between reified and consensual universes, this article explores the interplay between these two sources of knowledge through the analysis of the social representations of justice produced by justice professionals. In particular, the exploration of the social representations of justice amongst experts offers intriguing clues to overtake the idea that the lay understanding of justice is somehow opposed to the expert viewpoint and to accept the polyphasic understanding of this complex object. The article reports the findings of a qualitative investigation of the social representations of justice amongst professionals. The staff members of the Youth Social Services (YSS) and the Juvenile Classification Home and Residential Community (JCHRC) were interviewed, and transcriptions were content analysed. The findings indicated that professionals generate multiple theories of justice with each presenting a particular articulation of the basic interplay between expert and lay viewpoints. Most important, findings indicate that the context of everyday working practice has a significant symbolic valence that goes beyond the boundaries of the reified context of institutional justice system.

Basic-level categorization of intermediate complexity fragments reveals top-down effects of expertise in visual perception.

PubMed

Harel, Assaf; Ullman, Shimon; Harari, Danny; Bentin, Shlomo

2011-07-28

Visual expertise is usually defined as the superior ability to distinguish between exemplars of a homogeneous category. Here, we ask how real-world expertise manifests at basic-level categorization and assess the contribution of stimulus-driven and top-down knowledge-based factors to this manifestation. Car experts and novices categorized computer-selected image fragments of cars, airplanes, and faces. Within each category, the fragments varied in their mutual information (MI), an objective quantifiable measure of feature diagnosticity. Categorization of face and airplane fragments was similar within and between groups, showing better performance with increasing MI levels. Novices categorized car fragments more slowly than face and airplane fragments, while experts categorized car fragments as fast as face and airplane fragments. The experts' advantage with car fragments was similar across MI levels, with similar functions relating RT with MI level for both groups. Accuracy was equal between groups for cars as well as faces and airplanes, but experts' response criteria were biased toward cars. These findings suggest that expertise does not entail only specific perceptual strategies. Rather, at the basic level, expertise manifests as a general processing advantage arguably involving application of top-down mechanisms, such as knowledge and attention, which helps experts to distinguish between object categories. © ARVO

Development Of Knowledge Systems For Trouble Shooting Complex Production Machinery

NASA Astrophysics Data System (ADS)

Sanford, Richard L.; Novak, Thomas; Meigs, James R.

1987-05-01

This paper discusses the use of knowledge base system software for microcomputers to aid repairmen in diagnosing electrical failures in complex mining machinery. The knowledge base is constructed to allow the user to input initial symptoms of the failed machine, and the most probable cause of failure is traced through the knowledge base, with the software requesting additional information such as voltage or resistance measurements as needed. Although the case study presented is for an underground mining machine, results have application to any industry using complex machinery. Two commercial expert-system development tools (M1 TM and Insight 2+TM) and an Al language (Turbo PrologTM) are discussed with emphasis on ease of application and suitability for this study.

Knowledge acquisition and representation for the Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS)

NASA Technical Reports Server (NTRS)

Seamster, Thomas L.; Eike, David R.; Ames, Troy J.

1990-01-01

This presentation concentrates on knowledge acquisition and its application to the development of an expert module and a user interface for an Intelligent Tutoring System (ITS). The Systems Test and Operations Language (STOL) ITS is being developed to assist NASA control center personnel in learning a command and control language as it is used in mission operations rooms. The objective of the tutor is to impart knowledge and skills that will permit the trainee to solve command and control problems in the same way that the STOL expert solves those problems. The STOL ITS will achieve this object by representing the solution space in such a way that the trainee can visualize the intermediate steps, and by having the expert module production rules parallel the STOL expert's knowledge structures.

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development

PubMed Central

Alvarez, Stéphanie; Timler, Carl J.; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A.; Groot, Jeroen C. J.

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia’s Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies. PMID:29763422

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development.

PubMed

Alvarez, Stéphanie; Timler, Carl J; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A; Groot, Jeroen C J

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.

Measuring practical knowledge about balanced meals: development and validation of the brief PKB-7 scale.

PubMed

Mötteli, S; Barbey, J; Keller, C; Bucher, T; Siegrist, M

2016-04-01

As a high-quality diet is associated with a lower risk for several diseases and all-cause mortality, current nutrition education tools provide people with information regarding how to build a healthy and a balanced meal. To assess this basic nutrition knowledge, the research aim was to develop and validate a brief scale to measure the Practical Knowledge about Balanced meals (PKB-7). A pool of 25 items was pretested with experts and laypeople before being tested on a random sample in Switzerland (n=517). For item selection, a Rasch model analysis was applied. The validity and reliability of the new scale were assessed by three additional studies including laypeople (n=597; n=145) and nutrition experts (n=59). The final scale consists of seven multiple-choice items, which met the assumptions of the Rasch model. The validity of the new scale was shown by several aspects: the Rasch model was replicated in a second study, and nutrition experts achieved significantly higher scores than laypeople (t(148)=20.27, P<0.001, d=1.78). In addition, the PKB-7 scale was correlated with other nutrition-related constructs and associated with reported vegetable consumption. Test-retest reliability (r=0.68, P<0.001) was acceptable. The PKB-7 scale is a reliable and a valid Rasch-based instrument in Swiss citizens aged between 18 and 80 years for measuring the practical knowledge about balanced meals based on current dietary guidelines. This brief and easy-to-use scale is intended for application in both research and practice.

[Pitfalls in 'orthodox knowledge'].

