• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.28-42
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• 1996

This paper describes a new automated simulation system for micromachines whose size range $10^{-6}$ to $10^{-3}$ m. An automic finite element (FE) mesh generation technique, which is bases on the fuzzy knowledge processing and computation al geometry technique, is incorporated into the system, together with one of commerical FE analysis codes, MARC ,and one of commerical solid modelers, Designbase. The system allows a geometry model of concern to be automatically converted to different FE models, depending on physical phenomena of micromachines to be analyzed , i,e. electrostatic analysis, stress analysis, modal analysis and so on. The FEmodels are then automatically analyzed using the FE analysis code, Among a whole process of analysis, the definition of a geometry model, the designation of local node patterns and the assignment of material properties and boundary conditions onto the geometry model are only the interactive process to be done by a user. The interactive operations can be processed in a few minutes. The other processes which are time consuming and labour-intensive in conventional CAE systems are fully automatically performed in a popular engineering workstation environment. This automated simulation system is successfully applied to evaluate an electrostatic micro wobble actuator.

• 한국지능시스템학회논문지
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• 제14권4호
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• pp.445-450
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• 2004

본 논문은 실질적인 최적화 구조물의 설계를 위한 시스템에 대한 것으로 퍼지이론에 바탕을 둔 자동 유한요소 생성 망 기술과 계산 기하학적 기술, 해석코드 및 솔리드모델러를 시스템에 통합시켰다. 최적해 또는 만족해는 자동해석 시스템과 함께 탐색공간을 위한 유전자 알고리즘을 이용하여 자동적으로 탐색되어 진다. 또한, 유전자 알고리즘을 이용함으로써 본 설계 시스템은 다차원 해를 얻을 수 있다. 개발된 시스템은 터널전류에 바탕을 둔 마이크로 가속도계의 형상설계에 적용하였다.

• 한국정보처리학회논문지
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• 제1권3호
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• pp.319-326
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• 1994

자동제어는 그 대상이 근사적 수식화가 가능한 선형시스템에 주로 적용되고 있다. 제어대상에 대한 수학적 모델링이 명확하게 결정되지 않는 경우에는 사람이 직접 제 어하는 수동제어를 하게 된다. 본 논문에서는 수영장과 같이 거의 전적으로 숙력가의 경험에 의존하고 있는 수동제어를 자동제어가 가능하게 FLC(Fuzzy Logic Controller) 를 구축하고, 여기서 사용되는 지식을 가장 최적의 상태로 유지하기 위해 genetic 알고리즘을 사용하여 전문가로부터 얻어온 지식을 개선한다. 또한 규칙부와 소속함수 는 동시에 수정되도록 알고리즘을 설계하여 수동제어보다 제어 성능이 향상됨을 보인 다.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.893-913
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• 2017

The handwriting based person identification systems use their designer's perceived structural properties of handwriting as features. In this paper, we present a system that uses those structural properties as features that graphologists and expert handwriting analyzers use for determining the writer's personality traits and for making other assessments. The advantage of these features is that their definition is based on sound historical knowledge (i.e., the knowledge discovered by graphologists, psychiatrists, forensic experts, and experts of other domains in analyzing the relationships between handwritten stroke characteristics and the phenomena that imbeds individuality in stroke). Hence, each stroke characteristic reflects a personality trait. We have measured the effectiveness of these features on a subset of handwritten Devnagari and Latin script datasets from the Center for Pattern Analysis and Recognition (CPAR-2012), which were written by 100 people where each person wrote three samples of the Devnagari and Latin text that we have designed for our experiments. The experiment yielded 100% correct identification on the training set. However, we observed an 88% and 89% correct identification rate when we experimented with 200 training samples and 100 test samples on handwritten Devnagari and Latin text. By introducing the majority voting based rejection criteria, the identification accuracy increased to 97% on both script sets.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• 인지과학
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• 제13권1호
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• pp.13-21
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• 2002

