• Korean Journal of Acupuncture
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• 제29권3호
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• pp.431-440
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• 2012

Objectives : Recently, network science is very popular topic in various scientific fields and many studies have reported that it gives meaningful results on studying characteristics of a complex system. In this study, based on network theory, we made acupoints network using data of combined acupoints which appeared at "Beijiqianjinyaofang". We focused to find out the distinctive roles of remote and local combinations on the network. Furthermore, we aimed to identify the possibility of numerical and quantitative application to acupuncture researches. Methods : Based on examples of combined acupoints in "Beijiqianjinyaofang", the network consisted of 291 nodes and 2,431 links. The spatial distances between combined acupoints were calculated by the human dummy model. We removed the links step by step for the three cases - remote, local, and random cases, and observed the characteristic changes by calculating path lengths, similarity indices, and clustering coefficients. Also cluster analysis was carried out. Results : The network had a small number of remote links, and a large number of local links. These two links had the distinct characteristics. Whereas the local links formed a cluster of nearby nodes, remote links played a role to increase the correlation between the clusters. Conclusions : These results suggest that acupoints network increases the connectivity between the distal part and the trunk of human body, and enables various combinations of the acupoints. This finding conclusively showed that mechanism of combined acupoints could be interpreted meaningfully by applying network theory in acupuncture researches.

• 한국환경과학회:학술대회논문집
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• 한국환경과학회 2003년도 International Symposium on Clean Environment
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• 천문학회보
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• 제36권2호
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• pp.121-121
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• 2011

Thanks to KMTNet's wide field of view, it is time to implement imaging survey of extensive area of clusters of galaxies in the southern sky with modern instrument. As part of potential long-term survey of nearby (D < 50 Mpc) well-known clusters of galaxies, we propose a wide-field and deep survey of Fornax cluster as a first step of the project. By imaging the 400 square deg region (100 fields) enclosed within the five times virial radius of the Fornax cluster, in three SDSSfilters(g', r', i'), we can provide an unprecedented view of structure of Fornax cluster using sample from giant to dwarf galaxies. We will secure galaxies with brightness comparable to the limiting magnitude (r'=23.1 AB mag) of SDSS. Furthermore, we also request extremely deep (limiting surface brightness of ~ 28 mag $arcsec^{-2}$forr'band) survey for the central region (16 square degree, i.e., four fields) of Fornax cluster. This will allow us to detect the diffuse intracluster light (ICL) that permeates clusters as a valuable tool for studying the hierarchical nature of cluster assembly. In order to complete whole survey, about 285 hr observing time (without overhead) is required. By combining data available at other wavelengths, it will offer unique constraints on the formation of large-scale structure and also provide important clues for theories of galaxy formation and evolution. Our proposed survey will be implemented in the close collaboration with researchers in various countries (Germany, Australia, UK, USA) and ongoing project (e.g., SkyMapper).

• 대한의용생체공학회:의공학회지
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• 제21권4호
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• pp.333-338
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• 2000

본 논문에서는 T1 강조영상, T2 강조 영상 그리고 PD의 영상의 특징을 상호 보완적으로 이용한 자동적인 영상 분할법을 제안한다. 제안한 분할 알고리듬은 3단계로 이루어지는데, 첫 단계에서는 PD 영상으로부터 대뇌 마스크를 획득한 후, T1과 T2, PD의 입력 영상에 대뇌 마스크를 씌워 각각의 대뇌 영상을 추출하고, 둘째 단계에서는 대뇌 내부 조직에 해당하는 두드러진 클러스터(outstanding cluster)를 3차원 클러스터들 중에서 선택한다. 3차원 클러스터는 최적스케일 영상(optimal scale image)으로 이루어지는 3차원 공간상에서 화소가 밀집된 봉우리들을 교집합해서 생성되는 클러스터로 결정한다. 최적스케일 영상은 각 2타원 히스토그램에 스케일 스페이스 필터링을 적용시키고 그래프(graph) 구조를 검색하여 2차원 히스토그램의 모양을 가장 잘 나타내는 봉우리(peak) 영상을 최적 스케일 영상으로 선택한다. 마지막 단계에서는 앞에서 찾은 두드러진 클러스터의 중심값을 FCM 알고리듬의 초기중심 값으로 두고, FCM 알고리듬을 이용하여 대뇌 영상을 분할한다. 제안한 분할 알고리듬은 정확한 클러스터의 중심값을 계산함으로 초기 값을 영향을 많이 받는 FCM 알고리듬의 단점을 보완하였고 다중 스펙트럼 영상의 특성을 조합하여 분할에 이용함으로 단일 스펙트럼 영상만을 이용하는 방법보다 향상된 결과를 얻을 수 있었다.

• Journal of Korean Neurosurgical Society
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• 제48권6호
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• pp.506-517
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• 2010

Objective : We investigated whether Disability Evaluation (DE) situations influence patients' neuropsychological test performances and psychopathological characteristics and which variable play a role to establish an explanation model using statistical analysis. Methods : Patients were 536 (56.6%) brain-injured persons who met inclusion and exclusion criteria, classified into the DE group (DE; n = 300, 56.0%) and the non-DE group (NDE; n = 236, 44.0%) according to the neuropsychological testing's purpose. Next, we classified DE subjects into DE cluster 1 (DEC1; 91, 17.0%), DE cluster 2 (DEC2; 125; 23.3%), and DE cluster 3 (DEC3; 84, 15.7%) via two-step cluster analysis, to specify DE characteristics. All patients completed the K-WAIS, K-MAS, K-BNT, SCL-90-R, and MMPI. Results : In comparisons between DE and NDE, the DE group showed lower intelligence quotients and more severe psychopathologic symptoms, as evaluated by the SCL-90-R and MMPI, than the NDE group did. When comparing the intelligence among the DE groups and NDE group, DEC1 group performed worst on intelligence and memory and had most severe psychopathologic symptoms than the NDE group did. The DEC2 group showed modest performance increase over the DEC1 and DEC3, similar to the NDE group. Paradoxically, the DEC3 group performed better than the NDE group did on all variables. Conclusion : The DE group showed minimal "faking bad" patterns. When we divided the DE group into three groups, the DEC1 group showed typical malingering patterns, the DEC2 group showed passive malingering patterns, and the DEC3 group suggested denial of symptoms and resistance to treatment.

