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.

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.

Combining factual and heuristic knowledge in knowledge acquisition

NASA Technical Reports Server (NTRS)

Gomez, Fernando; Hull, Richard; Karr, Clark; Hosken, Bruce; Verhagen, William

1992-01-01

A knowledge acquisition technique that combines heuristic and factual knowledge represented as two hierarchies is described. These ideas were applied to the construction of a knowledge acquisition interface to the Expert System Analyst (OPERA). The goal of OPERA is to improve the operations support of the computer network in the space shuttle launch processing system. The knowledge acquisition bottleneck lies in gathering knowledge from human experts and transferring it to OPERA. OPERA's knowledge acquisition problem is approached as a classification problem-solving task, combining this approach with the use of factual knowledge about the domain. The interface was implemented in a Symbolics workstation making heavy use of windows, pull-down menus, and other user-friendly devices.

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.

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.

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

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.

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.

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)

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.

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.

SNIFFER: a System that Understands Bugs.

DTIC Science & Technology

1981-06-01

NUMBER •) A~ ATHO... S CONTRACT OR GRANT NUMBER(s) I Daniel G..Shapiro ’ NO014-80-C-0505 9. PERFORMING ORGANIZATION NAME AND ADDRESS .|O. PROGRAM...debugginoi knowledge in Sniffer is organized as a collectioni of indcpendent experts which understand spcciftc errors. Each expert fuinctions by...be organized , as opposed to representing them as differences from an established norm. This mechanism makes it possible for individual bug experts to

Experiential knowledge of expert coaches can help identify informational constraints on performance of dynamic interceptive actions.

PubMed

Greenwood, Daniel; Davids, Keith; Renshaw, Ian

2014-01-01

Coordination of dynamic interceptive movements is predicated on cyclical relations between an individual's actions and information sources from the performance environment. To identify dynamic informational constraints, which are interwoven with individual and task constraints, coaches' experiential knowledge provides a complementary source to support empirical understanding of performance in sport. In this study, 15 expert coaches from 3 sports (track and field, gymnastics and cricket) participated in a semi-structured interview process to identify potential informational constraints which they perceived to regulate action during run-up performance. Expert coaches' experiential knowledge revealed multiple information sources which may constrain performance adaptations in such locomotor pointing tasks. In addition to the locomotor pointing target, coaches' knowledge highlighted two other key informational constraints: vertical reference points located near the locomotor pointing target and a check mark located prior to the locomotor pointing target. This study highlights opportunities for broadening the understanding of perception and action coupling processes, and the identified information sources warrant further empirical investigation as potential constraints on athletic performance. Integration of experiential knowledge of expert coaches with theoretically driven empirical knowledge represents a promising avenue to drive future applied science research and pedagogical practice.

Keeping an Eye on Learning: Differences between Expert and Novice Teachers' Representations of Classroom Management Events

ERIC Educational Resources Information Center

Wolff, Charlotte E.; van den Bogert, Niek; Jarodzka, Halszka; Boshuizen, Henny P. A.

2015-01-01

Classroom management represents an important skill and knowledge set for achieving student learning gains, but poses a considerable challenge for beginning teachers. Understanding how teachers' cognition and conceptualizations differ between experts and novices is useful for enhancing beginning teachers' expertise development. We created a coding…

Guide to Experts in Forestry and Natural Resources

Treesearch

Northeastern Research Station

2000-01-01

To help you gain access to what the Forest Service knows, we?ve compiled a list of experts who work for the Northeastern Research Station. They represent a diversity of scientific disciplines and knowledge?from forestry to sociology, from plant pathology to meteorology, from genetic engineering to economics. Together with other scientists, technicians and...

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

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.

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

PubMed

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

2014-09-01

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

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…

Inferring heuristic classification hierarchies from natural language input

NASA Technical Reports Server (NTRS)

Hull, Richard; Gomez, Fernando

1993-01-01

A methodology for inferring hierarchies representing heuristic knowledge about the check out, control, and monitoring sub-system (CCMS) of the space shuttle launch processing system from natural language input is explained. Our method identifies failures explicitly and implicitly described in natural language by domain experts and uses those descriptions to recommend classifications for inclusion in the experts' heuristic hierarchies.

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.

Explainable expert systems: A research program in information processing

NASA Technical Reports Server (NTRS)

Paris, Cecile L.

1993-01-01

Our work in Explainable Expert Systems (EES) had two goals: to extend and enhance the range of explanations that expert systems can offer, and to ease their maintenance and evolution. As suggested in our proposal, these goals are complementary because they place similar demands on the underlying architecture of the expert system: they both require the knowledge contained in a system to be explicitly represented, in a high-level declarative language and in a modular fashion. With these two goals in mind, the Explainable Expert Systems (EES) framework was designed to remedy limitations to explainability and evolvability that stem from related fundamental flaws in the underlying architecture of current expert systems.

Knowledge Representation and Self-Regulatory Experiences of Expert and Novice Certified Athletic Trainers in College and University Settings

ERIC Educational Resources Information Center

Gardin, Fredrick Anthony

2009-01-01

The purpose of this study was to describe how male, collegiate, certified athletic trainers (AT's) represent knowledge during 5 injury evaluation scenarios. A second purpose of the study was to identify what self-regulatory behaviors participants engaged in to improve or maintain their skills. Knowledge representation was studied as cue selection…

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

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.

Profiles of Selected Promising Professional Development Initiatives.

ERIC Educational Resources Information Center

Cohen, Carol; Gerber, Peter; Handley, Claire; Kronley, Robert; Parry, Megan

In 2000, the Finance Project received a planning grant to launch a new initiative on financing professional development in education. This report represents efforts to identify and develop a database on promising new approaches to professional development in education, profiling 16 initiatives recommended by knowledge experts and representing a…

Representing and Inferring Visual Perceptual Skills in Dermatological Image Understanding

ERIC Educational Resources Information Center

Li, Rui

2013-01-01

Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. Eliciting and representing their visual strategies and some aspects of domain knowledge will benefit a wide range of studies and applications. For example, image understanding may be…

Virtual reality training improves students' knowledge structures of medical concepts.

PubMed

Stevens, Susan M; Goldsmith, Timothy E; Summers, Kenneth L; Sherstyuk, Andrei; Kihmm, Kathleen; Holten, James R; Davis, Christopher; Speitel, Daniel; Maris, Christina; Stewart, Randall; Wilks, David; Saland, Linda; Wax, Diane; Panaiotis; Saiki, Stanley; Alverson, Dale; Caudell, Thomas P

2005-01-01

Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.

EDNA: Expert fault digraph analysis using CLIPS

NASA Technical Reports Server (NTRS)

Dixit, Vishweshwar V.

1990-01-01

Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

How to Fully Represent Expert Information about Imprecise Properties in a Computer System – Random Sets, Fuzzy Sets, and Beyond: An Overview

PubMed Central

Nguyen, Hung T.; Kreinovich, Vladik

2014-01-01

To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-defined) properties which are either true or false for each object: we simply store the corresponding “true” and “false” values in the computer. The challenge is how to store information about imprecise properties. In this paper, we overview different ways to fully store the expert information about imprecise properties. We show that in the simplest case, when the only source of imprecision is disagreement between different experts, a natural way to store all the expert information is to use random sets; we also show how fuzzy sets naturally appear in such random-set representation. We then show how the random-set representation can be extended to the general (“fuzzy”) case when, in addition to disagreements, experts are also unsure whether some objects satisfy certain properties or not. PMID:25386045

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.

Expert nurses' clinical reasoning under uncertainty: representation, structure, and process.

PubMed Central

Fonteyn, M. E.; Grobe, S. J.

1992-01-01

How do expert nurses reason when planning care and making clinical decisions for a patient who is at risk, and whose outcome is uncertain? In this study, a case study involving a critically ill elderly woman whose condition deteriorated over time, was presented in segments to ten expert critical care nurses. Think aloud method was used to elicit knowledge from these experts to provide conceptual information about their knowledge and to reveal their reasoning processes and problem-solving strategies. The verbatim transcripts were then analyzed using a systematic three-step method that makes analysis easier and adds creditability to study findings by providing a means of retracing and explaining analysis results. Findings revealed information about how patient problems were represented during reasoning, the manner in which experts subjects structured their plan of care, and the reasoning processes and heuristics they used to formulate solutions for resolving the patient's problems and preventing deterioration in the patient's condition. PMID:1482907

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.

Bayesian belief networks: applications in ecology and natural resource management.

Treesearch

R.K. McCann; B.G. Marcot; R. Ellis

2006-01-01

We review the use of Bayesian belief networks (BBNs) in natural resource management and ecology. We suggest that BBNs are useful tools for representing expert knowledge of a system, evaluating potential effects of alternative management decisions, and communicating to nonexperts about resource decision issues. BBNs can be used effectively to represent uncertainty in...

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.

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-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.

A Knowledge Engineering Approach to Analysis and Evaluation of Construction Schedules

DTIC Science & Technology

1990-02-01

software engineering discipline focusing on constructing KBSs. It is an incremental and cyclical process that requires the interaction of a domain expert(s...the U.S. Army Coips of Engineers ; and (3) the project management software developer, represented by Pinnell Engineering , Inc. Since the primary...the programming skills necessary to convert the raw knowledge intn a form a computer can understand. knowledge engineering : The software engineering

PSYCHE: An Object-Oriented Approach to Simulating Medical Education

PubMed Central

Mullen, Jamie A.

1990-01-01

Traditional approaches to computer-assisted instruction (CAI) do not provide realistic simulations of medical education, in part because they do not utilize heterogeneous knowledge bases for their source of domain knowledge. PSYCHE, a CAI program designed to teach hypothetico-deductive psychiatric decision-making to medical students, uses an object-oriented implementation of an intelligent tutoring system (ITS) to model the student, domain expert, and tutor. It models the transactions between the participants in complex transaction chains, and uses heterogeneous knowledge bases to represent both domain and procedural knowledge in clinical medicine. This object-oriented approach is a flexible and dynamic approach to modeling, and represents a potentially valuable tool for the investigation of medical education and decision-making.

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 Study to Determine the Contribution Made by Concept Maps to a Computer Architecture and Organization Course

ERIC Educational Resources Information Center

Aydogan, Tuncay; Ergun, Serap

2016-01-01

Concept mapping is a method of graphical learning that can be beneficial as a study method for concept linking and organization. Concept maps, which provide an elegant, easily understood representation of an expert's domain knowledge, are tools for organizing and representing knowledge. These tools have been used in educational environments to…

Development of a Design Supporting System for Nano-Materials based on a Framework for Integrated Knowledge of Functioning-Manufacturing Process

NASA Astrophysics Data System (ADS)

Tarumi, Shinya; Kozaki, Kouji; Kitamura, Yoshinobu; Mizoguchi, Riichiro

In the recent materials research, much work aims at realization of ``functional materials'' by changing structure and/or manufacturing process with nanotechnology. However, knowledge about the relationship among function, structure and manufacturing process is not well organized. So, material designers have to consider a lot of things at the same time. It would be very helpful for them to support their design process by a computer system. In this article, we discuss a conceptual design supporting system for nano-materials. Firstly, we consider a framework for representing functional structures and manufacturing processes of nano-materials with relationships among them. We expand our former framework for representing functional knowledge based on our investigation through discussion with experts of nano-materials. The extended framework has two features: 1) it represents functional structures and manufacturing processes comprehensively, 2) it expresses parameters of function and ways with their dependencies because they are important for material design. Next, we describe a conceptual design support system we developed based on the framework with its functionalities. Lastly, we evaluate the utility of our system in terms of functionality for design supports. For this purpose, we tried to represent two real examples of material design. And then we did an evaluation experiment on conceptual design of material using our system with the collaboration of domain experts.

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.

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.

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.

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.

Public discourse on mental health and psychiatry: Representations in Swedish newspapers.

PubMed

Ohlsson, Robert

2018-05-01

Mass media plays a central role in shaping public discourse on health and illness. In order to examine media representations of mental health and expert knowledge in this field, two major Swedish daily newspapers from the year 2009 were qualitatively analysed. Drawing on the theory of social representations, the analysis focused on how issues concerning mental health and different perspectives are represented. The results show how the concept of mental illness is used in different and often taken-for-granted ways and how the distinction between normal and pathological is a central underlying question. Laypersons' perspectives are supplemented by views of professionals in the newspapers, where signs of confidence and dependence on expert knowledge are juxtaposed with critique and expressions of distrust. The newspaper discourse thus has salient argumentative features and the way that conflicts are made explicit and issues concerning authoritative knowledge are addressed indicates ambivalence towards the authoritative role of expert knowledge concerning mental health. In this way, the newspapers provide a complex epistemic context for everyday sense-making that can be assumed to have implications for relations between laypersons and professionals in the field of mental health.

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.

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.

Maritime Threat Detection using Plan Recognition

DTIC Science & Technology

2012-11-01

logic with a probabilistic interpretation to represent expert domain knowledge [13]. We used Alchemy [14] to implement MLN-BR. It interfaces with the...Domingos, P., & Lowd, D. (2009). Markov logic: An interface layer for AI. Morgan & Claypool. [14] Alchemy (2011). Alchemy ─ Open source AI. [http

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.

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.

Microcomputer-Based Intelligent Tutoring Systems: An Assessment.

ERIC Educational Resources Information Center

Schaffer, John William

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

Register of hydrogen technology experts

NASA Technical Reports Server (NTRS)

Ludtke, P. R.

1975-01-01

This register presents the names of approximately 235 individuals who are considered experts, or very knowledgeable, in various fields of technology related to hydrogen. Approximately 90 organizations are represented. Each person is listed by organizational affiliation, address, and principal area of expertise. The criteria for selection of names for the register are extensive experience in a given field of work, participation in or supervision of relevant research programs, contributions to the literature, or being recognized as an expert in a particular field. The purpose of the register is to present, in easy form, sources of dependable information regarding highly technical areas of hydrogen technology, with particular emphasis on safety. The register includes two indexes: an alphabetical listing of the experts and an alphabetical listing of the organizations with which they are affiliated.

Representing Mutually Exclusive Knowledge in a Property Hierarchy for a Reasoning System in Clinical Gynecology

PubMed Central

Small, Steven L.; Muechler, Eberhard K.

1985-01-01

The education and practice of clinical medicine can benefit significantly from the use of computational assistants. This article describes the development of a prototype system called SURGES (Strong/University of Rochester Gynecological Expert System) for representing medical knowledge and then applying this knowledge to suggest diagnostic procedures in medical gynecology. The paper focuses on the representation technique of property inheritance, which facilitates the simple common sense reasoning required to enable execution of the more complex medical inferences. Such common sense can be viewed as a collection mundane inferences, which are the simple conclusions drawn from knowledge that an exclusive or (XOR) relation (i.e., mutual exclusion) holds among a number of facts. The paper discusses the use of a property hierarchy for this purpose and shows how it simplifies knowledge representation in medical artificial intelligence (AIM) computer systems.

Expert and non-expert knowledge in medical practice.

PubMed

Nordin, I

2000-01-01

One problematic aspect of the rationality of medical practice concerns the relation between expert knowledge and non-expert knowledge. In medical practice it is important to match medical knowledge with the self-knowledge of the individual patient. This paper tries to study the problem of such matching by describing a model for technological paradigms and comparing it with an ideal of technological rationality. The professionalised experts tend to base their decisions and actions mostly on medical knowledge while the rationality of medicine also involves just as important elements of the personal evaluation and knowledge of the patients. Since both types of knowledge are necessary for rational decisions, the gap between the expert and the non-expert has to be bridged in some way. A solution to the problem is suggested in terms of pluralism, with the patient as ultimate decision-maker.

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

Towards a General Scientific Reasoning Engine.

ERIC Educational Resources Information Center

Carbonell, Jaime G.; And Others

Expert reasoning in the natural sciences appears to make extensive use of a relatively small number of general principles and reasoning strategies, each associated with a larger number of more specific inference patterns. Using a dual declarative hierarchy to represent strategic and factual knowledge, a framework for a robust scientific reasoning…

An Expert Vision System for Autonomous Land Vehicle Road Following.

DTIC Science & Technology

1988-01-01

TR-138, Center for Automa- tioii Hesearch, University of Maryland, July 1985. ’Miinskyl Minsky , Marvin , "A Framework for Representing Knowledge", in...relationships, frames have been chosen to model objects , Minsky ]. A frame is a data structure containing a set of slots (or attributes) which en- capsulate

Semantically Enabling Knowledge Representation of Metamorphic Petrology Data

NASA Astrophysics Data System (ADS)

West, P.; Fox, P. A.; Spear, F. S.; Adali, S.; Nguyen, C.; Hallett, B. W.; Horkley, L. K.

2012-12-01

More and more metamorphic petrology data is being collected around the world, and is now being organized together into different virtual data portals by means of virtual organizations. For example, there is the virtual data portal Petrological Database (PetDB, http://www.petdb.org) of the Ocean Floor that is organizing scientific information about geochemical data of ocean floor igneous and metamorphic rocks; and also The Metamorphic Petrology Database (MetPetDB, http://metpetdb.rpi.edu) that is being created by a global community of metamorphic petrologists in collaboration with software engineers and data managers at Rensselaer Polytechnic Institute. The current focus is to provide the ability for scientists and researchers to register their data and search the databases for information regarding sample collections. What we present here is the next step in evolution of the MetPetDB portal, utilizing semantically enabled features such as discovery, data casting, faceted search, knowledge representation, and linked data as well as organizing information about the community and collaboration within the virtual community itself. We take the information that is currently represented in a relational database and make it available through web services, SPARQL endpoints, semantic and triple-stores where inferencing is enabled. We will be leveraging research that has taken place in virtual observatories, such as the Virtual Solar Terrestrial Observatory (VSTO) and the Biological and Chemical Oceanography Data Management Office (BCO-DMO); vocabulary work done in various communities such as Observations and Measurements (ISO 19156), FOAF (Friend of a Friend), Bibo (Bibliography Ontology), and domain specific ontologies; enabling provenance traces of samples and subsamples using the different provenance ontologies; and providing the much needed linking of data from the various research organizations into a common, collaborative virtual observatory. In addition to better representing and presenting the actual data, we also look to organize and represent the knowledge information and expertise behind the data. Domain experts hold a lot of knowledge in their minds, in their presentations and publications, and elsewhere. Not only is this a technical issue, this is also a social issue in that we need to be able to encourage the domain experts to share their knowledge in a way that can be searched and queried over. With this additional focus in MetPetDB the site can be used more efficiently by other domain experts, but can also be utilized by non-specialists as well in order to educate people of the importance of the work being done as well as enable future domain experts.

Circumpolar biodiversity monitoring program (CBMP): Coastal expert workshop meeting report

USGS Publications Warehouse

Anderson, Rebecca D.; McLennan, Donald; Thomson, Laura; Wegeberg, Susse; Pettersvik Arvnes, Maria; Sergienko, Liudmila; Behe, Carolina; Moss-Davies, Pitseolak; Fritz, Stacey; Christensen, Thomas K.; Price, Courtney

2016-01-01

The Coastal Expert Workshop, which took place in Ottawa, Canada from March 1 to 3, 2016, initiated the development of the Arctic Coastal Biodiversity Monitoring Plan (Coastal Plan). Meeting participants, including northern residents, representatives from industry, non-governmental organisations (NGOs), academia, and government regulators and agencies from across the circumpolar Arctic, discussed current biodiversity monitoring efforts, key issues facing biodiversity in Arctic coastal areas, and collectively identified monitoring indicators, or Focal Ecosystem Components (FECs). On February 29, the day before the workshop, a full day was allocated to Traditional Knowledge (TK) holders to meet and elucidate how this important knowledge can be included in the process of building the Coastal Plan and monitoring biodiversity in Arctic coastal areas, along with scientific data and variables. This document provides 1) background information about the Circumpolar Biodiversity Monitoring Programme and the Coastal Expert Monitoring Group, 2) overviews on workshop presentations and breakout sessions, and 3) details regarding outcomes of the workshop that will inform the drafting of the Coastal Plan.

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.

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.

Overview of MDX-A System for Medical Diagnosis

PubMed Central

Mittal, S.; Chandrasekaran, B.; Smith, J.

1979-01-01

We describe the design and performance of MDX, an experimental medical diagnosis system, which currently diagnoses in the syndrome called Cholestasis. The needed medical knowledge is represented in a scheme called conceptual structures, which can be viewed as a collection of conceptual experts interacting according to certain well-defined principles. MDX has three components: the diagnostic system, a patient data base and a radiology consultant. We describe these components, the inter-expert communication system and the query language used by these components. The system is illustrated by means of its performance on a real case.

Implementation of lung cancer CT screening in the Nordic countries.

PubMed

Pedersen, Jesper Holst; Sørensen, Jens Benn; Saghir, Zaigham; Fløtten, Øystein; Brustugun, Odd Terje; Ashraf, Haseem; Strand, Trond-Eirik; Friesland, Signe; Koyi, Hirsh; Ek, Lars; Nyrén, Sven; Bergman, Per; Jekunen, Antti; Nieminen, Eeva-Maija; Gudbjartsson, Tomas

2017-10-01

We review the current knowledge of CT screening for lung cancer and present an expert-based, joint protocol for the proper implementation of screening in the Nordic countries. Experts representing all the Nordic countries performed literature review and concensus for a joint protocol for lung cancer screening. Areas of concern and caution are presented and discussed. We suggest to perform CT screening pilot studies in the Nordic countries in order to gain experience and develop specific and safe protocols for the implementation of such a program.

Evolution of a research prototype expert system for endemic populations of mountain pine beetle in lodgepole pine forests

Treesearch

Dale L. Bartos; Kent B. Downing

1989-01-01

A knowledge acquisition program was written to aid in obtaining knowledge from the experts concerning endemic populations of mountain pine beetle in lodgepole pine forest. An application expert system is then automatically generated by the knowledge acquisition program that contains the codified base of expert knowledge. Data can then be entered into the expert system...

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.

Use of artificial intelligence in analytical systems for the clinical laboratory

PubMed Central

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

1995-01-01

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

Major Events Coordinated Security Solutions: The Application of the Project Management Body of Knowledge for Managing a Science and Technology Project

DTIC Science & Technology

2011-02-01

subject matter experts, to analysis of laboratory samples during V2010. Significance: The MECSS project produced more than 195 scientific reports...represents the sum of knowledge related to project management and includes best practises and techniques generally accepted by the project...2011-03 2.2.1 Science Town Science Town is the moniker for a multi-agency, mobile laboratory capability that brings together world

Diagnosis and sensor validation through knowledge of structure and function

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

1987-01-01

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Automatic programming of arc welding robots

NASA Astrophysics Data System (ADS)

Padmanabhan, Srikanth

Automatic programming of arc welding robots requires the geometric description of a part from a solid modeling system, expert weld process knowledge and the kinematic arrangement of the robot and positioner automatically. Current commercial solid models are incapable of storing explicitly product and process definitions of weld features. This work presents a paradigm to develop a computer-aided engineering environment that supports complete weld feature information in a solid model and to create an automatic programming system for robotic arc welding. In the first part, welding features are treated as properties or attributes of an object, features which are portions of the object surface--the topological boundary. The structure for representing the features and attributes is a graph called the Welding Attribute Graph (WAGRAPH). The method associates appropriate weld features to geometric primitives, adds welding attributes, and checks the validity of welding specifications. A systematic structure is provided to incorporate welding attributes and coordinate system information in a CSG tree. The specific implementation of this structure using a hybrid solid modeler (IDEAS) and an object-oriented programming paradigm is described. The second part provides a comprehensive methodology to acquire and represent weld process knowledge required for the proper selection of welding schedules. A methodology of knowledge acquisition using statistical methods is proposed. It is shown that these procedures did little to capture the private knowledge of experts (heuristics), but helped in determining general dependencies, and trends. A need was established for building the knowledge-based system using handbook knowledge and to allow the experts further to build the system. A methodology to check the consistency and validity for such knowledge addition is proposed. A mapping shell designed to transform the design features to application specific weld process schedules is described. A new approach using fixed path modified continuation methods is proposed in the final section to plan continuously the trajectory of weld seams in an integrated welding robot and positioner environment. The joint displacement, velocity, and acceleration histories all along the path as a function of the path parameter for the best possible welding condition are provided for the robot and the positioner to track various paths normally encountered in arc welding.

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.

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.

A Mixed-Response Intelligent Tutoring System Based on Learning from Demonstration

ERIC Educational Resources Information Center

Alvarez Xochihua, Omar

2012-01-01

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

Potential Uses of Bayesian Networks as Tools for Synthesis of Systematic Reviews of Complex Interventions

ERIC Educational Resources Information Center

Stewart, G. B.; Mengersen, K.; Meader, N.

2014-01-01

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention.…

MedRapid--medical community & business intelligence system.

PubMed

Finkeissen, E; Fuchs, H; Jakob, T; Wetter, T

2002-01-01

currently, it takes at least 6 months for researchers to communicate their results. This delay is caused (a) by partial lacks of machine support for both representation as well as communication and (b) by media breaks during the communication process. To make an integrated communication between researchers and practitioners possible, a general structure for medical content representation has been set up. The procedure for data entry and quality management has been generalized and implemented in a web-based authoring system. The MedRapid-system supports the medical experts in entering their knowledge into a database. Here, the level of detail is still below that of current medical guidelines representation. However, the symmetric structure for an area-wide medical knowledge representation is highly retrievable and thus can quickly be communicated into daily routine for the improvement of the treatment quality. In addition, other sources like journal articles and medical guidelines can be references within the MedRapid-system and thus be communicated into daily routine. The fundamental system for the representation of medical reference knowledge (from reference works/books) itself is not sufficient for the friction-less communication amongst medical staff. Rather, the process of (a) representing medical knowledge, (b) refereeing the represented knowledge, (c) communicating the represented knowledge, and (d) retrieving the represented knowledge has to be unified. MedRapid will soon support the whole process on one server system.

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.

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.

The use of mental models in chemical risk protection: developing a generic workplace methodology.

PubMed

Cox, Patrick; Niewöhmer, Jörg; Pidgeon, Nick; Gerrard, Simon; Fischhoff, Baruch; Riley, Donna

2003-04-01

We adopted a comparative approach to evaluate and extend a generic methodology to analyze the different sets of beliefs held about chemical hazards in the workplace. Our study mapped existing knowledge structures about the risks associated with the use of perchloroethylene and rosin-based solder flux in differing workplaces. "Influence diagrams" were used to represent beliefs held by chemical experts; "user models" were developed from data elicited from open-ended interviews with the workplace users of the chemicals. The juxtaposition of expert and user understandings of chemical risks enabled us to identify knowledge gaps and misunderstandings and to reinforce appropriate sets of safety beliefs and behavior relevant to chemical risk communications. By designing safety information to be more relevant to the workplace context of users, we believe that employers and employees may gain improved knowledge about chemical hazards in the workplace, such that better chemical risk management, self-protection, and informed decision making develop over time.

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.

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.

Explanation production by expert planners

NASA Technical Reports Server (NTRS)

Bridges, Susan; Jhannes, James D.

1988-01-01

Although the explanation capability of expert systems is usually listed as one of the distinguishing characteristics of these systems, the explanation facilities of most existing systems are quite primitive. Computer generated explanations are typically produced from canned text or by direct translation of the knowledge structures. Explanations produced in this manner bear little resemblance to those produced by humans for similar tasks. The focus of our research in explanation is the production of justifications for decisions by expert planning systems. An analysis of justifications written by people for planning tasks has been taken as the starting point. The purpose of this analysis is two-fold. First, analysis of the information content of the justifications will provide a basis for deciding what knowledge must be represented if human-like justifications are to be produced. Second, an analysis of the textual organization of the justifications will be used in the development of a mechanism for selecting and organizing the knowledge to be included in a computer-produced explanation. This paper describes a preliminary analysis done of justifications written by people for a planning task. It is clear that these justifications differ significantly from those that would be produced by an expert system by tracing the firing of production rules. The results from the text analysis have been used to develop an augmented phrase structured grammar (APSG) describing the organization of the justifications. The grammar was designed to provide a computationally feasible method for determining textual organization that will allow the necessary information to be communicated in a cohesive manner.

