• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.35-40
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• 2009

FCM 알고리즘은 입력 벡터와 각 클러스터의 유클리드 거리를 이용하여 구해진 소속도만를 비교하여 데이터를 분류하기 때문에 클러스터링 된 공간에서의 데이터들의 분포에 따라 바람직하지 못한 클러스터링 결과를 보일 수 있다. 이러한 문제점을 개선하기 위해 대칭적 성질을 이용하는 대칭성 측도에 퍼지 이론을 적용하여 군집간의 거리에 따른 변화와 군집 중심의 위치, 그리고 군집 형태에 따라 영향을 덜 받는 개선된 FCM이 제안되었다. 본 논문에서는 효과적으로 패턴을 분류하기 위해 개선된 FCM 알고리즘을 적용한 개선된 하이브리드 네트워크를 제안한다. 제안된 하이브리드 네트워크는 개선된 FCM 알고리즘을 입력층과 중간층의 학습구조 적용하고 중간층과 출력층의 학습구조는 일반화된 델타학습법을 적용한다. 제안된 방법의 인식성능을 평가하기 위해 2차원 좌표평면 상의 데이터를 기존의 Max_Min 신경망을 이용한 FCM 기반 RBF 네트워크와 FCM 기반 RBF 네트워크, HCM 기반 네트워크와 제안된 방법 간의 학습 및 인식 성능을 비교 및 분석하였다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.5
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• pp.461-468
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• 2017

The introduction of BIM in domestic construction industry has become more active. Library development and standardization in civil-engineering are unexhausted. This research develop and standardize prototype library for railway infrastructure. We define target facility for library based on railway standard drawings and select BIM software according characteristic of each facility. In this research, we develop libraries composed of 199 files and 489 types for alignment, roadbed and track and make specifications as defined attribution item and description. As we consider for application to diverse use case, develop prototype library in low LoD. We expect that library can increase 3D design productivity and ensure consistency of quality.

• Korean Journal of Cognitive Science
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• v.19 no.1
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• pp.41-56
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• 2008

Previous studies, while investigating factors of sensibility, had rarely considered its internal structure. This study hypothesized that sensibility had sensational aspects and emotional aspects and the former corresponded to objective adjectives, describing attributes of objects, and the latter to subjective adjectives, describing psychology of experiencers. Forty-three objective adjectives and 21 subjective adjectives describing color sensibility were selected both by a linguistic criterion and an empirical evaluation. Factor analysis on semantic differential responses to these two groups of adjectives resulted in 5 sensational factors and 3 emotional factors of color sensibility respectively. Hierarchical structure was derived by regressing emotional factor scores on sensational factor scores. In consequence, emotional aspects were interpreted by different combinations of sensational factors. Limitations and significance of this study were discussed.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.7-24
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• 2009

Since the Web is dynamic, it is necessary to analyze scholarly Web space with both quantitative and qualitative methods for better understanding of communication characteristics. In this study, we analyzed contents of pages and links to ascertain the characteristics of Korean scholarly Web space in terms of network structure and communication behavior. The result shows that the structure of the original network with all the external links remained is not much different from that of the network with activated external links only. However, the purposes of linking vary among scholarly institutions. The centrality measures correlate more strongly with the clustering coefficient than with the constraint index implying the similar explanatory power of the two types of structural indices.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.355-362
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• 2016

This research analyzed 'esquisse', that is one of among the visual representation tools of designers in design-thinking process. They were classified into five different types(M, N, O, P, Q) and categorized about preferred type of brain dominance area based on Ned Herrmann's 'Brain 4 division theory'. By contrasting and analyzing five types of sketch tendencies and brain tendencies through Structural left -brain type(M), Emotional limbic-brain type(N), Visual right-brain type(O), Plane expressional right-brain type(P) and Text expressional right-brain type(Q), it was deduced that which utilization the designer with each brain type with various Styles and characteristics shows internally in the design thinking process can be analyzed.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.61-77
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• 2017