• World Technopolis Review
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• 제6권2호
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• pp.130-147
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• 2017

This paper aims to identify the spatial concentrations and linkage properties of industrial clusters in the Chungbuk Province region in Korea using a three-step approach, which is composed of the cluster index, Getis-Ord's $Gi^*$, and qualitative input-output analysis. The results of the study reveal: a) what industrial sectors are concentrated and where they are; b) where the spatially interdependent industries are; and c) how the industrial sectors of the identified clusters in different locations are vertically interconnected. In addition, the degree of strength of the interindustry linkages between industrial clusters are assessed. Based on the findings, some plausible industrial policies are suggested.

• 전자공학회논문지A
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• 제30A권3호
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• pp.139-145
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• 1993

Partitioning is an important step in the hierarchical design of very large scale integrated circuits. In this research, a new effective partitioning algorithm based on 2-level hierarchy is presented. At the beginning, clusters are formed to reduce the problem size. To overcome the weakness of the iterative improvement techniques that the partitioning result is dependent on the initial partitioning and to consistently produce good results, the cluster-level partitioning is performed several times using several sets of parameters. Then the best result of cluster-partitioning is used as the initial solution for lower level partitioning. For each partitioning, the gradual constraint enforcing partitioning method has been used. The clustering-based partitioning algorithm has been applied to several benchmark examples and produced promising results which show that this algorithm is efficient and effective.

• Journal of Microbiology and Biotechnology
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• 제12권6호
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• pp.929-935
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• 2002

The 5-stage biological nutrient removal (BNR) process with step feed system showed a very stable organic carbon and nutrient removal efficiency ($87\%\;COD\,;79\%\;nitrogen,\;and\;87\%$ phosphorus) for an operation period of 2 years. In each stage at the pilot plant, microbial communities, which are important in removing nitrogen and phosphorus, were investigated using fluorescence in-situ hybridization (FISH) and 165 rDNA characterization. All tanks of 5-stage sludge had a similar composition of bacterial communities. The totat cell numbers of each reactor were found to be around $2.36-2.83{\times}10^9$ cells/ml. About $56.5-62.0\%$ of total 4,6-diamidino-2-phenylindol (DAPI) cells were hybridized to the bacterial-specific probe EUB388. Members of ${\beta}$-proteobacteria were the most abundant proteobacterial group, accounting for up to $20.6-26.7\%$. The high G+C Gram-positive bacterial group and Cytophaga-Flexibacter cluster counts were also found to be relatively high. The beta subclass proteobacteria did not accumulate a large amount of polyphosphate. The proportion of phosphorus-accumulating organisms (PAOs) in the total population of the sludge was almost $50\%$ in anoxic-1 tank. The high G+C Gram-positive bacteria and Cytophaga-Flexibacter cluster indicate a key role of denitrifying phosphorus-accumulating organisms (dPAOs). Both groups might be correlated with some other subclass of proteobacteria for enhancing nitrogen and phosphorus removal in this process.

• 센서학회지
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• 제24권4호
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• pp.258-263
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• 2015

In order to prevent drink-driving by detecting concentration of alcohol from driver's exhale breath, twenty chemical sensors fabricated. The one of purposes for sensor array which consists of those sensors is to discriminate between target gas(alcohol) and interference gases($CH_3CH_2OH$, CO, NOx, Toluene, and Xylene). Wilks's lambda was presented to achieve above purpose and optimal sensors were selected using the method. In this paper, step-wise sensor elimination based on Euclidean distance was investigated for selecting optimal sensors and compared with a result of Wilks's lambda method. The selectivity and sensitivity of sensor array were used for comparing performance of sensor array as a result of two methods. The data acquired from selected sensor were analyzed by pattern analysis methods, principal component analysis and Sammon's mapping to analyze cluster tendency in the low space (2D). The sensor array by stepwise sensor elimination method had a better sensitivity and selectivity compared to a result of Wilks's lambda method.

• 한국항공우주학회지
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• 제31권10호
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• pp.1-9
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• 2003

컴퓨팅 그리드 환경에서는 컴퓨팅 그리드 시스템을 구성하는 단위 시스템들의 성능이 균일하지 않기 때문에, 영역을 균등하게 분할하는 일반적인 로드밸런싱 기법을 적용하기가 적절하지 않다. 본 연구에서는 그래프 분할기법을 기반으로 하여, 컴퓨팅 그리드 시스템을 구성하는 단위 시스템들의 성능가중치를 계산하여 분할하는 2단계 영역 분할 기법을 제시하였다. 2단계 영역 분할 기법 시 발생하는 통신량의 증가는 그래프 분할기법인 WEVM을 적용하여 최소화 할 수 있었으며, 멀티 클러스터 환경과 WAN에서 타당성과 효율성을 검증해 보았다.