Will-to-Fight: Japan’s Imperial Institution and the U.S. Strategy to End World War II

DTIC Science & Technology

2012-05-17

Military Theory ........................................................................................................................... 6 Current U.S...simultaneously.6 Individual Mental Models or gestalt represent those deep-seated, personal, perhaps unconscious assumptions about the way the world works based...disciplines provide a theoretical framework for understanding the interplay of expert knowledge, goals, personal gestalt , contemporary thought, and

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

NASA Technical Reports Server (NTRS)

Liebowitz, J.

1986-01-01

The development of an expert system prototype for software functional requirement determination for NASA Goddard's Command Management System, as part of its process of transforming general requests into specific near-earth satellite commands, is described. The present knowledge base was formulated through interactions with domain experts, and was then linked to the existing Knowledge Engineering Systems (KES) expert system application generator. Steps in the knowledge-base development include problem-oriented attribute hierarchy development, knowledge management approach determination, and knowledge base encoding. The KES Parser and Inspector, in addition to backcasting and analogical mapping, were used to validate the expert system-derived requirements for one of the major functions of a spacecraft, the solar Maximum Mission. Knowledge refinement, evaluation, and implementation procedures of the expert system were then accomplished.

The Nature Index: a general framework for synthesizing knowledge on the state of biodiversity.

PubMed

Certain, Grégoire; Skarpaas, Olav; Bjerke, Jarle-Werner; Framstad, Erik; Lindholm, Markus; Nilsen, Jan-Erik; Norderhaug, Ann; Oug, Eivind; Pedersen, Hans-Christian; Schartau, Ann-Kristin; van der Meeren, Gro I; Aslaksen, Iulie; Engen, Steinar; Garnåsjordet, Per-Arild; Kvaløy, Pål; Lillegård, Magnar; Yoccoz, Nigel G; Nybø, Signe

2011-04-22

The magnitude and urgency of the biodiversity crisis is widely recognized within scientific and political organizations. However, a lack of integrated measures for biodiversity has greatly constrained the national and international response to the biodiversity crisis. Thus, integrated biodiversity indexes will greatly facilitate information transfer from science toward other areas of human society. The Nature Index framework samples scientific information on biodiversity from a variety of sources, synthesizes this information, and then transmits it in a simplified form to environmental managers, policymakers, and the public. The Nature Index optimizes information use by incorporating expert judgment, monitoring-based estimates, and model-based estimates. The index relies on a network of scientific experts, each of whom is responsible for one or more biodiversity indicators. The resulting set of indicators is supposed to represent the best available knowledge on the state of biodiversity and ecosystems in any given area. The value of each indicator is scaled relative to a reference state, i.e., a predicted value assessed by each expert for a hypothetical undisturbed or sustainably managed ecosystem. Scaled indicator values can be aggregated or disaggregated over different axes representing spatiotemporal dimensions or thematic groups. A range of scaling models can be applied to allow for different ways of interpreting the reference states, e.g., optimal situations or minimum sustainable levels. Statistical testing for differences in space or time can be implemented using Monte-Carlo simulations. This study presents the Nature Index framework and details its implementation in Norway. The results suggest that the framework is a functional, efficient, and pragmatic approach for gathering and synthesizing scientific knowledge on the state of biodiversity in any marine or terrestrial ecosystem and has general applicability worldwide.

The Nature Index: A General Framework for Synthesizing Knowledge on the State of Biodiversity

PubMed Central

Certain, Grégoire; Skarpaas, Olav; Bjerke, Jarle-Werner; Framstad, Erik; Lindholm, Markus; Nilsen, Jan-Erik; Norderhaug, Ann; Oug, Eivind; Pedersen, Hans-Christian; Schartau, Ann-Kristin; van der Meeren, Gro I.; Aslaksen, Iulie; Engen, Steinar; Garnåsjordet, Per-Arild; Kvaløy, Pål; Lillegård, Magnar; Yoccoz, Nigel G.; Nybø, Signe

2011-01-01

The magnitude and urgency of the biodiversity crisis is widely recognized within scientific and political organizations. However, a lack of integrated measures for biodiversity has greatly constrained the national and international response to the biodiversity crisis. Thus, integrated biodiversity indexes will greatly facilitate information transfer from science toward other areas of human society. The Nature Index framework samples scientific information on biodiversity from a variety of sources, synthesizes this information, and then transmits it in a simplified form to environmental managers, policymakers, and the public. The Nature Index optimizes information use by incorporating expert judgment, monitoring-based estimates, and model-based estimates. The index relies on a network of scientific experts, each of whom is responsible for one or more biodiversity indicators. The resulting set of indicators is supposed to represent the best available knowledge on the state of biodiversity and ecosystems in any given area. The value of each indicator is scaled relative to a reference state, i.e., a predicted value assessed by each expert for a hypothetical undisturbed or sustainably managed ecosystem. Scaled indicator values can be aggregated or disaggregated over different axes representing spatiotemporal dimensions or thematic groups. A range of scaling models can be applied to allow for different ways of interpreting the reference states, e.g., optimal situations or minimum sustainable levels. Statistical testing for differences in space or time can be implemented using Monte-Carlo simulations. This study presents the Nature Index framework and details its implementation in Norway. The results suggest that the framework is a functional, efficient, and pragmatic approach for gathering and synthesizing scientific knowledge on the state of biodiversity in any marine or terrestrial ecosystem and has general applicability worldwide. PMID:21526118

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…

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

Ferrada, J.J.; Osborne-Lee, I.W.; Grizzaffi, P.A.

Expert systems are known to be useful in capturing expertise and applying knowledge to chemical engineering problems such as diagnosis, process control, process simulation, and process advisory. However, expert system applications are traditionally limited to knowledge domains that are heuristic and involve only simple mathematics. Neural networks, on the other hand, represent an emerging technology capable of rapid recognition of patterned behavior without regard to mathematical complexity. Although useful in problem identification, neural networks are not very efficient in providing in-depth solutions and typically do not promote full understanding of the problem or the reasoning behind its solutions. Hence, applicationsmore » of neural networks have certain limitations. This paper explores the potential for expanding the scope of chemical engineering areas where neural networks might be utilized by incorporating expert systems and neural networks into the same application, a process called hybridization. In addition, hybrid applications are compared with those using more traditional approaches, the results of the different applications are analyzed, and the feasibility of converting the preliminary prototypes described herein into useful final products is evaluated. 12 refs., 8 figs.« less

A study on interaction App platform between expert knowledge and community applied on disaster education

NASA Astrophysics Data System (ADS)

Ruljigaljig, T.; Huang, M. L.

2015-12-01

This study development interface for Mobile Application (App) use cloud technology, Web 2.0 and online community of technology to build the Environmental-Geological Disaster Network(EDN). The interaction App platform between expert knowledge and community is developed as a teaching tool, which bases on the open data released by Central Geological Survey. The APP can through Augmented Reality technology to potential hazards position through the camera lens, the real show in real-world environment. The interaction with experts in the community to improve the general public awareness of disaster. Training people to record the occurrence of geological disasters precursor, thereby awakened their to natural disaster consciousness and attention.General users obtain real-time information during travel, mountaineering and teaching process. Using App platform to upload and represent the environmental geological disaster data collected by themselves. It is expected that by public joint the open platform can accumulate environmental geological disaster data effectively, quickly, extensively and correctly. The most important thing of this study is rooting the concept of disaster prevention, reduction, and avoidance through public participation.

Expert knowledge as a foundation for the management of secretive species and their habitat

USGS Publications Warehouse

Drew, C. Ashton; Collazo, Jaime

2012-01-01

In this chapter, we share lessons learned during the elicitation and application of expert knowledge in the form of a belief network model for the habitat of a waterbird, the King Rail (Rallus elegans). A belief network is a statistical framework used to graphically represent and evaluate hypothesized cause and effect relationships among variables. Our model was a pilot project to explore the value of such a model as a tool to help the US Fish and Wildlife Service (USFWS) conserve species that lack sufficient empirical data to guide management decisions. Many factors limit the availability of empirical data that can support landscape-scale conservation planning. Globally, most species simply have not yet been subject to empirical study (Wilson 2000). Even for well-studied species, data are often restricted to specific geographic extents, to particular seasons, or to specific segments of a species’ life history. The USFWS mandates that the agency’s conservation actions (1) be coordinated across regional landscapes, (2) be founded on the best available science (with testable assumptions), and (3) support adaptive management through monitoring and assessment of action outcomes. Given limits on the available data, the concept of “best available science” in the context of conservation planning generally includes a mix of empirical data and expert knowledge (Sullivan et al. 2006).

An expert system for the design of heating, ventilating, and air-conditioning systems

NASA Astrophysics Data System (ADS)

Camejo, Pedro Jose

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are needed and have been developed to join the separate knowledge bases into one simple-to-use program unit.

Guidelines for biosafety laboratory competency: CDC and the Association of Public Health Laboratories.

PubMed

Delany, Judy R; Pentella, Michael A; Rodriguez, Joyce A; Shah, Kajari V; Baxley, Karen P; Holmes, David E

2011-04-15

These guidelines for biosafety laboratory competency outline the essential skills, knowledge, and abilities required for working with biologic agents at the three highest biosafety levels (BSLs) (levels 2, 3, and 4). The competencies are tiered to a worker's experience at three levels: entry level, midlevel (experienced), and senior level (supervisory or managerial positions). These guidelines were developed on behalf of CDC and the Association of Public Health Laboratories (APHL) by an expert panel comprising 27 experts representing state and federal public health laboratories, private sector clinical and research laboratories, and academic centers. They were then reviewed by approximately 300 practitioners representing the relevant fields. The guidelines are intended for laboratorians working with hazardous biologic agents, obtained from either samples or specimens that are maintained and manipulated in clinical, environmental, public health, academic, and research laboratories.

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...

Mining knowledge from corpora: an application to retrieval and indexing.

PubMed

Soualmia, Lina F; Dahamna, Badisse; Darmoni, Stéfan

2008-01-01

The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Association rules method is applied to documents. The process is carried out on three major document categories referring to e-health information consumers: health professionals, students and lay people. Association rules evaluation is founded on statistical measures combined with domain knowledge. Association rules represent existing relations between medical concepts (60.62%) and new knowledge (54.21%). Based on observations, 463 expert rules are defined by medical librarians for retrieval and indexing. Association rules bear out existing relations, produce new knowledge and support users and indexers in document retrieval and indexing.

Circumpolar Biodiversity Monitoring Programme: Coastal Expert Workshop meeting summary

USGS Publications Warehouse

Thomson, L.; McLennan, Donald; Anderson, Rebecca D.; Wegeberg, S.; Pettersvik Arvnes, Maria; Sergienko, Liudmila; Behe, Carolina; Moss-Davies, Pitseolak; Fritz, S.; Christensen, T.; Price, C.

2016-01-01

The Coastal Expert Workshop brought together a diverse group of coastal experts with the common goal of developing a biodiversity monitoring program for coastal ecosystems across the circumpolar Arctic. Meeting participants, including northern residents, industry and Non-Governmental Organization (NGO) representatives, scientists, and government regulators from across the circumpolar Arctic, gathered at the Lord Elgin Hotel in Ottawa from March 1 to 3, 2016, to discuss current biodiversity monitoring efforts, understand key issues facing biodiversity in the Arctic coastal areas and suggest monitoring indicators, or Focal Ecosystem Components, for the program. A Traditional Knowledge Holders meeting was held on February 29, 2016 in conjunction with the workshop. The following document provides a summary of the workshop activities and outcomes, and will be followed by a more complete Workshop Report.

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

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...

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.

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.

Expert system for the design of heating, ventilating, and air-conditioning systems. Master's thesis

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

Camejo, P.J.

1989-12-01

Expert systems are computer programs that seek to mimic human reason. An expert system shelf, a software program commonly used for developing expert systems in a relatively short time, was used to develop a prototypical expert system for the design of heating, ventilating, and air-conditioning (HVAC) systems in buildings. Because HVAC design involves several related knowledge domains, developing an expert system for HVAC design requires the integration of several smaller expert systems known as knowledge bases. A menu program and several auxiliary programs for gathering data, completing calculations, printing project reports, and passing data between the knowledge bases are neededmore » and have been developed to join the separate knowledge bases into one simple-to-use program unit.« less

State of the Art in HIV Drug Resistance: Science and Technology Knowledge Gap.

PubMed

Boucher, Charles A; Bobkova, Marina R; Geretti, Anna Maria; Hung, Chien-Ching; Kaiser, Rolf; Marcelin, Anne-Geneviève; Streinu-Cercel, Adrian; van Wyk, Jean; Dorr, Pat; Vandamme, Anne-Mieke

2018-01-01

Resistance to antiretroviral therapy (ART) threatens the efficacy of human immunodeficiency virus type 1 (HIV-1) treatment. We present a review of knowledge gaps in the science and technologies of acquired HIV-1 drug resistance (HIVDR) in an effort to facilitate research, scientific exchange, and progress in clinical management. The expert authorship of this review convened to identify data gaps that exist in the field of HIVDR and discuss their clinical implications. A subsequent literature review of trials and current practices was carried out to provide supporting evidence. Several gaps were identified across HIVDR science and technology. A summary of the major gaps is presented, with an expert discussion of their implications within the context of the wider field. Crucial to optimizing the use of ART will be improved understanding of protease inhibitors and, in particular, integrase strand transfer inhibitors (INSTI) in the context of HIVDR. Limited experience with INSTI represents an important knowledge gap in HIV resistance science. Utilizing such knowledge in a clinical setting relies on accurate testing and analysis of resistance-associated mutations. As next-generation sequencing becomes more widely available, a gap in the interpretation of data is the lack of a defined, clinically relevant threshold of minority variants. Further research will provide evidence on where such thresholds lie and how they can be most effectively applied. Expert discussion identified a series of gaps in our knowledge of HIVDR. Addressing prefsuch gaps through further research and characterization will facilitate the optimal use of ART therapies and technologies.

A framework for the computer-aided planning and optimisation of manufacturing processes for components with functional graded properties

NASA Astrophysics Data System (ADS)

Biermann, D.; Gausemeier, J.; Heim, H.-P.; Hess, S.; Petersen, M.; Ries, A.; Wagner, T.

2014-05-01

In this contribution a framework for the computer-aided planning and optimisation of functional graded components is presented. The framework is divided into three modules - the "Component Description", the "Expert System" for the synthetisation of several process chains and the "Modelling and Process Chain Optimisation". The Component Description module enhances a standard computer-aided design (CAD) model by a voxel-based representation of the graded properties. The Expert System synthesises process steps stored in the knowledge base to generate several alternative process chains. Each process chain is capable of producing components according to the enhanced CAD model and usually consists of a sequence of heating-, cooling-, and forming processes. The dependencies between the component and the applied manufacturing processes as well as between the processes themselves need to be considered. The Expert System utilises an ontology for that purpose. The ontology represents all dependencies in a structured way and connects the information of the knowledge base via relations. The third module performs the evaluation of the generated process chains. To accomplish this, the parameters of each process are optimised with respect to the component specification, whereby the result of the best parameterisation is used as representative value. Finally, the process chain which is capable of manufacturing a functionally graded component in an optimal way regarding to the property distributions of the component description is presented by means of a dedicated specification technique.

Expert knowledge maps for knowledge management: a case study in Traditional Chinese Medicine research.

PubMed

Cui, Meng; Yang, Shuo; Yu, Tong; Yang, Ce; Gao, Yonghong; Zhu, Haiyan

2013-10-01

To design a model to capture information on the state and trends of knowledge creation, at both an individual and an organizational level, in order to enhance knowledge management. We designed a graph-theoretic knowledge model, the expert knowledge map (EKM), based on literature-based annotation. A case study in the domain of Traditional Chinese Medicine research was used to illustrate the usefulness of the model. The EKM successfully captured various aspects of knowledge and enhanced knowledge management within the case-study organization through the provision of knowledge graphs, expert graphs, and expert-knowledge biography. Our model could help to reveal the hot topics, trends, and products of the research done by an organization. It can potentially be used to facilitate knowledge learning, sharing and decision-making among researchers, academicians, students, and administrators of organizations.

Expert opinions on good practice in evaluation of health promotion and primary prevention measures related to children and adolescents in Germany.

PubMed

Korber, Katharina; Becker, Christian

2017-10-02

Determining what constitutes "good practice" in the measurement of the costs and effects of health promotion and disease prevention measures is of particular importance. The aim of this paper was to gather expert knowledge on (economic) evaluations of health promotion and prevention measures for children and adolescents, especially on the practical importance, the determinants of project success, meaningful parameters for evaluations, and supporting factors, but also on problems in their implementation. This information is targeted at people responsible for the development of primary prevention or health promotion programs. Partially structured open interviews were conducted by two interviewers and transcribed, paraphrased, and summarized for further use. Eight experts took part in the interviews. The interviewed experts saw evaluation as a useful tool to establish the effects of prevention programs, to inform program improvement and further development, and to provide arguments to decision making. The respondents' thought that determinants of a program's success were effectiveness with evidence of causality, cost benefit relation, target-group reach and sustainability. It was considered important that hard and soft factors were included in an evaluation; costs were mentioned only by one expert. According to the experts, obstacles to evaluation were lacking resources, additional labor requirements, and the evaluators' unfamiliarity with a program's contents. It was recommended to consider evaluation design before a program is launched, to co-operate with people involved in a program and to make use of existing structures. While in in this study only a partial view of expert knowledge is represented, it could show important points to consider when developing evaluations of prevention programs. By considering these points, researchers could further advance towards a more comprehensive approach of evaluation targeting measures in children and adolescents.

Teacher Behavioral Process Criteria Grading Practices and the Effect on Student Achievement in English and Mathematics

ERIC Educational Resources Information Center

Kahney, Jon

2017-01-01

Teacher grading practices commonly do not align with the grading practices recommended by leading grading authorities in the field of education. The experts advocate for grades to be determined solely from measures of product criteria that represent a students current level of knowledge and what they can do. Most teachers, however, still use a mix…

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.

Knowledge-based fault diagnosis system for refuse collection vehicle

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

Tan, CheeFai; Juffrizal, K.; Khalil, S. N.

The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledgemore » that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.« less

AMPHION: Specification-based programming for scientific subroutine libraries

NASA Technical Reports Server (NTRS)

Lowry, Michael; Philpot, Andrew; Pressburger, Thomas; Underwood, Ian; Waldinger, Richard; Stickel, Mark

1994-01-01

AMPHION is a knowledge-based software engineering (KBSE) system that guides a user in developing a diagram representing a formal problem specification. It then automatically implements a solution to this specification as a program consisting of calls to subroutines from a library. The diagram provides an intuitive domain oriented notation for creating a specification that also facilitates reuse and modification. AMPHION'S architecture is domain independent. AMPHION is specialized to an application domain by developing a declarative domain theory. Creating a domain theory is an iterative process that currently requires the joint expertise of domain experts and experts in automated formal methods for software development.

Expressing Biomedical Ontologies in Natural Language for Expert Evaluation.

PubMed

Amith, Muhammad; Manion, Frank J; Harris, Marcelline R; Zhang, Yaoyun; Xu, Hua; Tao, Cui

2017-01-01

We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology.

Current state of knowledge and experts' perspective on the subcutaneous implantable cardioverter-defibrillator.

PubMed

Santini, Massimo; Cappato, Riccardo; Andresen, Dietrich; Brachmann, Johannes; Davies, D Wyn; Cleland, John; Filippi, Alessandro; Gronda, Edoardo; Hauer, Richard; Steinbeck, Gerhard; Steinhaus, David

2009-06-01

ICD implantation is today a well-recognized therapy to prevent sudden cardiac death. The available implantable devices at present need the use of permanent endocavitary leads which may cause, in some instances, serious troubles to the patients (lead dislodgement, ventricular perforation, lead infections, etc.). A new implantable defibrillator provided by only a subcutaneous lead is at present under evaluation. Its potential indications, usefulness benefits, and problems represent an interesting field of investigation and discussion. This paper describes the conclusions recently reached by a panel of experts, with regard to the potential role of an implantable subcutaneous defibrillator in the prevention of sudden cardiac death.

Students' Refinement of Knowledge during the Development of Knowledge Bases for Expert Systems.

ERIC Educational Resources Information Center

Lippert, Renate; Finley, Fred

The refinement of the cognitive knowledge base was studied through exploration of the transition from novice to expert and the use of an instructional strategy called novice knowledge engineering. Six college freshmen, who were enrolled in an honors physics course, used an expert system to create questions, decisions, rules, and explanations…

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.

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.

Semantic technologies in a decision support system

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

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.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-08-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

PubMed Central

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-01-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features. PMID:26705504

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

Representing Learning With Graphical Models

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Attitudes and local ecological knowledge of experts fishermen in relation to conservation and bycatch of sea turtles (reptilia: testudines), Southern Bahia, Brazil

PubMed Central

2013-01-01

Background The use of ethnoecological tools to evaluate possible damage and loss of biodiversity related to the populations of species under some degree of threat may represent a first step towards integrating the political management of natural resources and conservation strategies. From this perspective, this study investigates fishermen’s ecological knowledge about sea turtles and attitudes towards the conservation and bycatch in Ilhéus, Southern Bahia, Brazil. Methods Fishermen experts semi-structured interviews were performed using snowball sampling method. The interviews consisted of a series of questions relating to the fishermen’s profile, structure and work equipment, the local ecological knowledge of fishermen about sea turtles and bycatch, a projective test, attitudes towards turtle conservation and beliefs and taboos regarding turtles. Indicators for quantitative comparisons of respondents in terms of their broad knowledge and attitudes towards turtle conservation were created. Correlation analyses were made between indicators of knowledge and attitude as well as the relationship between education level and knowledge and attitudes. Results Thirty experts were interviewed for the study. The local ecological knowledge and attitudes of fishermen towards the conservation of sea turtles were respectively medium (0.43) and moderate (0.69) according to experts (based on Likert scale and Cronbach’s Alpha). Potential areas of spawning were reported from Barra Grande to Una covering the entire coast of Ilhéus. Methods for identifying the animal, behavior, and popular names were described by fishermen. The most recent captures of turtles were attributed to fishing line, but according to the respondents, lobster nets and shrimp traps are more likely to capture turtles. Knowledge and attitudes were weakly inversely correlated (r = −0.38, p = 0.04), and the education level of the respondent showed a positive correlation with positive attitudes towards turtle conservation (H = 8.33; p = 0.04). Life history, habitat, specific and exogenous taboos, beliefs and the use of hawksbill turtle to make glasses and other handcrafts are also reported in the study. Conclusions Monitoring of spawning areas, preservation of traditional practices, strategies to moderate the use of fishery resources and the local ecological knowledge/attitudes can provide data to improve the conservation practices and management of sea turtles. PMID:23448503

Attitudes and local ecological knowledge of experts fishermen in relation to conservation and bycatch of sea turtles (reptilia: testudines), Southern Bahia, Brazil.

PubMed

Braga, Heitor de Oliveira; Schiavetti, Alexandre

2013-03-01

The use of ethnoecological tools to evaluate possible damage and loss of biodiversity related to the populations of species under some degree of threat may represent a first step towards integrating the political management of natural resources and conservation strategies. From this perspective, this study investigates fishermen's ecological knowledge about sea turtles and attitudes towards the conservation and bycatch in Ilhéus, Southern Bahia, Brazil. Fishermen experts semi-structured interviews were performed using snowball sampling method. The interviews consisted of a series of questions relating to the fishermen's profile, structure and work equipment, the local ecological knowledge of fishermen about sea turtles and bycatch, a projective test, attitudes towards turtle conservation and beliefs and taboos regarding turtles. Indicators for quantitative comparisons of respondents in terms of their broad knowledge and attitudes towards turtle conservation were created. Correlation analyses were made between indicators of knowledge and attitude as well as the relationship between education level and knowledge and attitudes. Thirty experts were interviewed for the study. The local ecological knowledge and attitudes of fishermen towards the conservation of sea turtles were respectively medium (0.43) and moderate (0.69) according to experts (based on Likert scale and Cronbach's Alpha). Potential areas of spawning were reported from Barra Grande to Una covering the entire coast of Ilhéus. Methods for identifying the animal, behavior, and popular names were described by fishermen. The most recent captures of turtles were attributed to fishing line, but according to the respondents, lobster nets and shrimp traps are more likely to capture turtles. Knowledge and attitudes were weakly inversely correlated (r = -0.38, p = 0.04), and the education level of the respondent showed a positive correlation with positive attitudes towards turtle conservation (H = 8.33; p = 0.04). Life history, habitat, specific and exogenous taboos, beliefs and the use of hawksbill turtle to make glasses and other handcrafts are also reported in the study. Monitoring of spawning areas, preservation of traditional practices, strategies to moderate the use of fishery resources and the local ecological knowledge/attitudes can provide data to improve the conservation practices and management of sea turtles.

Juvenile Justice and Delinquency Prevention Act: Preventing Juvenile Crime at School and in the Community. Hearing before the Subcommittee on Early Childhood, Youth and Families of the Committee on Education and the Workforce. House of Representatives, One Hundred Sixth Congress, First Session (Washington, DC, March 18, 1999).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Education and the Workforce.

This document presents discussion on the Juvenile Crime Control and Delinquency Prevention Act (H.R. 1150) and provides testimonies of experts with first-hand knowledge of quality delinquency and violence prevention programs. An opening statement from Representative Mike Castle (Delaware) related the problem of children who become involved in…

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.

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…

Expert and Knowledge Based Systems.

ERIC Educational Resources Information Center

Demaid, Adrian; Edwards, Lyndon

1987-01-01

Discusses the nature and current state of knowledge-based systems and expert systems. Describes an expert system from the viewpoints of a computer programmer and an applications expert. Addresses concerns related to materials selection and forecasts future developments in the teaching of materials engineering. (ML)

Firesetting, arson, pyromania, and the forensic mental health expert.

PubMed

Burton, Paul R S; McNiel, Dale E; Binder, Renée L

2012-01-01

Firesetting is a common behavior that is frequently encountered by forensic mental health experts when consulting on criminal and civil legal cases. Despite its prevalence, minimal attention has been paid in the literature to conducting firesetting-related forensic evaluations. In this article, we discuss the differences in the behavior of firesetting, the crime of arson, and the diagnosis of pyromania. The literature on adult firesetter characteristics, classification systems, recidivism, and treatment is reviewed. Several types of common criminal and civil firesetting-related evaluations referred to forensic mental health experts are discussed, along with case examples illustrating how the courts have approached such assessments. To our knowledge, this article is the first in 20 years to address firesetting-related forensic evaluations within the psychiatry literature. It also represents the first comprehensive discussion of civil evaluations related to firesetting.

Framing of scientific knowledge as a new category of health care research.

PubMed

Salvador-Carulla, Luis; Fernandez, Ana; Madden, Rosamond; Lukersmith, Sue; Colagiuri, Ruth; Torkfar, Ghazal; Sturmberg, Joachim

2014-12-01

The new area of health system research requires a revision of the taxonomy of scientific knowledge that may facilitate a better understanding and representation of complex health phenomena in research discovery, corroboration and implementation. A position paper by an expert group following and iterative approach. 'Scientific evidence' should be differentiated from 'elicited knowledge' of experts and users, and this latter typology should be described beyond the traditional qualitative framework. Within this context 'framing of scientific knowledge' (FSK) is defined as a group of studies of prior expert knowledge specifically aimed at generating formal scientific frames. To be distinguished from other unstructured frames, FSK must be explicit, standardized, based on the available evidence, agreed by a group of experts and subdued to the principles of commensurability, transparency for corroboration and transferability that characterize scientific research. A preliminary typology of scientific framing studies is presented. This typology includes, among others, health declarations, position papers, expert-based clinical guides, conceptual maps, classifications, expert-driven health atlases and expert-driven studies of costs and burden of illness. This grouping of expert-based studies constitutes a different kind of scientific knowledge and should be clearly differentiated from 'evidence' gathered from experimental and observational studies in health system research. © 2014 John Wiley & Sons, Ltd.

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.

