• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.2
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• pp.211-220
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• 1994

The purpose of this study was to analyze the foot type by cluster analysis for footwear. The sample size for the study was 200 college womens between age 19 and 23 in Pusan urban area. There were measured 17 items of the foot for factor analysis and cluster analysis. The result was as follows : 1. 1'here were 9 items selected by factor analysis. 2.'rho cluster analysis of the foot must be analyzed by direct and indirect measurement indivisually. 3. The cluster analysis of the direct measurement ; Cluster 1 : 1'he foot length is all much the same to mean value of this age group and the items of width and circumference are relatively small to other clusters. Cluster 2 ; The foot length is relatively small to other clusters and the items of width and circumference are all much the same to mean value of this age group. Cluster 3 ; The foot sine Is relatively large to other clusters. 4. The cluster analysis of indirect measurement ; Cluster 1 ; The (cot print angle is high find Metatarso-Phalanx angle is transformed Cluster 2 ; The foot print angle is low and Melatarso-Phalanx angle is normal. Cluster 3 : Tho foot print angle Is middle and Metatarso-Phalanx angle is all the mush same to mean value of this age group. Cluster 4 . The foot print angle Is the most value and Metatarso-Phalanx angle is normal.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.5
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• pp.637-645
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• 1994

The purpose of this study was to analyze the characteristics of men's foot and the foot type by cluster analysis for men's footwear. The sample size for the study was 200 college men between age 19 and 24 in Pusan urban area. There were measured 17 items of the foot for factor analysis and cluster analysis. The result was as follows: 1. The size of If items of men's foot is larger than women's foot. 2. There were 9 items selected by factor analysis. 3. The cluster analysis of the direct measurement: Cluster 1: The items of the direct measurement is all much the same to mean value of this age group. Cluster 2: The foot size is relatively small to other clusters. Cluster 3: The foot size is relatively large to other clusters. 4. The cluster analysis of indirect measurement: Cluster 1: The foot print angle is the most value and Metatarso-Phalanx angle is nomral Cluster 2: The foot print angle is middle and Metatarso-Phalanx angle is normal. Cluster 3: The foot print angle is high and Metatarso-Phalanx angle is the smallest. Cluster 4: The foot print angle is low and Metatarso-Phalanx angle is all the much same to mean value of this age group.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3477-3485
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• 2012

This research focused on the cluster analysis for the vitalization of the innovation cluster, Gwanggyo Technovalley. The study was performed based on both theoretical study and quantitative and qualitative study approaches. Particularly, questionnaire survey was performed for the cluster analysis of the innovation cluster. The major determinants for vitalization of the innovation cluster, Gwanggyo Technovalley can be summarized as follows; the strategy formulation for the development of the innovation cluster, the enhancement of the host institution capability and gradual enlargement of the role of the host institution. In terms of the needs of times, this study regarding the cluster analysis for the vitalization of the innovation cluster, Gwanggyo Technovalley is anticipated to be a good reference for the R&D organizations and technology cluster participants in coming years.

• Journal of Korean Society of Forest Science
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• v.99 no.5
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• pp.736-743
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• 2010

This study examined the ecological attributes of classified forest community by cluster analysis in the mixed forest of Mt. Seokbyung Experimental Forest of Gangwon-Do. The vegetation data were collected in randomly established 51 sample plots (2.04 ha) and analysis adopted the cluster analysis, importance value index, and Shannon's diversity index. Main results were as follows; 1) the study area was classified into 4 clusters (A, B, C and D). 2) The cluster A was dominated by Pinus densiflora with an importance value of 71.6%. The most dominant species in the cluster B and cluster C were Larix leptolepis (57.1%) and Quercus mongolica (40.2%), respectively. Finally, The cluster D was dominated by P. densiflora (30.6%) and Q. mongolica (31.0%) with the mixed forest. 3) In the P. densiflora community (cluster A), distribution of DBH class showed a reverse J-shaped curve. In the L. leptolepis community (cluster B), individuals of dominant species had the bell-shaped distribution. Oak species indicated uniform distribution of DBH class (under 25 cm) in the mixed P. densiflora - Q. mongolica community (cluster D). 4) The species diversity index of the communities in descending order were: Pinus densiflora - Q. mongolica community > Larix leptolepis community > Pinus densiflora community > Quercus mongolica community.

• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.57-61
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• 2014

This study measured the stream data from the several sensors, and stores the database in MapReduce framework environment, and it aims to design system with the small performance and cluster analysis error rate through the KMSVM algorithm. Through the KM-SVM algorithm, the cluster analysis effective data was used for U-health system. In the results of experiment by using 2003 data sets obtained from 52 test subjects, the k-NN algorithm showed 79.29% cluster analysis accuracy, K-means algorithm showed 87.15 cluster analysis accuracy, and SVM algorithm showed 83.72%, KM-SVM showed 90.72%. As a result, the process speed and cluster analysis effective ratio of KM-SVM algorithm was better.

