• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.275-278
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• 1996

This fault diagnosis system consists of qualitative models, qualitative interpreter, and inference engine. Qualitative models are formed by analysis of the relationships between faults and behaviors of sensor trends, which are described by state transition trees. Qualitative interpreter outputs confidence factors with three qualitative quantities which represent the states of sensor trends. And then, the possible faults are detected by inference module which matches the states of trends within a window size with the qualitative models using the well-known min-max operation.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.81-89
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• 1992

After much research on qualitative reasoning, the problem of ambiguities still hampers the practicality of this important AI tool. In this paper, the sources of ambiguities are examined in depth with a systems engineering point of view and possible directions to disambiguation are suggested. This includes some modeling strategies and an architecture of temporal inference for building unambiguous qualitative models of practical complexity. It is argued that knowledge of multiple levels in abstraction hierarchy must be reflected in the modeling to resolve ambiguities by introducing the designer's decisions. The inference engine must be able to integrate two different types of temporal knowledge representation to determine the partial ordering of future events. As an independent quantity management system that supports the suggested modeling approach, LIQUIDS(Linear Quantity-Information Deriving System) is described. The inference scheme can be conjoined with ordinary rule-based reasoning systems and hence generalized into many different domains.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1782-1787
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• 1997

A combined algorithm called APEXS(Alarm Processing and Diagnosis Expert System) for power plants has been developed on the time-based alarm processing with a proper alarm prioritization and a diagnosis with a qualitative model(QM), qualitative interpreter(QI), and a state-transition trees(STT).

• The Journal of Korean Association of Computer Education
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• v.17 no.1
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• pp.97-105
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• 2014

To enhance the practical usage of solely quantitative evaluation method for each students on the current public education fields which might cause some social problems, an intelligent and adaptive fuzzy logical inference methodology for the additional qualitative evaluation technique is proposed to utilize each students personal characteristic properties to be evaluated. Proposed method uses some verbal descriptions for the linguistic qualifier in addition to the grade points. An imaginary virtual experimentation only has been implemented due to some difficulties with the critical national educational policy problems in the case of some possibly real and practical experimental environments to be utilized for the simulation.

• IE interfaces
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• v.17 no.2
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• pp.169-179
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• 2004

In supply chain management, supplier capacity is very important to meet the customer demand quickly. This paper studies a supplier evaluation structure and then suggests a methodology using fuzzy theory for selecting an effective supplier. Several quantitative and qualitative evaluation factors should be analyzed in the evaluation structure. The qualitative factors includes not only product and service qualities but financial condition. The methodology deals with both the quantitative and qualitative factors together through fuzzy inference. A case study is also presented to show how to choose the best one among potential suppliers.

• 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.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1324-1331
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• 1999

물체의 공간에서의 운동을 다루는 공간 추론의 연구에서 충돌을 이해하는 것은 중요하다. 본 논문에서는 정성적 충돌 이론과 추론 기법을 소개하고자 한다. 충돌 해석에 있어 관련된 물체의 공간적 속성과 운동방향의 상호작용을 분석하여 충돌로 인한 힘과 운동 방향의 전달을 계산하였다. 추론 과정에 있어서는 충돌이 갖는 특성인 불연속적인 변화에 대한 분석과 회전 운동으로 인한 변화의 분석이 소개되었다. 제안된 충돌 이론과 추론 기법은 구현되어 자동차 충돌 사고의 충돌에 적용되어 유효성을 입증할 수 있었다. Abstract Understanding collision is important in spatial reasoning problems that study the motions of objects. This paper introduces qualitative collision theory and reasoning techniques. Force and motion transfers are computed by analyzing the interactions of the spatial properties and motions of the objects. This paper also presents inference techniques for handling discontinuous changes and angular changes by rotation. These theories and inference techniques are implemented and applied to real car-to-car collision accidents. The test results verify the reliabilities of our techniques.

• Journal of Families and Better Life
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• v.10 no.1 s.19
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• pp.131-138
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• 1992

Regression analysis has become a standard statistical tool in the behavioral science. Because of its widespread popularity. regression has been often misused. Such is the case when the dependent variable is a qualitative measure rather than a continuous, interval measure. Regression estimates with a qualitative dependent variable does not meet the assumptions underlying regression. It can lead to serious errors in the standard statistical inference. Logit model is recommended as alternatives to the regression model for qualitative dependent variables. Researchers can employ this model to measure the relationship between independent variables and qualitative dependent variables without assuming that logit model was derived from probabilistic choice theory. Coefficients in logit model are typically estimated by the method of Maximum Likelihood Estimation in contrast to ordinary regression model which estimated by the method of Least Squares Estimation. Goodness of fit in logit model is based on the likelihood ratio statistics and the t-statistics is used for testing the null hypothesis.

• Proceedings of the KWS Conference
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• 1994.05a
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• pp.186-189
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• 1994

This paper proposes an expert system for the selection of the appropriate laser cutting variables from the available database. Optimum cutting conditions were searched and qualitative comments which are hard to choose as database variables were shown using the binary and fuzzy inference.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.92-97
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• 1995

In medical diagnostic process we are dealing with the preliminary diagnosis based on the interview chart. We will quantify the qualitative information of a patient by dual scaling and establish both prototypes of fuzzy diagnostic sets and the fuzzy linear regressions. Its utility is shown in the diagnosis of headache and CAFDDH.