PubMed

Taneda, Hiroyuki

2003-03-01

Within contemporary society both 'pseudoscience' and 'pseudomedicine' can be found. Such knowledge is seen as incorrect, wrong or irrational. I call them 'unorthodox (uncertain) knowledge'. Conversely, 'orthodox knowledge'--for example, science, medicine, etc.--is seen as correct, right or rational. Some people believe 'unorthodox (uncertain) knowledge'. Experts castigate such people from the standpoint that they lack the basic understanding of 'orthodox knowledge'. That is, experts see the ordinary lay person as subjective, ignorant or irrational (whereas they see themselves as objective, analytical, prudent or rational). But are people ignorant or irrational? The aim of this paper is to examine this question in terms of analyzing the interplay among the characteristics of 'orthodox knowledge', 'unorthodox (uncertain) knowledge' and the nature of people's concerns. Thus, this paper explains that people develop certain situated understandings of 'orthodox knowledge' and/or 'unorthodox (uncertain) knowledge' through their intensive experiences. Also, this paper suggests that people need to rethink or reflect on the good institutions which mediate between people and experts.

Rationales of a Shift towards Knowledge Economy in Jordan from the Viewpoint of Educational Experts and Relationship with Some Variables

ERIC Educational Resources Information Center

Al Zboon, Mohammad Saleem; Al Ahmad, Suliman Diab Ali; Al Zboon, Saleem Odeh

2009-01-01

The purpose of the present study was to identify rationales underlying a shift towards knowledge economy in education as perceived by the educational experts in Jordan and relationship with some variables. The random stratum sample (n = 90) consisted of educational experts representing faculty members in the Jordanian universities and top leaders…

An expert system for diagnosing environmentally induced spacecraft anomalies

NASA Technical Reports Server (NTRS)

Rolincik, Mark; Lauriente, Michael; Koons, Harry C.; Gorney, David

1992-01-01

A new rule-based, machine independent analytical tool was designed for diagnosing spacecraft anomalies using an expert system. Expert systems provide an effective method for saving knowledge, allow computers to sift through large amounts of data pinpointing significant parts, and most importantly, use heuristics in addition to algorithms, which allow approximate reasoning and inference and the ability to attack problems not rigidly defined. The knowledge base consists of over two-hundred (200) rules and provides links to historical and environmental databases. The environmental causes considered are bulk charging, single event upsets (SEU), surface charging, and total radiation dose. The system's driver translates forward chaining rules into a backward chaining sequence, prompting the user for information pertinent to the causes considered. The use of heuristics frees the user from searching through large amounts of irrelevant information and allows the user to input partial information (varying degrees of confidence in an answer) or 'unknown' to any question. The modularity of the expert system allows for easy updates and modifications. It not only provides scientists with needed risk analysis and confidence not found in algorithmic programs, but is also an effective learning tool, and the window implementation makes it very easy to use. The system currently runs on a Micro VAX II at Goddard Space Flight Center (GSFC). The inference engine used is NASA's C Language Integrated Production System (CLIPS).

MVP-CA Methodology for the Expert System Advocate's Advisor (ESAA)

DOT National Transportation Integrated Search

1997-11-01

The Multi-Viewpoint Clustering Analysis (MVP-CA) tool is a semi-automated tool to provide a valuable aid for comprehension, verification, validation, maintenance, integration, and evolution of complex knowledge-based software systems. In this report,...

The effect of expert knowledge on medical search: medical experts have specialized abilities for detecting serious lesions.

PubMed

Nakashima, Ryoichi; Watanabe, Chisaki; Maeda, Eriko; Yoshikawa, Takeharu; Matsuda, Izuru; Miki, Soichiro; Yokosawa, Kazuhiko

2015-09-01

How does domain-specific knowledge influence the experts' performance in their domain of expertise? Specifically, can visual search experts find, with uniform efficiency, any type of target in their domain of expertise? We examined whether acquired knowledge of target importance influences an expert's visual search performance. In some professional searches (e.g., medical screenings), certain targets are rare; one aim of this study was to examine the extent to which experts miss such targets in their searches. In one experiment, radiologists (medical experts) engaged in a medical lesion search task in which both the importance (i.e., seriousness/gravity) and the prevalence of targets varied. Results showed decreased target detection rates in the low prevalence conditions (i.e., the prevalence effect). Also, experts were better at detecting important (versus unimportant) lesions. Results of an experiment using novices ruled out the possibility that decreased performance with unimportant targets was due to low target noticeability/visibility. Overall, the findings suggest that radiologists do not have a generalized ability to detect any type of lesion; instead, they have acquired a specialized ability to detect only those important lesions relevant for effective medical practices.

A Real-Time Knowledge Based Expert System For Diagnostic Problem Solving

NASA Astrophysics Data System (ADS)

Esteva, Juan C.; Reynolds, Robert G.

1986-03-01

This paper is a preliminary report of a real-time expert system which is concerned with the detection and diagnosis of electrical deviations in on-board vehicle-based electrical systems. The target systems are being tested at radio frequencies to evaluate their capability to be operated at designed levels of efficiency in an electromagnetic environment. The measurement of this capability is known as ElectroMagnetic Compatibility (EMC). The Intelligent Deviation Diagnosis (IDD) system consists of two basic modules the Automatic Data Acquisition Module (ADAM) and the Diagnosis System (DS). In this paper only the diagnosis system is described.

An operation support expert system based on on-line dynamics simulation and fuzzy reasoning for startup schedule optimization in fossil power plants

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

Matsumoto, H.; Eki, Y.; Kaji, A.

1993-12-01

An expert system which can support operators of fossil power plants in creating the optimum startup schedule and executing it accurately is described. The optimum turbine speed-up and load-up pattern is obtained through an iterative manner which is based on fuzzy resonating using quantitative calculations as plant dynamics models and qualitative knowledge as schedule optimization rules with fuzziness. The rules represent relationships between stress margins and modification rates of the schedule parameters. Simulations analysis proves that the system provides quick and accurate plant startups.