Expert Systems for the Prediction of Ovulation: Comparison of an Expert System Shell (Expertech Xi Plus) with a Program Written in a Traditional Language (BASIC)

1990 ◽  
Vol 29 (02) ◽  
pp. 140-145 ◽  
Author(s):  
A. Schreiner ◽  
T. Chard
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Diagnostic Accuracy ◽  
Knowledge Base ◽  
Ease Of Use ◽  
User Friendliness ◽  
Patient Response ◽  
Memory Space ◽  
Computer Diagnosis ◽  
Expert System Shell

AbstractThe use of an expert system shell (EXPERTECH Xi Plus) in the construction of an expert system for the diagnosis of infertility has been evaluated. A module was devised for predicting ovulation from the medical history alone. Two versions of this system were constructed, one using the expert system shell, and the other using QuickBASIC. The two systems have been compared with respect to: (1) ease of construction; (2) ease of knowledge base update; (3) help and explanation facilities; (4) diagnostic accuracy; (5) acceptability to patients and clinicians; (6) user-friendliness and ease of use; (7) use of memory space; and (8) run time. The responses of patients and clinicians were evaluated by questionnaires. The predictions made by the computer systems were compared to the conclusions reached by clinicians and to the “gold standard” of day 21 progesterone.The conclusions of this pilot study are: (1) the construction of this expert system was NOT facilitated by the use of this expert system shell; (2) update of the knowledge base was not facilitated either; (3) the expert system shell offered built-in help and explanation facilities, but as the system increased in complexity these became less useful; (4) after initial adjustment of decision thresholds the diagnostic accuracy of the system equalled that of the clinician; (5) the patient response to computer history-taking was very favorable but much less favorable to computer diagnosis; (6) the clinicians took a positive attitude to computer diagnosis; (7) the systems were easy to use; (8) the expert systems shell required much more memory space and had a much slower response time than the system written in BASIC.

Developing and Using an Expert System for Planning the Production of Structural Piece-Parts

1992 ◽  
Vol 8 (03) ◽  
pp. 163-183
Author(s):  
Mark Spicknall
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Production Process ◽  
Production Facility ◽  
Inference Process ◽  
Expert System Shell ◽  
Production Processes ◽  
Potential Applications ◽  
Part Production

This paper presents an example of how expert systems can be developed and used for planning structural piece-part production. First, expert systems are briefly and generically described. Then the production processes within a shipyard-like structural piece-part production facility are defined within an expert system "shell"; that is, the "objects," "attributes," and "rules" describing the production process are established and explained. Then various structural piece-parts are described to the system and the system identifies the required production processes for each described part. The inference process underlying the identification of these processes is described for each of these parts. Finally, potential applications of expert systems to other areas of shipbuilding operations are discussed.

Ontology-Based Document Management System for Public Institutions

2014 ◽  
pp. 234-254
Author(s):  
Aurelia Pătraşcu ◽  
Ana Tănăsescu ◽  
Constanţa-Nicoleta Bodea ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Open Source ◽  
Management System ◽  
Public Institutions ◽  
Town Planning ◽  
Document Management ◽  
Application Server ◽  
Expert System Shell ◽  
Document Management System

This chapter presents an ontology-based document management system developed for the Romanian public institutions. The system meets both general and specific requirements for this type of organization. The system has a three-tier architecture. FileZilla ftp server version 0.9.37 was used as application server. Jess Expert System Shell version 7.0p1 was the solution in developing knowledge base of the system and MySQL open-source server, version 5.0.51 is chosen for data tier. The system ontology is developed using the Protégé environment. The system is validated and deployed at Ploiesti City Hall. Employees from different departments (town planning, taxes etc.) working with the system provided validation information.

