• Journal of KIISE:Computer Systems and Theory
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• v.36 no.6
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• pp.476-487
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• 2009

The virtual memory system in 4.4 BSD operating systems exploits a clustering scheme to reduce disk I/Os in paging out (or flushing) modified pages that are intended to be replaced in order to make free rooms in memory. Upon the page out of a victim page, the scheme stores a cluster (or group) of modified pages contiguous with the victim in the virtual address space to swap disk at a single disk write. However, it fails to find large clusters of contiguous pages if applications change pages not adjacent with each other in the virtual address space. To address the problem, we propose a new clustering scheme called Multiple-Object Clustering (MOC), which together stores multiple clusters in the virtual address space at a single disk write instead of paging out the clusters to swap space at separate disk I/Os. This multiple-cluster transfer allows the virtual memory system to significantly decrease disk writes, thus improving the page-out performance. Our experiments in the FreeBSD 6.2 show that MOC improves the execution times of realistic benchmarks such as NS2, Scimark2 SOR, and nbench LU over the traditional clustering scheme ranging from 9 to 45%.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.853-855
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• 2001

네트워크 기술의 발전으로 저비용으로 고성능을 얻고자 하는 클러스터 시스템에 대한 연구가 많아지고 있다. SPMD(Single Program Multiple Data) 형태의 병렬 프로그램을 사용한 클러스터 시스템의 주된 성능 장애는 부하 불균등 현상이다 본 논문에서는 이러한 문제를 해결하기 위해 마스터 노드가 정보를 모으는 횟수와 주기를 시뮬레이션을 통해 최적의 값으로 결정하고 그 주기 동안에 각 노드의 태스크 당 평균 수행시간을 계산한다. 통신비용의 오버헤드를 고려한 시스템의 실행시간을 평균 수행시간으로 예측하여 각 노드가 이동할 태스크의 수를 결정하는 동적 부하 균등 알고리즘을 제안한다 제안한 알고리즘의 클러스터 시스템을 모델링하고 성능 분석을 위한 시뮬레이션을 한다.

• Journal of the Ergonomics Society of Korea
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• v.12 no.1
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• pp.75-86
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• 1993

Hypermedia systems allow the retrieval and representation of multimedia in- formation such as text, graphics, image and voice/sound using navigation and browsing mechanisms. In this study we developed a hypermedia system which provides hierarchical group, local map and cluster view for effective navigation in hyperspace. The system also supports hot link, reference link, move-to link and multiple link to browse the multimedia information space effectively. This system has been designed to integrate the navigation, browsing and searching function of the hypermedia system in hyman factor perspective and provides the user-friendly user interface mechanism.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.147.1-147.1
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• 2012

We present empirical fiducial sequences for horizontal-branch (HB) stars in a set of bright Galactic globular clusters previously observed in SDSS (An et al. 2008). Mean loci of HB stars are derived on color-magnitude diagrams with multiple color indices (u - g, g - r, g - i, and g - z ) in order to identify foreground/background objects as well as cluster RR Lyrae variables. We compare our fiducial sequences to the model predictions from Yonsei-Yale isochrones and test the accuracy of the stellar evolution models.

• Annual Conference of KIPS
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• 2006.05a
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• pp.1435-1438
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• 2006

일반적인 비 공유 저장장치를 가진 시스템에서는 특정 컨텐츠에 대한 편향된(skewed) 요청 문제를 피할 수 없다. 본 논문에서는 비 공유 저장장치 모델로 설계/구현된 클러스터 기반의 시트리밍 서버에서 사용자의 편향된 컨텐츠 요청에 대처할 수 있고 스트리밍 서비스 중인 서버 또는 NS 카드에 문제가 생기더라도 스트리밍 서비스가 중단되지 않도록 다중 스트리밍 방법인 MDC(Multiple Description Coding)를 적용한 스트리밍 전송방법을 제안한다. 제안하는 방법은 클러스터 시스템에서 단일 세션으로 스트리밍 서비스를 제공하는 것이 아니라 MDC 를 활용하여 다중 세션을 통한 스트리밍 서비스를 제공함으로써 모든 서버의 부하가 같아지고, 특정 서버에 문제가 발생하더라도 스트리밍 서비스가 끊어지지 않으면서 MDC 의 특성인 적응형 서비스도 가능하게 되는 장점이 있다.