Acquisition, representation and rule generation for procedural knowledge

NASA Technical Reports Server (NTRS)

Ortiz, Chris; Saito, Tim; Mithal, Sachin; Loftin, R. Bowen

1991-01-01

Current research into the design and continuing development of a system for the acquisition of procedural knowledge, its representation in useful forms, and proposed methods for automated C Language Integrated Production System (CLIPS) rule generation is discussed. The Task Analysis and Rule Generation Tool (TARGET) is intended to permit experts, individually or collectively, to visually describe and refine procedural tasks. The system is designed to represent the acquired knowledge in the form of graphical objects with the capacity for generating production rules in CLIPS. The generated rules can then be integrated into applications such as NASA's Intelligent Computer Aided Training (ICAT) architecture. Also described are proposed methods for use in translating the graphical and intermediate knowledge representations into CLIPS rules.

Expert systems for superalloy studies

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Kaukler, William F.

1990-01-01

There are many areas in science and engineering which require knowledge of an extremely complex foundation of experimental results in order to design methodologies for developing new materials or products. Superalloys are an area which fit well into this discussion in the sense that they are complex combinations of elements which exhibit certain characteristics. Obviously the use of superalloys in high performance, high temperature systems such as the Space Shuttle Main Engine is of interest to NASA. The superalloy manufacturing process is complex and the implementation of an expert system within the design process requires some thought as to how and where it should be implemented. A major motivation is to develop a methodology to assist metallurgists in the design of superalloy materials using current expert systems technology. Hydrogen embrittlement is disasterous to rocket engines and the heuristics can be very complex. Attacking this problem as one module in the overall design process represents a significant step forward. In order to describe the objectives of the first phase implementation, the expert system was designated Hydrogen Environment Embrittlement Expert System (HEEES).

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.

Development of an Expert System for Representing Procedural Knowledge

NASA Technical Reports Server (NTRS)

Georgeff, Michael P.; Lansky, Amy L.

1985-01-01

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Development of a Spacecraft Materials Selector Expert System

NASA Technical Reports Server (NTRS)

Pippin, G.; Kauffman, W. (Technical Monitor)

2002-01-01

This report contains a description of the knowledge base tool and examples of its use. A downloadable version of the Spacecraft Materials Selector (SMS) knowledge base is available through the NASA Space Environments and Effects Program. The "Spacecraft Materials Selector" knowledge base is part of an electronic expert system. The expert system consists of an inference engine that contains the "decision-making" code and the knowledge base that contains the selected body of information. The inference engine is a software package previously developed at Boeing, called the Boeing Expert System Tool (BEST) kit.

Institutional Memory Preservation at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Coffey, J.; Moreman, Douglas; Dyer, J.; Hemminger, J. A.

1999-01-01

In this era of downsizing and deficit reduction, the preservation of institutional memory is a widespread concern for U.S. companies and governmental agencies. The National Aeronautical and Space Administration faces the pending retirement of many of the agency's long-term, senior engineers. NASA has a marvelous long-term history of success, but the agency faces a recurring problem caused by the loss of these engineers' unique knowledge and perspectives on NASA's role in aeronautics and space exploration. The current work describes a knowledge elicitation effort aimed at demonstrating the feasibility of preserving the more personal, heuristic knowledge accumulated over the years by NASA engineers, as contrasted with the "textbook" knowledge of launch vehicles. Work on this project was performed at NASA Glenn Research Center and elsewhere, and focused on launch vehicle systems integration. The initial effort was directed toward an historic view of the Centaur upper stage which is powered by two RL-10 engines. Various experts were consulted, employing a variety of knowledge elicitation techniques, regarding the Centaur and RL-10. Their knowledge is represented in searchable Web-based multimedia presentations. This paper discusses the various approaches to knowledge elicitation and knowledge representation employed, and assesses successes and challenges in trying to perform large-scale knowledge preservation of institutional memory. It is anticipated that strategies for knowledge elicitation and representation that have been developed in this grant will be utilized to elicit knowledge in a variety of domains including the complex heuristics that underly use of simulation software packages such as that being explored in the Expert System Architecture for Rocket Engine Numerical Simulators.

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.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

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.

Expert explanations of honeybee losses in areas of extensive agriculture in France: Gaucho® compared with other supposed causal factors

NASA Astrophysics Data System (ADS)

Maxim, L.; van der Sluijs, J. P.

2010-01-01

Debates on causality are at the core of controversies as regards environmental changes. The present paper presents a new method for analyzing controversies on causality in a context of social debate and the results of its empirical testing. The case study used is the controversy as regards the role played by the insecticide Gaucho®, compared with other supposed causal factors, in the substantial honeybee (Apis mellifera L.) losses reported to have occurred in France between 1994 and 2004. The method makes use of expert elicitation of the perceived strength of evidence regarding each of Bradford Hill's causality criteria, as regards the link between each of eight possible causal factors identified in attempts to explain each of five signs observed in honeybee colonies. These judgments are elicited from stakeholders and experts involved in the debate, i.e., representatives of Bayer Cropscience, of the Ministry of Agriculture, of the French Food Safety Authority, of beekeepers and of public scientists. We show that the intense controversy observed in confused and passionate public discourses is much less salient when the various arguments are structured using causation criteria. The contradictions between the different expert views have a triple origin: (1) the lack of shared definition and quantification of the signs observed in colonies; (2) the lack of specialist knowledge on honeybees; and (3) the strategic discursive practices associated with the lack of trust between experts representing stakeholders having diverging stakes in the case.

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.

A second generation expert system for checking and diagnosing AXAF's electric power system

NASA Technical Reports Server (NTRS)

Bykat, Alex

1992-01-01

AXAF - Advanced X-ray Astrophysics Facility - is a third NASA's great space observatory. Each of these observatories is intended to cover different parts of the electromagnetic spectrum (x-ray for AXAF) and to provide high resolution images of celestial sources in our universe. While the spacecraft is in orbit, the electric power system (EPS) performance is monitored via sensors measuring voltages, currents, pressures, and temperatures. The sensor data are sent from the spacecraft to the ground station as telemetry and analyzed on arrival. Monitoring, diagnosis and maintenance of such EPS is an arduous task which requires expertise and constant attention of the ground personnel. To help the ground crew in this task, much of it should be automated and delegated to expert systems, which draw engineer's attention to possible malfunctions and allows him to review the telemetry to determine the source of the trouble, diagnose the suspected fault and to propose a corrective action. Those systems are built on assumptions such as: (1) domain knowledge is available and can be represented as a set of rules; (2) domain knowledge is circumscribed, static, and monotonic; and (3) expert decision making can be emulated by a logical inference mechanism.

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.

College students' memory for vocabulary in their majors: evidence for a nonlinear relation between knowledge and memory.

PubMed

DeMarie, Darlene; Aloise-Young, Patricia A; Prideaux, Cheri L; Muransky-Doran, Jean; Gerda, Julie Hart

2004-09-01

The effect of domain knowledge on students' memory for vocabulary terms was investigated. Participants were 142 college students (94 education majors and 48 business majors). The measure of domain knowledge was the number of courses completed in the major. Students recalled three different lists (control, education, and business) of 20 words. Knowledge effects were estimated controlling for academic aptitude, academic achievement, and general memory ability. Domain-specific knowledge consistently predicted recall, above and beyond the effect of these control variables. Moreover, nonlinear models better represented the relation between knowledge and memory, with very similar functions predicting recall in both knowledge domains. Specifically, early in the majors more classes corresponded with increased memory performance, but a plateau period, when more classes did not result in higher recall, was evident for both majors. Longitudinal research is needed to explore at what point in learning novices' performance begins to resemble experts' performance.

Professional expertise amongst speech-language therapists: "willing to share".

PubMed

Jackson, Bianca N; Purdy, Suzanne Carolyn; Cooper-Thomas, Helena

2017-09-18

Purpose The current healthcare environment provides several challenges to the existing roles of healthcare professionals. The value of the professional expert is also under scrutiny. The purpose of this paper is to generate a construction of professional expertise amongst practitioners in the current healthcare environment. It used the speech-language therapy community in New Zealand (NZ) as an example. Design/methodology/approach Speech-language therapists currently practicing in NZ completed an online survey including qualitative and quantitative components. The range of experience and work settings of participants ( n=119) was representative of the workforce. Findings Participants clearly identified being "highly experienced" and "having in-depth knowledge" as essential elements of professional expertise. Thematic analysis generated two interconnected themes of a professional expert being a personal leader and teacher, and a highly experienced, knowledgeable and skilful practitioner. Additionally, practitioners needed to be seen to contribute to the community in order to be known as experts. Clinical practice was valued differently from research generation. Originality/value This study is novel in exploring a construction of professional expertise amongst practitioners in a current healthcare community. Within that community, experts could be viewed as highly effective practitioners that visibly contribute to the professional community. The study draws attention to the role of reputation and the impacts of being a clinical teacher or leader compared with pursuing a research role. This could be particularly relevant in the promotion of evidence-based practice.

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…

PVDaCS - A prototype knowledge-based expert system for certification of spacecraft data

NASA Technical Reports Server (NTRS)

Wharton, Cathleen; Shiroma, Patricia J.; Simmons, Karen E.

1989-01-01

On-line data management techniques to certify spacecraft information are mandated by increasing telemetry rates. Knowledge-based expert systems offer the ability to certify data electronically without the need for time-consuming human interaction. Issues of automatic certification are explored by designing a knowledge-based expert system to certify data from a scientific instrument, the Orbiter Ultraviolet Spectrometer, on an operating NASA planetary spacecraft, Pioneer Venus. The resulting rule-based system, called PVDaCS (Pioneer Venus Data Certification System), is a functional prototype demonstrating the concepts of a larger system design. A key element of the system design is the representation of an expert's knowledge through the usage of well ordered sequences. PVDaCS produces a certification value derived from expert knowledge and an analysis of the instrument's operation. Results of system performance are presented.

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.

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…

METEOR - an artificial intelligence system for convective storm forecasting

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

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

1987-03-01

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

REDEX - The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.

REDEX: The ranging equipment diagnostic expert system

NASA Technical Reports Server (NTRS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-01-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.

REDEX - The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990s.

REDEX: The ranging equipment diagnostic expert system

NASA Astrophysics Data System (ADS)

Luczak, Edward C.; Gopalakrishnan, K.; Zillig, David J.

1989-04-01

REDEX, an advanced prototype expert system that diagnoses hardware failures in the Ranging Equipment (RE) at NASA's Ground Network tracking stations is described. REDEX will help the RE technician identify faulty circuit cards or modules that must be replaced, and thereby reduce troubleshooting time. It features a highly graphical user interface that uses color block diagrams and layout diagrams to illustrate the location of a fault. A semantic network knowledge representation technique was used to model the design structure of the RE. A catalog of generic troubleshooting rules was compiled to represent heuristics that are applied in diagnosing electronic equipment. Specific troubleshooting rules were identified to represent additional diagnostic knowledge that is unique to the RE. Over 50 generic and 250 specific troubleshooting rules have been derived. REDEX is implemented in Prolog on an IBM PC AT-compatible workstation. Block diagram graphics displays are color-coded to identify signals that have been monitored or inferred to have nominal values, signals that are out of tolerance, and circuit cards and functions that are diagnosed as faulty. A hypertext-like scheme is used to allow the user to easily navigate through the space of diagrams and tables. Over 50 graphic and tabular displays have been implemented. REDEX is currently being evaluated in a stand-alone mode using simulated RE fault scenarios. It will soon be interfaced to the RE and tested in an online environment. When completed and fielded, REDEX will be a concrete example of the application of expert systems technology to the problem of improving performance and reducing the lifecycle costs of operating NASA's communications networks in the 1990's.

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.

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

NASA Technical Reports Server (NTRS)

Liebowitz, Jay

1986-01-01

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

SWAN: An expert system with natural language interface for tactical air capability assessment

NASA Technical Reports Server (NTRS)

Simmons, Robert M.

1987-01-01

SWAN is an expert system and natural language interface for assessing the war fighting capability of Air Force units in Europe. The expert system is an object oriented knowledge based simulation with an alternate worlds facility for performing what-if excursions. Responses from the system take the form of generated text, tables, or graphs. The natural language interface is an expert system in its own right, with a knowledge base and rules which understand how to access external databases, models, or expert systems. The distinguishing feature of the Air Force expert system is its use of meta-knowledge to generate explanations in the frame and procedure based environment.

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…

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…

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

ERIC Educational Resources Information Center

Wilson, Brent G.; Welsh, Jack R.

1986-01-01

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

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…

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

NASA Astrophysics Data System (ADS)

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

1997-06-01

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

Preliminary Design of a Consultation Knowledge-Based System for the Minimization of Distortion in Welded Structures

DTIC Science & Technology

1989-02-01

which capture the knowledge of such experts. These Expert Systems, or Knowledge-Based Systems’, differ from the usual computer programming techniques...their applications in the fields of structural design and welding is reviewed. 5.1 Introduction Expert Systems, or KBES, are computer programs using Al...procedurally constructed as conventional computer programs usually are; * The knowledge base of such systems is executable, unlike databases 3 "Ill

Characterizing novice-expert differences in macrocognition: an exploratory study of cognitive work in the emergency department.

PubMed

Schubert, Christiane C; Denmark, T Kent; Crandall, Beth; Grome, Anna; Pappas, James

2013-01-01

The objectives of this study are to elicit and document descriptions of emergency physician expertise, to characterize cognitive differences between novice and expert physicians, and to identify areas in which novices' skill and knowledge gaps are most pronounced. The nature of the differences between novices and experts needs to be explored to develop effective instructional modalities that accelerate the learning curve of inexperienced physicians who work in high-complexity environments. We interviewed novice emergency physicians (first-year residents) and attending physicians with significant expertise, working in an academic Level I trauma center in Southern California. With cognitive task analysis, we used task diagrams to capture nonroutine critical incidents that required the use of complex cognitive skills. Timelines were constructed to develop a detailed understanding of challenging incidents and the decisions involved as the incident unfolded, followed by progressive deepening to tease out situation-specific cues, knowledge, and information that experts and novices used. A thematic analysis of the interview transcripts was conducted to identify key categories. Using classification techniques for data reduction, we identified a smaller set of key themes, which composed the core findings of the study. Five interns and 6 attending physicians participated in the interviews. Novice physicians reported having difficulties representing the patient's story to attending physicians and other health care providers. Overrelying on objective data, novice physicians use linear thinking to move to diagnosis quickly and are likely to discount and explain away data that do not "fit" the frame. Experienced physicians draw on expertise to recognize cues and patterns while leaving room for altering or even changing their initial diagnosis. Whereas experts maintain high levels of spatial, temporal, and organizational systems awareness when overseeing treatment modalities of multiple patients, novices have difficulty seeing and maintaining the "big picture." Novice physicians use sense-making styles that differ from those of experts. Training novices to respond to the high cognitive demand of complex environments early in their careers requires instructional modalities that not only increase their knowledge base but also accelerate the integration of knowledge and practice. Simulation and custom-designed avatar-mediated virtual worlds are a promising new technology that may facilitate such training. Future research should expand on the results of this study through the use of larger sample sizes and interviews conducted at multiple sites to increase generalizability. Copyright © 2012. Published by Mosby, Inc.

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Two implementations of the Expert System for the Flight Analysis System (ESFAS) project

NASA Technical Reports Server (NTRS)

Wang, Lui

1988-01-01

A comparison is made between the two most sophisticated expert system building tools, the Automated Reasoning Tool (ART) and the Knowledge Engineering Environment (KEE). The same problem domain (ESFAS) was used in making the comparison. The Expert System for the Flight Analysis System (ESFAS) acts as an intelligent front end for the Flight Analysis System (FAS). FAS is a complex configuration controlled set of interrelated processors (FORTRAN routines) which will be used by the Mission Planning and Analysis Div. (MPAD) to design and analyze Shuttle and potential Space Station missions. Implementations of ESFAS are described. The two versions represent very different programming paradigms; ART uses rules and KEE uses objects. Due to each of the tools philosophical differences, KEE is implemented using a depth first traversal algorithm, whereas ART uses a user directed traversal method. Either tool could be used to solve this particular problem.

JPRS Report, Soviet Union, Foreign Military Review, No. 5, May 1988

DTIC Science & Technology

1988-10-31

nology, Carnegie-Mellon University, and Stanford Uni- versity taking the lead. New constructive ideas were advanced in this period for simulating human...for representing stereotyped situations), products (logical constructions according to rules such as "if..., then..."), semantic networks (formal...battle). A prototype of the expert system, OB.l KB (Order of Battlefield [sic] Variant No. 1 Knowledge Base), was constructed as a result of

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.

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.

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.

VisEL: Visualisation of Expertise Level in a Special Interest Group Knowledge Portal

NASA Astrophysics Data System (ADS)

Zulhafizsyam Wan Ahmad, Wan Muhammad; Sulaiman, Shahida; Yusof, Umi Kalsom

A variety of portals are available nowadays to support diverse purposes such as commercial, publishing, personal, affinity and corporate portals. Affinity portals promote electronic communities who share common interest such as a special interest group (SIG). Knowledge portal is an emerging trend that benefits the existing portal technology by designing such portals with proper representation of the members' shared knowledge. Besides textual representation for diverse expertise levels, graphical visualisation will be able to support the requirements in searching and representing expertise level among e-community. There is a number of existing SIG portals available. However, they do not visualise effectively and accurately the expertise level of members and make it difficult for users to search their targeted experts for instance searching the highest expertise level to have a discussion and to solve their problems related to a project. The goal of this paper is to propose a graphical visualisation of expertise level method (VisEL) using an interactive tag cloud technique that represents expertise level of each member based on their knowledge in a software engineering SIG portal.

Assessing the safety effects of cooperative intelligent transport systems: A bowtie analysis approach.

PubMed

Ehlers, Ute Christine; Ryeng, Eirin Olaussen; McCormack, Edward; Khan, Faisal; Ehlers, Sören

2017-02-01

The safety effects of cooperative intelligent transport systems (C-ITS) are mostly unknown and associated with uncertainties, because these systems represent emerging technology. This study proposes a bowtie analysis as a conceptual framework for evaluating the safety effect of cooperative intelligent transport systems. These seek to prevent road traffic accidents or mitigate their consequences. Under the assumption of the potential occurrence of a particular single vehicle accident, three case studies demonstrate the application of the bowtie analysis approach in road traffic safety. The approach utilizes exemplary expert estimates and knowledge from literature on the probability of the occurrence of accident risk factors and of the success of safety measures. Fuzzy set theory is applied to handle uncertainty in expert knowledge. Based on this approach, a useful tool is developed to estimate the effects of safety-related cooperative intelligent transport systems in terms of the expected change in accident occurrence and consequence probability. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

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…

Measuring University students' understanding of the greenhouse effect - a comparison of multiple-choice, short answer and concept sketch assessment tools with respect to students' mental models

NASA Astrophysics Data System (ADS)

Gold, A. U.; Harris, S. E.

2013-12-01

The greenhouse effect comes up in most discussions about climate and is a key concept related to climate change. Existing studies have shown that students and adults alike lack a detailed understanding of this important concept or might hold misconceptions. We studied the effectiveness of different interventions on University-level students' understanding of the greenhouse effect. Introductory level science students were tested for their pre-knowledge of the greenhouse effect using validated multiple-choice questions, short answers and concept sketches. All students participated in a common lesson about the greenhouse effect and were then randomly assigned to one of two lab groups. One group explored an existing simulation about the greenhouse effect (PhET-lesson) and the other group worked with absorption spectra of different greenhouse gases (Data-lesson) to deepen the understanding of the greenhouse effect. All students completed the same assessment including multiple choice, short answers and concept sketches after participation in their lab lesson. 164 students completed all the assessments, 76 completed the PhET lesson and 77 completed the data lesson. 11 students missed the contrasting lesson. In this presentation we show the comparison between the multiple-choice questions, short answer questions and the concept sketches of students. We explore how well each of these assessment types represents student's knowledge. We also identify items that are indicators of the level of understanding of the greenhouse effect as measured in correspondence of student answers to an expert mental model and expert responses. Preliminary data analysis shows that student who produce concept sketch drawings that come close to expert drawings also choose correct multiple-choice answers. However, correct multiple-choice answers are not necessarily an indicator that a student produces an expert-like correlating concept sketch items. Multiple-choice questions that require detailed knowledge of the greenhouse effect (e.g. direction of re-emission of infrared energy from greenhouse gas) are significantly more likely to be answered correctly by students who also produce expert-like concept sketch items than by students who don't include this aspect in their sketch and don't answer the multiple choice questions correctly. This difference is not as apparent for less technical multiple-choice questions (e.g. type of radiation emitted by Sun). Our findings explore the formation of student's mental models throughout different interventions and how well the different assessment techniques used in this study represent the student understanding of the overall concept.

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.

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.

Eight habitats, 38 threats and 55 experts: Assessing ecological risk in a multi-use marine region

PubMed Central

Jones, Alice R.; Deveney, Marty R.; Ward, Tim M.; Gillanders, Bronwyn M.

2017-01-01

Identifying the relative risk human activities pose to a habitat, and the ecosystem services they provide, can guide management prioritisation and resource allocation. Using a combination of expert elicitation to assess the probable effect of a threat and existing data to assess the level of threat exposure, we conducted a risk assessment for 38 human-mediated threats to eight marine habitats (totalling 304 threat-habitat combinations) in Spencer Gulf, Australia. We developed a score-based survey to collate expert opinion and assess the relative effect of each threat to each habitat, as well as a novel and independent measure of knowledge-based uncertainty. Fifty-five experts representing multiple sectors and institutions participated in the study, with 6 to 15 survey responses per habitat (n = 81 surveys). We identified key threats specific to each habitat; overall, climate change threats received the highest risk rankings, with nutrient discharge identified as a key local-scale stressor. Invasive species and most fishing-related threats, which are commonly identified as major threats to the marine environment, were ranked as low-tier threats to Spencer Gulf, emphasising the importance of regionally-relevant assessments. Further, we identified critical knowledge gaps and quantified uncertainty scores for each risk. Our approach will facilitate prioritisation of resource allocation in a region of increasing social, economic and environmental importance, and can be applied to marine regions where empirical data are lacking. PMID:28489912

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts.

PubMed

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains.

Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts

PubMed Central

Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam

2015-01-01

Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. PMID:26495435

Developing and piloting an expert system for better routine voluntary HIV counseling and testing in China: preliminary results and lessons.

PubMed

Chai, Jing; Wang, DeBin; Zhou, Meng; Xu, WangQuan; Liang, Guojun; Shen, Yi Fang

2012-01-01

This study aims at developing and testing a pragmatic expert system for HIV voluntary counseling (VCT-ES) that leverages best practices. The VCT-ES was developed via evolutionary prototyping and piloted in 10 voluntary HIV counseling and testing (VCT) clinics from Anhui and Beijing representative of prefecture and county level VCT clinics in China. All counselors with the clinics and the clients to the clinics within selected two weeks at baseline and the end of study were invited to participate. Assessment measures included essential counseling procedures (ECPs); clients' satisfaction, knowledge, and behavior efficacy. VCT-ES was developed which tries to model and facilitate standard VCT operation procedures and best practices. One hundred and eighty-two (96 at baseline vs. 86 after intervention) cases recordings, 172 (96 vs. 76) client questionnaires, 10 counselor, and 2 expert rating instruments were collected; and 17 clients and 8 counselors participated in qualitative interviews. VCT-ES increased delivery of ECPs from 18.94% to 66.39% on average; increased clients' knowledge from 40.51% to 86.34% and self-efficacy by 22.42%. The VCT-ES applications listed were rated 9.1 on average (maximum = 10). The VCT-ES could be an easy and effective solution to better routine VCT and merits further research.

A Knowledge-Based System Developer for aerospace applications

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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.

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

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)

Language of CTO interventions - Focus on hardware.

PubMed

Mishra, Sundeep

2016-01-01

The knowledge of variety of chronic total occlusion (CTO) hardware and the ability to use them represents the key to success of any CTO interventions. However, the multiplicity of CTO hardware and their physical character and the terminology used by experts create confusion in the mind of an average interventional cardiologist, particularly a beginner in this field. This knowledge is available but is scattered. We aim to classify and compare the currently used devices based on their properties focusing on how physical character of each device can be utilized in a specific situation, thus clarifying and simplifying the technical discourse. Copyright © 2016. Published by Elsevier B.V.

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.

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.

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 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.

Interactive Inverse Groundwater Modeling - Addressing User Fatigue

NASA Astrophysics Data System (ADS)

Singh, A.; Minsker, B. S.

2006-12-01

This paper builds on ongoing research on developing an interactive and multi-objective framework to solve the groundwater inverse problem. In this work we solve the classic groundwater inverse problem of estimating a spatially continuous conductivity field, given field measurements of hydraulic heads. The proposed framework is based on an interactive multi-objective genetic algorithm (IMOGA) that not only considers quantitative measures such as calibration error and degree of regularization, but also takes into account expert knowledge about the structure of the underlying conductivity field expressed as subjective rankings of potential conductivity fields by the expert. The IMOGA converges to the optimal Pareto front representing the best trade- off among the qualitative as well as quantitative objectives. However, since the IMOGA is a population-based iterative search it requires the user to evaluate hundreds of solutions. This leads to the problem of 'user fatigue'. We propose a two step methodology to combat user fatigue in such interactive systems. The first step is choosing only a few highly representative solutions to be shown to the expert for ranking. Spatial clustering is used to group the search space based on the similarity of the conductivity fields. Sampling is then carried out from different clusters to improve the diversity of solutions shown to the user. Once the expert has ranked representative solutions from each cluster a machine learning model is used to 'learn user preference' and extrapolate these for the solutions not ranked by the expert. We investigate different machine learning models such as Decision Trees, Bayesian learning model, and instance based weighting to model user preference. In addition, we also investigate ways to improve the performance of these models by providing information about the spatial structure of the conductivity fields (which is what the expert bases his or her rank on). Results are shown for each of these machine learning models and the advantages and disadvantages for each approach are discussed. These results indicate that using the proposed two-step methodology leads to significant reduction in user-fatigue without deteriorating the solution quality of the IMOGA.

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.

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

Centralizing content and distributing labor: a community model for curating the very long tail of microbial genomes.

PubMed

Putman, Tim E; Burgstaller-Muehlbacher, Sebastian; Waagmeester, Andra; Wu, Chunlei; Su, Andrew I; Good, Benjamin M

2016-01-01

The last 20 years of advancement in sequencing technologies have led to sequencing thousands of microbial genomes, creating mountains of genetic data. While efficiency in generating the data improves almost daily, applying meaningful relationships between taxonomic and genetic entities on this scale requires a structured and integrative approach. Currently, knowledge is distributed across a fragmented landscape of resources from government-funded institutions such as National Center for Biotechnology Information (NCBI) and UniProt to topic-focused databases like the ODB3 database of prokaryotic operons, to the supplemental table of a primary publication. A major drawback to large scale, expert-curated databases is the expense of maintaining and extending them over time. No entity apart from a major institution with stable long-term funding can consider this, and their scope is limited considering the magnitude of microbial data being generated daily. Wikidata is an openly editable, semantic web compatible framework for knowledge representation. It is a project of the Wikimedia Foundation and offers knowledge integration capabilities ideally suited to the challenge of representing the exploding body of information about microbial genomics. We are developing a microbial specific data model, based on Wikidata's semantic web compatibility, which represents bacterial species, strains and the gene and gene products that define them. Currently, we have loaded 43,694 gene and 37,966 protein items for 21 species of bacteria, including the human pathogenic bacteriaChlamydia trachomatis.Using this pathogen as an example, we explore complex interactions between the pathogen, its host, associated genes, other microbes, disease and drugs using the Wikidata SPARQL endpoint. In our next phase of development, we will add another 99 bacterial genomes and their gene and gene products, totaling ∼900,000 additional entities. This aggregation of knowledge will be a platform for community-driven collaboration, allowing the networking of microbial genetic data through the sharing of knowledge by both the data and domain expert. © The Author(s) 2016. Published by Oxford University Press.

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.

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.

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…

Modeling aspects of human memory for scientific study.

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

Caudell, Thomas P.; Watson, Patrick; McDaniel, Mark A.

Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closermore » to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.« less

Neuropsychologist Experts and Civil Capacity Evaluations: Representative Cases.