Logic Programming Languages for Expert Systems

2011 ◽  
pp. 593-603
Author(s):  
James D. Jones
Keyword(s):  
Expert System ◽  
Knowledge Representation ◽  
Expert Systems ◽  
Logic Programming ◽  
Programming Languages ◽  
Default Reasoning ◽  
Enterprise Information ◽  
Expert System Shell ◽  
Closed World ◽  
Logic Programming Languages

“Expert systems” are a significant subset of what is known as “decision support systems” (DSS). This article suggests a different paradigm for expert systems than what is commonly used. Most often, expert systems are developed with a tool called an “expert system shell.” For the more adventurous, an expert system might be developed with Prolog, a language for artificial intelligence. Both Prolog and expert system shells stem from technology that is approximately 30 years old.1 There have been updates to these platforms, such as GUI interfaces, XML interfaces, and other “bells and whistles.” However, the technology is still fundamentally old. As an analogy, the current technology is akin to updating a 30-year-old car with new paint (a gooey interface), new upholstery, GPS, and so forth. However, the car is fundamentally still a 30-year-old car. It may be in far better shape than another 30-year-old car without the updates, but it cannot compete from an engineering perspective with current models.2 Similarly, the reasoning power of current expert system technology cannot compete with the reasoning power of the state of the art in logic programming. These advances that have taken place in the logic programming community since the advent of Prolog and expert system shells include: a well developed theory of multiple forms of negation, an understanding of open domains, and the closed world assumption, default reasoning with exceptions, reasoning with respect to time (i.e., a solution to the frame problem and introspection with regard to previous beliefs), reasoning about actions, introspection, and maintaining multiple views of the world simultaneously (i.e., reasoning with uncertainty). This article examines a family of logic programming languages. This article in conjunction with a companion article this volume, Knowledge Representation That Can Empower Expert Systems, suggest that logic programs employing recent advances in semantics and in knowledge representation provide a more robust framework in which to develop expert systems. The author has successfully applied this paradigm and these ideas to financial applications, security applications, and enterprise information systems.

Experiments with Expert Systems in Management Education

1991 ◽  
Vol 6 (1) ◽  
pp. 34-38
Author(s):  
Malcolm King ◽  
Laurie Mcaulay
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Management Education ◽  
Simple System ◽  
Expert System Shell ◽  
Educational Requirements ◽  
Management Students ◽  
Simple Systems ◽  
Education Process

A simple system has been developed using expert systems technology to assist lecturers in teaching specific groups of professional and management students. To enable comparisons to be made, two versions of the system were built; one in prolog and one in an inexpensive expert system shell. The systems were designed to relieve lecturers by providing answers and explanations for examination questions in the area of standard costing. The experiments show that such simple systems can be developed by lecturers for their own use, although there are limitations, especially in the knowledge which can be captured. Testing of the system in practice has shown benefits in terms of reduced lecturer load and positive responses from students. The experiments show that integrating simple expert systems into the education process can be beneficial when the technology is adapted to match the educational requirements.

Knowledge-acquisition tools with explicit problem-solving models

1993 ◽  
Vol 8 (1) ◽  
pp. 5-25 ◽  
Author(s):  
William Birmingham ◽  
Georg Klinker
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Code Generation ◽  
System Development ◽  
Generalization Error ◽  
Domain Experts ◽  
The Past

AbstractIn the past decade, expert systems have been applied to a wide variety of application tasks. A central problem of expert system development and maintenance is the demand placed on knowledge engineers and domain experts. A commonly proposed solution is knowledge-acquisition tools. This paper reviews a class of knowledge-acquisition tools that presuppose the problem-solving method, as well as the structure of the knowledge base. These explicit problem-solving models are exploited by the tools during knowledge-acquisition, knowledge generalization, error checking and code generation.

scholarly journals Diagnose Expert System Computer Malfunction Certainty Factor Method

2020 ◽  
Vol 2 (1) ◽  
pp. 63-71
Author(s):  
Djouking Kiray ◽  
Fricles Ariwisanto Sianturi
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Base System ◽  
Certainty Factor ◽  
Factor Method ◽  
Knowledge Base System ◽  
Two Factors ◽  
Computer Based