퍼지 논리를 이용한 추론은 일부의 정보가 무시되어 적절하지 못한 추론 결과를 초래할 수 있다. 또한 신경망은 패턴 처리에는 적합하지만 인간의 지식을 모델링하기 위해서 필요한 논리적인 추론에는 부적합하다. 하지만 신경 망의 변형인 신경 논리 망을 이용하면 논리적인 추론이 가능하다. 따라서 본 논문에서는 기존의 신경 논리 망을 기반으로 하는 추론 망을 확장하여 퍼지 추론 망을 구성하고 기존의 추론 망에서 사용되는 전파규칙을 보완하여 적용하고자 한다. 퍼지 추론 망에서 퍼지 규칙의 결론부에 해당하는 명제의 믿음 값을 결정하기 위해서는 추론하고자 하는 명제에 연결된 노드들을 탐색해야 한다. 이를 위해, 연결된 모든 노드들의 링크를 따라 순차적인 탐색을 하는 경우와 링크에 부여된 우선순위에 의해 탐색을 하는 경우의 탐색비용에 대하여 실험을 통해 비교 평가하였다. 실험결과 퍼지 추론 망의 크기가 확장될수록, 그리고 탐색 경험의 횟수가 증가할수록 순차적인 탐색전략보다 우선순위에 의한 탐색전략이 탐색 비용면에서 효율성이 더욱 증가함을 알 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.2126-2133
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• 2014

We present a scalable object tracking framework, which is capable of removing shadows and tracking the people. The framework consists of background subtraction, fuzzy based shadow removal and boundary tracking algorithm. This work proposes a general-purpose method that combines statistical assumptions with the object-level knowledge of moving objects, apparent objects, and shadows acquired in the processing of the previous frames. Pixels belonging to moving objects and shadows are processed differently in order to supply an object-based selective update. Experimental results demonstrate that the proposed method is able to track the object boundaries under significant shadows with noise and background clutter.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.24-26
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• 2005

At present, KS-1000 which is one of a commercial measurement instrument for motor fault diagnosis has been used in industrial field. The measurement system of KS-1000 is composed of three part : harmonic acquisition, signal processing by KS-1000 algorithm, diagnosis for motor fault. First of all, voltage signal taken from harmonic sensor is analysed for frequency by KS-1000 algorithm. Then, based on the result values of analysis skilled expert makes a judgment about whether motor system is the abnormality or degradation state. But the expert system such a motor fault diagnosis is very difficult to bring the expectable results by mathematical modeling due to the complexity of judgment process. In this reason, we propose an automation system using fuzzy model based on genetic algorithm(GA) that builded a qualitative model of a system without priori knowledge about a system provided numerical input output data.

• International Journal of Precision Engineering and Manufacturing
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• 제3권1호
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• pp.43-48
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• 2002

This paper describes an automated computer-aided engineering (CAE) system for three-dimensional structures. An automatic finite element mesh-generation technique, which is based on fuzzy knowledge processing and computational geometry techniques, is incorporated into the system, together with a commercial FE analysis code, and a commercial solid modeler. The system allows a geometry model of interest to be automatically converted to different FE models, depending on the physical phenomena of the structures to be analyzed, i.e., electrostatic analysis, stress analysis, modal analysis, and so on. Also, with the aid of multilayer neural networks, the present system allows us to obtain automatically a design window in which a number of satisfactory design solutions exist in a multi-dimensional design parameter space. The developed CAE system is successfully applied to evaluate an electrostatic micromachines.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.21-26
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• 2016

Canine cataract is developed with aging and can cause the blindness or surgical treatment if not treated timely. The first observation must be made by pet owners but they do not have proper equipment and knowledge to see the abnormalities. In this paper, we propose an intelligent image processing method to extract canine cataract suspicious object from non-professional equipment such as ordinary digital camera and cellular phone photographs so that even casual owners of pet dog can make a pre-diagnosis of such a surgery-needed disease as soon as possible. The experiment shows that the proposed method is successful in most cases except the dog has similar colored hair to the color of cataract.