PubMed

Kaufmann, Paul M

2016-09-01

Clinical neuropsychologists accept more forensic referrals now and spend more time in forensic consulting than ever before. Recent surveys show weekly hours devoted to forensic consulting increased 97% in the past decade. During the same time period, the number of board certified neuropsychologists more than doubled. Under recently published Specialty Guidelines for Forensic Psychology, clinical neuropsychologists practice forensic psychology when applying scientific, technical, or specialized knowledge of neuropsychology to the law to assist in addressing legal, contractual, or administrative matters. Among those increasingly varied forensic referrals, clinical neuropsychologists are conducting more civil competency and capacity evaluations. Representative cases from three jurisdictions demonstrate how neuropsychologists provide expertize in matters involving testamentary capacity, contractual capacity, business judgments, and job capacity. Case presentations illustrate some of the strengths and weaknesses of neuropsychological evaluation of civil capacities. The article concludes with a "battle of experts" case involving five neuropsychologists with opposing opinions recently heard in a Federal Appellate court. Implications for neuropschology training and forensic competencies are considered. In offering quality services to the legal profession, neuropsychologists support the truth-seeking function of the judiciary, promote justice, protect the profession, and serve public policy. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Assistance to neurosurgical planning: using a fuzzy spatial graph model of the brain for locating anatomical targets in MRI

NASA Astrophysics Data System (ADS)

Villéger, Alice; Ouchchane, Lemlih; Lemaire, Jean-Jacques; Boire, Jean-Yves

2007-03-01

Symptoms of neurodegenerative pathologies such as Parkinson's disease can be relieved through Deep Brain Stimulation. This neurosurgical technique relies on high precision positioning of electrodes in specific areas of the basal ganglia and the thalamus. These subcortical anatomical targets must be located at pre-operative stage, from a set of MRI acquired under stereotactic conditions. In order to assist surgical planning, we designed a semi-automated image analysis process for extracting anatomical areas of interest. Complementary information, provided by both patient's data and expert knowledge, is represented as fuzzy membership maps, which are then fused by means of suitable possibilistic operators in order to achieve the segmentation of targets. More specifically, theoretical prior knowledge on brain anatomy is modelled within a 'virtual atlas' organised as a spatial graph: a list of vertices linked by edges, where each vertex represents an anatomical structure of interest and contains relevant information such as tissue composition, whereas each edge represents a spatial relationship between two structures, such as their relative directions. The model is built using heterogeneous sources of information such as qualitative descriptions from the expert, or quantitative information from prelabelled images. For each patient, tissue membership maps are extracted from MR data through a classification step. Prior model and patient's data are then matched by using a research algorithm (or 'strategy') which simultaneously computes an estimation of the location of every structures. The method was tested on 10 clinical images, with promising results. Location and segmentation results were statistically assessed, opening perspectives for enhancements.

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.

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.

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

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

Implementation issues for consumer-directed programs: comparing views of policy experts, consumers, and representatives.

PubMed

Simon-Rusinowitz, Lori; Marks, Lori N; Loughlin, Dawn M; Desmond, Sharon M; Mahoney, Kevin J; Zacharias, B Lee; Squillace, Marie R; Allison, Ann Marie

2002-01-01

An increasing number of aging community providers and consumers support consumer-direction (CD) in long-term care services. In regard to devolution, consumer-direction goes beyond the usual approach of shifting responsibilities from the federal government to state governments to bring programs "closer to the people." Consumer-direction goes even further by placing resources directly in the hands of consumers. Yet, many questions remain unanswered regarding how to implement CD personal assistance services in general, and especially for older persons. This article describes the importance of examining views from multiple key stakeholders involved in implementing CD programs. We report on three background studies that have informed the Cash and Counseling Demonstration and Evaluation (CCDE) design and implementation-policy expert interviews as well as surveys and focus groups with consumers and representatives. As a fourth data source, we drew upon experiences in designing the CCDE and initial results from the first year of implementation. Each of the three studies on its own provided essential information for planning the CCDE. However, when we examined the studies together, and added CCDE design and implementation experiences, views expressed by the different stakeholders formed a type of multi-perspective "dialogue" that expanded our knowledge about implementing CD services. We hope this increased knowledge will help expand the availability of such services for consumers of any age who want to direct their own care.

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.

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,...

A knowledge-based framework for image enhancement in aviation security.

PubMed

Singh, Maneesha; Singh, Sameer; Partridge, Derek

2004-12-01

The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

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.

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.

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.

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…

Clinicians and product sales representatives: developing a relationship that works.

PubMed

Harbit, Maryanne Drake; Driggers, Zola S

2002-02-01

In today's healthcare climate, clinicians in any specialty may be required to make product selections for their practice. The skills necessary to negotiate the world of sales include information about how sales relationships are conducted, product evaluations, negotiation management, and time management. Because these skills are not taught in traditional healthcare training programs, clinicians often learn these skills through trial and error. Credible and resourceful clinical experts have current information and a working knowledge about products that are available for patients. An excellent resource for this information is the product sales representative. Literature providing information for clinicians on how to establish and maintain productive relationships with medical product representatives is scarce. This article will explain what issues to address in discussions and negotiations with product representatives. Common pitfalls that often result from not understanding the agenda of the sales representative are identified. By employing the suggested strategies, a mutually beneficial relationship can be fostered.

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.

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 for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

Embedding Human Expert Cognition Into Autonomous UAS Trajectory Planning.

PubMed

Narayan, Pritesh; Meyer, Patrick; Campbell, Duncan

2013-04-01

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

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.

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…

Report from the National Institute of Allergy and Infectious Disease Workshop on Drug Allergy

PubMed Central

Wheatley, Lisa M; Plaut, Marshall; Schwaninger, Julie M; Banerji, Aleena; Castells, Mariana; Finkelman, Fred D.; Gleich, Gerald J.; Guttman-Yassky, Emma; Mallal, Simon A.K.; Naisbitt, Dean J.; Ostrov, David A.; Phillips, Elizabeth J.; Pichler, Werner J.; Platts-Mills, Thomas A. E.; Roujeau, Jean-Claude; Schwartz, Lawrence B.; Trepanier, Lauren A.

2015-01-01

Allergic reactions to drugs are a serious public health concern. In 2013, the National Institute of Allergy and Infectious Diseases, Division of Allergy, Immunology and Transplantation, sponsored a workshop on drug allergy. International experts in the field of drug allergy with backgrounds in allergy, immunology, infectious diseases, dermatology, clinical pharmacology and pharmacogenomics discussed the current state of drug allergy research. These experts were joined by representatives from several NIH Institutes and the U.S. Food and Drug Administration (FDA). The participants identified important advances that make new research directions feasible and made suggestions for research priorities and for development of infrastructure to advance our knowledge of the mechanisms, diagnosis, management, and prevention of drug allergy. The workshop summary and recommendations are presented herein. PMID:26254053

How to help intelligent systems with different uncertainty representations cooperate with each other

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.; Kumar, Sundeep

1991-01-01

In order to solve a complicated problem one must use the knowledge from different domains. Therefore, if one wants to automatize the solution of these problems, one has to help the knowledge-based systems that correspond to these domains cooperate, that is, communicate facts and conclusions to each other in the process of decision making. One of the main obstacles to such cooperation is the fact that different intelligent systems use different methods of knowledge acquisition and different methods and formalisms for uncertainty representation. So an interface f is needed, 'translating' the values x, y, which represent uncertainty of the experts' knowledge in one system, into the values f(x), f(y) appropriate for another one. The problem of designing such an interface as a mathematical problem is formulated and solved. It is shown that the interface must be fractionally linear: f(x) = (ax + b)/(cx + d).

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…

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

Semantic layers for illustrative volume rendering.

PubMed

Rautek, Peter; Bruckner, Stefan; Gröller, Eduard

2007-01-01

Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.

Disorders of orgasm and ejaculation in men.

PubMed

McMahon, Chris G; Abdo, Carmita; Incrocci, Luca; Perelman, Michael; Rowland, David; Waldinger, Marcel; Xin, Zhong Cheng

2004-07-01

Ejaculatory/orgasmic disorders, common male sexual dysfunctions, include premature ejaculation, inhibited ejaculation, anejaculation, retrograde ejaculation and anorgasmia. To provide recommendations/guidelines concerning state-of-the-art knowledge for management of ejaculation/orgasmic disorders in men. An International Consultation in collaboration with the major urology and sexual medicine associations assembled over 200 multidisciplinary experts from 60 countries into 17 committees. Committee members established specific objectives and scopes for various male and female sexual medicine topics. The recommendations concerning state-of-the-art knowledge in the respective sexual medicine topic represent the opinion of experts from five continents developed in a process over a 2-year period. Concerning the Disorders of Ejaculation/Orgasm in Men Committee, there were nine experts from six countries. Expert opinion was based on grading of evidence-based medical literature, widespread internal committee discussion, public presentation and debate. Premature ejaculation management is dependent upon etiology. When secondary to ED, etiology-specific treatment is employed. When lifelong, initial pharmacotherapy (SSRI, topical anesthesia, PDE5 inhibitors) is appropriate. When associated with psychogenic/relationship factors, behavioral therapy is indicated. When acquired, pharmacotherapy and/or behavioral therapies are preferred. Retrograde ejaculation, diagnosed with spermatozoa and fructose in centrifuged post-ejaculatory voided urine, is managed by education, patient reassurance, pharmacotherapy or bladder neck reconstruction. Men with anejaculation or anorgasmia have a biologic failure of emission and/or psychogenic inhibited ejaculation. Men with age-related penile hypoanesthesia should be educated, reassured and be instructed in revised sexual techniques which maximize arousal. More research is needed in understanding management of men with ejaculation/orgasmic dysfunction.

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.

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…

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.

Towards Agile Ontology Maintenance

NASA Astrophysics Data System (ADS)

Luczak-Rösch, Markus

Ontologies are an appropriate means to represent knowledge on the Web. Research on ontology engineering reached practices for an integrative lifecycle support. However, a broader success of ontologies in Web-based information systems remains unreached while the more lightweight semantic approaches are rather successful. We assume, paired with the emerging trend of services and microservices on the Web, new dynamic scenarios gain momentum in which a shared knowledge base is made available to several dynamically changing services with disparate requirements. Our work envisions a step towards such a dynamic scenario in which an ontology adapts to the requirements of the accessing services and applications as well as the user's needs in an agile way and reduces the experts' involvement in ontology maintenance processes.

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

Examing nursing students' understanding of the cardiovascular system in a BSN program

NASA Astrophysics Data System (ADS)

Stuart, Parker Emerson

This study investigated the alignment of important cardiovascular system (CVS) concepts identified by expert nurses with nursing student's knowledge. Specifically, it focused on the prevalence of nursing students' alternative conceptions for these important concepts as a potential reason for a theory-practice gap in nursing (Corlett, 2000; Jordan, 1994). This is the first study to target nursing student alternative conceptions exclusively whereas other studies focused on diverse groups of undergraduates' CVS knowledge (Michael et al., 2002). The study was divided into two phases and used a case study approach with each phase of the study representing a single case. The first phase of the study sought to understand what CVS concepts expert nurses deemed relevant to their daily practice and how these experts used these concepts. The second phase identified nursing student alternative conceptions through the use of open-ended scenarios based on the results of phase I. For the first phase of the study involved four CVS expert nurses practicing in emergency rooms and cardiac intensive care units at two local hospitals. Interviews were used to elicit important CVS concepts. The expert nurses identified five broad concepts as important to their practice. These concepts were a) cardiovascular anatomical concepts; b) cardiovascular physiological concepts; c) homeostasis and diseases of the CVS; d) the interdependence and interaction of the CVS with other organ systems and e) the intersection of the CVS and technology in patient diagnosis and treatment. These finding reinforce concepts already being taught to nursing students but also suggest that instruction should focus more on how the CVS interacts with other organ systems and how technology and the CVS interact. The presence of alternative conceptions in the nursing students was examined through the use of open-ended questions. A total of 17 students fully completed the scenario questions. Results indicate that this group of nursing students hold some CVS alternative conceptions. Overall, the alternative conceptions can be grouped into four categories: a) CVS anatomy, b) blood flow and pressure, c) anthropomorphic views and d) miscellaneous alternative conceptions. These findings suggest there is indeed a misalignment between expert nurses' and nursing students' knowledge of the CVS with this misalignment potentially contributing to the theory-practice gap.

Fuzzy logic system able to detect interesting areas of a video sequence

NASA Astrophysics Data System (ADS)

De Vleeschouwer, Christophe; Marichal, Xavier; Delmot, Thierry; Macq, Benoit M. M.

1997-06-01

This paper introduces an automatic tool able to analyze the picture according to the semantic interest an observer attributes to its content. Its aim is to give a 'level of interest' to the distinct areas of the picture extracted by any segmentation tool. For the purpose of dealing with semantic interpretation of images, a single criterion is clearly insufficient because the human brain, due to its a priori knowledge and its huge memory of real-world concrete scenes, combines different subjective criteria in order to assess its final decision. The developed method permits such combination through a model using assumptions to express some general subjective criteria. Fuzzy logic enables the user to encode knowledge in a form that is very close the way experts think about the decision process. This fuzzy modeling is also well suited to represent multiple collaborating or even conflicting experts opinions. Actually, the assumptions are verified through a non-hierarchical strategy that considers them in a random order, each partial result contributing to the final one. Presented results prove that the tool is effective for a wide range of natural pictures. It is versatile and flexible in that it can be used stand-alone or can take into account any a priori knowledge about the scene.

Structure/activity relationships for biodegradability and their role in environmental assessment

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

Boethling, R.S.

1994-12-31

Assessment of biodegradability is an important part of the review process for both new and existing chemicals under the Toxic Substances Control Act. It is often necessary to estimate biodegradability because experimental data are unavailable. Structure/biodegradability relationships (SBR) are a means to this end. Quantitative SBR have been developed, but this approach has not been very useful because they apply only to a few narrowly defined classes of chemicals. In response to the need for more widely applicable methods, multivariate analysis has been used to develop biodegradability classification models. For example, recent efforts have produced four new models. Two calculatemore » the probability of rapid biodegradation and can be used for classification; the other two models allow semi-quantitative estimation of primary and ultimate biodegradation rates. All are based on multiple regressions against 36 preselected substructures plus molecular weight. Such efforts have been fairly successful by statistical criteria, but in general are hampered by a lack of large and consistent datasets. Knowledge-based expert systems may represent the next step in the evolution of SBR. In principle such systems need not be as severely limited by imperfect datasets. However, the codification of expert knowledge and reasoning is a critical prerequisite. Results of knowledge acquisition exercises and modeling based on them will also be described.« less

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.

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.

Safe Schools, Safe Students. Proceedings of the National Education Goals Panel/National Alliance of Pupil Services Organizations Conference on "Safe Schools, Safe Students: A Collaborative Approach to Achieving Safe, Disciplined, and Drug-free Schools Conducive to Learning" (Washington, D.C., October 28-29, 1994).

ERIC Educational Resources Information Center

Talley, Ronda C., Ed.; Walz, Garry R., Ed.

The "Safe Schools, Safe Students" conference brought together leading researchers and practitioners in order to share knowledge about innovative safety strategies being used in America's schools. The papers here represent the thinking of scientific experts and school-based pupil service providers who are implementing programs to prevent…

Hologram representation of design data in an expert system knowledge base

NASA Technical Reports Server (NTRS)

Shiva, S. G.; Klon, Peter F.

1988-01-01

A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

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

[Evaluation of new and emerging health technologies. Proposal for classification].

PubMed

Prados-Torres, J D; Vidal-España, F; Barnestein-Fonseca, P; Gallo-García, C; Irastorza-Aldasoro, A; Leiva-Fernández, F

2011-01-01

Review and develop a proposal for the classification of health technologies (HT) evaluated by the Health Technology Assessment Agencies (HTAA). Peer review of AETS of the previous proposed classification of HT. Analysis of their input and suggestions for amendments. Construction of a new classification. Pilot study with physicians. Andalusian Public Health System. Spanish HTAA. Experts from HTAA. Tutors of family medicine residents. HT Update classification previously made by the research team. Peer review by Spanish HTAA. Qualitative and quantitative analysis of responses. Construction of a new and pilot study based on 12 evaluation reports of the HTAA. We obtained 11 thematic categories that are classified into 6 major head groups: 1, prevention technology; 2, diagnostic technology; 3, therapeutic technologies; 4, diagnostic and therapeutic technologies; 5, organizational technology, and 6, knowledge management and quality of care. In the pilot there was a good concordance in the classification of 8 of the 12 reports reviewed by physicians. Experts agree on 11 thematic categories of HT. A new classification of HT with double entry (Nature and purpose of HT) is proposed. APPLICABILITY: According to experts, the classification of the work of the HTAA may represent a useful tool to transfer and manage knowledge. Moreover, an adequate classification of the HTAA reports would help clinicians and other potential users to locate them and this can facilitate their dissemination. Copyright © 2010 SECA. Published by Elsevier Espana. All rights reserved.

Pain care for patients with epidermolysis bullosa: best care practice guidelines.

PubMed

Goldschneider, Kenneth R; Good, Julie; Harrop, Emily; Liossi, Christina; Lynch-Jordan, Anne; Martinez, Anna E; Maxwell, Lynne G; Stanko-Lopp, Danette

2014-10-09

Inherited epidermolysis bullosa (EB) comprises a group of rare disorders that have multi-system effects and patients present with a number of both acute and chronic pain care needs. Effects on quality of life are substantial. Pain and itching are burdensome daily problems. Experience with, and knowledge of, the best pain and itch care for these patients is minimal. Evidence-based best care practice guidelines are needed to establish a base of knowledge and practice for practitioners of many disciplines to improve the quality of life for both adult and pediatric patients with EB. The process was begun at the request of Dystrophic Epidermolysis Bullosa Research Association International (DEBRA International), an organization dedicated to improvement of care, research and dissemination of knowledge for EB patients worldwide. An international panel of experts in pain and palliative care who have extensive experience caring for patients with EB was assembled. Literature was reviewed and systematically evaluated. For areas of care without direct evidence, clinically relevant literature was assessed, and rounds of consensus building were conducted. The process involved a face-to-face consensus meeting that involved a family representative and methodologist, as well as the panel of clinical experts. During development, EB family input was obtained and the document was reviewed by a wide variety of experts representing several disciplines related to the care of patients with EB. The first evidence-based care guidelines for the care of pain in EB were produced. The guidelines are clinically relevant for care of patients of all subtypes and ages, and apply to practitioners of all disciplines involved in the care of patients with EB. When the evidence suggests that the diagnosis or treatment of painful conditions differs between adults and children, it will be so noted. Evidence-based care guidelines are a means of standardizing optimal care for EB patients, whose disease is often times horrific in its effects on quality of life, and whose care is resource-intensive and difficult. The guideline development process also highlighted areas for research in order to improve further the evidence base for future care.

[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.

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.

Assessing Residents' Readiness for OR Autonomy: A Qualitative Descriptive Study of Expert Surgical Teachers' Best Practices.

PubMed

Chen, Xiaodong Phoenix; Sullivan, Amy M; Alseidi, Adnan; Kwakye, Gifty; Smink, Douglas S

Providing resident autonomy in the operating room (OR) is one of the major challenges for surgical educators today. The purpose of this study was to explore what approaches expert surgical teachers use to assess residents' readiness for autonomy in the OR. We particularly focused on the assessments that experts make prior to conducting the surgical time-out. We conducted semistructured in-depth interviews with expert surgical teachers from March 2016 to September 2016. Purposeful sampling and snowball sampling were applied to identify and recruit expert surgical teachers from general surgery residency programs across the United States to represent a range of clinical subspecialties. All interviews were audio-recorded, deidentified, and transcribed. We applied the Framework Method of content analysis, discussed and reached final consensus on the themes. We interviewed 15 expert teachers from 9 institutions. The majority (13/15) were Program or Associate Program Directors; 47% (7/15) primarily performed complex surgical operations (e.g., endocrine surgery). Five themes regarding how expert surgical teachers determine residents' readiness for OR autonomy before the surgical time-out emerged. These included 3 domains of evidence elicited about the resident (resident characteristics, medical knowledge, and beyond the current OR case), 1 variable relating to attending characteristics, and 1 variable composed of contextual factors. Experts obtained one or more examples of evidence, and adjusted residents' initial autonomy using factors from the attending variable and the context variable. Expert surgical teachers' assessments of residents' readiness for OR autonomy included 5 key components. Better understanding these inputs can contribute to both faculty and resident development, enabling increased resident autonomy and preparation for independent practice. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

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.

The power of techknowledgy.

PubMed

Kabachinski, Jeff

2010-01-01

Knowledge can range from complex, accumulated expertise (tacit knowledge) to structured explicit content like service procedures. For most of us, knowledge management should only be one of many collaborative means to an end, not the end in itself (unless you are the corporate knowledge management director or chief knowledge officer). For that reason, KM is important only to the extent that it improves an organization's capability and capacity to deal with, and develop in, the four dimensions of capturing, codifying, storing, and using knowledge. Knowledge that is more or less explicit can be embedded in procedures or represented in documents and databases and transferred with reasonable accuracy. Tacit knowledge transfer generally requires extensive personal contact. Take for example troubleshooting circuits. While troubleshooting can be procedural to an extent, it is still somewhat of an art that pulls from experience and training. This is the kind of tacit knowledge where partnerships, mentoring, or an apprenticeship, are most effective. The most successful organizations are those where knowledge management is part of everyone's job. Tacit, complex knowledge that is developed and internalized over a long period of time is almost impossible to reproduce in a document, database, or expert system. Even before the days of "core competencies", the learning organization, expert systems, and strategy focus, good managers valued the experience and know-how of employees. Today, many are recognizing that what is needed is more than a casual approach to corporate knowledge if they are to succeed. In addition, the aging population of the baby boomers may require means to capture their experience and knowledge before they leave the workforce. There is little doubt that knowledge is one of any organization's most important resources, or that knowledge workers' roles will grow in importance in the years ahead. Why would an organization believe that knowledge and knowledge workers are important, yet not advocate active management of knowledge itself? Taking advantage of already accumulated corporate intellectual property is by far the most low-cost way to increase capability and competitive stature. These are all good reasons why it might pay to take a look at your KM usage.

[Locally advanced head and neck cancers: recommendations of an expert panel and perspectives for the use of TPF regimen (docetaxel, cisplatin and fluoro-uracil) as induction therapy].

PubMed

Bardet, E; Bourhis, J; Cals, L; Fayette, J; Guigay, J; Hans, S; Saint-Guily, J Lacau; Lagarde, F; Lallemant, B; Milano, G; Rolland, F; Lefebvre, J-L

2009-10-01

The purpose of the present article was to evaluate indications, regimens, treatment modalities, and predictive factors of response to treatment in locally advanced squamous cell carcinoma of the head and neck (SCCHN). An expert panel including otolaryngology and head and neck surgery specialists, oncologists, radiotherapists and biologists analyzed the literature providing a synthesis and giving some recommendations. Findings from the main randomized phase III trials highlight that the TPF regimen (docetaxel, cisplatin, fluorouracil) represent a preferential option when induction chemotherapy is indicated in either operable or non-operable patients. Given the potential fragility of patients presenting with SCCHN, treatment modalities in routine use require applying preventive measures and tailored follow-up according to each patient's profile. As regards predictive factors of response to TPF regimen, no factor is currently validated, but ongoing trials should provide better knowledge. Progresses in induction chemotherapy have allowed improving the prognosis of patients with locally advanced SCCHN. The TPF regimen represents a major improvement in this indication, and ongoing strategic clinical trials should refine its indications.

Knowledge representation issues for explaining plans

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen; Johannes, James D.

1988-01-01

Explanations are recognized as an important facet of intelligent behavior. Unfortunately, expert systems are currently limited in their ability to provide useful, intelligent justifications of their results. We are currently investigating the issues involved in providing explanation facilities for expert planning systems. This investigation addresses three issues: knowledge content, knowledge representation, and explanation structure.

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.

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

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.

TrOn: an anatomical ontology for the beetle Tribolium castaneum.

PubMed

Dönitz, Jürgen; Grossmann, Daniela; Schild, Inga; Schmitt-Engel, Christian; Bradler, Sven; Prpic, Nikola-Michael; Bucher, Gregor

2013-01-01

In a morphological ontology the expert's knowledge is represented in terms, which describe morphological structures and how these structures relate to each other. With the assistance of ontologies this expert knowledge is made processable by machines, through a formal and standardized representation of terms and their relations to each other. The red flour beetle Tribolium castaneum, a representative of the most species rich animal taxon on earth (the Coleoptera), is an emerging model organism for development, evolution, physiology, and pest control. In order to foster Tribolium research, we have initiated the Tribolium Ontology (TrOn), which describes the morphology of the red flour beetle. The content of this ontology comprises so far most external morphological structures as well as some internal ones. All modeled structures are consistently annotated for the developmental stages larva, pupa and adult. In TrOn all terms are grouped into three categories: Generic terms represent morphological structures, which are independent of a developmental stage. In contrast, downstream of such terms are concrete terms which stand for a dissectible structure of a beetle at a specific life stage. Finally, there are mixed terms describing structures that are only found at one developmental stage. These terms combine the characteristics of generic and concrete terms with features of both. These annotation principles take into account the changing morphology of the beetle during development and provide generic terms to be used in applications or for cross linking with other ontologies and data resources. We use the ontology for implementing an intuitive search function at the electronic iBeetle-Base, which stores morphological defects found in a genome wide RNA interference (RNAi) screen. The ontology is available for download at http://ibeetle-base.uni-goettingen.de.

Knowledge management: An abstraction of knowledge base and database management systems

NASA Technical Reports Server (NTRS)

Riedesel, Joel D.

1990-01-01

Artificial intelligence application requirements demand powerful representation capabilities as well as efficiency for real-time domains. Many tools exist, the most prevalent being expert systems tools such as ART, KEE, OPS5, and CLIPS. Other tools just emerging from the research environment are truth maintenance systems for representing non-monotonic knowledge, constraint systems, object oriented programming, and qualitative reasoning. Unfortunately, as many knowledge engineers have experienced, simply applying a tool to an application requires a large amount of effort to bend the application to fit. Much work goes into supporting work to make the tool integrate effectively. A Knowledge Management Design System (KNOMAD), is described which is a collection of tools built in layers. The layered architecture provides two major benefits; the ability to flexibly apply only those tools that are necessary for an application, and the ability to keep overhead, and thus inefficiency, to a minimum. KNOMAD is designed to manage many knowledge bases in a distributed environment providing maximum flexibility and expressivity to the knowledge engineer while also providing support for efficiency.

Test and Evaluation for Enhanced Security: A Quantitative Method to Incorporate Expert Knowledge into Test Planning Decisions.

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

Rizzo, Davinia; Blackburn, Mark

Complex systems are comprised of technical, social, political and environmental factors as well as the programmatic factors of cost, schedule and risk. Testing these systems for enhanced security requires expert knowledge in many different fields. It is important to test these systems to ensure effectiveness, but testing is limited to due cost, schedule, safety, feasibility and a myriad of other reasons. Without an effective decision framework for Test and Evaluation (T&E) planning that can take into consideration technical as well as programmatic factors and leverage expert knowledge, security in complex systems may not be assessed effectively. Therefore, this paper coversmore » the identification of the current T&E planning problem and an approach to include the full variety of factors and leverage expert knowledge in T&E planning through the use of Bayesian Networks (BN).« less

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.

Marketing practitioner’s tacit knowledge acquisition using Repertory Grid Technique (RTG)

NASA Astrophysics Data System (ADS)

Azmi, Afdhal; Adriman, Ramzi

2018-05-01

The tacit knowledge of Marketing practitioner’s experts is excellent resources and priceless. It takes into account their experiential, skill, ideas, belief systems, insight and speculation into management decision-making. This expertise is an individual intuitive judgment and personal shortcuts to complete the work efficiently. Tacit knowledge of Marketing practitioner’s experts is one of best problem solutions in marketing strategy, environmental analysis, product management and partner’s relationship. This paper proposes the acquisition method of tacit knowledge from Marketing practitioner’s using Repertory Grid Technique (RGT). The RGT is a software application for tacit acquisition knowledge to provide a systematic approach to capture and acquire the constructs from an individual. The result shows the understanding of RGT could make TKE and MPE get a good result in capturing and acquiring tacit knowledge of Marketing practitioner’s experts.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2010-01-01

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys. PMID:20530533

Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding.

