Human Factors in the Interpretation of Physiography by Symbolic and Numerical Representations within an Expert System

2001 ◽  
Author(s):  
Demetre Argialas ◽  
G Ch. Miliaresis
Keyword(s):  
Expert System ◽  
Human Factors ◽  
Numerical Representations

Human Factors in Education: Strategic Planning for the Future

1987 ◽  
Vol 31 (7) ◽  
pp. 746-750
Author(s):  
Daniel M. Jesse ◽  
Donald J. Montague
Keyword(s):  
Expert System ◽  
Strategic Planning ◽  
Human Factors ◽  
Future Design ◽  
The Future

This paper will describe the progress and future design of a project to develop an expert system for strategic planning in education. The importance, the applicability, the methodology, objectives and anticipated results will be described in detail along with the educational and scientific importance such a system is capable of achieving.

A Desktop Expert System as a Human Factors Work Aid

1987 ◽  
Vol 31 (10) ◽  
pp. 1087-1090 ◽  
Author(s):  
Craig S. Hartley ◽  
John R. Rice
Keyword(s):  
Expert System ◽  
Human Factors ◽  
Expert Systems ◽  
Knowledge Base ◽  
System Development ◽  
Scientific Publication ◽  
Problem Area ◽  
Video Display ◽  
Problem Domain ◽  
Topic Area

The advent of increasingly powerful microcomputers, coupled with the development of small, feature-packed expert systems now makes it cost effective to provide workers with relatively inexpensive desktop expert systems. In order to evaluate the value of such systems as work aids for human factors engineers, we developed a small demonstration system using a commercially available expert system development tool, NEXPERTTM, released in 1985 by Neuron Data, Inc. of Palo Alto, CA. We selected a candidate problem area based on four criteria: 1) the problem domain had to be small enough to be covered comprehensively by a relatively small knowledge base; 2) the problem domain had to be potentially useful to video display terminal (VDT) screen designers; 3) appropriate information had to be readily available in human factors guidelines, published reports, and journal articles; and 4) the problem should provide the opportunity to exercise as many of the features of NEXPERT as possible. The topic area we selected was “video display screen color”. Our goal was to produce a job performance aid (JPA) that non-human factors VDT screen designers could use to select appropriate colors for screen features. Because the system users typically have little or no formal training in human factors, the JPA has to supply color recommendations in the form of clearly stated requirements, but with the decision rationale and additional references also immediately available for users wanting more information. Using the expert system shell provided by NEXPERT, we constructed a knowledge base containing more than one hundred IF …, THEN … rules representing knowledge gained from a detailed literature review. We initially validated our expert system by posing a wide variety of hypothetical design problems and assessing its conclusions against our expectations. Based on our work so far, we have concluded that small expert systems can be useful in providing human factors expertise to system designers. We believe that increasing use of expert systems may soon lead to changes in the typical current scientific publication format to include knowledge base rules provided by the author(s).

Formulation of Expert System Knowledge

1989 ◽  
Vol 33 (5) ◽  
pp. 350-350
Author(s):  
Deborah A. Mitta
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Human Factors ◽  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Mental Models ◽  
Formal Education ◽  
Domain Expert ◽  
Cognitive Problem ◽  
System Knowledge

Expert system knowledge represents expertise obtained through formal education, training, and/or experience. Formal education provides deep knowledge of a particular domain; experience and training result in heuristic knowledge. A knowledge base defines the range of information and understanding with which the system is capable of dealing; therefore, its information must be structured and filed for ready access. The objective of this symposium is to address the challenges associated with establishment of valid expert system knowledge, specifically, knowledge to be used by expert system shells. As expert system knowledge is obtained, structured, and stored, it is formulated. In this symposium, knowledge formulation is addressed as a three-phase process: knowledge acquisition, the mechanics associated with structuring knowledge, and knowledge porting. Knowledge acquisition is the process of extracting expertise from a domain expert. Expertise may be collected through a series of interviews between the expert and a knowledge engineer or through sessions the expert holds with an automated knowledge acquisition tool. Thus, the ultimate outcome of knowledge acquisition is a collection of raw knowledge data. The following human factors issues become apparent: documenting mental models (where mental models are the expert's conceptualization of a problem), recording cognitive problem-solving strategies, and specifying an appropriate interface between the domain expert and the acquisition methodology. The knowledge structuring process involves the refinement of raw knowledge data, where knowledge is organized and assigned a semantic structure. One issue that must be considered is how to interpret knowledge data such that formal definitions, logical relationships, and facts can be established. Finally, formulation involves knowledge porting, that is, the movement of an expert system shell's knowledge base to various other shells. The outcome of this process is a portable knowledge base, where the challenges lie in maintaining consistent knowledge, understanding the constraints inherent to a shell (the shell's ability to incorporate all relevant knowledge), and designing an acceptable user-expert system interface. The fundamental component of any expert system is its knowledge base. The issues to be presented in this symposium are important because they address three processes that are critical to the development of a knowledge base. In addition to presenting computer science challenges, knowledge base formulation also presents human factors challenges, for example, understanding cognitive problem-solving processes, representing uncertain information, and defining human-expert system interface problems. This symposium will provide a forum for discussion of both types of challenges.

Human Factors Issues in Designing Explanation Facilities for Expert Troubleshooting Systems

1986 ◽  
Vol 30 (5) ◽  
pp. 502-506
Author(s):  
Elizabeth R. Phillips ◽  
David R. Eike ◽  
Stephen A. Fleger
Keyword(s):  
Expert System ◽  
Literature Review ◽  
Human Factors ◽  
System Design ◽  
Alternative Explanation ◽  
Extensive Literature ◽  
Ongoing Research ◽  
Advice Giving ◽  
Computational Aspects

Research has revealed that the extent to which users will utilize an advice-giving expert system is dependent on the quality of the system's explanation facility (Woods, 1986). Independent researchers have attempted to explore alternative explanation concepts by designing and building separate systems to test explanation facility theory. These efforts have focused primarily on the computational aspects of expert system design, leaving many of the central issues concerning human requirements of explanation facilities unresolved. This paper presents results of an extensive literature review designed to identify and define specific human factors issues which must be addressed to determine guidelines or standards for explanation facility design. The work described in this paper is part of an ongoing research program to develop guidelines for developers and users of expert troubleshooting systems (ETS).

Human Factors Evaluation of Gas Turbine Expert System

1987 ◽  
Vol 31 (10) ◽  
pp. 1133-1137
Author(s):  
Christopher G. Koch
Keyword(s):  
User Interface ◽  
Expert System ◽  
Human Factors ◽  
Gas Turbine ◽  
Field Evaluation ◽  
Development Project ◽  
User Training ◽  
Knowledge Based ◽  
Modular Software ◽  
Communications Protocol

A research and development project is under way to specify, design, construct, and evaluate a user interface system to meet the unique requirements of a delivery vehicle for a knowledge-based system applied to gas turbine electronics maintenance and trouble-shooting. The prototype user interface is a portable device with text display, video and overlay graphics display, voice recognition and speech production, special-function keypad, and printer. A modular software structure based on a serial communications protocol between user interface device and expert system host computer provides flexibility, expandability, and a simple, effective user interface dialog. A human factors field evaluation is being conducted to assess aspects of system usability: device hardware, system operability, information presentation effectiveness, and user training.

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