• Atmosphere
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• v.16 no.4
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• pp.259-267
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• 2006

In the present study, the neural network (NN) model with cluster analysis method was developed to predict storm surge in the whole Korean coastal regions with special focuses on the regional extension. The model used in this study is NN model for each cluster (CL-NN) with the cluster analysis. In order to find the optimal clustering of the stations, agglomerative method among hierarchical clustering methods was used. Various stations were clustered each other according to the centroid-linkage criterion and the cluster analysis should stop when the distances between merged groups exceed any criterion. Finally the CL-NN can be constructed for predicting storm surge in the cluster regions. To validate model results, predicted sea level value from CL-NN model was compared with that of conventional harmonic analysis (HA) and of the NN model in each region. The forecast values from NN and CL-NN models show more accuracy with observed data than that of HA. Especially the statistics analysis such as RMSE and correlation coefficient shows little differences between CL-NN and NN model results. These results show that cluster analysis and CL-NN model can be applied in the regional storm surge prediction and developed forecast system.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.178-192
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• 2021

File system forensics typically focus on the contents or timestamps of a file, and it is common to work around file/directory centers. But to recover a deleted file on the disk or use a carving technique to find and connect partial missing content, the evidence must be analyzed using cluster-centered analysis. Forensics tools such as EnCase, TSK, and X-ways, provide a basic ability to get information about disk clusters, but these are not the core functions of the tools. Alternatively, Sysinternals' DiskView tool provides a more intuitive visualization function, which makes it easier to obtain information around disk clusters. In addition, most current tools are for Windows. There are very few forensic analysis tools for MacOS, and furthermore, cluster analysis tools are very rare. In this paper, we developed a tool named FACT (Forensic Analyzer based Cluster Information Tool) for analyzing the state of clusters in a HFS+ file system, for digital forensics. The FACT consists of three features, a Cluster based analysis, B-tree based analysis, and Directory based analysis. The Cluster based analysis is the main feature, and was basically developed for cluster analysis. The FACT tool's cluster visualization feature plays a central role. The FACT tool was programmed in two programming languages, C/C++ and Python. The core part for analyzing the HFS+ filesystem was programmed in C/C++ and the visualization part is implemented using the Python Tkinter library. The features in this study will evolve into key forensics tools for use in MacOS, and by providing additional GUI capabilities can be very important for cluster-centric forensics analysis.

• The Korean Journal of Ecology
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• v.6 no.2
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• pp.145-151
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• 1983

The epiphytic lichen communities were analysed in terms of cluster analysis on forty two stands and eight environmental variables in Mt. Duckyoo. Ordination of stand and species by principal component analysis (PCA) and sum of square algorithm (SSA) gave similar results. Species cluster showed three groups(I, II, III) and stand revealed three groups (A, B, C). Interaction of stand and species cluster was interpreted by analysis of concentration technique. The results indicated a significant cluster structure at the level of different environment variable.

• Korean Journal of Community Nutrition
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• v.5 no.1
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• pp.83-91
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• 2000

The aims of this study are to evaluate the quality of hospital food services and the evaluate the quality in selected hospitals trough the use of the questionnaires. A survey of 30 hospital food and nutrition service department was undertaken and detailed information was collected from each, including, surveys of 1, 016 patient. Statistical data analysis was completed using the SAS/win 6.11 package for descriptive analysis, t-test X$^2$-test ANOVA principal component analysis , and cluster analysis and cluster analysis. In the case of patient satisfaction with hospital food and food services, overall satisfaction scores of male and female were 3.54 and 3.45 showing higher levels than the average score(3.00) The aspect of the food and food service which received the lowest ratings by patients was 'meal rounding while dining'. After conduction of factor analysis of variables affecting the patients meal satisfaction 3 groups including the 'menu satisfaction factor', 'service satisfaction factor ' and 'nutrition management satisfaction factor ' were selected. 3 clusters were categorized by the 'service cluster' 'nutrition management cluster', 'men cluster', and 'menu nutrition service cluster' after conducting a cluster analysis with influencing variables affecting patients meal satisfaction. The overview results of patient satisfaction by cluster were : in the case of the service group, such factors as taste, portion size, dealing with complaints while dining meal rounding while dining should be managed with caution In case of the nutrition management group, such factors as taste, portion size, temperature of the food intake, and dependence on hospital food should be managed with care, In the case of the menu groups, such factors as punctuality of meal times, contaminated substances in meals and serving mistakes, cleanliness of dishes, kindness of the server meal rounding while dining should by particularly managed with importance.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.7
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• pp.1019-1028
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• 2004

The purpose of this study was to compare the body measurements of cyclists and non-cyclists and to classify cyclists＇ body types to offer basic information for the bicycle apparel manufacturer in Korea. The anthropometric data was collected including both direct and indirect measurements of 81 cyclists (40 female, 41 male) aged from 19 to 24. Anthropometric measurements were analyzed using percentiles, T-test, factor and cluster analysis. The results were as follows; Comparison of anthropomeoic data between cyclist and non-cyclist was to clarify that cyclists have bigger size than non-cyclists; especially the thigh circumference shows big differences. As the result of factor analysis, 5 factors, which explain 74% of variance, were extracted from all items for male and female cyclists. The results of cluster analysis classified body types into 3 groups. Cluster 1 among three female cyclist groups has biggest torso and had an erect back. Cluster 2 has small size among three female group and drooping shoulders. Cluster 3 has the bended forward shoulders and shows the protrusion back. In case of male cyclists, cluster 1 has thin body type owing to big height measurements and small girth measurements. Cluster 2 among three male groups has the biggest torso and thigh circumference. Cluster 3 has big forward angle of shoulders and shows the protrusion of the back as female cyclist.