• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.44-57
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.28-43
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• 1995

This paper concerns with automatic generation of fuzzy rules which can be used for pattern classification. Feature space is recursively subdivided into hyperspheres, and each hypersphere is represented by its centroid and bounding distance. Fuzzy rules are then generated based on the constructed hyperspheres. The resulting fuzzy rules have very simple premise parts, and they can be organized into a hierarchical structure so that classification process can be implemented very rapidly. The experimented results show that the suggested method works very well compared to other methods.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.51-63
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• 1997

Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.

• Proceedings of the KSRS Conference
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• v.1
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• pp.260-262
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• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.

• Journal of the Korean Society of Industry Convergence
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• v.11 no.3
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• pp.141-148
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• 2008

Most of the recent studies on Seowon have been done just in terms of classification of general kinds of building layout, so there are a few things ignored such as the way they were arranged, the compositional process of buildings etc.. Although the classification of types itself is meaningful in the study on Korean traditional architecture, there has been some limitation in deep analysis of each style. The aim of this study is to find out the characteristics of the building layout and space composition of Dodong-Seowon with the viewpoint of the process of changes of it during the time through the survey and analysis on both the existing site layout and the measuring unite of scale applied to the original construction of each building. Hierarchical order scheme was considered in the design of the space proceeding from the entrance to the main space and of the building position, axis and the roof heights of buildings.

• Phonetics and Speech Sciences
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• v.2 no.4
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• pp.109-118
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• 2010

Using a speeded classification task (Garner, 1978), we investigated the perceptual interaction of distinctive features in Korean consonants. The main questions of this study were whether listeners can perceptually identify the component features that make up complex consonant sounds, whether these features are processed independently or dependently and whether there is a systematic hierarchy in their dependency. Participants were asked to classify syllables based on their difference in distinctive features in the task. Reaction times for this task were also gathered. For example, participants classified spoken syllables /ta/ and /pa/ as one category and /$t^ha$/ and /$p^ha$/ as another in terms of aspiration condition. In terms of articulation, participants classified /ta/ and /$t^ha$/ as one category and /pa/ and /$p^ha$/ as another. We assumed that the difference between their RTs represents their interdependency. We compared the laryngeal features and place features (Experiment 1), resonance features and place features (Experiment 2), and manner features and laryngeal features (Experiment 3). The results showed that distinctive features were not perceived in a completely independent way, but they had an asymmetric and hierarchical interdependency. The laryngeal features were found to be more independent compared to place and manner features. We discuss these results in the context of perceptual basis in phonology.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2350-2364
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• 1999

In this paper, we propose a method of class library repository design for provide reuser the object-oriented C++ class component. To class library design, we started by studying the characteristics of a reusable component. We formally defined the reusable component model using an entity relationship model. This formal definition has been directly used as the database schema for storing the reusable component in a repository. The reusable class library may be considered a knowledge base for software reuse. Thus, we used that Enumerative classification of breakdown of knowledge based. And another used classification is clustering of based on class similarity. The class similarity composes member function similarity and member data similarity. Finally, we have designed class library for hierarchical inheritance mechanism of object-oriented concept Generalization, Specialization and Aggregation.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.59-64
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• 2022

한국표준질병사인분류(KCD)는 사람의 질병과 사망 원인을 유사성에 따라 체계적으로 유형화한 분류체계이다. KCD는 계층적 분류체계로 구성되어 있어 분류마다 연관성이 존재하지만, 일반적인 텍스트 분류 모델은 각각의 분류를 독립적으로 예측하기 때문에 계층적 정보를 반영하는 데 한계가 있다. 본 논문은 계층적 분류체계를 적용한 KCD 예측 모델을 제안한다. 제안 방법의 효과를 입증하기 위해 비교 실험을 진행한 결과 F1-score 기준 최대 0.5%p의 성능 향상을 확인할 수 있었다. 특히 비교 모델이 잘 예측하지 못했던 저빈도의 KCD에 대해서 제안 모델은 F1-score 기준 최대 1.1%p의 성능이 향상되었다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.3
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• pp.187-207
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• 2024

This study addresses the limitations of the rigid and simplistic relational structure of the KDC 6th edition's relative index by systematically analyzing the relationships between index terms. Based on this analysis, a flexible and detailed model for structuring the relationships within the relative index is proposed. The study categorizes these relationships into hierarchical, associative, and equivalence relationships, further subdividing them to capture the complexity of the interactions. The proposed model is implemented using RDF syntax, suggesting the potential for extending the relative index into linked data. This model not only clarifies the complex relationships between KDC index terms but also contributes to the development of a dynamic and adaptable classification system capable of effectively incorporating new information.

• Journal of the Korean Geographical Society
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• v.30 no.3
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• pp.296-310
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• 1995

Classification of spatial units into meaningful sets is an important procedure in spatial analysis. It is crucial in characterizing and identifying spatial structures. But traditional classification methods such as cluster analysis require an exact database and impose a clear-cut boundary between classes. Scrutiny of realistic classification problems, however, reveals that available infermation may be vague and that the boundary may be ambiguous. The weakness of conventional methods is that they fail to capture the fuzzy data and the transition between classes. Fuzzy subsets theory is useful for solving these problems. This paper aims to come to the understanding of theoretical foundations of fuzzy spatial analysis, and to find the characteristics of fuzzy classification methods. It attempts to do so through the literature review and the case study of urban classification of the Cities and Eups of Kyung-Nam Province. The main findings are summarized as follows: 1. Following Dubois and Prade, fuzzy information has an imprecise and/or uncertain evaluation. In geography, fuzzy informations about spatial organization, geographical space perception and human behavior are frequent. But the researcher limits his work to numerical data processing and he does not consider spatial fringe. Fuzzy spatial analysis makes it possible to include the interface of groups in classification. 2. Fuzzy numerical taxonomic method is settled by Deloche, Tranquis, Ponsard and Leung. Depending on the data and the method employed, groups derived may be mutually exclusive or they may overlap to a certain degree. Classification pattern can be derived for each degree of similarity/distance $\alpha$. By takina the values of $\alpha$ in ascending or descending order, the hierarchical classification is obtained. 3. Kyung-Nam Cities and Eups were classified by fuzzy discrete classification, fuzzy conjoint classification and cluster analysis according to the ratio of number of persons employed in industries. As a result, they were divided into several groups which had homogeneous characteristies. Fuzzy discrete classification and cluste-analysis give clear-cut boundary, but fuzzy conjoint classification delimit the edges and cores of urban classification. 4. The results of different methods are varied. But each method contributes to the revealing the transparence of spatial structure. Through the result of three kinds of classification, Chung-mu city which has special characteristics and the group of Industrial cities composed by Changwon, Ulsan, Masan, Chinhai, Kimhai, Yangsan, Ungsang, Changsungpo and Shinhyun are evident in common. Even though the appraisal of the fuzzy classification methods, this framework appears to be more realistic and flexible in preserving information pertinent to urban classification.