• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.673-675
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• 2005

The art psychotherapy expert system is a computer system which helps to analyse one's psychology through pictures. However we need a standard criterion because the psychology, the target of the art psychotherapy, does not only have a ambiguous criterion but also a vast range. We're going to suggest a criterion in the field of the art psychotherapy by constructing systematic database through knowledge acquirement of the art psychotherapy expert system. In this study we introduce a system which enables systematic classification and confirmation of symptoms according to mental analyses. The suggested system enables confirmation of a classical structure and systematic classification of knowledges through conversation by extracting nouns through sentence analysis from the knowledge of descriptive form based on the clinical purpose of sentence analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.11-22
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• 2008

Humans are well-known for being adept at using intuition and expertise in many situations. However, human experts are still susceptible to errors in judgment or execution, and failure to recognize the limits of knowledge. This would happen especially in semi-structured situations, in multi-disciplinary settings, under time or other stress, under uncertainty, or when knowledge is outdated Human errors are caused by cognitive biases, attentional slips/memory lapses, cultural motivations, and missing knowledge. The purpose of this research is to study errors of human experts committed in judgment and the general idea of critiquing systems as corresponding plan. Compared to expert systems, critiquing systems are narrowly focused programs useful in limited situations for collaborating with and supporting experts in their task activities. It supports an expert by detecting the human's errors by deploying various strategies that stimulate humans to improve their performance. A variety of types of critiquing systems has spread through numerous application areas.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.662-670
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• 1998

In order to overcome the problems with first generation expert systems at the symbol level, recently various knowledge level development techniques of second generation expert systems have been proposed. But, these techniques are conceptual modelling techniques. This paper modifies and complements these conceptual modelling techniques and proposes a Task Object Modelling (TOM) technique as a practical knowledge level expert system development technique. This paper defines a Task Object(TO) as a knowledge unit consisted of a goal, execution conditions, behaviour knowledge, and so on. And, we define a Task Object Diagram(TOD) to depict structual, dynamic, and functional aspects of TO easily. We also define Inference Types as basic units to describe behaviour knowledge of TOs. In order to utilize the proposed TOM technique as not a simple conceptual modelling technique but a practical second generalion expert system development technique, we implement a TOD editor, a TO editor, and TO processing algorithm based on the state of TOs. Also we implement a Inference Types Library, in which each inference type is corresponded to an IRE(Jntelligent Rules Element) method, to transform the defined inference types into IRE methods automatically.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.6
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• pp.153-163
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• 1996

An expert system to design compressor valve systems has been developed. Design process is viewed as a chain of devisions based on the results of necessary analyses. Actual design is implemented by the interaction between the expert system and the user. In this work, it is demonstrated how a final design is achieved by utilizing the rule bases and analysis capability of the system. The structure of the rule bases and related parameter studies are also explained. Advantages of using an expert system approach for valve designs are explained using a practical example.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.960-972
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• 1992

This paper deals with the development of expert system in distribution system which combined with graphic user interface. The proposed expert system can recognize and adjust to the system change, and includes the rule bases of security monitoring. Also it provides load transfer algorithm for efficient load distribution. The graphic user environment for expert system is implemented in the mouse-oriented user interface with overlapped window functions and pull-down menus. Therefore, the developed graphic integrated expert system can afford to assist system operators very conveniently through the various graphic function in proposing an optimal plan of load transfer for fault restoration and outage schedule.

• Journal of the Korean Society of Safety
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• v.7 no.4
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• pp.95-99
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• 1992

The attraction of using expert system in operator support systems for modern plant is that it offers a way of dealing with the problem of information overload that can occur during a severe disturbance at a modern industrial plant. During such a disturance the volume of information presented to operators may be such that they are unable to decide quickly what is important and what is not. Therefore, arriving at a correct diagnosis of the initialling fault may be delayed. An expert system operator sup-port system is a means of focusing attention on what really matters and cutting out the rest. This paper presents the development of prototype expert system which detect the fault part, machine, system and decide action priority. This prototype expert system has 6 sub- system which is Interface Manager, Decision Maker, Inference Engine, Knowledge base, Simulatio, and D.P System ( Diagnosis and predictor)

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.190-192
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• 1997

In this paper we developed an object-based expert system for electric power system fault diagnosis. The object corresponds to a hardware or event in real world and they are independent each other. The expert system is designed to estimate the fault sections and identify the false operation, nonoperation of protective devices. The expert system was developed using C++ language in pentium PC. We applied the expert system in various sample systems and showed that making up a knowledge base is easier and diagnosis was done in a approximately real time.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.50-57
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• 2005

This paper describes an expert system for soldiers psychology diagnosis. In the field warfare, platoon leaders or company commanders have to diagnose his soldier's condition correctly. The expert systems, a field of artificial intelligence, can be appropriate approach for ill-structured paradigm. This use an UNIK system. This UNIK system is composed of UNIK-FRAME, UNIK-BWD, UNIK-WBI, UNIK-INDUCE and UNIK-Interface. Especially, UNIK-WBI system is very useful to display soldiers psychology diagnosis and so easy to use it. Any leader or commander can easily do this. This paper data is based on DSMIV. Through This expert system, combat power can be kept and accidents be protected.

• Journal of Welding and Joining
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• v.12 no.3
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• pp.71-81
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• 1994

Laser cutting is experiencing a rising worldwide acceptance in the industry. Expert systems are necessary for the systematic arrangement and searching of experimental data existing in journal papers, job handbooks, etc.. This paper proposes an expert system for the selection of the appropriate laser cutting variables from the available database. Optimum cutting conditions according to the given cutting velocity were searched and qualitative comments which are difficult to be used as database variables were shown at each velocity using the binary and fuzzy inference. These comments could be informative to unskilled operators of the laser cutting process. Typical cutting conditions of the mild steel and stainless steel were included and the working range and quality variations were displayed graphically. The proposed algorithm was implemented in an IBM compatible personal computer as an expert system for CO$_{2}$ laser cutting to derive the optimum cutting conditions by using the turbo prolog.