• Journal of the Korean Society of Costume
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• v.52 no.5
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• pp.187-196
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• 2002

The purpose of this study was to clarify differences in their perceptions in relation to clothing quality and service quality of internet shopping mall according to classified consumer groups by clothing involvement. The 248 questionnaires were collected from female and male students of university who experienced browsing at the website for clothing shopping. Using SPSS Win package, Cronbach's $\alpha$, frequency. percentage, factor analysis, cluster analysis, ANOVA, SNK multiple range test and multiple regression analysis were performed. The results could be summarized as follows. First. the dimension of clothing involvement divided consumers into three different groups: fashion/importance group, pleasure group and symbol group. Second, the significant differences among the classified clothing involvement groups were found in the perceptions in relation to clothing product quality and service quality of internet shopping mall. Third. pleasure and symbol of clothing involvement, physical attributes and expressive goals of clothing quality, and product assortment and promotion of service quality in the internet shopping mall had an effect on the purchase intend of internet shopping mall.

• Journal of Microbiology
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• v.42 no.1
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• pp.9-13
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• 2004

Culture-independent approaches, based on 16S rDNA sequences, are extensively used in modern microbial ecology. Sequencing of the clone library generated from environmental DNA has advantages over fingerprint-based methods, such as denaturing gradient gel electrophoresis, as it provides precise identification and quantification of the phylotypes present in samples. However, to date, no method exists for comparing multiple bacterial community structures using clone library sequences. In this study, an automated method to achieve this has been developed, by applying pair wise alignment, hierarchical clustering and principle component analysis. The method has been demonstrated to be successful in comparing samples from various environments. The program, named CommCluster, was written in JAVA, and is now freely available, at http://chunlab.snu.ac.kr/commcluster/.

• Journal of the Korean Society of Clothing and Textiles
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• v.13 no.3 s.31
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• pp.197-206
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• 1989

This study was to investigate brand images of ladies wear and the effects of fashion advertisements, and to determine the difference of brand image preference and the effects of fashion advertising by clothing life style. 421 subjects were gathered through stratified sampling method and, for data analysis, frequency distribution, $x^2-test$, Cronbach'$\alpha$, ANOVA, Duncan's multiple Range test, Multiple Dimentional Scaling (M.D.S.), Factor analysis, Cluster analysis, were conducted. The results are as follows; 1. In image formation process, feminine as formal image, manish as casual image, were recognized. 2. Four factors were determined for analysis of clothing life styles and with these factors five different clothing life style groups were classified. 3. There was a meaningful difference between clothing life style and brand image preference, and also between clothing life style and the effects of fashion advertisement. From these findings, general and specific fashion advertising strategies are proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.188-197
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• 2012

DEA 모델중 널리 사용되는 교차평가모델(cross efficiency model)은 가중치에 제한을 두지 않고 어떤 특정분야에 탁월한 성과를 내는 DMU(Decision Making Unit)보다는 보다 전반적인 분야에서 두각을 나타내는 DMU를 선발함으로써 많은 연구자들이 DEA문헌에서 적용하여 왔다. 본 연구에서는 이러한 교차평가모델이 실제에 있어서는 암묵적으로 고정 가중치를 사용한다는 것과 동일한 결과를 나타낸다는 것을 분석적으로 밝혔다(one input, multi output case). 또한 multi-input, multi-output case의 경우에도 overall performer의 cluster에 근접한 대다수 DMU의 경우에는 고정 가중치를 사용한 경우와 거의 차이가 없음을 보였다. 교차평가 모델에 적용된 변수의 가중치를 보다 명확히 함으로써 연구자들이 모델의 평가결과를 이해하는데 도움이 될 수 있을 것이다. 또한 교차 평가의 가중치 도식을 더 명확히 보여주기 위해 biplot을 제안한다.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.9-15
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• 2009

In the case of traditional binary encoding technique, it takes long time to converge the optimal solutions and brings about complexity of the systems due to encoding and decoding procedures. However, the ROGAs (real-coded genetic algorithms) do not require these procedures, and the k-means clustering algorithm can avoid global searching space. Thus, this paper proposes a new approach by using their advantages. The proposed method constructs the multiple predictors using the optimal differences that can reveal the patterns better and properties concealed in non-stationary time series where the k-means clustering algorithm is used for data classification to each predictor, then selects the best predictor. After selecting the best predictor, the cluster centers of the predictor are tuned finely via RCGKA in secondary tuning procedure. Therefore, performance of the predictor can be more enhanced. Finally, we verifies the prediction performance of the proposed system via simulating typical time series examples.