• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.4
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3815-3835
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• 2022

Density-based outlier detection is one of the hot issues in data mining. A point is determined as outlier on basis of the density of points near them. The existing density-based detection algorithms have high time complexity, in order to reduce the time complexity, a new outlier detection algorithm DODMD (Density-based Outlier Detection in Multidimensional Datasets) is proposed. Firstly, on the basis of ZH-tree, the concept of micro-cluster is introduced. Each leaf node is regarded as a micro-cluster, and the micro-cluster is calculated to achieve the purpose of batch filtering. In order to obtain n sets of approximate outliers quickly, a greedy method is used to calculate the boundary of LOF and mark the minimum value as LOF_min. Secondly, the outliers can filtered out by LOF_min, the real outliers are calculated, and then the result set is updated to make the boundary closer. Finally, the accuracy and efficiency of DODMD algorithm are verified on real dataset and synthetic dataset respectively.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.702-712
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• 2023

Load balancing plays a crucial role in ensuring the stable operation of information management systems during periods of high user access requests; therefore, load balancing approaches should be reasonably selected. Moreover, appropriate load balancing techniques could also result in an appropriate allocation of system resources, improved system service, and economic benefits. Nginx is one of the most widely used loadbalancing software packages, and its deployment is representative of load-balancing application research. This study introduces Nginx into an educational administration system, builds a server cluster, and compares and sets the optimal cluster working strategy based on the characteristics of the system, Furthermore, it increases the stability of the system when user access is highly concurrent and uses the Nginx reverse proxy service function to improve the cluster's ability to resist illegal attacks. Finally, through concurrent access verification, the system cluster construction becomes stable and reliable, which significantly improves the performance of the information system service. This research could inform the selection and application of load-balancing software in information system services.

• Journal of the Korean Society of Clothing and Textiles
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• v.10 no.3
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• pp.37-48
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• 1986

The purpose of this study was to analyze 'the natural groupings' of subjects in order to classify highly similar somatotype for clothing construction. The sample for the study was drawn randomly out of senior high school boys in Seoul urban area. The sample size was 425 boys between age 16 and 18. Cluster analysis was more concerned with finding the hierarchical structure of subjects by three dimensional distance of stature. bust girth and sleeve length. The groups forming a partition can be subdivided into 5 and 6 sets by the hierarchical tree of the given subjects. Ward's Minimum Variance Method was applied after extraction of distance matrix by the Standardized Euclidean Distance. All of the above data was analyzed by the computer installed at Korea Advanced Institute of Science and Technology. The major findings, take for instance, of 16 age group can be summarized as follows. The results of cluster analysis of this study: 1. Cluster 1 (32 persons means $18.29\%$ of the total) is characterized with smaller bust girth than that of cluster 5, but stature and sleeve length of the cluster 1 are the largest group. 2. Cluster 2 (18 Persons means $10.29\%$ of the total) is characterized with the group of the smallest stature and sleeve length, but bust girth larger than that of cluster 3. 3. Cluster 3(35persons means $20\%$ of the total) is classified with the smallest group of all the stature, bust girth and sleeve length. 4. Cluster 4(60 persons means $34.29\%$ of the total) is grouped with the same value of sleeve length with the mean value of 16 age group, but the stature and bust girth is smaller than the mean value of this age group. 5. Cluster 5(30 persons means $17.14\%$ of the total) is characterized with smaller stature than that of cluster 1, and with larger bust girth than that of cluster 1, but with the same value of the sleeve length with the mean value of the 16 age group.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.80-89
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• 2009

A fast and efficient search algorithm to determine an optimal number of clusters in clustering algorithms is presented. The method is based on cluster validity index which is a measure for clustering optimality. As the clustering procedure progresses and reaches an optimal cluster configuration, the cluster validity index is expected to be minimized or maximized. In this Paper, a fast non-exhaustive search method for finding the optimal number of clusters is designed and shown to work well in clustering. The proposed algorithm is implemented with the k-mean++ algorithm as underlying clustering techniques using CB and PBM as a cluster validity index. Experimental results show that the proposed method provides the computation time efficiency without loss of accuracy on several artificial and real-life data sets.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.1-24
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• 2014