An expert system is a knowledge base system that solves problems using an expert's knowledge that is entered into a computer, thereby increasing productivity, Because an expert can work faster than a human lay works like an expert. Expert systems Also solve problems by imitating the ways in the which an expert expert offer section with problems in his field, one of the which is in the field of computer repair, the problem of computer damage Becomes a fairly complicated problem, this problem is Generally experienced by individuals and institutions. One of them is in school institutions that have computer laboratories. to diagnose computer use can damage the certainty factor method that helps identify damage to the computer and find the cause of damage to the computer based on the symptoms that occur and the solution to repair it. Certainty Factor is one of the techniques used to deal with uncertainty in decision making. In dealing with a problem, answers are Often found that do not have full certainty. This uncertainty is influenced by two factors items, namely the uncertain rules and user uncertain answers. Uncertain rules are rules of symptoms that are determined for a damage.

The application of expert systems in the clinical laboratory.

1989 ◽  
Vol 35 (8) ◽  
pp. 1595-1600 ◽  
Author(s):  
P Winkel
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Clinical Laboratory ◽  
Laboratory Medicine ◽  
General Nature ◽  
Inference System

Abstract An "expert system" consists of a knowledge base containing information of a general nature and an inference system that receives data from the user and applies the knowledge base to produce advice and explanations. An expert system stripped of its knowledge base (a tool) may be used to build new expert systems. Existing systems relevant for laboratory medicine are reviewed. The role in the laboratory of expert systems and their integration and evaluation are discussed.

scholarly journals Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

2020 ◽  
Vol 10 (23) ◽  
pp. 8423
Author(s):  
Donatas Vitkus ◽  
Jonathan Salter ◽  
Nikolaj Goranin ◽  
Dainius Čeponis
Keyword(s):  
Expert System ◽  
Risk Analysis ◽  
Expert Systems ◽  
Knowledge Base ◽  
Automated Analysis ◽  
Knowledge Bases ◽  
It Security ◽  
Security Risk ◽  
Attack Tree ◽  
Attack Trees

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.

An Expert System Shell for Fault Diagnosis

Robotica ◽  
2001 ◽  
Vol 19 (6) ◽  
pp. 669-674 ◽  
Author(s):  
Jie Yang ◽  
Chenzhou Ye ◽  
Xiaoli Zhang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Expert System ◽  
Knowledge Representation ◽  
Expert Systems ◽  
Knowledge Representation And Reasoning ◽  
Multiple Models ◽  
Object Model ◽  
Knowledge Models ◽  
Expert System Shell

Traditional expert systems for fault diagnosis have a bottleneck in knowledge acquisition, and have limitations in knowledge representation and reasoning. A new expert system shell for fault diagnosis is presented in this paper to develop multiple knowledge models (object model, rules, neural network, case-base and diagnose models) hierarchically based on multiple knowledge. The structure of the expert system shell and the knowledge representation of multiple models are described. Diagnostic algorithms are presented for automatic modeling and hierarchical reasoning. It will be shown that the expert system shell is very effective in building diagnostic expert systems.

Pest Plant Disease Prevention and Identification System Using Certainty Factor Method

2018 ◽  
Vol 7 (3.2) ◽  
pp. 763 ◽  
Author(s):  
Robbi Rahim ◽  
Nuning Nurna Dewi S ◽  
M Zamroni ◽  
Lilla Puji Lestari ◽  
Muh Barid Nizarudin Wajdi ◽  
...  
Keyword(s):  
Expert System ◽  
Disease Prevention ◽  
Expert Systems ◽  
Knowledge Base ◽  
Plant Disease ◽  
Expert Knowledge ◽  
Identification System ◽  
Certainty Factor ◽  
Factor Method

Diseases in plants are something that can happen to many plants either caused by pests or other factors, the disease in plants can be detected based on the symptoms that appear on the plant before spreading to all plants, to recognize the symptoms and types of diseases contained in plants require plant experts or also by applying expert systems with expert knowledge base applied to the system by using certain methods such as certainty factor method. Expected results with the availability of this expert system to the user can help many users to detect diseases in plants.  

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