• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.237-240
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• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.262-273
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• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.3
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• pp.35-53
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• 1994

Orthographic views ore traditionally used for engineering drawings. This paper presents a methodology for 3D parametric design using orthographic views. The parametric design technique, which is used to design 2D orthographic views, is based on production rules. In the production rule-base, several view interrelation rules and over 50 geometric rules are included. An efficient algorithm is also developed to expedite the reasoning process. For 3D object construction from orthographic views, the approach known as bottom-up geometrical approach is used. The approach consists of 4 steps : 1) generation of wire-frame, 2) construction of face from wire frame, 3) formation of 3D subobjects from faces, and 4) construction of final 3D objects. Curvilinear solids as well as planar solids can be constructed. A method of converting existing 2D CAD data to parametric 3D CAD data is also presented.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.132-137
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• 1993

In this paper, a fish drying process control system is proposed, which predicts the proper change with time in weight of the material fish and the drying conditions in advance, based on the performance of skilled worker. In order to implement a human expertise into an automated fish drying process control system, an experimental analysis is made and a model for the process is built. The proposed system divided into two procedures: The procedure before drying and the one during drying. The procedure before drying is for the prediction of necessary drying time. To estimate the necessary drying time, first, the proper change in weight for the product is obtained by using fuzzy reasoning. The condition part of the production rule consists of the factors of fish body and the expected degree of dryness. Kext, the necessary drying time is obtained by regression models. The variables employed in the models are the factors, inferred change in weight and drying conditions. The model for the procedure during drying is also proposed for more accurate estimation, which is described by a system of linear-differential equations.

• Journal of Internet Computing and Services
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• v.4 no.2
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• pp.61-67
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• 2003

It has recently become known that the social issue of obesity, caused by increased caloric intake and lack of exercise, is a risk factor in the cause of various adult diseases. Above all, to prevent or cure obesity, we must accurately evaluate the degree of obesity, and we have used BML, WHR, and waist measurements for this purpose. In this paper, we propose an obesity evaluation system based on fuzzy inference using BML and waist measurement. For this purpose, we decided reasoning rule and membership function about BML and waist measurements. The inference result is presented in a descriptive sentence.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.185-192
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• 2005

There are many data mining techniques such as association rule, decision tree, neural network analysis, clustering, genetic algorithm, bayesian network, memory-based reasoning, etc. We analyze 2003 Gyeongnam social indicator survey data using k-means clustering technique for environmental information. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper, we used k-means clustering of several clustering techniques. The k-means clustering is classified as a partitional clustering method. We can apply k-means clustering outputs to environmental preservation and environmental improvement.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.1-12
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• 1999

강건설계(robust design)는 낮은 비용으로 잡음에 강건한 고품질의 제품이나 공정을 설계하는 체계적이고 효율적인 방법이다. 그러나 강건설계의 과정 중 비표준 직교배열의 사용과 교호인자을 포함한 실험계획은 다소 복잡하고, 전문지식이 필요한 부분으로 비전문가에는 난해한 작업이다. 이를 해결하기 위하여 본 연구에서는 표준직교배열의 변형과 선점도를 이용하여 교호인자를 직교배열의 열에 자동으로 할당하는 전문가시스템 prototype을 개발하였다. 사용자가 수준별 인자수와 교호작용의 유무를 입력하면, 시스템은 적절한 직교배열을 선정하여 필요에 따라 변형하며, 제어인자와 교호작용을 직교배열표에 자동으로 할당하여 출력한다. 개발된 시스템을 사용함으로써 초보자도 직교배열을 쉽게 변형할 수 있으며 다수의 교호인자를 포함한 실험계획을 빠르게 할 수 있다. 본 연구에서 이용된 지식은 문헌에서 추출하였으며, 추론 전략으로는 규칙기반추론(rule-based reasoning)을 이용하였다.

• Journal of Intelligence and Information Systems
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• v.3 no.1
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• pp.13-30
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• 1997

인공지능 분야 중 하나의 전문시스템 기술은 현재 산업현장에서 여러 가지 분야의 문제 해결에 이용되고 있다. 본 논문은 공압설계를 자동화하기 위한 전문가시스템 PDES(Pneumatic Design Expert System)의 프로토타입 개발에 관한 것이다. 공압설계를 위한 요구 조건이 시스템의 입력정보로 제공되면 공압설계 시방과 공압회로도, 공압작업요소의 영상이 시스템의 출력으로 제시된다. PDES의 지식 베이스는 산업분야 전문가의 전문지식과 경험적 지식을 획득, 분석하여 전문가 시스템 쉘을 이용하여 구성하였으며 추론전략으로는 전향추론을 적용한 규칙기반추론(Rule-Based Reasoning)을 이용하였다. PDES는 공압설계시 설계 업무를 자동화 하여 능률을 향상시켜 줄 뿐만 아니라 공압 관련 비전문가가 공압설계를 할 때에는 큰도움을 줄 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.36-51
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• 1995

An approach to robot hybrid position/force control, which allows force manipulations to be realized without overshoot and overdamping while in the presence of unknown environment, is given in this paper. The manin idea is to used dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify the unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resovled acceleration control method, dynamic compensation and PD control based on known robot dynamics, kinematics and estimated environment stiffness is introduced. To avoid overshoot the whole control system is constructed with overdamping. In the second stage, the unknown environment stiffness is identified by using fuzzy reasoning, where the fuzzy compensation rules are obtained priori as the expression of the relationship betweenenvironment stiffness and system. Based on the simulation result, comparison between cases with or without fuzzy identifications are given, which illustrate the improvement achieced.