PubMed

Menger, Vincent; Spruit, Marco; Hagoort, Karin; Scheepers, Floor

2016-01-01

The surge in the amount of available data in health care enables a novel, exploratory research approach that revolves around finding new knowledge and unexpected hypotheses from data instead of carrying out well-defined data analysis tasks. We propose a specification of the Cross Industry Standard Process for Data Mining (CRISP-DM), suitable for conducting expert sessions that focus on finding new knowledge and hypotheses in collaboration with local workforce. Our proposed specification that we name CRISP-IDM is evaluated in a case study at the psychiatry department of the University Medical Center Utrecht. Expert interviews were conducted to identify seven research themes in the psychiatry department, which were researched in cooperation with local health care professionals using data visualization as a modeling tool. During 19 expert sessions, two results that were directly implemented and 29 hypotheses for further research were found, of which 24 were not imagined during the initial expert interviews. Our work demonstrates the viability and benefits of involving work floor people in the analyses and the possibility to effectively find new knowledge and hypotheses using our CRISP-IDM method.

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…

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.

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.

Development and psychometric evaluation of a cardiovascular risk and disease management knowledge assessment tool.

PubMed

Rosneck, James S; Hughes, Joel; Gunstad, John; Josephson, Richard; Noe, Donald A; Waechter, Donna

2014-01-01

This article describes the systematic construction and psychometric analysis of a knowledge assessment instrument for phase II cardiac rehabilitation (CR) patients measuring risk modification disease management knowledge and behavioral outcomes derived from national standards relevant to secondary prevention and management of cardiovascular disease. First, using adult curriculum based on disease-specific learning outcomes and competencies, a systematic test item development process was completed by clinical staff. Second, a panel of educational and clinical experts used an iterative process to identify test content domain and arrive at consensus in selecting items meeting criteria. Third, the resulting 31-question instrument, the Cardiac Knowledge Assessment Tool (CKAT), was piloted in CR patients to ensure use of application. Validity and reliability analyses were performed on 3638 adults before test administrations with additional focused analyses on 1999 individuals completing both pretreatment and posttreatment administrations within 6 months. Evidence of CKAT content validity was substantiated, with 85% agreement among content experts. Evidence of construct validity was demonstrated via factor analysis identifying key underlying factors. Estimates of internal consistency, for example, Cronbach's α = .852 and Spearman-Brown split-half reliability = 0.817 on pretesting, support test reliability. Item analysis, using point biserial correlation, measured relationships between performance on single items and total score (P < .01). Analyses using item difficulty and item discrimination indices further verified item stability and validity of the CKAT. A knowledge instrument specifically designed for an adult CR population was systematically developed and tested in a large representative patient population, satisfying psychometric parameters, including validity and reliability.

Report from the National Institute of Allergy and Infectious Diseases workshop on drug allergy.

PubMed

Wheatley, Lisa M; Plaut, Marshall; Schwaninger, Julie M; Banerji, Aleena; Castells, Mariana; Finkelman, Fred D; Gleich, Gerald J; Guttman-Yassky, Emma; Mallal, Simon A K; Naisbitt, Dean J; Ostrov, David A; Phillips, Elizabeth J; Pichler, Werner J; Platts-Mills, Thomas A E; Roujeau, Jean-Claude; Schwartz, Lawrence B; Trepanier, Lauren A

2015-08-01

Allergic reactions to drugs are a serious public health concern. In 2013, the Division of Allergy, Immunology, and Transplantation of the National Institute of Allergy and Infectious Diseases sponsored a workshop on drug allergy. International experts in the field of drug allergy with backgrounds in allergy, immunology, infectious diseases, dermatology, clinical pharmacology, and pharmacogenomics discussed the current state of drug allergy research. These experts were joined by representatives from several National Institutes of Health institutes and the US Food and Drug Administration. The participants identified important advances that make new research directions feasible and made suggestions for research priorities and for development of infrastructure to advance our knowledge of the mechanisms, diagnosis, management, and prevention of drug allergy. The workshop summary and recommendations are presented herein. Published by Elsevier Inc.

Conditioning of high voltage radio frequency cavities by using fuzzy logic in connection with rule based programming

NASA Astrophysics Data System (ADS)

Perreard, S.; Wildner, E.

1994-12-01

Many processes are controlled by experts using some kind of mental model to decide on actions and make conclusions. This model, based on heuristic knowledge, can often be represented by rules and does not have to be particularly accurate. Such is the case for the problem of conditioning high voltage RF cavities; the expert has to decide, by observing some criteria, whether to increase or to decrease the voltage and by how much. A program has been implemented which can be applied to a class of similar problems. The kernel of the program is a small rule base, which is independent of the kind of cavity. To model a specific cavity, we use fuzzy logic which is implemented as a separate routine called by the rule base, to translate from numeric to symbolic information.

Experts' Views on Using History and Philosophy of Science in the Practice of Physics Instruction

NASA Astrophysics Data System (ADS)

Galili, Igal; Hazan, Amnon

This study examines the views of a representative sample of experts in physics, physics education and history and philosophy of science (HPS) on the incorporation of HPS based materials in physics instruction. The obtained spectrum of views addresses three areas: the rationale to include HPS, the most appropriate ways of doing so, and anticipated difficulties in such a new educational approach. The elicited views, interpreted and categorized, reflect the attitude of the community of science educators in Israeli colleges and universities with regard to the subject. The constructed profiles indicate low awareness of the recent changes in the understanding of learning and the role of HPS in the light of these changes. Such knowledge can guide the activities of those who devote their efforts to constructing and implementing learning materials utilizing HPS contents in science education.

International Pediatric MS Study Group Clinical Trials Summit: meeting report.

PubMed

Chitnis, Tanuja; Tardieu, Marc; Amato, Maria Pia; Banwell, Brenda; Bar-Or, Amit; Ghezzi, Angelo; Kornberg, Andrew; Krupp, Lauren B; Pohl, Daniela; Rostasy, Kevin; Tenembaum, Silvia; Waubant, Emmanuelle; Wassmer, Evangeline

2013-03-19

Pediatric studies for new biological agents are mandated by recent legislation, necessitating careful thought to evaluation of emerging multiple sclerosis (MS) therapies in children with MS. Challenges include a small patient population, the lack of prior randomized clinical trials, and ethical concerns. The goal of this meeting was to assess areas of consensus regarding clinical trial design and outcome measures among academic experts involved in pediatric MS care and research. The Steering Committee of the International Pediatric MS Study Group identified key focus areas for discussion. A total of 69 meeting attendees were assembled, including 35 academic experts. Regulatory and pharmaceutical representatives also attended, and provided input, which informed academic expert consensus decisions. The academic experts agreed that clinical trials were necessary in pediatric MS to obtain pharmacokinetic, safety and efficacy data, and regulatory approval allowing for greater medication access. The academic experts agreed that relapse was an appropriate primary outcome measure for phase III pediatric trials. An international standardized cognitive battery was identified. The pros and cons of various trial designs were discussed. Guidelines surrounding MRI studies, pharmacokinetics, pharmacodynamics, and registries were developed. The academic experts agreed that given the limited subject pool, a stepwise approach to the launch of clinical trials for the most promising medications is necessary in order to ensure study completion. Alternative approaches could result in unethical exposure of patients to trial conditions without gaining knowledge. Consensus points for conduct of clinical trials in the rare disease pediatric MS were identified amongst a panel of academic experts, informed by regulatory and industry stakeholders.

[Development And Validation Of A Breastfeeding Knowledge And Skills Questionnaire].

PubMed

Gómez Fernández-Vegue, M; Menéndez Orenga, M

2015-12-01

Pediatricians play a key role in the onset and duration of breastfeeding. Although it is known that they lack formal education on this subject, there are currently no validated tools available to assess pediatrician knowledge regarding breastfeeding. To develop and validate a Breastfeeding Knowledge and Skills Questionnaire for Pediatricians. Once the knowledge areas were defined, a representative sample of pediatricians was chosen to carry out the survey. After pilot testing, non-discriminating questions were removed. Content validity was assessed by 14 breastfeeding experts, who examined the test, yielding 22 scorable items (maximum score: 26 points). To approach criterion validity, it was hypothesized that a group of pediatricians with a special interest in breastfeeding (1) would obtain better results than pediatricians from a hospital without a maternity ward (2), and the latter would obtain a higher score than the medical residents of Pediatrics training in the same hospital (3). The questionnaire was also evaluated before and after a basic course in breastfeeding. Breastfeeding experts have an index of agreement of >.90 for each item. The 3 groups (n=82) were compared, finding significant differences between group (1) and the rest. Moreover, an improvement was observed in the participants who attended the breastfeeding course (n=31), especially among those with less initial knowledge. Regarding reliability, internal consistency (KR-20=.87), interobserver agreement, and temporal stability were examined, with satisfactory results. A practical and self-administered tool is presented to assess pediatrician knowledge regarding breastfeeding, with a documented validity and reliability. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

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…

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.

Expert Seeker

NASA Technical Reports Server (NTRS)

Fernandez, Becerra

2003-01-01

Expert Seeker is a computer program of the knowledge-management-system (KMS) type that falls within the category of expertise-locator systems. The main goal of the KMS system implemented by Expert Seeker is to organize and distribute knowledge of who are the domain experts within and without a given institution, company, or other organization. The intent in developing this KMS was to enable the re-use of organizational knowledge and provide a methodology for querying existing information (including structured, semistructured, and unstructured information) in a way that could help identify organizational experts. More specifically, Expert Seeker was developed to make it possible, by use of an intranet, to do any or all of the following: Assist an employee in identifying who has the skills needed for specific projects and to determine whether the experts so identified are available. Assist managers in identifying employees who may need training opportunities. Assist managers in determining what expertise is lost when employees retire or otherwise leave. Facilitate the development of new ways of identifying opportunities for innovation and minimization of duplicated efforts. Assist employees in achieving competitive advantages through the application of knowledge-management concepts and related systems. Assist external organizations in requesting speakers for specific engagements or determining from whom they might be able to request help via electronic mail. Help foster an environment of collaboration for rapid development in today's environment, in which it is increasingly necessary to assemble teams of experts from government, universities, research laboratories, and industries, to quickly solve problems anytime, anywhere. Make experts more visible. Provide a central repository of information about employees, including information that, heretofore, has typically not been captured by the human-resources systems (e.g., information about past projects, patents, or hobbies). Unify myriad collections of data into Web-enabled repository that could easily be searched for relevant data.

Bridging science and traditional knowledge to assess cumulative impacts of stressors on ecosystem health.

PubMed

Mantyka-Pringle, Chrystal S; Jardine, Timothy D; Bradford, Lori; Bharadwaj, Lalita; Kythreotis, Andrew P; Fresque-Baxter, Jennifer; Kelly, Erin; Somers, Gila; Doig, Lorne E; Jones, Paul D; Lindenschmidt, Karl-Erich

2017-05-01

Cumulative environmental impacts driven by anthropogenic stressors lead to disproportionate effects on indigenous communities that are reliant on land and water resources. Understanding and counteracting these effects requires knowledge from multiple sources. Yet the combined use of Traditional Knowledge (TK) and Scientific Knowledge (SK) has both technical and philosophical hurdles to overcome, and suffers from inherently imbalanced power dynamics that can disfavour the very communities it intends to benefit. In this article, we present a 'two-eyed seeing' approach for co-producing and blending knowledge about ecosystem health by using an adapted Bayesian Belief Network for the Slave River and Delta region in Canada's Northwest Territories. We highlight how bridging TK and SK with a combination of field data, interview transcripts, existing models, and expert judgement can address key questions about ecosystem health when considerable uncertainty exists. SK indicators (e.g., bird counts, mercury in fish, water depth) were graded as moderate, whereas TK indicators (e.g., bird usage, fish aesthetics, changes to water flow) were graded as being poor in comparison to the past. SK indicators were predominantly spatial (i.e., comparing to other locations) while the TK indicators were predominantly temporal (i.e., comparing across time). After being populated by 16 experts (local harvesters, Elders, governmental representatives, and scientists) using both TK and SK, the model output reported low probabilities that the social-ecological system is healthy as it used to be. We argue that it is novel and important to bridge TK and SK to address the challenges of environmental change such as the cumulative impacts of multiple stressors on ecosystems and the services they provide. This study presents a critical social-ecological tool for widening the evidence-base to a more holistic understanding of the system dynamics of multiple environmental stressors in ecosystems and for developing more effective knowledge-inclusive partnerships between indigenous communities, researchers and policy decision-makers. This represents new transformational empirical insights into how wider knowledge discourses can contribute to more effective adaptive co-management governance practices and solutions for the resilience and sustainability of ecosystems in Northern Canada and other parts of the world with strong indigenous land tenure. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

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.

KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

NASA Technical Reports Server (NTRS)

Han, Chia Yung; Wan, Liqun; Wee, William G.

1990-01-01

A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

The adversarial court system and the expert medical witness: 'The truth the whole truth and nothing but the truth?'.

PubMed

Ryan, Matthew

2003-06-01

This discussion aims to provide the occasional medical expert witness with background knowledge of the adversarial court system and the role of the medical expert witness within it. The parallel evolution of the adversarial and inquisitorial legal systems has been more out of tradition rather than any systematic review of the effectiveness of one system or the other. Both legal systems have their merits and limitations. Witnesses within the adversarial system are required to present evidence in a structured and highly stylized format consisting of 'evidence in chief' followed by 'cross-examination'. This format is an attempt to exclude unreliable evidence. The medical witness is an 'expert' by means of specialized knowledge not possessed by the general public. This distinction allows the expert medical witness to offer his or her opinion as evidence. There remain several limitations to the expert's evidence and these relate to common knowledge, field of expertise and the 'ultimate issue'. The current practice of selection of expert medical witnesses is seriously flawed with several pressures operating to maximise bias and inaccurate testimony. Doctors should not only anticipate change in this area they should lead reform in this area.

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.

General public knowledge, preferred dosage forms, and beliefs toward medicines in western Saudi Arabia.

PubMed

Alhaddad, Mahmoud S; Abdallah, Qasem M; Alshakhsheer, Sami M; Alosaimi, Salman B; Althmali, Ahmed R; Alahmari, Solaiman A

2014-06-01

To measure general public knowledge, source of knowledge, preferred dosage forms, and beliefs toward medicines. A cross-sectional study design using convenience-sampling technique was used. A pre-validated questionnaire was designed and distributed to the general public through face-to-face interviews. All data were analyzed, and p-values less than 0.05 were considered significant. The study took place in the Clinical Pharmacy Department, Taif University, Taif, Kingdom of Saudi Arabia between August 2012 and February 2013 RESULTS: Nine hundred participants successfully responded to this study. Males represented two-thirds of the respondents (66.8%). In addition, 52% of respondents were of high education level. Modern (74.2%) and alternative medicines (88.7%) were understood by most respondents. Tablets (69.6%) and capsules (37.6%) represented the highest preferred dosage forms. In addition, physicians (66.6%) and pharmacists (46.2%) were the main sources of information regarding medicines. In terms of beliefs, respondents showed wrong beliefs in many statements used in this study. There is a need to improve public knowledge and beliefs toward medicines as well as utilizing public preferred dosage forms. In addition, pharmacists should play a major role in these programs since they are experts on medicines and play a more active role in patient education and counseling.

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

40 CFR 194.26 - Expert judgment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... judgment elicitation processes and the reasoning behind those results. Documentation of interviews used to elicit judgments from experts, the questions or issues presented for elicitation of expert judgment... expert judgment elicitation comports with the level of knowledge required by the questions or issues...

An Alternative Expert Knowledge Transfer Model: A Case Study of an Indigenous Storytelling Approach

ERIC Educational Resources Information Center

Spaulding, Roderick Jay

2010-01-01

The increasing complexity of technical work, the demand for highly skilled workers, and the vital challenges facing the world at large have combined to create a need for better ways to transfer knowledge, especially expert knowledge. In this dissertation, I attempted to see if an approach to this process that is more holistic than is typical in…

Best Practices for Reduction of Uncertainty in CFD Results

NASA Technical Reports Server (NTRS)

Mendenhall, Michael R.; Childs, Robert E.; Morrison, Joseph H.

2003-01-01

This paper describes a proposed best-practices system that will present expert knowledge in the use of CFD. The best-practices system will include specific guidelines to assist the user in problem definition, input preparation, grid generation, code selection, parameter specification, and results interpretation. The goal of the system is to assist all CFD users in obtaining high quality CFD solutions with reduced uncertainty and at lower cost for a wide range of flow problems. The best-practices system will be implemented as a software product which includes an expert system made up of knowledge databases of expert information with specific guidelines for individual codes and algorithms. The process of acquiring expert knowledge is discussed, and help from the CFD community is solicited. Benefits and challenges associated with this project are examined.

[Multicenter evaluation of the Nutri-Expert Telematic System in diabetic patients].

PubMed

Turnin, M C; Bolzonella-Pene, C; Dumoulin, S; Cerf, I; Charpentier, G; Sandre-Banon, D; Valensi, P; Grenier, J L; Cathelineau, G; Mattei, C

1995-02-01

Nutri-Expert is a system for self-monitoring and dietetic education, accessible through Minitel. A preliminary randomised evaluation of one hundred diabetic patients in the Midi-Pyrénées region showed that Nutri-Expert improved dietetic knowledge, dietary habits and metabolic balance. The aim of the present study was to show that the system can be successfully prescribed to patients by physicians outside the center which originated it, indicating the benefit of a wider use of Nutri-Expert, among the diabetic population. One hundred and fifty-five patients, recruited by six French centres of diabetology, used Nutri-Expert from their homes for six months. Clinical examination, tests of dietetic knowledge and biological tests, including lipid fractions, were carried out before and after six months of use. After six months, there was a significant improvement in the patients' dietetic knowledge and in some biological parameters. Nutri-Expert is thus useful even when prescribed by a centre other than the hospital which devised the system. It is an additional beneficial tool in the ambulatory management of diabetic patients.

Computers Simulate Human Experts.

ERIC Educational Resources Information Center

Roberts, Steven K.

1983-01-01

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

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.

The development of a prototype intelligent user interface subsystem for NASA's scientific database systems

NASA Technical Reports Server (NTRS)

Campbell, William J.; Roelofs, Larry H.; Short, Nicholas M., Jr.

1987-01-01

The National Space Science Data Center (NSSDC) has initiated an Intelligent Data Management (IDM) research effort which has as one of its components the development of an Intelligent User Interface (IUI).The intent of the latter is to develop a friendly and intelligent user interface service that is based on expert systems and natural language processing technologies. The purpose is to support the large number of potential scientific and engineering users presently having need of space and land related research and technical data but who have little or no experience in query languages or understanding of the information content or architecture of the databases involved. This technical memorandum presents prototype Intelligent User Interface Subsystem (IUIS) using the Crustal Dynamics Project Database as a test bed for the implementation of the CRUDDES (Crustal Dynamics Expert System). The knowledge base has more than 200 rules and represents a single application view and the architectural view. Operational performance using CRUDDES has allowed nondatabase users to obtain useful information from the database previously accessible only to an expert database user or the database designer.

Applications of artificial intelligence to digital photogrammetry

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

Kretsch, J.L.

1988-01-01

The aim of this research was to explore the application of expert systems to digital photogrammetry, specifically to photogrammetric triangulation, feature extraction, and photogrammetric problem solving. In 1987, prototype expert systems were developed for doing system startup, interior orientation, and relative orientation in the mensuration stage. The system explored means of performing diagnostics during the process. In the area of feature extraction, the relationship of metric uncertainty to symbolic uncertainty was the topic of research. Error propagation through the Dempster-Shafer formalism for representing evidence was performed in order to find the variance in the calculated belief values due to errorsmore » in measurements made together the initial evidence needed to being labeling of observed image features with features in an object model. In photogrammetric problem solving, an expert system is under continuous development which seeks to solve photogrammetric problems using mathematical reasoning. The key to the approach used is the representation of knowledge directly in the form of equations, rather than in the form of if-then rules. Then each variable in the equations is treated as a goal to be solved.« less

Software Assists in Responding to Anomalous Conditions

NASA Technical Reports Server (NTRS)

James, Mark; Kronbert, F.; Weiner, A.; Morgan, T.; Stroozas, B.; Girouard, F.; Hopkins, A.; Wong, L.; Kneubuhl, J.; Malina, R.

2004-01-01

Fault Induced Document Retrieval Officer (FIDO) is a computer program that reduces the need for a large and costly team of engineers and/or technicians to monitor the state of a spacecraft and associated ground systems and respond to anomalies. FIDO includes artificial-intelligence components that imitate the reasoning of human experts with reference to a knowledge base of rules that represent failure modes and to a database of engineering documentation. These components act together to give an unskilled operator instantaneous expert assistance and access to information that can enable resolution of most anomalies, without the need for highly paid experts. FIDO provides a system state summary (a configurable engineering summary) and documentation for diagnosis of a potentially failing component that might have caused a given error message or anomaly. FIDO also enables high-level browsing of documentation by use of an interface indexed to the particular error message. The collection of available documents includes information on operations and associated procedures, engineering problem reports, documentation of components, and engineering drawings. FIDO also affords a capability for combining information on the state of ground systems with detailed, hierarchically-organized, hypertext- enabled documentation.

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.

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

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.

Social Network Analysis of the Irish Biotech Industry: Implications for Digital Ecosystems

NASA Astrophysics Data System (ADS)

van Egeraat, Chris; Curran, Declan

This paper presents an analysis of the socio-spatial structures of innovation, collaboration and knowledge flow among SMEs in the Irish biotech sector. The study applies social network analysis to determine the structure of networks of company directors and inventors in the biotech sector. In addition, the article discusses the implications of the findings for the role and contours of a biotech digital ecosystem. To distil these lessons, the research team organised a seminar which was attended by representatives of biotech actors and experts.

Defense Small Business Innovation Research Program (SBIR). Volume 4. Defense Agency Projects, Abstracts of Phase 1 Awards from FY 1989 SBIR Solicitation

DTIC Science & Technology

1990-04-01

EXPLOSIVE ACTIVITY . FINDINGS AND MEASUREMENTS FROM EACH IMAGE WILL BE COMBINED IN A GEOGRAPHIC INFORMATION DATA BASE . VARIOUS IMAGE AND MAP PROJECTS WILL BE...PROPOSAL OF LAND MINES DETECTION BY A NUCLEAR ACTIVATION METHOD IS BASED ON A NEW EXTREMELY INTENSE, COMPACT PULSED SOURCE OF 14.1 MeV NEUTRONS (WITH A...CONVENTIONAL KNOWLEDGE- BASED SYSTEMS TOPIC# 38 OFFICE: PM/SBIR IDENT#: 33862 CASE- BASED REASONING (CBR) REPRESENTS A POWERFUL NEW PARADIGM FOR BUILDING EXPERT

Fault diagnosis in orbital refueling operations

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1988-01-01

Usually, operation manuals are provided for helping astronauts during space operations. These manuals include normal and malfunction procedures. Transferring operation manual knowledge into a computerized form is not a trivial task. This knowledge is generally written by designers or operation engineers and is often quite different from the user logic. The latter is usually a compiled version of the former. Experiments are in progress to assess the user logic. HORSES (Human - Orbital Refueling System - Expert System) is an attempt to include both of these logics in the same tool. It is designed to assist astronauts during monitoring and diagnosis tasks. Basically, HORSES includes a situation recognition level coupled to an analytical diagnoser, and a meta-level working on both of the previous levels. HORSES is a good tool for modeling task models and is also more broadly useful for knowledge design. The presentation is represented by abstract and overhead visuals only.

Semantically enabling pharmacogenomic data for the realization of personalized medicine

PubMed Central

Samwald, Matthias; Coulet, Adrien; Huerga, Iker; Powers, Robert L; Luciano, Joanne S; Freimuth, Robert R; Whipple, Frederick; Pichler, Elgar; Prud’hommeaux, Eric; Dumontier, Michel; Marshall, M Scott

2014-01-01

Understanding how each individual’s genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients’ medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products. PMID:22256869

Computational Fact Checking from Knowledge Networks

PubMed Central

Ciampaglia, Giovanni Luca; Shiralkar, Prashant; Rocha, Luis M.; Bollen, Johan; Menczer, Filippo; Flammini, Alessandro

2015-01-01

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation. PMID:26083336

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.

Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding

PubMed Central

Scheepers, Floor

2016-01-01

The surge in the amount of available data in health care enables a novel, exploratory research approach that revolves around finding new knowledge and unexpected hypotheses from data instead of carrying out well-defined data analysis tasks. We propose a specification of the Cross Industry Standard Process for Data Mining (CRISP-DM), suitable for conducting expert sessions that focus on finding new knowledge and hypotheses in collaboration with local workforce. Our proposed specification that we name CRISP-IDM is evaluated in a case study at the psychiatry department of the University Medical Center Utrecht. Expert interviews were conducted to identify seven research themes in the psychiatry department, which were researched in cooperation with local health care professionals using data visualization as a modeling tool. During 19 expert sessions, two results that were directly implemented and 29 hypotheses for further research were found, of which 24 were not imagined during the initial expert interviews. Our work demonstrates the viability and benefits of involving work floor people in the analyses and the possibility to effectively find new knowledge and hypotheses using our CRISP-IDM method. PMID:27630736

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.

Heart health risk assessment system: a nonintrusive proposal using ontologies and expert rules.

PubMed

Garcia-Valverde, Teresa; Muñoz, Andrés; Arcas, Francisco; Bueno-Crespo, Andrés; Caballero, Alberto

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions.

PubMed

Stewart, G B; Mengersen, K; Meader, N

2014-03-01

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to 'empty' reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence. Copyright © 2013 John Wiley & Sons, Ltd.

Heart Health Risk Assessment System: A Nonintrusive Proposal Using Ontologies and Expert Rules

PubMed Central

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch. PMID:25045715

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.

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…

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.

Knowledge Brokers in the Making: Opportunities to Connect Researchers and Stakeholders

NASA Astrophysics Data System (ADS)

Pennell, K. G.; Pennell, M. C.

2014-12-01

Environmental science and engineering graduate students often lack training on how to communicate with policy decision makers who are grappling with questions to which research is responding. They communicate directly with mutual experts, but are many times unable to engage with non-experts about their research, thereby limiting the reach and impact of their findings. This presentation highlights opportunities within environmental science and engineering research to create opportunities for researchers to hone skills as knowledge brokers, so they learn ways to meaningfully engage with a range of stakeholders. A knowledge broker is an individual who connects scientific experts and relevant stakeholders with meaningful and useable information. Recognizing that information must flow in multiple directions, the knowledge broker must quickly and effectively translate needs and questions using established relationships. It is these relationships, as well as the synthesis of scientific knowledge into useable information, on which the success of the knowledge broker lies. Using lessons learned, as well as communication science theory related to knowledge brokering, this presentation highlights training opportunities for knowledge brokers who are primarily educated in science and engineering fields, yet seek to engage with societally relevant stakeholders. We present case study examples of knowledge brokering within two large multi-disciplinary research centers. These centers provide unique experiences for researchers to build relationships with stakeholders, so that the scientific experts not only create novel research within their specific discipline, but also inform policy decision makers, community members and regulatory officials.

Personalized Knowledge Transfer for Caregiving Relatives.

PubMed

Wolff, Dominik; Behrends, Marianne; Gerlach, Mario; Kupka, Thomas; Marschollek, Michael

2018-01-01

Caregiving relatives have to manage very diverse tasks and need a lot of care-relevant knowledge. For most of them it is not easy to find the knowledge required. Thus, a personalized knowledge transfer for caregiving relatives is necessary. Against this background, methods to determine the personal relevance and importance of knowledge resources for caregiving relatives are developed. To evaluate these methods, an exemplary fictitious person is created by experts in Nursing Science. In this evaluation, the approach's results are compared with an expert opinion. The approach indicates that a personalized knowledge transfer is possible, providing caregiving relatives with necessary care knowledge according to their personal life situation.

