• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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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).

• Korean Journal of Acupuncture
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• v.29 no.3
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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.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.333-338
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.

• Journal of Korean Neurosurgical Society
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• v.48 no.6
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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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• v.6 no.2
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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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.3
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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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• v.12 no.6
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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.

• Journal of Sensor Science and Technology
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• v.24 no.4
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.1-9
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• 2003

In GRID environments, an efficient load balancing algorithm should be adopted since the system performances of GRID system are not homogeneous. In this work, a new two-step mesh-partitioning scheme based on the graph-partitioning scheme was introduced to consider the difference of system performance. In the two-step mesh-partitioning scheme, the system performance weights were calculated to reflect the effect of heterogeneous system performances and WEVM(Weighted Edge and vertex Method) was adopted to minimize the increase' of communications. Numerical experiments were carried out in multi-cluster environment and WAN (Wide Area Network) environment to investigate the effectiveness of the two-step mesh-partitioning scheme.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.459-469
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• 2016

The purpose of this study is to classify the subtypes of perpetrators of school violence based on their psychological characteristics. In order to classify the students, questionnaires/interviews which consist of 6 factors (Cognitive Impulsivity, Unplanned Impulsivity, Depression, Anxiety, Peer Conformity, and Self assertion) and 19 questions were administered to 86 perpetrators of school violence. Then, a two-step cluster analysis was performed with the survey results of 74 perpetrators. As a result, three clusters were identified and named as follows: 1) Impulsive Vulnerability, 2) Emotional Vulnerability, and 3) Social Vulnerability. Scrutinizing the detailed characteristics of each cluster, the first cluster, Impulsive Vulnerability, showed higher scores on Cognitive Impulsivity and Unplanned Impulsivity, compared to the other two clusters, while Depression and Anxiety scores were lower. The second cluster, Emotional Vulnerability, showed higher scores on Depression and Anxiety, while Cognitive Impulsivity and Unplanned Impulsivity scores were lower. The third cluster, Social Vulnerability, showed the highest score on Peer Conformity among the three clusters. However, Self assertion scores were the lowest in this cluster, and Cognitive Impulsivity, Unplanned Impulsivity, depression, and anxiety scores were lower than in the others. This study will provide a useful insight for facilitating teachers and parents' understanding of the psychological characteristics of school violence perpetrators and thereby contributing to effective intervention.