The new Korean government sets its main policy direction as Creative Economy. The Creative Economy can be defined as a growth strategy that establishes new companies, enhances the competitiveness of established companies and creates new markets, industries and jobs in consequence of combining of creative imagination, science and technology and ICT. In this context, the concept of innovation cluster, which aims to foster technological innovations from an organic ecosystem perspective, can be a valid policy instrument for attaining Creative Economy. Innovation cluster can and must make a contribution to achieving the Creative Economy of Korea. In particular, the ICT Convergence Innovation Cluster will be a good strategy for this purpose. Based on this conceptual background, this paper analyzes a recently notable case of an ICT Convergence Cluster in Korea, Pangyo Technovalley (PTV). We argue that the Pangyo Technovalley is a representative cluster of converging ICT and science and technology. We identify the major factors for successful development of ICT cluster: regional government's flexible response to environmental change, careful pre-planning and balance between private and public involvement. In addition, we also found that additional factors, settlement condition for securing good workforce, agglomeration of various innovation actors for promoting convergence, and cluster network revitalization are also important for implementing the creative ICT convergence cluster.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.573-580
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• 2001

The large amounts of high dimensional data contains a significant amount of noises by it own sparsity, which adds difficulties in high dimensional clustering. The CLIP is developed as a clustering algorithm to support characteristics of the high dimensional data. The CLIP is based on the incremental one dimensional projection on each axis and find product sets of the dimensional clusters. These product sets contain not only all high dimensional clusters but also they may contain noises. In this paper, we propose extended CLIP algorithm which refines the product sets that contain cluster. We remove high dimensional noises by applying two dimensional projections iteratively on the already found product sets by CLIP. To evaluate the performance of extended algorithm, we demonstrate its effectiveness through a series of experiments on synthetic data sets.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.481-488
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• 2007

The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values prohibits it from being used to cluster real world data containing categorical values. The k-modes algorithm is to extend the k-means paradigm to categorical domains. The algorithm requires a pre-setting or random selection of initial points (modes) of the clusters. This paper improved the problem of k-modes algorithm, using the Max-Min method that is a kind of methods to decide initial values in k-means algorithm. we introduce new similarity measures to deal with using the categorical data for clustering. We show that the mushroom data sets and soybean data sets tested with the proposed algorithm has shown a good performance for the two aspects(accuracy, run time).

• Journal of Periodontal and Implant Science
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• v.26 no.3
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• pp.725-734
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• 1996

The present study has been performed to revise the forms of early-onset periodontitis(EOP) into the homogeneous phenotypic subsets by cluster analysis using sets of clinical parameters. Retrospective radiographic interproximal alveolar bone levels were measured from cemento-enamel junctions on patients who have previously been diagnosed as having one of EOP during last 5 years. Mean interproximal bone levels(BL) and mesial bone level(Ratio) of 1st molars relative to mean interproximal bone levels of adjacent teeth(lst and 2nd premolars and canines)were calculated on each patient. Using parameters BL and Ratio(BR group) or BL, Ratio and age(BRA group), cluster analysis was performed to revise EOP patients into homogeneous subsets. At least three or four cluster could be homogeneously formed both in BR or BRA groups with statistically significant differences in parameters used among clusters as evidenced by MANOVA test. It was shown that the greater the BL, the smaller the Ratio was. It was also evident that mean interproximal bone levels were lowest aroud 1st molars and/or incisors regardless of cluster types. The results has provided cluster-based studies for identifying laboratory markers responsible for the development of EOP subsets.

• Publications of The Korean Astronomical Society
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• v.25 no.3
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• pp.101-105
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• 2010

Taking the great advantage of Subaru's wide field coverage both in the optical and in the near infrared, we have been providing panoramic views of distant clusters and their surrounding environments over the wide redshift range of 0:4 < z < 3. From our unique data sets, a consistent picture has been emerging that the star forming activity is once enhanced and then truncated in galaxy groups in the outskirts of clusters during the course of cluster assembly at z < 1. Such activity is shifted into cluster cores as we go further back in time to z ~ 1.5. At z = 2 - 2.5, we begin to enter the epoch when massive galaxies are actually forming in the cluster core. And by z ~ 3, we eventually go beyond the major epoch of massive galaxy formation. It is likely that the environmental dependence of star forming activity is at least partly due to the external environmental effects such as galaxy-galaxy interaction in medium density regions at z < 1, while the intrinsic effect of galaxy formation bias overtakes the external effect at higher redshifts, resulting in a large star formation activity in the cluster center.