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Using the Internet to Collaborate with Consumers in Redefining a Psychosocial Agenda for Families with Hereditary Breast Cancer

DTIC Science & Technology

2007-06-01

expert patient and has broad relevance in terms of people developing the knowledge to maintain their health and manage illness, thereby having...growing controversy concerning the expert patient [32] revolves around whether it is possible for lay persons to actually renegotiate a more balanced...participating in this thread seem to fulfill the more empowering view of the expert patient by integrat- ing personal and medical knowledge to renegotiate

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.

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.

Passenger head in impact with frontal airbag in OOP postures

NASA Astrophysics Data System (ADS)

Ovidiu Soica, Adrian; Toganel, George-Radu

2017-10-01

Road accidents represent an aspect of road traffic that may lead negative consequences. In order to solve the problems associated with such events, interdisciplinary knowledge is called for, complex teams of engineers, doctors, lawyers, experts working together in order to reduce the severity of such events. Road safety is a continuous concern for both experts and various government organizations with the aim of protecting the lives of the participants in traffic. It has been estimated that the costs of traffic accidents account for 1-3% of a country GDP, depending on the level of country development [26]. In this paper we analyze a particular class of cases of injuries caused to passengers caused by the inflation of the frontal airbag when they are with the passenger out of position. Head kinematics, accelerations, as well as the severity of injuries expressed by HIC, as related to the AIS scale have been analysed.

[Thrombosis and post-thrombotic syndrome as a consequence of an accident].

PubMed

Wahl, U; Hirsch, T

2015-10-01

Phlebothromboses represent alarming complications in accident victims since they can cause fatal pulmonary embolisms. More than half of those affected also develop post-thrombotic syndrome in the course of the illness. In addition to making clinical assessments, the traumatologist should also have fundamental knowledge about diagnostic methods and be familiar with interpreting internal findings. Colour-coded duplex sonography plays a central role in diagnosing thrombosis and in assessing functional limitations. Further information can be gathered from various phlebological procedures. The expert evaluation of the immediate, as well as the long-term consequences of an accident frequently require leg swelling to be classified. It is not uncommon for post-thrombotic syndrome to be diagnosed for the first time during this process. An additional vascular appraisal is often required. An appreciation of social-medical and insurance-related aspects means a high degree of responsibility is placed on the expert.

Allocation of surgical procedures to operating rooms.

PubMed

Ozkarahan, I

1995-08-01

Reduction of health care costs is of paramount importance in our time. This paper is a part of the research which proposes an expert hospital decision support system for resource scheduling. The proposed system combines mathematical programming, knowledge base, and database technologies, and what is more, its friendly interface is suitable for any novice user. Operating rooms in hospitals represent big investments and must be utilized efficiently. In this paper, first a mathematical model similar to job shop scheduling models is developed. The model loads surgical cases to operating rooms by maximizing room utilization and minimizing overtime in a multiple operating room setting. Then a prototype expert system which replaces the expertise of the operations research analyst for the model, drives the modelbase, database, and manages the user dialog is developed. Finally, an overview of the sequencing procedures for operations within an operating room is also presented.

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.

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.

Assessing communities of practice in health policy: a conceptual framework as a first step towards empirical research

PubMed Central

2013-01-01

Communities of Practice (CoPs) are groups of people that interact regularly to deepen their knowledge on a specific topic. Thanks to information and communication technologies, CoPs can involve experts distributed across countries and adopt a ‘transnational’ membership. This has allowed the strategy to be applied to domains of knowledge such as health policy with a global perspective. CoPs represent a potentially valuable tool for producing and sharing explicit knowledge, as well as tacit knowledge and implementation practices. They may also be effective in creating links among the different ‘knowledge holders’ contributing to health policy (e.g., researchers, policymakers, technical assistants, practitioners, etc.). CoPs in global health are growing in number and activities. As a result, there is an increasing need to document their progress and evaluate their effectiveness. This paper represents a first step towards such empirical research as it aims to provide a conceptual framework for the analysis and assessment of transnational CoPs in health policy. The framework is developed based on the findings of a literature review as well as on our experience, and reflects the specific features and challenges of transnational CoPs in health policy. It organizes the key elements of CoPs into a logical flow that links available resources and the capacity to mobilize them, with knowledge management activities and the expansion of knowledge, with changes in policy and practice and, ultimately, with an improvement in health outcomes. Additionally, the paper addresses the challenges in the operationalization and empirical application of the framework. PMID:24139662

Assessing communities of practice in health policy: a conceptual framework as a first step towards empirical research.

PubMed

Bertone, Maria Paola; Meessen, Bruno; Clarysse, Guy; Hercot, David; Kelley, Allison; Kafando, Yamba; Lange, Isabelle; Pfaffmann, Jérôme; Ridde, Valéry; Sieleunou, Isidore; Witter, Sophie

2013-10-20

Communities of Practice (CoPs) are groups of people that interact regularly to deepen their knowledge on a specific topic. Thanks to information and communication technologies, CoPs can involve experts distributed across countries and adopt a 'transnational' membership. This has allowed the strategy to be applied to domains of knowledge such as health policy with a global perspective. CoPs represent a potentially valuable tool for producing and sharing explicit knowledge, as well as tacit knowledge and implementation practices. They may also be effective in creating links among the different 'knowledge holders' contributing to health policy (e.g., researchers, policymakers, technical assistants, practitioners, etc.). CoPs in global health are growing in number and activities. As a result, there is an increasing need to document their progress and evaluate their effectiveness. This paper represents a first step towards such empirical research as it aims to provide a conceptual framework for the analysis and assessment of transnational CoPs in health policy.The framework is developed based on the findings of a literature review as well as on our experience, and reflects the specific features and challenges of transnational CoPs in health policy. It organizes the key elements of CoPs into a logical flow that links available resources and the capacity to mobilize them, with knowledge management activities and the expansion of knowledge, with changes in policy and practice and, ultimately, with an improvement in health outcomes. Additionally, the paper addresses the challenges in the operationalization and empirical application of the framework.

Validation of a semi-quantitative job exposure matrix at a Söderberg aluminum smelter.

PubMed

Friesen, M C; Demers, P A; Spinelli, J J; Le, N D

2003-08-01

We tested the validity of a job exposure matrix (JEM) for coal tar pitch volatiles (CTPV) at a Söderberg aluminum smelter. The JEM had been developed by a committee of company hygienists and union representatives for an earlier study of cancer incidence and mortality. Our aim was to test the validity and reliability of the expert-based assignments. Personal CTPV exposure measurements (n = 1879) overlapped 11 yr of the JEM. The arithmetic mean was calculated for 35 job/time period combinations (35% of the exposed work history), categorized using the original exposure intervals, and compared with the expert-based assignments. The expert-based and the measurement-based exposure assignments were only moderately correlated (Spearman's rho = 0.42; weighted kappa = 0.39, CI 0.10-0.69). Only 40% of the expert-based medium category assignments were correctly assigned, with better agreement in the low (84%) and high (100%) categories. Pot operation jobs exhibited better agreement (rho = 0.60) than the maintenance and pot shell repair jobs (rho = 0.25). The mid-point value of the medium category was overestimated by 0.3 mg/m(3). The expert-based exposure assignments may be improved by better characterizing the transitions between exposure categories, by accounting for exposure differences between pot lines and by re-examining the category mid-point values used in calculating the cumulative exposure. Lack of historical exposure measurements often requires reliance on expert knowledge to assess exposure levels. Validating the experts' estimates against available exposure measurements may help to identify weaknesses in the exposure assessment where improvements may be possible, as was shown here.

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

Perspectives of policy and political decision makers on access to formal dementia care: expert interviews in eight European countries.

PubMed

Broda, Anja; Bieber, Anja; Meyer, Gabriele; Hopper, Louise; Joyce, Rachael; Irving, Kate; Zanetti, Orazio; Portolani, Elisa; Kerpershoek, Liselot; Verhey, Frans; Vugt, Marjolein de; Wolfs, Claire; Eriksen, Siren; Røsvik, Janne; Marques, Maria J; Gonçalves-Pereira, Manuel; Sjölund, Britt-Marie; Woods, Bob; Jelley, Hannah; Orrell, Martin; Stephan, Astrid

2017-08-03

As part of the ActifCare (ACcess to Timely Formal Care) project, we conducted expert interviews in eight European countries with policy and political decision makers, or representatives of relevant institutions, to determine their perspectives on access to formal care for people with dementia and their carers. Each ActifCare country (Germany, Ireland, Italy, The Netherlands, Norway, Portugal, Sweden, United Kingdom) conducted semi-structured interviews with 4-7 experts (total N = 38). The interview guide addressed the topics "Complexity and Continuity of Care", "Formal Services", and "Public Awareness". Country-specific analysis of interview transcripts used an inductive qualitative content analysis. Cross-national synthesis focused on similarities in themes across the ActifCare countries. The analysis revealed ten common themes and two additional sub-themes across countries. Among others, the experts highlighted the need for a coordinating role and the necessity of information to address issues of complexity and continuity of care, demanded person-centred, tailored, and multidisciplinary formal services, and referred to education, mass media and campaigns as means to raise public awareness. Policy and political decision makers appear well acquainted with current discussions among both researchers and practitioners of possible approaches to improve access to dementia care. Experts described pragmatic, realistic strategies to influence dementia care. Suggested innovations concerned how to achieve improved dementia care, rather than transforming the nature of the services provided. Knowledge gained in these expert interviews may be useful to national decision makers when they consider reshaping the organisation of dementia care, and may thus help to develop best-practice strategies and recommendations.

In the public interest: assessing expert and stakeholder influence in public deliberation about biobanks.

PubMed

MacLean, Samantha; Burgess, Michael M

2010-07-01

Providing technical and experiential information without overwhelming participants' perspectives presents a major challenge to public involvement in policy decisions. This article reports the design and analysis of a case study on incorporating expert and stakeholder knowledge without including them as deliberators, while supporting deliberative participants' ability to introduce and critically assess different perspectives. Analysis of audio-recorded deliberations illustrates how expert and stakeholder knowledge was cited, criticized and incorporated into deliberations. In conclusion, separating experts and stakeholders from deliberations may be an important prima facie principle when the goal is to enhance citizen representation on technical issues and related policy.

Nutrition knowledge of active-duty Navy personnel.

PubMed

Trent, L K

1992-06-01

As evidence continues to mount implicating diet in the etiology of disease, the US Navy is developing nutrition education programs designed to reflect the consolidated dietary recommendations of national expert agencies. The purpose of this study was to provide a baseline assessment of the level of nutrition knowledge among Navy personnel. Forty true/false questions were developed to test nutrition knowledge as conveyed by the Navy's instructional manual for nutrition educators. The questionnaire was mailed to a representative sample of all active-duty Navy personnel. Usable questionnaires were received from 2,938 participants (72.7% response rate). Mean number of correct items was 26.1 (65%). Nutrition knowledge was higher among older respondents, more highly educated personnel, whites, officers, women, and overweight individuals. Knowledge was weakest in the areas of calories/food intake and carbohydrates and strongest on vitamins/minerals and fiber. Program managers were recommended to intensify efforts to reach low-scoring subgroups, place more emphasis on the role of complex carbohydrates, disseminate guidelines for using nutrition labels on products, and develop point-of-choice nutrition education interventions for military dining facilities.

Computerization of guidelines: a knowledge specification method to convert text to detailed decision tree for electronic implementation.

PubMed

Aguirre-Junco, Angel-Ricardo; Colombet, Isabelle; Zunino, Sylvain; Jaulent, Marie-Christine; Leneveut, Laurence; Chatellier, Gilles

2004-01-01

The initial step for the computerization of guidelines is the knowledge specification from the prose text of guidelines. We describe a method of knowledge specification based on a structured and systematic analysis of text allowing detailed specification of a decision tree. We use decision tables to validate the decision algorithm and decision trees to specify and represent this algorithm, along with elementary messages of recommendation. Edition tools are also necessary to facilitate the process of validation and workflow between expert physicians who will validate the specified knowledge and computer scientist who will encode the specified knowledge in a guide-line model. Applied to eleven different guidelines issued by an official agency, the method allows a quick and valid computerization and integration in a larger decision support system called EsPeR (Personalized Estimate of Risks). The quality of the text guidelines is however still to be developed further. The method used for computerization could help to define a framework usable at the initial step of guideline development in order to produce guidelines ready for electronic implementation.

Teacher Knowledge for Active-Learning Instruction: Expert-Novice Comparison Reveals Differences.

PubMed

Auerbach, A J; Higgins, M; Brickman, P; Andrews, T C

2018-01-01

Active-learning strategies can improve science, technology, engineering, and mathematics (STEM) undergraduates' abilities to learn fundamental concepts and skills. However, the results instructors achieve vary substantially. One explanation for this is that instructors commonly implement active learning differently than intended. An important factor affecting how instructors implement active learning is knowledge of teaching and learning. We aimed to discover knowledge that is important to effective active learning in large undergraduate courses. We developed a lesson-analysis instrument to elicit teacher knowledge, drawing on the theoretical construct of teacher noticing. We compared the knowledge used by expert ( n = 14) and novice ( n = 29) active-learning instructors as they analyzed lessons. Experts and novices differed in what they noticed, with experts more commonly considering how instructors hold students accountable, topic-specific student difficulties, whether the instructor elicited and responded to student thinking, and opportunities students had to generate their own ideas and work. Experts were also better able to support their lesson analyses with reasoning. This work provides foundational knowledge for the future design of preparation and support for instructors adopting active learning. Improving teacher knowledge will improve the implementation of active learning, which will be necessary to widely realize the potential benefits of active learning in undergraduate STEM. © 2018 A. J. Auerbach et al. CBE—Life Sciences Education © 2018 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Expert Knowledge Influences Decision-Making for Couples Receiving Positive Prenatal Chromosomal Microarray Testing Results.

PubMed

Rubel, M A; Werner-Lin, A; Barg, F K; Bernhardt, B A

2017-09-01

To assess how participants receiving abnormal prenatal genetic testing results seek information and understand the implications of results, 27 US female patients and 12 of their male partners receiving positive prenatal microarray testing results completed semi-structured phone interviews. These interviews documented participant experiences with chromosomal microarray testing, understanding of and emotional response to receiving results, factors affecting decision-making about testing and pregnancy termination, and psychosocial needs throughout the testing process. Interview data were analyzed using a modified grounded theory approach. In the absence of certainty about the implications of results, understanding of results is shaped by biomedical expert knowledge (BEK) and cultural expert knowledge (CEK). When there is a dearth of BEK, as in the case of receiving results of uncertain significance, participants rely on CEK, including religious/spiritual beliefs, "gut instinct," embodied knowledge, and social network informants. CEK is a powerful platform to guide understanding of prenatal genetic testing results. The utility of culturally situated expert knowledge during testing uncertainty emphasizes that decision-making occurs within discourses beyond the biomedical domain. These forms of "knowing" may be integrated into clinical consideration of efficacious patient assessment and counseling.

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

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

The development of children's ability to fill the gaps in their knowledge by consulting experts.

PubMed

Aguiar, Naomi R; Stoess, Caryn J; Taylor, Marjorie

2012-01-01

This research investigated children's ability to recognize gaps in their knowledge and seek missing information from appropriate informants. In Experiment 1, forty-five 4- and 5-year-olds were adept in assigning questions from 3 domains (medicine, firefighting, and farming) to corresponding experts (doctor, firefighter, or farmer). However, when given the options of answering the same questions themselves or assigning them to an expert (Experiment 2), only 6-year-olds were consistently able to recognize when they did not know answers and then assign test questions correctly. Four- and 5-year-olds tended to overestimate their own knowledge or assign questions to the wrong expert. This result was replicated in Experiment 3, in which 5-year-olds were given incentives for correct answers. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

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

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.

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.

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.

[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.

Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation

Treesearch

J.-P. Puyravaud; Samuel Cushman; P. Davidar; D. Madappa

2016-01-01

Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that is subjective and not spatially synoptic. Landscape analysis allows generalization of expert knowledge when satellite tracking or genetic data are not available. The Nilgiri Biosphere Reserve in southern India...

The Instructional Developer, Expert Systems, and the Front End Process.

ERIC Educational Resources Information Center

Dills, Charles R.; Romiszowski, Alexander

This paper is intended to provide the instructional technologist already possessing some understanding of expert systems with some insight into two of the many steps involved in the design and production of such systems: knowledge acquisition and knowledge structuring or representation. It is also intended to help technologists to see how they…

How Instructional Design Experts Use Knowledge and Experience to Solve Ill-Structured Problems

ERIC Educational Resources Information Center

Ertmer, Peggy A.; Stepich, Donald A.; York, Cindy S.; Stickman, Ann; Wu, Xuemei (Lily); Zurek, Stacey; Goktas, Yuksel

2008-01-01

This study examined how instructional design (ID) experts used their prior knowledge and previous experiences to solve an ill-structured instructional design problem. Seven experienced designers used a think-aloud procedure to articulate their problem-solving processes while reading a case narrative. Results, presented in the form of four…

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…

Influence of Domain Knowledge on Monitoring Performance across the Life Span

ERIC Educational Resources Information Center

Löffler, Elisabeth; von der Linden, Nicole; Schneider, Wolfgang

2016-01-01

Two studies were conducted to investigate effects of domain knowledge on metacognitive monitoring across the life span in materials of different complexity. Participants from 4 age groups (3rd-grade children, adolescents, younger and older adults) were compared using an expert-novice paradigm. In Study 1, soccer experts' and novices'…

The Significance of Practical Training in Linking Theoretical Studies with Practice

ERIC Educational Resources Information Center

Katajavuori, Nina; Lindblom-Ylanne, Sari; Hirvonen, Jouni

2006-01-01

Today's experts must continuously reconstruct their expertise and be able to apply their theoretical knowledge in actual work. The development of expertise is a long process, during which theoretical, practical and metacognitive elements of expert knowledge are integrated into a coherent whole. It is important to foster student's learning and…

Decision support system for nursing management control

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

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

Information/Knowledge Acquisition Methods for Decision Support Systems and Expert Systems.

ERIC Educational Resources Information Center

Yang, Heng-Li

1995-01-01

Compares information requirement-elicitation (IRE) methods for decision support systems (DSS) with knowledge acquisition (KA) methods for expert systems (ES) development. The definition and architectures of ES and DSS are compared and the systems' development cycles and IRE/KA methods are discussed. Differences are noted between ES and DSS…

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

What Is An Expert System? ERIC Digest.

ERIC Educational Resources Information Center

Boss, Richard W.

This digest describes and defines the various components of an expert system, e.g., a computerized tool designed to enhance the quality and availability of knowledge required by decision makers. It is noted that expert systems differ from conventional applications software in the following areas: (1) the existence of the expert systems shell, or…

RAMBOT: A Connectionist Expert System That Learns by Example.

ERIC Educational Resources Information Center

Mozer, Michael C.

One solution to the problem of getting expert knowledge into expert systems would be to endow the systems with powerful learning procedures that could discover appropriate behaviors by observing an expert in action. A promising source of such learning procedures can be found in recent work on connectionist networks, which are massively parallel…

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…

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola.

PubMed

Wilkinson, Nicholas M; Van Duc, Luong

2017-06-01

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard-to-detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts' assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural-appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best-performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola. © 2016 Society for Conservation Biology.

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

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)

ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

PubMed

Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

2014-03-01

Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Trematode diversity in freshwater fishes of the Globe I: 'Old World'.

PubMed

Scholz, Tomáš; Besprozvannykh, Vladimir V; Boutorina, Tamara E; Choudhury, Anindo; Cribb, Thomas H; Ermolenko, Alexey V; Faltýnková, Anna; Shedko, Marina B; Shimazu, Takeshi; Smit, Nico J

2016-03-01

In this paper, we review, continent by continent, the trematode fauna of freshwater fishes of the 'Old World', a vast area consisting of the Palaearctic, Ethiopian, Oriental and Australasian zoogeographical regions. Knowledge of this fauna is highly uneven and clearly incomplete for almost all regions, sometimes dramatically so. Although the biggest problem remains the completion of the 'first pass' of alpha taxonomy, there are in addition great problems relating to biogeography and elucidation of life-cycles. For the latter, molecular data, i.e. matching DNA sequences of larval stages and corresponding adults, may represent a powerful tool that should be used in future studies. Another challenging problem represents the existence of cryptic species and, in particular, considerable decrease of experts in taxonomy and life-cycles of trematodes.

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.

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

Wusor II: A Computer Aided Instruction Program with Student Modelling Capabilities.

DTIC Science & Technology

1977-06-01

The Wun ,pus Advisor The Expert The Expert Chapter 3 Overview of the Expert From the work which was done on the expert of Wusor I, it was...network are numbered and represent caves. Circ led numbers represent caves which have been v is i ted by the player. To the top right of each v is i... ted cave is a marker for whether or not any warnings were sensed. (“U” indicates that a warn ing was sensed, and a “NW” means that a warning was not

Second CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

Giarratano, Joseph (Editor); Culbert, Christopher J. (Editor)

1991-01-01

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems.

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.

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.

Reasoning Based Quality Assurance of Medical Ontologies: A Case Study

PubMed Central

Horridge, Matthew; Parsia, Bijan; Noy, Natalya F.; Musenm, Mark A.

2014-01-01

The World Health Organisation is using OWL as a key technology to develop ICD-11 – the next version of the well-known International Classification of Diseases. Besides providing better opportunities for data integration and linkages to other well-known ontologies such as SNOMED-CT, one of the main promises of using OWL is that it will enable various forms of automated error checking. In this paper we investigate how automated OWL reasoning, along with a Justification Finding Service can be used as a Quality Assurance technique for the development of large and complex ontologies such as ICD-11. Using the International Classification of Traditional Medicine (ICTM) – Chapter 24 of ICD-11 – as a case study, and an expert panel of knowledge engineers, we reveal the kinds of problems that can occur, how they can be detected, and how they can be fixed. Specifically, we found that a logically inconsistent version of the ICTM ontology could be repaired using justifications (minimal entailing subsets of an ontology). Although over 600 justifications for the inconsistency were initially computed, we found that there were three main manageable patterns or categories of justifications involving TBox and ABox axioms. These categories represented meaningful domain errors to an expert panel of ICTM project knowledge engineers, who were able to use them to successfully determine the axioms that needed to be revised in order to fix the problem. All members of the expert panel agreed that the approach was useful for debugging and ensuring the quality of ICTM. PMID:25954373

Disorders of orgasm and ejaculation in men.

PubMed

Rowland, David; McMahon, Chris G; Abdo, Carmita; Chen, Juza; Jannini, Emmanuele; Waldinger, Marcel D; Ahn, Tai Young

2010-04-01

Ejaculatory/orgasmic disorders are common male sexual dysfunctions, and include premature ejaculation (PE), inhibited ejaculation, anejaculation, retrograde ejaculation, and anorgasmia. To provide recommendations and guidelines concerning current state-of-the-art knowledge for management of ejaculation/orgasmic disorders in men. An international consultation in collaboration with the major urology and sexual medicine associations assembled over 200 multidisciplinary experts from 60 countries into 25 committees. Committee members established specific objectives and scopes for various male and female sexual medicine topics. The recommendations concerning state-of-the-art knowledge of disorders of orgasm and ejaculation represent the opinion of seven experts from seven countries developed in a process over a 2-year period. Expert opinion was based on grading of evidence-based medical literature, widespread internal committee discussion, public presentation and debate. Premature ejaculation management is largely dependent upon etiology. Lifelong PE is best managed with PE pharmacotherapy (selective serotonin re-uptake inhibitor [SSRI] and/or topical anesthetics). The management of acquired PE is etiology specific and may include erectile dysfunction (ED) pharmacotherapy in men with comorbid ED. Behavioral therapy is indicated when psychogenic or relationship factors are present and is often best combined with PE pharmacotherapy in an integrated treatment program. Retrograde ejaculation is managed by education, patient reassurance, pharmacotherapy, or bladder neck reconstruction. Delayed ejaculation, anejaculation, and/or anorgasmia may have a biogenic and/or psychogenic atiology. Men with age-related penile hypoanesthesia should be educated, reassured, and instructed in revised sexual techniques which maximize arousal. Additional research is required to further the understanding of the disorders of ejaculation and orgasm.

Use of artificial intelligence in supervisory control

NASA Technical Reports Server (NTRS)

Cohen, Aaron; Erickson, Jon D.

1989-01-01

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

Knowledge-Based Reinforcement Learning for Data Mining

NASA Astrophysics Data System (ADS)

Kudenko, Daniel; Grzes, Marek

Data Mining is the process of extracting patterns from data. Two general avenues of research in the intersecting areas of agents and data mining can be distinguished. The first approach is concerned with mining an agent’s observation data in order to extract patterns, categorize environment states, and/or make predictions of future states. In this setting, data is normally available as a batch, and the agent’s actions and goals are often independent of the data mining task. The data collection is mainly considered as a side effect of the agent’s activities. Machine learning techniques applied in such situations fall into the class of supervised learning. In contrast, the second scenario occurs where an agent is actively performing the data mining, and is responsible for the data collection itself. For example, a mobile network agent is acquiring and processing data (where the acquisition may incur a certain cost), or a mobile sensor agent is moving in a (perhaps hostile) environment, collecting and processing sensor readings. In these settings, the tasks of the agent and the data mining are highly intertwined and interdependent (or even identical). Supervised learning is not a suitable technique for these cases. Reinforcement Learning (RL) enables an agent to learn from experience (in form of reward and punishment for explorative actions) and adapt to new situations, without a teacher. RL is an ideal learning technique for these data mining scenarios, because it fits the agent paradigm of continuous sensing and acting, and the RL agent is able to learn to make decisions on the sampling of the environment which provides the data. Nevertheless, RL still suffers from scalability problems, which have prevented its successful use in many complex real-world domains. The more complex the tasks, the longer it takes a reinforcement learning algorithm to converge to a good solution. For many real-world tasks, human expert knowledge is available. For example, human experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data collection behaviour in the respective domains. In future work, we intend to demonstrate and evaluate our techniques on concrete real-world data mining applications.

A Description of the Strategic Knowledge of Experts Solving Transmission Genetics Problems.

ERIC Educational Resources Information Center

Collins, Angelo

Descriptions of the problem-solving strategies of experts solving realistic, computer-generated transmission genetics problems are presented in this paper and implications for instruction are discussed. Seven experts were involved in the study. All of the experts had a doctoral degree and experience in both teaching and doing research in genetics.…

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…

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.

Impact of Secondary Students' Content Knowledge on Their Communication Skills in Science

ERIC Educational Resources Information Center

Kulgemeyer, Christoph

2018-01-01

The "expert blind spot" (EBS) hypothesis implies that even some experts with a high content knowledge might have problems in science communication because they are using the structure of the content rather than their addressee's prerequisites as an orientation. But is that also true for students? Explaining science to peers is a crucial…

Using Historical Knowledge to Reason about Contemporary Political Issues: An Expert-Novice Study

ERIC Educational Resources Information Center

Shreiner, Tamara L.

2014-01-01

People often justify history's place in the curriculum by its relationship to citizenship, yet there is little research to help educators picture how people use historical knowledge for civic purposes. This expert-novice study used the think-aloud method to examine how eight political scientists and eight high school students employed…

Development and Validation of Pre-Service Teachers' Personal Epistemologies of Teaching Scale (PT-PETS)

ERIC Educational Resources Information Center

Yu, Ji Hyun

2013-01-01

The Internet has changed not only how we conceptualize knowledge, but also how we learn in classroom. Knowledge is not any longer transmitted from experts to non-experts, but is constructed through communication, collaboration, and integration among a network of people. In this context, teachers are expected to facilitate student-centered learning…

The Development of Children's Ability to Fill the Gaps in Their Knowledge by Consulting Experts

ERIC Educational Resources Information Center

Aguiar, Naomi R.; Stoess, Caryn J.; Taylor, Marjorie

2012-01-01

This research investigated children's ability to recognize gaps in their knowledge and seek missing information from appropriate informants. In Experiment 1, forty-five 4- and 5-year-olds were adept in assigning questions from 3 domains (medicine, firefighting, and farming) to corresponding experts (doctor, firefighter, or farmer). However, when…

Cognitive Task Analysis for Instruction in Single-Injection Ultrasound Guided-Regional Anesthesia

ERIC Educational Resources Information Center

Gucev, Gligor V.