Recently, the number of academic conference information on the Internet has rapidly increased, the automatic classification of academic conference information according to research subjects enables researchers to find the related academic conference efficiently. Information provided by most conference listing services is limited to title, date, location, and website URL. However, among these features, the only feature containing topical words is title, which causes information insufficiency problem. Therefore, we propose methods that aim to resolve information insufficiency problem by utilizing web contents. Specifically, the proposed methods the extract main contents from a HTML document collected by using a website URL. Based on the similarity between the title of a conference and its main contents, the topical keywords are selected to enforce the important keywords among the main contents. The experiment results conducted by using a real-world dataset showed that the use of additional information extracted from the conference websites is successful in improving the conference classification performances. We plan to further improve the accuracy of conference classification by considering the structure of websites.

• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1045-1054
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• 2001

To improve classification accuracy in this paper, we proposed an algorithm for the chromosome image reconstruction in the image preprocessing part and also proposed the pattern classification method using the hierarchical multilayer neural network(HMNN) to classify the chromosome karyotype. It reconstructed chromosome images for twenty normal human chromosome by the image reconstruction algorithm. The four morphological and ten density feature parameters were extracted from the 920 reconstructed chromosome images. The each combined feature parameters of ten human chromosome images were used to learn HMNN and the rest of them were used to classify the chromosome images. The experimental results in this paper were composed to optimized HMNN and also obtained about 98.26％ to recognition ratio.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.134-138
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• 2003

The purpose of this study is to analyse the argument alternations in terms of semantic perspective. Argument alternation has long been an interesting topic for the linguists regardless of their linguistic schools. Semantic analysis of argument alternation is attempted by Dowty(2001) based on the Levin(1993)'s classification. The study is focused on the phenomenon where meaning changes with argument alternations even though those sentences look the same syntactically and lineally. 1 tried not only to classify verbs according to the meaning changes but to explain the alternations in semantic point of view. The verbs are divided into 4 types- Touch type, Hit type, Cut type, and Break type. Each type of verbs are tested if they show special characteristics with three alternations-Middle alternation, Body-part possessor Ascension, and Conative Alternation. And semantic analysis is tried based on that classification.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.100-109
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• 1998

The coding of video sequences has been the focus of research in recent years. High Definition TV(HDTV), video conferencing and video on demand(VOD) are some of the well known applications. In the moving picture compression, motion estimation algorithm plays a very important role, but due to its high computational complexity, there has been many approaches to overcome this difficulty. We propose a new block matching criterion that uses modified cost functions. This new block matching criterion classifies pixels into 2-levels, 4-levels and 8-levels with a suitable thresholding method. We also show that our new proposed algorithms can easily be combined with many other fast motion estimation algorithms with good performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.191-194
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• 2005

본 논문에서는 방송 영상에서 조명효과와 크기변화 등에 강인한 얼굴패턴 검출기법을 제시한다. 제안된 얼굴검출 모델은 영상 전처리 과정과 얼굴패턴 검출 과정으로 이루어진다. 전처리 과정은 조명변화에 대한 보정기능과 다중필터에 의한 후보영역 선별기능으로 구분된다. 얼굴패턴 검출과정은 다단계의 특징지도 생성과정과 패턴분류 과정으로 이루어진다. 특징지도를 생성하기 위하여 가보(Gabor) 필터계층을 포함하는 CNN(Convolutional Neural Networks)모델을 도입하였다. 다양한 배경을 고려한 효과적인 학습을 위하여 본 논문에서는 억제성의 뉴런(Inhibitory neuron)을 포함하는 구조의 CNN모델을 적용한다. CNN으로부터 추출되는 특징집합은 최종 단계에서 WFMM(Weighted Fuzzy Min Max) 모델을 사용하여 분류된다. 이때 사용되는 특징집합의 크기는 분류기의 규모 및 계산량의 결정적인 역할을 준다. 이에 본 연구에서는 최종 분류 과정에 사용되는 특징의 수를 효과적으로 줄이기 위해 FMM모델을 사용하는 적응적인 특징 선별 기법을 제안한다. 또한 실제 영상을 통한 실험결과로부터 제안된 이론의 타당성을 고찰한다.