• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.80-90
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• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.5
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• pp.457-467
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• 2000

본 논문에서는 분산 메모리 구조를 갖는 병렬 컴퓨터 상에서 방대한 크기를 갖는 볼륨 데이터의 효과적인 가시화를 위한 병렬 광선 투사법을 제안한다. 데이터의 압축을 기반으로 하는 본 기법은 다른 프로세서의 메모리로부터 데이터를 읽기보다는 자신의 지역 메모리에 존재하는 압축된 데이터를 빠르게 복원함으로써 병렬 렌더링 성능을 향상시키는 것을 목표로 한다. 본 기법은 객체-순서와 영상-순서 탐색 알고리즘 모두의 정점을 이용하여 성능을 향상시켰다. 즉, 블록 단위의 최대-최소 팔진트리의 탐색과 각 픽셀의 불투명도 값을 동적으로 유지하는 실시간 사진트리를 응용함으로써 객체-공간과 영상-공간 각각의 응집성을 이용하였다. 본 논문에서 제안하는 압축 기반 병렬 볼륨 렌더링 방법은 렌더링 수행 중 발생하는 프로세서간의 통신을 최소화하도록 구현되었는데, 이러한 특징은 프로세서 사이의 상당히 높은 데이터 통신 비용을 감수하여야 하는 PC 및 워크스테이션의 클러스터와 같은 더욱 실용적인 분산 환경에서 매우 유용하다. 본 논문에서는 Cray T3E 병렬 컴퓨터 상에서 Visible Man 데이터를 이용하여 실험을 수행하였다.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.366-368
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• 2009

본 논문에서는 모바일 로봇이 작업하는 공간상에서 빠르고 안전한 최적 경로계획을 수행할 수 있게 하는 가변적 리드 맵을 이용한 장애물 밀집 정보 기반 경로계획을 제안한다. 모바일 로봇이 작업 공간에 대해서 빠르고 안전한 경로계획을 해 클러스터링 기법을 이용하여 정적 및 동적 장애물의 분포에 대한 맵 정보를 재구성하여 정보화 시킨다. 최적의 경로계획을 위해서는 재구성된 장애물 밀집 클러스터 데이터를 이용하여 전통적 기법의 GA 방법을 변형한 최적 경로계획을 수행한다. 제안한 기술의 효율성을 검증하기 위해 그리드 기반 경로계획 중의 하나인 A*알고리즘과 다양한 맵을 이용하여 성능 비교를 수행하였다. 실험결과 제안한 경로계획 기술은 기존 알고리즘 보다 빠른 처리 성능과 동적 장애물이 밀집한 지역을 회피하는 최적 경로계획을 수행함을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.709-716
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• 2006

본 논문에서는 무선 센서 네트워크의 다양한 응용 환경 및 상/하향 트래픽 스트림의 특성에 따라 유연하게 적용할 수 있는 새로운 매체접근제어 프로토콜을 제안한다. HiPERMAC(Hierarchically-Paired Evolutionary Radio MAC)이라고 불리는 제안 매체접근제어방식은 다양한 클러스터링 방식에 의하여 구축된 다 계층 (Hierarchical) 네트워크에서 별도의 대역 확산 전송방식이나 다수의 주파수 채널을 사용하지 않고, 단 2개의 시간 구간을 공간적으로 재활용하여 N 계층의 개별적인 통신이 가능한 구조를 제공한다. 즉, 제안방식은 단일 주파수 개념을 이용하여 계층화된 우선 센서 네트워크를 계층적 이중화(Hierarchically-Paired)하고 이때 발생하는 클러스터 간 상호 간섭의 요인들을 시간 및 공간적으로 분리하여 망 확장성과 자원 효율성을 극대화 하는 새로운 매체접근 제어 방식 이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.895-900
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• 2006

In this paper, we propose DBSCAN-I that is an algorithm for clustering with influence. DBSCAN-I that extends traditional DBSCAN and DBSCAN-W converts from non-spatial feature to influence while doing spatial clustering. This is an algorithm that increases probability of allocation to cluster when influence is more higher than other. And also, we present the result that selects effectively optimum allocation with influence to apply the proposed algorithm.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1072-1079
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• 2003

This study is purported for suggesting a new clustering algorithm that enables incremental categorization of numerous documents. The suggested algorithm adopts the natures of the spherical k-means algorithm, which clusters a mass amount of high-dimensional documents, and the fuzzy ART(adaptive resonance theory) neural network, which performs clustering incrementally. In short, the suggested algorithm is a combination of the spherical k-means vector space model and concept vector and fuzzy ART vigilance parameter. The new algorithm not only supports incremental clustering and automatically sets the appropriate number of clusters, but also solves the current problems of overfitting caused by outlier and noise. Additionally, concerning the objective function value, which measures the cluster's coherence that is used to evaluate the quality of produced clusters, tests on the CLASSIC3 data set showed that the newly suggested algorithm works better than the spherical k-means by 8.04% in average.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.100-109
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• 2021

Flooding usually brings in disruptions and aggravated congestions to the roadway network. Hence, right information should be provided to road users to avoid the flood-impacted areas and for city officials to recover the network. However, the information about individual link congestion may not be conveyed to roadway users and city officials because too many links are congested at the same time. Therefore, more significant information may be desired, especially in a disastrous situation. This information may include 1) which places to avoid during flooding 2) which places are feasible to drive avoiding flooding. Hence, this paper aims to develop a framework to identify the flood-impacted areas in a roadway network and their criticality. Various impacted clusters and their spatiotemporal properties were identified with field data. From this data, roadway users can reroute their trips, and city officials can take the right actions to recover the affected areas. The information resulting from the developed framework would be significant enough for roadway users and city officials to cope with flooding.

• Journal of Practical Engineering Education
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• v.11 no.2
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• pp.259-268
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• 2019

The purpose of the study was to examine the vocational educational system of Egypt, focusing on the effectiveness of the three consecutive cycle-based curriculum and integrated technical education clusters (ITECs) in order to suggest some implications for innovating the current vocational education system of Korea. The vocational education system of Egypt is similar to that of Korea, in terms of general education to go to university and vocational education to go to labor market. However, the Egyptian system is different from the system of Korea in light of the three consecutive cycle-based curriculum that links secondary vocational education, vocational education of college level, and advanced technical and vocational education. In addition, the Egyptian system has adopted the "cluster" approach which integrates technical secondary school, intermediate technical college, and advanced technical college around one physical area so as to promote vocational education in collaboration with regional industries and to guarantee education quality. In the last part, some potential implications were suggested for upgrading the quality of vocational education of Korea based upon the benchmark results of the Egyptian vocational education system and career development of students.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.339-346
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• 2000

Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.

• Journal of the Economic Geographical Society of Korea
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• v.8 no.2
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• pp.217-236
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• 2005

This paper aims to analysis the production linkage relationships between large firm and its subcontracting firms, especially focus on the spatial network and collaboration network. For the purpose of it, the division of semiconductor in Samsung Electronics and its most important subcontracting firms are picked up for the case study. The empirical study show that the location distribution pattern of Samsung Electronic's subcontracting firms is concentrated very highly on the Kyeong-Ki Province and Chung-Nam Province in Korea, which is the location sites of Samsung Electronic's key plants as well as the best environment for business in Korea. And the major subcontracting firms seems to be in the hierarchic and vertical relationship with Samsung Electronics rather than horizontal and good collaboration network in this case.