2012-01-01

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…

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

A Novice-Expert Study of Modeling Skills and Knowledge Structures about Air Quality

ERIC Educational Resources Information Center

Hsu, Ying-Shao; Lin, Li-Fen; Wu, Hsin-Kai; Lee, Dai-Ying; Hwang, Fu-Kwun

2012-01-01

This study compared modeling skills and knowledge structures of four groups as seen in their understanding of air quality. The four groups were: experts (atmospheric scientists), intermediates (upper-level graduate students in a different field), advanced novices (talented 11th and 12th graders), and novices (10th graders). It was found that when…

Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study

PubMed Central

2012-01-01

Background The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S. Methods Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices. Results The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction. Conclusions These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors. PMID:22333210

Future Targets for Female Sexual Dysfunction.

PubMed

Farmer, Melissa; Yoon, Hana; Goldstein, Irwin

2016-08-01

Female sexual function reflects a dynamic interplay of central and peripheral nervous, vascular, and endocrine systems. The primary challenge in the development of novel treatments for female sexual dysfunction is the identification and targeted modulation of excitatory sexual circuits using pharmacologic treatments that facilitate the synthesis, release, and/or receptor binding of neurochemicals, peptides, and hormones that promote female sexual function. To develop an evidence-based state-of-the-art consensus report that critically integrates current knowledge of the therapeutic potential for known molecular and cellular targets to facilitate the physiologic processes underlying female sexual function. State-of-the-art review representing the opinions of international experts developed in a consensus process during a 1-year period. Expert opinion was established by grading the evidence-based medical literature, intensive internal committee discussion, public presentation, and debate. Scientific investigation is urgently needed to expand knowledge and foster development of future treatments that maintain genital tissue integrity, enhance genital physiologic responsiveness, and optimize positive subjective appraisal of internal and external sexual cues. This article critically condenses the current knowledge of therapeutic manipulation of molecular and cellular targets within biological systems responsible for female sexual physiologic function. Future treatment targets include pharmacologic modulation of emotional learning circuits, restoration of normal tactile sensation, growth factor therapy, gene therapy, stem cell-based therapies, and regenerative medicine. Concurrent use of centrally and peripherally acting therapies could optimize treatment response. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Expert knowledge in palliative care on the World Wide Web: palliativedrugs.org.

PubMed

Gavrin, Jonathan

2009-01-01

In my last Internet-related article, I speculated that social networking would be the coming wave in the effort to share knowledge among experts in various disciplines. At the time I did not know that a palliative care site on the World Wide Web (WWW), palliativedrugs.com, already provided the infrastructure for sharing expert knowledge in the field. The Web site is an excellent traditional formulary but it is primarily devoted to "unlicensed" ("off-label") use of medications in palliative care, something we in the specialty often do with little to support our interventions except shared knowledge and experience. There is nothing fancy about this Web site. In a good way, its format is a throwback to Web sites of the 1990s. In only the loosest sense can one describe it as "multimedia." Yet, it provides the perfect forum for expert knowledge and is a "must see" resource. Its existing content is voluminous and reliable, filtered and reviewed by renowned clinicians and educators in the field. Although its origin and structure were not specifically designed for social or professional networking, the Web site's format makes it a natural way for practitioners around the world to contribute to an ever-growing body of expertise in palliative care.

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.

Self-help organisations as patient representatives in health care and policy decision-making.

PubMed

Rojatz, Daniela; Forster, Rudolf

2017-10-01

A crucial question about participation is who is legitimised, willing and capable of representing particular collectives. Social insurance health care systems tend to focus on representation by patient organisations. Self-help organisations (SHOs), as one type of 'health consumer and patient organisation', often take over this role. Research findings indicate that participation by SHOs is accompanied by high expectations, but also by concerns about the risks of instrumental abuse, overload and professionalisation. However, there is a dearth of in-depth knowledge about both potential and risks of participating for the SHO. To tackle this research gap, a qualitative study design was used to investigate fifteen SHOs in Austria. Data were generated by expert interviews with SHO representatives and documentary analysis of SHO websites. Content analysis was applied. SHOs in Austria advocate for patients' interests, participate in invited spaces and have various forms of cooperative relations with the health care system. Thereby, they draw on the experiential knowledge of their members without, however, systematising it. Experiences with professionalisation and instrumental use are ambiguous, whereas overload is prevalent. SHOs need resources for reflection in order to define their position visà- vis the health system and to realise their potential as patient representatives. Deepening co-operation with the health care system might lead to new participatory practices acknowledging differences in culture and the resources of both sides. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigating Public trust in Expert Knowledge: Narrative, Ethics, and Engagement.

PubMed

Camporesi, Silvia; Vaccarella, Maria; Davis, Mark

2017-03-01

"Public Trust in Expert Knowledge: Narrative, Ethics, and Engagement" examines the social, cultural, and ethical ramifications of changing public trust in the expert biomedical knowledge systems of emergent and complex global societies. This symposium was conceived as an interdisciplinary project, drawing on bioethics, the social sciences, and the medical humanities. We settled on public trust as a topic for our work together because its problematization cuts across our fields and substantive research interests. For us, trust is simultaneously a matter of ethics, social relations, and the cultural organization of meaning. We share a commitment to narrative inquiry across our fields of expertise in the bioethics of transformative health technologies, public communications on health threats, and narrative medicine. The contributions to this symposium have applied, in different ways and with different effects, this interdisciplinary mode of inquiry, supplying new reflections on public trust, expertise, and biomedical knowledge.

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.

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 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

Real Time Data System (RTDS)

NASA Technical Reports Server (NTRS)

Muratore, John F.

1991-01-01

Lessons learned from operational real time expert systems are examined. The basic system architecture is discussed. An expert system is any software that performs tasks to a standard that would normally require a human expert. An expert system implies knowledge contained in data rather than code. And an expert system implies the use of heuristics as well as algorithms. The 15 top lessons learned by the operation of a real time data system are presented.

A hierarchically distributed architecture for fault isolation expert systems on the space station

NASA Technical Reports Server (NTRS)

Miksell, Steve; Coffer, Sue

1987-01-01

The Space Station Axiomatic Fault Isolating Expert Systems (SAFTIES) system deals with the hierarchical distribution of control and knowledge among independent expert systems doing fault isolation and scheduling of Space Station subsystems. On its lower level, fault isolation is performed on individual subsystems. These fault isolation expert systems contain knowledge about the performance requirements of their particular subsystem and corrective procedures which may be involved in repsonse to certain performance errors. They can control the functions of equipment in their system and coordinate system task schedules. On a higher level, the Executive contains knowledge of all resources, task schedules for all systems, and the relative priority of all resources and tasks. The executive can override any subsystem task schedule in order to resolve use conflicts or resolve errors that require resources from multiple subsystems. Interprocessor communication is implemented using the SAFTIES Communications Interface (SCI). The SCI is an application layer protocol which supports the SAFTIES distributed multi-level architecture.

Modeling the Distribution of Migratory Bird Stopovers to Inform Landscape-Scale Siting of Wind Development

PubMed Central

Pocewicz, Amy; Estes-Zumpf, Wendy A.; Andersen, Mark D.; Copeland, Holly E.; Keinath, Douglas A.; Griscom, Hannah R.

2013-01-01

Conservation of migratory birds requires understanding the distribution of and potential threats to their migratory habitats. However, although migratory birds are protected under international treaties, few maps have been available to represent migration at a landscape scale useful to target conservation efforts or inform the siting of wind energy developments that may affect migratory birds. To fill this gap, we developed models that predict where four groups of birds concentrate or stopover during their migration through the state of Wyoming, USA: raptors, wetland, riparian and sparse grassland birds. The models were based on existing literature and expert knowledge concerning bird migration behavior and ecology and validated using expert ratings and known occurrences. There was significant agreement between migratory occurrence data and migration models for all groups except raptors, and all models ranked well with experts. We measured the overlap between the migration concentration models and a predictive model of wind energy development to assess the potential exposure of migratory birds to wind development and illustrate the utility of migratory concentration models for landscape-scale planning. Wind development potential is high across 15% of Wyoming, and 73% of this high potential area intersects important migration concentration areas. From 5.2% to 18.8% of each group’s important migration areas was represented within this high wind potential area, with the highest exposures for sparse grassland birds and the lowest for riparian birds. Our approach could be replicated elsewhere to fill critical data gaps and better inform conservation priorities and landscape-scale planning for migratory birds. PMID:24098379

Sherlock Holmes: an expert's view of expertise.

PubMed

André, Didierjean; Fernand, Gobet

2008-02-01

In recent years, there has been an intense research effort to understand the cognitive processes and structures underlying expert behaviour. Work in different fields, including scientific domains, sports, games and mnemonics, has shown that there are vast differences in perceptual abilities between experts and novices, and that these differences may underpin other cognitive differences in learning, memory and problem solving. In this article, we evaluate the progress made in the last years through the eyes of an outstanding, albeit fictional, expert: Sherlock Holmes. We first use the Sherlock Holmes character to illustrate expert processes as described by current research and theories. In particular, the role of perception, as well as the nature and influence of expert knowledge, are all present in the description of Conan Doyle's hero. In the second part of the article, we discuss a number of issues that current research on expertise has barely addressed. These gaps include, for example, several forms of reasoning, the influence of emotions on cognition, and the effect of age on experts' knowledge and cognitive processes. Thus, although nearly 120-year-old, Conan Doyle's books show remarkable illustrations of expert behaviour, including the coverage of themes that have mostly been overlooked by current research.

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.

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…

Using expert knowledge in landscape ecology [Book review

Treesearch

Eric J. Gustafson

2013-01-01

This volume perfectly illustrates the truism—"we don't know what it is that we don't know." I have been a landscape ecologist for over 20 years, and have even used expert knowledge many times in my own research. Yet I learned something profoundly new in almost every chapter of this collection of primers and case studies focused on the use...

The influence of political ideology and trust on willingness to vaccinate.

PubMed

Baumgaertner, Bert; Carlisle, Juliet E; Justwan, Florian

2018-01-01

In light of the increasing refusal of some parents to vaccinate children, public health strategies have focused on increasing knowledge and awareness based on a "knowledge-deficit" approach. However, decisions about vaccination are based on more than mere knowledge of risks, costs, and benefits. Individual decision making about vaccinating involves many other factors including those related to emotion, culture, religion, and socio-political context. In this paper, we use a nationally representative internet survey in the U.S. to investigate socio-political characteristics to assess attitudes about vaccination. In particular, we consider how political ideology and trust affect opinions about vaccinations for flu, pertussis, and measles. Our findings demonstrate that ideology has a direct effect on vaccine attitudes. In particular, conservative respondents are less likely to express pro-vaccination beliefs than other individuals. Furthermore, ideology also has an indirect effect on immunization propensity. The ideology variable predicts an indicator capturing trust in government medical experts, which in turn helps to explain individual-level variation with regards to attitudes about vaccine choice.

An easy-to-use diagnostic system development shell

NASA Technical Reports Server (NTRS)

Tsai, L. C.; Ross, J. B.; Han, C. Y.; Wee, W. G.

1987-01-01

The Diagnostic System Development Shell (DSDS), an expert system development shell for diagnostic systems, is described. The major objective of building the DSDS is to create a very easy to use and friendly environment for knowledge engineers and end-users. The DSDS is written in OPS5 and CommonLisp. It runs on a VAX/VMS system. A set of domain independent, generalized rules is built in the DSDS, so the users need not be concerned about building the rules. The facts are explicitly represented in a unified format. A powerful check facility which helps the user to check the errors in the created knowledge bases is provided. A judgement facility and other useful facilities are also available. A diagnostic system based on the DSDS system is question driven and can call or be called by other knowledge based systems written in OPS5 and CommonLisp. A prototype diagnostic system for diagnosing a Philips constant potential X-ray system has been built using the DSDS.

AI and simulation: What can they learn from each other

NASA Technical Reports Server (NTRS)

Colombano, Silvano P.

1988-01-01

Simulation and Artificial Intelligence share a fertile common ground both from a practical and from a conceptual point of view. Strengths and weaknesses of both Knowledge Based System and Modeling and Simulation are examined and three types of systems that combine the strengths of both technologies are discussed. These types of systems are a practical starting point, however, the real strengths of both technologies will be exploited only when they are combined in a common knowledge representation paradigm. From an even deeper conceptual point of view, one might even argue that the ability to reason from a set of facts (i.e., Expert System) is less representative of human reasoning than the ability to make a model of the world, change it as required, and derive conclusions about the expected behavior of world entities. This is a fundamental problem in AI, and Modeling Theory can contribute to its solution. The application of Knowledge Engineering technology to a Distributed Processing Network Simulator (DPNS) is discussed.

DETERMINATION OF RELATIVE IMPORTANCE OF NONPROLIFERATION FACTORS

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

Richard Metcalf

2009-07-01

Methodologies to determine the proliferation resistance (PR) of nuclear facilities often rely on either expert elicitation, a resource-intensive approach without easily reproducible results, or numeric evaluations, which can fail to take into account the institutional knowledge and expert experience of the nonproliferation community. In an attempt to bridge the gap and bring the institutional knowledge into numeric evaluations of PR, a survey was conducted of 33 individuals to find the relative importance of a set of 62 nonproliferation factors, subsectioned into groups under the headings of Diversion, Transportation, Transformation, and Weaponization. One third of the respondents were self-described nonproliferation professionals,more » and the remaining two thirds were from secondary professions related to nonproliferation, such as industrial engineers or policy analysts. The factors were taken from previous work which used multi-attribute utility analysis with uniform weighting of attributes and did not include institutional knowledge. In both expert and non-expert groups, all four headings and the majority of factors had different relative importance at a confidence of 95% (p=0.05). This analysis and survey demonstrates that institutional knowledge can be brought into numeric evaluations of PR, if there is a sufficient investment of resources made prior to the evaluation.« less

Industrial knowledge design: an approach for designing information artifacts

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

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Industrial knowledge design: an approach for designing information artifacts

DOE PAGES

Schatz, Sae; Berking, Peter; Raybourn, Elaine M.

2017-01-19

In this study, the authors define a new approach that addresses the challenge of efficiently designing informational artefacts for optimal knowledge acquisition, an important issue in cognitive ergonomics. Termed Industrial Knowledge Design (or InK'D), it draws from information-related (e.g. informatics) and neurosciences-related (e.g. neuroergonomics) disciplines. Although it can be used for a broad scope of communication-driven business functions, our focus as learning professionals is on conveying knowledge for purposes of training, education, and performance support. This paper discusses preliminary principles of InK'D practice that can be employed to maximise the quality and quantity of transferred knowledge through interaction design. Themore » paper codifies tacit knowledge into explicit concepts that can be leveraged by expert and non-expert knowledge designers alike.« less

Pesticide risk perceptions and the differences between farmers and extensionists: Towards a knowledge-in-context model

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

Ríos-González, Adriana, E-mail: adrianariosg@hotmail.com; The Africa and Latin America Research Groups Network; Jansen, Kees, E-mail: Kees.Jansen@wur.nl

A growing body of literature analyzes farmer perceptions of pesticide risk, but much less attention has been given to differences in risk perception between farmers and technical experts. Furthermore, inconsistencies in knowledge have too easily been explained in terms of lack of knowledge rather than exploring the underlying reasons for particular forms of thinking about pesticide risks. By doing this, the division between expert and lay knowledge has been deepened rather than transcended. Objective: This study aims to understand differences and similarities among the perceptions of pesticide risks of farmers, farm workers, and technical experts such as extensionists, by applyingmore » a social science approach towards knowledge and risk attitudes. Methods: Semi-structured interviews and field observations were conducted to smallholders, farm workers, extensionists, health professionals and scientists involved in the use and handling of pesticides. Subsequently, a survey was carried out to quantify the farmers and extensionists' acceptance or rejection of typical assertions expressed previously in the semi-structured interviews. Results: Smallholders showed to gain knowledge from their own experiences and to adapt pesticides practices, which is a potential basis for transforming notions of pesticide safety and risk reduction strategies. Though extensionists have received formal education, they sometimes develop ideas deviating from the technical perspective. The risk perception of the studied actors appeared to vary according to their role in the agricultural labor process; they varied much less than expected according to their schooling level. Conclusions: Commitment to the technical perspective is not dramatically different for extensionists on the one hand and farmers as well as farm workers on the other hand. Ideas about a supposed lack of knowledge by farmers and the need of formal training are too much driven by a deficit model of knowledge. Further research on risk perceptions of pesticides and training of rural people will benefit from the development of a knowledge-in-context model. -- Highlights: • Researching perceptions of farmers' extensionists and other professionals. • Experts as well as farmers deviate from the technical perspective. • Blaming who is responsible for pesticide problems creates expert-lay division. • Qualitative and quantitative methods, not as complementary but integrated. • Knowledge-in-context model as an alternative to the knowledge-deficit model.« less

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

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.

Organization of Programming Knowledge of Novices and Experts.

ERIC Educational Resources Information Center

Wiedenbeck, Susan

1986-01-01

Reports on an experiment where novice and expert programmers made decisions about Fortran code segments. The results show that, although expert programmers are better able to extract and use functional information, they don't differ significantly from novices in their ability to use syntactic concepts. (Author/EM)

Nonlinear rescaling of control values simplifies fuzzy control

NASA Technical Reports Server (NTRS)

Vanlangingham, H.; Tsoukkas, A.; Kreinovich, V.; Quintana, C.

1993-01-01

Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.

What people know about electronic devices: A descriptive study

NASA Astrophysics Data System (ADS)

Kieras, D. E.

1982-10-01

Informal descriptive results on the nature of people's natural knowledge of electronic devices are presented. Expert and nonexpert subjects were given an electronic device to examine and describe orally. The devices ranged from familiar everyday devices, to those familiar only to the expert, to unusual devices unfamiliar even to an expert. College students were asked to describe everyday devices from memory. The results suggest that device knowledge consists of the major categories of what the device is for, how it is used, its structure in terms of subdevices, its physical layout, how it works, and its behavior. A preliminary theoretical framework for device knowledge is that it consists of a hierarchy of schemas, corresponding to a hierarchial decomposition of the device into subdevices, with each level containing the major categories of information.

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.

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.

The Roles of Knowledge Professionals for Knowledge Management.

ERIC Educational Resources Information Center

Kim, Seonghee

This paper starts by exploring the definition of knowledge and knowledge management; examples of acquisition, creation, packaging, application, and reuse of knowledge are provided. It then considers the partnership for knowledge management and especially how librarians as knowledge professionals, users, and technology experts can contribute to…

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...

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

Deliberative Mapping of options for tackling climate change: Citizens and specialists ‘open up’ appraisal of geoengineering

PubMed Central

Bellamy, Rob; Chilvers, Jason; Vaughan, Naomi E.

2014-01-01

Appraisals of deliberate, large-scale interventions in the earth’s climate system, known collectively as ‘geoengineering’, have largely taken the form of narrowly framed and exclusive expert analyses that prematurely ‘close down’ upon particular proposals. Here, we present the findings from the first ‘upstream’ appraisal of geoengineering to deliberately ‘open up’ to a broader diversity of framings, knowledges and future pathways. We report on the citizen strand of an innovative analytic–deliberative participatory appraisal process called Deliberative Mapping. A select but diverse group of sociodemographically representative citizens from Norfolk (United Kingdom) were engaged in a deliberative multi-criteria appraisal of geoengineering proposals relative to other options for tackling climate change, in parallel to symmetrical appraisals by diverse experts and stakeholders. Despite seeking to map divergent perspectives, a remarkably consistent view of option performance emerged across both the citizens’ and the specialists’ deliberations, where geoengineering proposals were outperformed by mitigation alternatives. PMID:25224904

Deliberative Mapping of options for tackling climate change: Citizens and specialists 'open up' appraisal of geoengineering.

PubMed

Bellamy, Rob; Chilvers, Jason; Vaughan, Naomi E

2016-04-01

Appraisals of deliberate, large-scale interventions in the earth's climate system, known collectively as 'geoengineering', have largely taken the form of narrowly framed and exclusive expert analyses that prematurely 'close down' upon particular proposals. Here, we present the findings from the first 'upstream' appraisal of geoengineering to deliberately 'open up' to a broader diversity of framings, knowledges and future pathways. We report on the citizen strand of an innovative analytic-deliberative participatory appraisal process called Deliberative Mapping. A select but diverse group of sociodemographically representative citizens from Norfolk (United Kingdom) were engaged in a deliberative multi-criteria appraisal of geoengineering proposals relative to other options for tackling climate change, in parallel to symmetrical appraisals by diverse experts and stakeholders. Despite seeking to map divergent perspectives, a remarkably consistent view of option performance emerged across both the citizens' and the specialists' deliberations, where geoengineering proposals were outperformed by mitigation alternatives. © The Author(s) 2014.

Governing by Testing: Circulation, Psychometric Knowledge, Experts and the "Alliance for Progress" in Latin America during the 1960s and 1970s

ERIC Educational Resources Information Center

Alarcón, Cristina

2015-01-01

This paper analyzes the activities, members, and effects of an inter-American expert network for the diffusion of psychometric knowledge, specifically of standardized aptitude testing for university admission in Latin America during the 1960s and 1970s. Within the framework of educational transfer studies, the role of international,…

Young Adults' Knowledge and Understanding of Personal Finance in Germany: Interviews with Experts and Test-Takers

ERIC Educational Resources Information Center

Happ, Roland; Förster, Manuel; Rüspeler, Ann-Katrin; Rothweiler, Jasmin

2018-01-01

In recent years, the financial education of young adults has gained importance in Germany; however, very few valid test instruments to assess the knowledge and understanding of personal finance are suitable for use in Germany. In this article, we describe results of a survey in which experts in Germany in areas related to personal finance judged…

Integrated computer-aided forensic case analysis, presentation, and documentation based on multimodal 3D data.

PubMed

Bornik, Alexander; Urschler, Martin; Schmalstieg, Dieter; Bischof, Horst; Krauskopf, Astrid; Schwark, Thorsten; Scheurer, Eva; Yen, Kathrin

2018-06-01

Three-dimensional (3D) crime scene documentation using 3D scanners and medical imaging modalities like computed tomography (CT) and magnetic resonance imaging (MRI) are increasingly applied in forensic casework. Together with digital photography, these modalities enable comprehensive and non-invasive recording of forensically relevant information regarding injuries/pathologies inside the body and on its surface. Furthermore, it is possible to capture traces and items at crime scenes. Such digitally secured evidence has the potential to similarly increase case understanding by forensic experts and non-experts in court. Unlike photographs and 3D surface models, images from CT and MRI are not self-explanatory. Their interpretation and understanding requires radiological knowledge. Findings in tomography data must not only be revealed, but should also be jointly studied with all the 2D and 3D data available in order to clarify spatial interrelations and to optimally exploit the data at hand. This is technically challenging due to the heterogeneous data representations including volumetric data, polygonal 3D models, and images. This paper presents a novel computer-aided forensic toolbox providing tools to support the analysis, documentation, annotation, and illustration of forensic cases using heterogeneous digital data. Conjoint visualization of data from different modalities in their native form and efficient tools to visually extract and emphasize findings help experts to reveal unrecognized correlations and thereby enhance their case understanding. Moreover, the 3D case illustrations created for case analysis represent an efficient means to convey the insights gained from case analysis to forensic non-experts involved in court proceedings like jurists and laymen. The capability of the presented approach in the context of case analysis, its potential to speed up legal procedures and to ultimately enhance legal certainty is demonstrated by introducing a number of representative forensic cases. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

Integrating public risk perception into formal natural hazard risk assessment

NASA Astrophysics Data System (ADS)

Plattner, Th.; Plapp, T.; Hebel, B.

2006-06-01

An urgent need to take perception into account for risk assessment has been pointed out by relevant literature, its impact in terms of risk-related behaviour by individuals is obvious. This study represents an effort to overcome the broadly discussed question of whether risk perception is quantifiable or not by proposing a still simple but applicable methodology. A novel approach is elaborated to obtain a more accurate and comprehensive quantification of risk in comparison to present formal risk evaluation practice. A consideration of relevant factors enables a explicit quantification of individual risk perception and evaluation. The model approach integrates the effective individual risk reff and a weighted mean of relevant perception affecting factors PAF. The relevant PAF cover voluntariness of risk-taking, individual reducibility of risk, knowledge and experience, endangerment, subjective damage rating and subjective recurrence frequency perception. The approach assigns an individual weight to each PAF to represent its impact magnitude. The quantification of these weights is target-group-dependent (e.g. experts, laypersons) and may be effected by psychometric methods. The novel approach is subject to a plausibility check using data from an expert-workshop. A first model application is conducted by means of data of an empirical risk perception study in Western Germany to deduce PAF and weight quantification as well as to confirm and evaluate model applicbility and flexibility. Main fields of application will be a quantification of risk perception by individual persons in a formal and technical way e.g. for the purpose of risk communication issues in illustrating differing perspectives of experts and non-experts. For decision making processes this model will have to be applied with caution, since it is by definition not designed to quantify risk acceptance or risk evaluation. The approach may well explain how risk perception differs, but not why it differs. The formal model generates only "snap shots" and considers neither the socio-cultural nor the historical context of risk perception, since it is a highly individualistic and non-contextual approach.

Essential Nutrition and Food Systems Components for School Curricula: Views from Experts in Iran

PubMed Central

SADEGHOLVAD, Sanaz; YEATMAN, Heather; OMIDVAR, Nasrin; PARRISH, Anne-Maree; WORSLEY, Anthony

2017-01-01

Background: This study aimed to investigate food experts’ views on important nutrition and food systems knowledge issues for education purposes at schools in Iran. Methods: In 2012, semi-structured, face-to-face or telephone interviews were conducted with twenty-eight acknowledged Iranian experts in food and nutrition fields. Participants were selected from four major provinces in Iran (Tehran, Isfahan, Fars and Gilan). Open-ended interview questions were used to identify nutrition and food systems knowledge issues, which experts considered as important to be included in school education programs. Qualitative interviews were analyzed thematically using NVivo. Results: A framework of knowledge that would assist Iranian students and school-leavers to make informed decisions in food-related areas was developed, comprising five major clusters and several sub-clusters. Major knowledge clusters included nutrition basics; food production; every day food-related practices; prevalent nutritional health problems in Iran and improvement of students’ ethical attitudes in the food domain. Conclusion: These findings provide a guide to curriculum developers and policy makers to assess current education curricula in order to optimize students’ knowledge of nutrition and food systems. PMID:28845405

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.

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.

12 CFR 390.91 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...: (1) The representation of another person at any adjudicatory, investigatory, removal or rulemaking... licensed expert which is filed with or submitted to the FDIC, with such expert's consent or knowledge in...

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 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.

Development and content validation of the information assessment method for patients and consumers.

