• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.463-466
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• 2003

Fuzzy set expressing category in fuzzy rating, which is a kind of psychological scaling, is dependent on situations. This paper assumes that a mapping exists between fuzzy sets expressing categories in some situation and those expressing same categories in another situation. fuzzy sets expressing categories in some situation are obtained by fuzzy sets expressing categories in another situation and the mapping between them. The usefulness of the present method is confirmed by the experiments comparing fuzzy sets obtained by the presented method with those identified directly by fuzzy rating. The normalized distance is used to compare both fuzzy sets and the experimental results show that the normalized distances between both fuzzy sets are enough small and that the presented method is useful for psychological scaling.

• Journal of Information Technology Applications and Management
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• 제11권4호
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• pp.95-102
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• 2004

This paper proposes a method of segmenting compound nouns which include unregistered nouns into a correct combination of unit nouns using characteristics of person's names, loanwords, and location names. Korean person's name is generally composed of 3 syllables, only relatively small number of syllables is used as last names, and the second and the third syllables combination is somewhat restrictive. Also many person's names appear with clue words in compound nouns. Most loanwords have one or more syllables which cannot appear in Korean words, or have sequences of syllables different from usual Korean words. Location names are generally used with clue words designating districts in compound nouns. Use of above characteristics to analyze compound nouns not only makes segmentation more accurate, helps natural language systems use semantic categories of those unregistered nouns. Experimental results show that the precision of our method is approximately 98% on average. The precision of human names and loanwords recognition is about 94% and about 92% respectively.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2003년도 춘계학술대회논문집
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• pp.319-322
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• 2003

For the analysis of leveling process by the 3-dimensional elastic-plastic finite element method, a finite element analysis program modeling large deformation of shell has been developed. This program fur analyzing large deformation of sheet during leveling includes spring-back analysis as well as efficient contact treatment between sheet and rolls of leveler. This is verified by the simple leveling experiment with 5 rolls at laboratory. Besides the leveling examples, problems within the category of large strain and rotation, such as 3-dimensional roll-up and gutter occurrence at continuous bending-unbending process are also tested for verification of the program. The residual curvatures of strip predicted by finite element analysis are within 20% error range of the experiment. The formation and direction of anticlastic curvature or gutter during bending-unbending under tension is predicted and this agrees with the experimental results.

• 한국경영과학회지
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• 제31권4호
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• pp.69-87
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• 2006

This paper proposes an effective approach for the part-machine grouping(PMG) based on the non-binary part-machine incidence matrix in which real manufacturing factors such as the operation sequences with multiple visits to the same machine and production volumes of parts are incorporated and each entry represents actual moves due to different operation sequences. The proposed approach adopts Fuzzy ART neural network to quickly create the Initial part families and their machine cells. A new performance measure to evaluate and compare the goodness of non-binary block diagonal solution is suggested. To enhance the poor solution due to category proliferation inherent to most artificial neural networks, a supplementary procedure reassigning parts and machines is added. To show effectiveness of the proposed approach to large-size PMG problems, a psuedo-replicated clustering procedure is designed. Experimental results with intermediate to large-size data sets show effectiveness of the proposed approach.

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.456-465
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• 2003

It is well-known that bio-systems does not calculate inverse dynamics for trajectory planning, but they move by proper modulation of system impedances. Inspired by bio-systems, a biomimetic trajectory planning method is proposed in this work. This scheme is based on employment of redundant actuation which prevails in bio-systems. We discuss that for the generation of the biomimetic trajectory, intelligent structure of bio-systems plays an important role. Redundant actuation and kinematic redundancy fall into such a category of intelligent structure. The proposed biomimetic trajectory planning modulates the complete dynamic behavior such as natural frequencies and damping ratios by using the intelligent structure. Experimental work is illustrated to show the effectiveness of the proposed biomimetic trajectory planning for a five-bar mechanism with redundant actuators.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Clinical and Experimental Pediatrics
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• 제52권6호
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• pp.643-648
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• 2009

Blood eosinophilia can be classified as either familial or acquired. Familial eosinophilia is a rare autosomal dominant disorder characterized by a stable eosinophil count. Acquired eosinophilia is classified further into a primary or secondary phenomenon depending on whether eosinophils are considered integral to the underlying disease. Primary eosinophilia is considered clonal in the presence of either a cytogenetic abnormality or bone marrow histological evidence of classified hematologic malignancies. Causes of secondary eosinophilia include infections, allergic or immunologic disorders, and drugs. Idiopathic eosinophilia belongs to a category of primary eosinophilia, and this is a diagnosis of exclusion. Cases with eosinophilia that lack evidence of clonality may be diagnosed as idiopathic hypereosinophilic syndrome after all causes of reactive eosinophilia have been eliminated. Genetic mutations involving the platelet-derived growth receptor genes (PDGFRA and PDGFRB) have been pathogenetically linked to clonal eosinophilia, and their presence predicts the treatment response to imatinib. In this review, I will present a clinical summary of both familial and acquired eosinophilia with emphasis on recent developments in molecular pathogenesis and treatment.

• 한국자동차공학회논문집
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• 제10권4호
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• pp.158-165
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• 2002

This Paper deals with the headlamp lens surface temperature distribution of p/c headlamp using the three categories of H4 halogen bulbs. Glass is gradually replaced by P/C for the lens material off vehicle headlamp due to the weight reduction and stream lined body of a vehicle. With this trend, the newly established standards for a headlamp with a P/C lens in Europe requires that the heat generated by a bulb should not distort the lens surface. Also the requirements fur the bulb of a headlamp are being enforced in U.S.A & Europe. However, such requirements are not established yet in Korea. By using three kinds (60/55w, 100/90w, 130/90w) of H4 halogen bulbs in this experiment, the surface temperature distribution and Max. temperature on the lens were measured. The results of this study implies the necessity of requirement fur the bulb off headlamp.

• Journal of the Korean Data and Information Science Society
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• 제11권1호
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• pp.19-30
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• 2000

정보통신기술의 비약적인 발전은 온라인으로 생성되는 전자문서의 양을 폭발적으로 증가시키고 있다. 따라서 수동으로 문서를 분류하던 종래의 방법 대신 문서의 자동분유 기술 개발이 특별히 요구되고 있다. 본 논문에서는 베이지안 학습 기법을 이용하여 문서를 자동으로 분류하는 방법을 연구하고, 20개의 유즈넷 뉴스그룹 문서들을 분류하도록 시험하였다. 사용한 알고리즘은 Naive Bayes Classifier이며, 구현한 시스템을 이용해 유즈넷 문서를 대상으로 자동분류를 실험한 결과 분류의 정확률이 약 77%로 나타났다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.