PubMed

Pluye, Pierre; Granikov, Vera; Bartlett, Gillian; Grad, Roland M; Tang, David L; Johnson-Lafleur, Janique; Shulha, Michael; Barbosa Galvão, Maria Cristiane; Ricarte, Ivan Lm; Stephenson, Randolph; Shohet, Linda; Hutsul, Jo-Anne; Repchinsky, Carol A; Rosenberg, Ellen; Burnand, Bernard; Légaré, France; Dunikowski, Lynn; Murray, Susan; Boruff, Jill; Frati, Francesca; Kloda, Lorie; Macaulay, Ann; Lagarde, François; Doray, Geneviève

2014-02-18

Online consumer health information addresses health problems, self-care, disease prevention, and health care services and is intended for the general public. Using this information, people can improve their knowledge, participation in health decision-making, and health. However, there are no comprehensive instruments to evaluate the value of health information from a consumer perspective. We collaborated with information providers to develop and validate the Information Assessment Method for all (IAM4all) that can be used to collect feedback from information consumers (including patients), and to enable a two-way knowledge translation between information providers and consumers. Content validation steps were followed to develop the IAM4all questionnaire. The first version was based on a theoretical framework from information science, a critical literature review and prior work. Then, 16 laypersons were interviewed on their experience with online health information and specifically their impression of the IAM4all questionnaire. Based on the summaries and interpretations of interviews, questionnaire items were revised, added, and excluded, thus creating the second version of the questionnaire. Subsequently, a panel of 12 information specialists and 8 health researchers participated in an online survey to rate each questionnaire item for relevance, clarity, representativeness, and specificity. The result of this expert panel contributed to the third, current, version of the questionnaire. The current version of the IAM4all questionnaire is structured by four levels of outcomes of information seeking/receiving: situational relevance, cognitive impact, information use, and health benefits. Following the interviews and the expert panel survey, 9 questionnaire items were confirmed as relevant, clear, representative, and specific. To improve readability and accessibility for users with a lower level of literacy, 19 items were reworded and all inconsistencies in using a passive or active voice have been solved. One item was removed due to redundancy. The current version of the IAM4all questionnaire contains 28 items. We developed and content validated the IAM4all in partnership with information providers, information specialists, researchers and representatives of information consumers. This questionnaire can be integrated within electronic knowledge resources to stimulate users' reflection (eg, their intention to use information). We claim that any organization (eg, publishers, community organizations, or patient associations), can evaluate and improve their online consumer health information from a consumers' perspective using this method.

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.

Expert Seeker: A People-Finder Knowledge Management System

NASA Technical Reports Server (NTRS)

Becerra-Fernandez, Irma

2000-01-01

The first objective for this report was to perform a comprehensive research of industry models currently being used for similar purposes, in order to provide the Center with ideas of what is being done in area by private companies and government agencies. The second objective was to evaluate the use of taxonomies or ontologies to describe and catalog the areas of expertise at GSFC. The creation of a knowledge taxonomy is necessary for information extraction in order for The Expert Seeker to adequately search and find experts in a particular area of expertise. The requirements to develop a taxonomy are: provide minimal descriptive text; have the appropriate level of abstration; facilitate browsing; ease of use and speed of data entry are critical for success; customized to the organization and its culture; extent of knowledge areas; expandable, so new skills could be develop; could be complemented with free text fields to allow users the option to describe their knowledge in detail.

The effect of food label cues on perceptions of quality and purchase intentions among high-involvement consumers with varying levels of nutrition knowledge.

PubMed

Walters, Amber; Long, Marilee

2012-01-01

To determine whether differences in nutrition knowledge affected how women (a high-involvement group) interpreted intrinsic cues (ingredient list) and extrinsic cues ("all natural" label) on food labels. A 2 (intrinsic cue) × 2 (extrinsic cue) × 2 (nutrition knowledge expert vs novice) within-subject factorial design was used. Participants were 106 female college students (61 experts, 45 novices). Dependent variables were perception of product quality and purchase intention. As predicted by the elaboration likelihood model, experts used central route processing to scrutinize intrinsic cues and make judgments about food products. Novices used peripheral route processing to make simple inferences about the extrinsic cues in labels. Consumers' levels of nutrition knowledge influenced their ability to process food labels. The United States Food and Drug Administration should regulate the "all natural" food label, because this claim is likely to mislead most consumers. Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Shifting public health practice to advance health equity: recommendations from experts and community leaders.

PubMed

Knight, Erin K

2014-01-01

While the evidence base regarding the social determinants of health and their relationship to health inequities grows, the field of public health is challenged to translate this knowledge into practice changes that advance health equity. Drawing on the knowledge, beliefs, and experiences of public health experts and community leaders working to advance health equity, our objective was to develop and disseminate recommendations for changing public health practice to better address this problem. We conducted semistructured, qualitative telephone interviews (n = 25) with key informants. Interviews were recorded and transcribed, and data were coded and analyzed using both inductive and deductive methods. Member checks were used to enhance quality. A purposeful sample of key informants was selected from content experts and community leaders involved with the development of the Unnatural Causes public impact campaign. Participants represented state and local health departments, community-based organizations, national research/advocacy organizations, and academic institutions across the country. Participants distinguished between social determinants of health and their structural precursors in social and political institutions. They believed that the field of public health has an obligation to address health inequities and shifts in practice are needed that focus more attention on societal factors that underlie such inequities. According to participants, specific practice changes are difficult to identify because actions should be community specific and community driven. Recommended approaches that may be adapted to community-based needs and assets include building nontraditional partnerships, engaging in political advocacy, promoting community leadership, collecting better data on social conditions and institutional factors, and enhancing communication for health equity. Recommended shifts in practice may be facilitated by revisiting our understanding of the 3 core functions of public health-assessment, assurance, and policy development.

A theory of expert leadership (TEL) in psychiatry.

PubMed

Goodall, Amanda H

2016-06-01

Leaders' technical competence - 'expert knowledge' - has been shown in many settings to be associated with better organizational performance. In universities, for example, there is longitudinal evidence that research-focused scholars make the best leaders; results from a hospital study show that doctors instead of professional managers are most closely associated with the best performing institutions. To explain these patterns, and raise hypotheses, a theory of expert leadership (TEL) has been developed that might explain these patterns. In this paper the framework for expert leadership is applied to psychiatry. The TEL proposes that psychiatric leaders, as opposed to non-expert managers, improve organizational performance through several channels. First, experts' knowledge influences organizational strategy. Second, having been 'one of them', a psychiatrist understands how to create the optimal work environment for psychiatric teams, through appropriate goal-setting, evaluation and support. These factors are positively associated with workers' wellbeing and performance. Third, exceptional psychiatrist-leaders are likely to set high standards for hiring. Fourth, leaders' credibility extends their influence among core workers, and also signals organizational priorities to stakeholders. Finally, a necessary prerequisite of TEL is that expert leaders have direct executive power inclusive of budgetary and strategic oversight. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Key attributes of expert NRL referees.

PubMed

Morris, Gavin; O'Connor, Donna

2017-05-01

Experiential knowledge of elite National Rugby League (NRL) referees was investigated to determine the key attributes contributing to expert officiating performance. Fourteen current first-grade NRL referees were asked to identify the key attributes they believed contributed to their expert refereeing performance. The modified Delphi method involved a 3-round process of an initial semi-structured interview followed by 2 questionnaires to reach consensus of opinion. The data revealed 25 attributes that were rated as most important that underpin expert NRL refereeing performance. Results illustrate the significance of the cognitive category, with the top 6 ranked attributes all cognitive skills. Of these, the referees ranked decision-making accuracy as the most important attribute, followed by reading the game, communication, game understanding, game management and knowledge of the rules. Player rapport, positioning and teamwork were the top ranked game skill attributes underpinning performance excellence. Expert referees also highlighted a number of psychological attributes (e.g., concentration, composure and mental toughness) that were significant to performance. There were only 2 physiological attributes (fitness, aerobic endurance) that were identified as significant to elite officiating performance. In summary, expert consensus was attained which successfully provided a hierarchy of the most significant attributes of expert NRL refereeing performance.

Methods for optimizing solutions when considering group arguments by team of experts

NASA Astrophysics Data System (ADS)

Chernyi, Sergei; Budnik, Vlad

2017-11-01

The article is devoted to methods of expert evaluation. The technology of expert evaluation is presented from the standpoint of precedent structures. In this paper, an aspect of the mathematical basis for constructing a component of decision analysis is considered. In fact, this approach leaves out any identification of their knowledge and skills of simulating organizational and manufacturing situations and taking efficient managerial decisions; it doesn't enable any identification and assessment of their knowledge on the basis of multi-informational and least loss-making methods and information technologies. Hence the problem is to research and develop a methodology for systemic identification of professional problem-focused knowledge acquired by employees operating adaptive automated systems of training management (AASTM operators), which shall also further the theory and practice of the intelligence-related aspects thereof.

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.

When science becomes too easy: Science popularization inclines laypeople to underrate their dependence on experts.

PubMed

Scharrer, Lisa; Rupieper, Yvonne; Stadtler, Marc; Bromme, Rainer

2017-11-01

Science popularization fulfills the important task of making scientific knowledge understandable and accessible for the lay public. However, the simplification of information required to achieve this accessibility may lead to the risk of audiences relying overly strongly on their own epistemic capabilities when making judgments about scientific claims. Moreover, they may underestimate how the division of cognitive labor makes them dependent on experts. This article reports an empirical study demonstrating that this "easiness effect of science popularization" occurs when laypeople read authentic popularized science depictions. After reading popularized articles addressed to a lay audience, laypeople agreed more with the knowledge claims they contained and were more confident in their claim judgments than after reading articles addressed to expert audiences. Implications for communicating scientific knowledge to the general public are discussed.

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.

Medical students' knowledge of ionizing radiation and radiation protection.

PubMed

Hagi, Sarah K; Khafaji, Mawya A

2011-05-01

To assess the knowledge of fourth-year medical students in ionizing radiation, and to study the effect of a 3-hour lecture in correcting their misconceptions. A cohort study was conducted on fourth-year medical students at King Abdul-Aziz University, Jeddah, Kingdom of Saudi Arabia during the academic year 2009-2010. A 7-question multiple choice test-type questionnaire administered before, and after a 3-hour didactic lecture was used to assess their knowledge. The data was collected from December 2009 to February 2010. The lecture was given to 333 (72%) participants, out of the total of 459 fourth-year medical students. It covered topics in ionizing radiation and radiation protection. The questionnaire was validated and analyzed by 6 content experts. Of the 333 who attended the lecture, only 253 (76%) students completed the pre- and post questionnaire, and were included in this study. The average student score improved from 47-78% representing a gain of 31% in knowledge (p=0.01). The results indicated that the fourth-year medical students' knowledge regarding ionizing radiation and radiation protection is inadequate. Additional lectures in radiation protection significantly improved their knowledge of the topic, and correct their current misunderstanding. This study has shown that even with one dedicated lecture, students can learn, and absorb general principles regarding ionizing radiation.

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…

When Do Children Trust the Expert? Benevolence Information Influences Children's Trust More than Expertise

ERIC Educational Resources Information Center

Landrum, Asheley R.; Mills, Candice M.; Johnston, Angie M.

2013-01-01

How do children use informant niceness, meanness, and expertise when choosing between informant claims and crediting informants with knowledge? In Experiment 1, preschoolers met two experts providing conflicting claims for which only one had relevant expertise. Five-year-olds endorsed the relevant expert's claim and credited him with knowledge…

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.

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

USGS Publications Warehouse

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

1994-01-01

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

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.

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.

ECLSS advanced automation preliminary requirements

NASA Technical Reports Server (NTRS)

Lukefahr, Brenda D.; Rochowiak, Daniel M.; Benson, Brian L.; Rogers, John S.; Mckee, James W.

1989-01-01

A description of the total Environmental Control and Life Support System (ECLSS) is presented. The description of the hardware is given in a top down format, the lowest level of which is a functional description of each candidate implementation. For each candidate implementation, both its advantages and disadvantages are presented. From this knowledge, it was suggested where expert systems could be used in the diagnosis and control of specific portions of the ECLSS. A process to determine if expert systems are applicable and how to select the expert system is also presented. The consideration of possible problems or inconsistencies in the knowledge or workings in the subsystems is described.

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.

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…

Cirrus: Inducing Subject Models from Protocol Data

DTIC Science & Technology

1988-08-16

Protocol analysis is used routinely by psychologists and other behavior scientists, and more recently, by knowledge engineers who wish to embed the...knowledge of human experts in an expert system. However, protocol analysis is notoriously difficult and time comsuming . Several systems have been developed to...formal trace of it (a problem behavior graph). The system, however, did not produce an abstract model of the subject. Bhaskar and Simon (1977) avoided the

Cirrus: Inducing Subject Models from Protocol Data

DTIC Science & Technology

1988-08-16

behavior scientists, and more recently, by knowledge engineers who wish to embed the knowledge of human experts in an expert system. However, protocol...analysis is notoriously difficult and time comsuming . Several systems have been developed to aid in protocol analysis. Waterman and Newell (1971, 1973...developed a system that could read the natural langauge of the protocol and produce a formal trace of it (a problem behavior graph). The system, however

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.

Knowledge Requirements and Management in Expert Decision Support Systems for (Military) Situation Assessment

DTIC Science & Technology

1983-08-01

constitutes a fundamental problem in many decision making processes. In business management we face this problem when determining the status of an...Tehiical Report 576 ( 1 ) 4 KNOWLEDGE REQUIREMENTS AND MANAGEMENT IN EXPERT DECISION SUPPORT SYSTEMS FOR (MILITARY) SITUATION ASSESSMENT MOOM sen...accomplished under contract for the Department of the Army The Israel Institute of Business Research Technical review by Robert H. Sasmor Joseph M

Knowledge Acquisition for Expert Systems in Construction

DTIC Science & Technology

1988-12-01

following scientific personnel have been closely involved in the execution of this research : Dr R J Allwood Mr A E Bryman Mr C N Cooper Dr J Cullen Mr...alternative methods and should use them flexibly as the position unfolds. This approach has been advocated by other researchers (eg Cordingley - see Diaper...currently engaged in research into methods of knowledge acquisition for expert systems. Although their original focus was on construction industry

TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed

NASA Technical Reports Server (NTRS)

Bull, John

1990-01-01

The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

We’re only in it for the knowledge? A problem solving turn in environment and health expert elicitation

PubMed Central

2012-01-01

Background The FP6 EU HENVINET project aimed at synthesizing the scientific information available on a number of topics of high relevance to policy makers in environment and health. The goal of the current paper is to reflect on the methodology that was used in the project, in view of exploring the usefulness of this and similar methodologies to the policy process. The topics investigated included health impacts of the brominated flame retardants decabrominated diphenylether (decaBDE) and hexabromocyclododecane (HBCD), phthalates highlighting di(2-ethylhexyl)phthalate (DEHP), the pesticide chlorpyrifos (CPF), nanoparticles, the impacts of climate change on asthma and other respiratory disorders, and the influence of environment health stressors on cancer induction. Methods Initially the focus was on identifying knowledge gaps in the state of the art in scientific knowledge. Literature reviews covered all elements that compose the causal chain of the different environmental health issues from emissions to exposures, to effects and to health impacts. Through expert elicitation, knowledge gaps were highlighted by assessing expert confidence using calibrated confidence scales. During this work a complementary focus to that on knowledge gaps was developed through interdisciplinary reflections. By extending the scope of the endeavour from only a scientific perspective, to also include the more problem solving oriented policy perspective, the question of which kind of policy action experts consider justifiable was addressed. This was addressed by means of a questionnaire. In an expert workshop the results of both questionnaires were discussed as a basis for policy briefs. Results The expert elicitation, the application of the calibrated confidence levels and the problem solving approach were all experienced as being quite challenging for the experts involved, as these approaches did not easily relate to mainstream environment and health scientific practices. Even so, most experts were quite positive about it. In particular, the opportunity to widen one’s own horizon and to interactively exchange knowledge and debate with a diversity of experts seemed to be well appreciated in this approach. Different parts of the approach also helped in focussing on specific relevant aspects of scientific knowledge, and as such can be considered of reflective value. Conclusions The approach developed by HENVINET was part of a practice of learning by doing and of interdisciplinary cooperation and negotiation. Ambitions were challenged by unforeseen complexities and difference of opinion and as no Holy Grail approach was at hand to copy or follow, it was quite an interesting but also complicated endeavour. Perfection, if this could be defined, seemed out of reach all the time. Nevertheless, many involved were quite positive about it. It seems that many felt that it fitted some important needs in current science when addressing the needs of policy making on such important issues, without anyone really having a clue on how to actually do this. Challenging questions remain on the quality of such approach and its product. Practice tells us that there probably is no best method and that the best we can do is dependent on contextual negotiation and learning from experiences that we think are relevant. PMID:22759503

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

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).

Development of a measure of knowledge use by stakeholders in rehabilitation technology

PubMed Central

Nobrega, Amanda R; Lane, Joseph P; Tomita, Machiko R; Usiak, Douglas J; Lockett, Michelle M

2014-01-01

Objectives: Uptake of new knowledge by diverse and diffuse stakeholders of health-care technology innovations has been a persistent challenge, as has been measurement of this uptake. This article describes the development of the Level of Knowledge Use Survey instrument, a web-based measure of self-reported knowledge use. Methods: The Level of Knowledge Use Survey instrument was developed in the context of assessing effectiveness of knowledge communication strategies in rehabilitation technology. It was validated on samples representing five stakeholder types: researchers, manufacturers, clinician–practitioners, knowledge brokers, and consumers. Its structure is broadly based on Rogers’ stages of innovation adoption. Its item generation was initially guided by Hall et al’s Levels of Use framework. Item selection was based on content validity indices computed from expert ratings (n 1 = 4; n 2 = 3). Five representative stakeholders established usability of the web version. The version included 47 items (content validity index for individual items >0.78; content validity index for a scale or set of items >0.90) in self-reporting format. Psychometrics were then established for the version. Results: Analyses of data from small (n = 69) and large (n = 215) samples using the Level of Knowledge Use Survey instrument suggested a conceptual model of four levels of knowledge use—Non-awareness, Awareness, Interest, and Use. The levels covered eight dimensions and six user action categories. The sequential nature of levels was inconclusive due to low cell frequencies. The Level of Knowledge Use Survey instrument showed adequate content validity (≈ 0.88; n = 3) and excellent test–retest reliability (1.0; n = 69). It also demonstrated good construct validity (n = 215) for differentiating among new knowledge outputs (p < 0.001) and among stakeholder types (0.001 < p ≤ 0.013). It showed strong responsiveness to change between baseline and follow-up testing (0.001 < p ≤ 0.002; n = 215). Conclusion: The Level of Knowledge Use Survey instrument is valid and reliable for measuring uptake of innovations across diffuse stakeholders of rehabilitation technologies and therefore also for tracking changes in knowledge use. PMID:26770743

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.

An expert systems approach to automated fault management in a regenerative life support subsystem

NASA Technical Reports Server (NTRS)

Malin, J. T.; Lance, N., Jr.

1986-01-01

This paper describes FIXER, a prototype expert system for automated fault management in a regenerative life support subsystem typical of Space Station applications. The development project provided an evaluation of the use of expert systems technology to enhance controller functions in space subsystems. The software development approach permitted evaluation of the effectiveness of direct involvement of the expert in design and development. The approach also permitted intensive observation of the knowledge and methods of the expert. This paper describes the development of the prototype expert system and presents results of the evaluation.

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

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

Human factors involvement in bringing the power of AI to a heterogeneous user population

NASA Technical Reports Server (NTRS)

Czerwinski, Mary; Nguyen, Trung

1994-01-01

The Human Factors involvement in developing COMPAQ QuickSolve, an electronic problem-solving and information system for Compaq's line of networked printers, is described. Empowering customers with expert system technology so they could solve advanced networked printer problems on their own was a major goal in designing this system. This process would minimize customer down-time, reduce the number of phone calls to the Compaq Customer Support Center, improve customer satisfaction, and, most importantly, differentiate Compaq printers in the marketplace by providing the best, and most technologically advanced, customer support. This represents a re-engineering of Compaq's customer support strategy and implementation. In its first generation system, SMART, the objective was to provide expert knowledge to Compaq's help desk operation to more quickly and correctly answer customer questions and problems. QuickSolve is a second generation system in that customer support is put directly in the hands of the consumers. As a result, the design of QuickSolve presented a number of challenging issues. Because the produce would be used by a diverse and heterogeneous set of users, a significant amount of human factors research and analysis was required while designing and implementing the system. Research that shaped the organization and design of the expert system component as well.

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.

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.

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.

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.

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.

Developpement energetique par modelisation et intelligence territoriale: Un outil de prise de decision participative pour le developpement durable des projets eoliens

NASA Astrophysics Data System (ADS)

Vazquez Rascon, Maria de Lourdes

This thesis focuses on the implementation of a participatory and transparent decision making tool about the wind farm projects. This tool is based on an (argumentative) framework that reflects the stakeholder's values systems involved in these projects and it employs two multicriteria methods: the multicriteria decision aide and the participatory geographical information systems, making it possible to represent this value systems by criteria and indicators to be evaluated. The stakeholder's values systems will allow the inclusion of environmental, economic and social-cultural aspects of wind energy projects and, thus, a sustainable development wind projects vision. This vision will be analyzed using the 16 sustainable principles included in the Quebec's Sustainable Development Act. Four specific objectives have been instrumented to favor a logical completion work, and to ensure the development of a successfultool : designing a methodology to couple the MCDA and participatory GIS, testing the developed methodology by a case study, making a robustness analysis to address strategic issues and analyzing the strengths, weaknesses, opportunities and threads of the developed methodology. Achieving the first goal allowed us to obtain a decision-making tool called Territorial Intelligence Modeling for Energy Development (TIMED approach). The TIMED approach is visually represented by a figure expressing the idea of a co-construction decision and where ail stakeholders are the focus of this methodology. TIMED is composed of four modules: Multi-Criteria decision analysis, participatory geographic Information systems, active involvement of the stakeholders and scientific knowledge/local knowledge. The integration of these four modules allows for the analysis of different implementation scenarios of wind turbines in order to choose the best one based on a participatory and transparent decision-making process that takes into account stakeholders' concerns. The second objective enabled the testing of TIMED in an ex-post experience of a wind farm in operation since 2006. In this test, II people participated representing four stakeholder' categories: the private sector, the public sector, experts and civil society. This test allowed us to analyze the current situation in which wind projects are currently developed in Quebec. The concerns of some stakeholders regarding situations that are not considered in the current context were explored through a third goal. This third objective allowed us to make simulations taking into account the assumptions of strategic levels. Examples of the strategic level are the communication tools used to approach the host community and the park property type. Finally, the fourth objective, a SWOT analysis with the participation of eight experts, allowed us to verify the extent to which TIMED approach succeeded in constructing four fields for participatory decision-making: physical, intellectual, emotional and procedural. From these facts, 116 strengths, 28 weaknesses, 32 constraints and 54 opportunities were identified. Contributions, applications, limitations and extensions of this research are based on giving a participatory decision-making methodology taking into account socio-cultural, environmental and economic variables; making reflection sessions on a wind farm in operation; acquiring MCDA knowledge for participants involved in testing the proposed methodology; taking into account the physical, intellectual, emotional and procedural spaces to al1iculate a participatory decision; using the proposed methodology in renewable energy sources other than wind; the need to an interdisciplinary team for the methodology application; access to quality data; access to information technologies; the right to public participation; the neutrality of experts; the relationships between experts and non-experts; cultural constraints; improvement of designed indicators; the implementation of a Web platform for participatory decision-making and writing a manual on the use of the developed methodology. Keywords: wind farm, multicriteria decision, geographic information systems, TIMED approach, sustainable wind energy projects development, renewable energy, social participation, robustness concern, SWOT analysis.

Fully automated reconstruction of three-dimensional vascular tree structures from two orthogonal views using computational algorithms and productionrules

NASA Astrophysics Data System (ADS)

Liu, Iching; Sun, Ying

1992-10-01

A system for reconstructing 3-D vascular structure from two orthogonally projected images is presented. The formidable problem of matching segments between two views is solved using knowledge of the epipolar constraint and the similarity of segment geometry and connectivity. The knowledge is represented in a rule-based system, which also controls the operation of several computational algorithms for tracking segments in each image, representing 2-D segments with directed graphs, and reconstructing 3-D segments from matching 2-D segment pairs. Uncertain reasoning governs the interaction between segmentation and matching; it also provides a framework for resolving the matching ambiguities in an iterative way. The system was implemented in the C language and the C Language Integrated Production System (CLIPS) expert system shell. Using video images of a tree model, the standard deviation of reconstructed centerlines was estimated to be 0.8 mm (1.7 mm) when the view direction was parallel (perpendicular) to the epipolar plane. Feasibility of clinical use was shown using x-ray angiograms of a human chest phantom. The correspondence of vessel segments between two views was accurate. Computational time for the entire reconstruction process was under 30 s on a workstation. A fully automated system for two-view reconstruction that does not require the a priori knowledge of vascular anatomy is demonstrated.

Using the "Expert Performance Approach" as a Framework for Improving Understanding of Expert Learning

ERIC Educational Resources Information Center

Williams, A. Mark; Fawver, Bradley; Hodges, Nicola J.

2017-01-01

The expert performance approach, initially proposed by Ericsson and Smith (1991), is reviewed as a systematic framework for the study of "expert" learning. The need to develop representative tasks to capture learning is discussed, as is the need to employ process-tracing measures during acquisition to examine what actually changes during…

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.

Theoretical implementation of prior knowledge in the design of a multi-scale prosthesis satisfaction questionnaire.

PubMed

Schürmann, Tim; Beckerle, Philipp; Preller, Julia; Vogt, Joachim; Christ, Oliver

2016-12-19

In product development for lower limb prosthetic devices, a set of special criteria needs to be met. Prosthetic devices have a direct impact on the rehabilitation process after an amputation with both perceived technological and psychological aspects playing an important role. However, available psychometric questionnaires fail to consider the important links between these two dimensions. In this article a probabilistic latent trait model is proposed with seven technical and psychological factors which measure satisfaction with the prosthesis. The results of a first study are used to determine the basic parameters of the statistical model. These distributions represent hypotheses about factor loadings between manifest items and latent factors of the proposed psychometric questionnaire. A study was conducted and analyzed to form hypotheses for the prior distributions of the questionnaire's measurement model. An expert agreement study conducted on 22 experts was used to determine the prior distribution of item-factor loadings in the model. Model parameters that had to be specified as part of the measurement model were informed prior distributions on the item-factor loadings. For the current 70 items in the questionnaire, each factor loading was set to represent the certainty with which experts had assigned the items to their respective factors. Considering only the measurement model and not the structural model of the questionnaire, 70 out of 217 informed prior distributions on parameters were set. The use of preliminary studies to set prior distributions in latent trait models, while being a relatively new approach in psychological research, provides helpful information towards the design of a seven factor questionnaire that means to identify relations between technical and psychological factors in prosthetic product design and rehabilitation medicine.

Developing expectations regarding the boundaries of expertise.

PubMed

Landrum, Asheley R; Mills, Candice M

2015-01-01

Three experiments examined elementary school-aged children's and adults' expectations regarding what specialists (i.e., those with narrow domains of expertise) and generalists (i.e., those with broad domains of expertise) are likely to know. Experiment 1 demonstrated developmental differences in the ability to differentiate between generalists and specialists, with younger children believing generalists have more specific trivia knowledge than older children and adults believed. Experiment 2 demonstrated that children and adults expected generalists to have more underlying principles knowledge than specific trivia knowledge about unfamiliar animals. However, they believed that generalists would have more of both types of knowledge than themselves. Finally, Experiment 3 demonstrated that children and adults recognized that underlying principles knowledge can be generalized between topics closely related to the specialists' domains of expertise. However, they did not recognize when this knowledge was generalizable to topics slightly less related, expecting generalists to know only as much as they would. Importantly, this work contributes to the literature by showing how much of and what kinds of knowledge different types of experts are expected to have. In sum, this work provides insight into some of the ways children's notions of expertise change over development. The current research demonstrates that between the ages of 5 and 10, children are developing the ability to recognize how experts' knowledge is likely to be limited. That said, even older children at times struggle to determine the breadth of an experts' knowledge. Copyright © 2014 Elsevier B.V. All rights reserved.

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.…

Perspective on intelligent avionics

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

Jones, H.L.

1987-01-01

Technical issues which could potentially limit the capability and acceptibility of expert systems decision-making for avionics applications are addressed. These issues are: real-time AI, mission-critical software, conventional algorithms, pilot interface, knowledge acquisition, and distributed expert systems. Examples from on-going expert system development programs are presented to illustrate likely architectures and applications of future intelligent avionic systems. 13 references.

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...

What Matters Most: A Comparison of Expert and Novice Teachers' Noticing of Mathematics Classroom Events

ERIC Educational Resources Information Center

Huang, Rongjin; Li, Yeping

2012-01-01

In this study, we examined 10 expert and 10 novice teachers' noticing of classroom events in China. It was found that both expert and novice teachers, who were selected from two cities in China, highly attended to developing students' mathematics knowledge coherently and developing students' mathematical thinking and ability; they also paid…