• Title, Summary, Keyword: cluster analysis

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Cluster Analysis for Foot Type(I) - The subject of the college women between the age of 19~23 years - (발의 형태 분석을 위한 군집분석(I) - 19~23세 여자 대학생을 중심으로 -)

  • 문명옥
    • 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.

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Cluster Analysis for Foot Type (II) -The subject of the college men between the age of 19~24 years- (발의 형태 분석을 위한 군집분석(II) -19~24세 남자대학생을 중심으로-)

  • 문명옥
    • 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.

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The Study on the Cluster Analysis for the Activation of the Innovation Cluster -Focused on the case of the Academia-Industrial Cooperation of the Gwanggyo Technovalley- (혁신클러스터 활성화를 위한 클러스터분석(Cluster Analysis) 연구 -광교테크노밸리 산학협력 분석사례를 중심으로-)

  • Lee, Won-Il
    • 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.

The Classification of Forest Communities by Cluster Analysis in Mt. Seokbyung Experimental Forest of Gangwon-Do

  • Chung, Sang-Hoon;Kim, Ji-Hong
    • 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.

Cluster Analysis of Car Parking Data, and Development of their Web Applications

  • Kubota, Takafumi;Hayashi, Takayuki;Tarumi, Tomoyuki
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.549-557
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    • 2011
  • In this paper, we apply cluster analysis to "Okayama parking data" that is one of the spatial point patterns data that includes locations and the fare structure of car parking space in Okayama central area. This study classifies the characteristics of small areas through Okayama parking data as well as visualizes the results of the cluster analysis. We develop web applications that connect the results of a cluster analysis and overlay objects including points of balloons and rectangles of small areas over a map of Okayama central area.

A Study on Efficient Cluster Analysis of Bio-Data Using MapReduce Framework

  • Yoo, Sowol;Lee, Kwangok;Bae, Sanghyun
    • Journal of the Chosun 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.

Regional Extension of the Neural Network Model for Storm Surge Prediction Using Cluster Analysis (군집분석을 이용한 국지해일모델 지역확장)

  • Lee, Da-Un;Seo, Jang-Won;Youn, Yong-Hoon
    • 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.

Analysis of Fabric Sounds by Quantification of Sound Color (음색의 정량화를 통한 직물의 소리 분석)

  • 조길수;이은주
    • Textile Science and Engineering
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    • v.36 no.7
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    • pp.554-564
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    • 1999
  • In order to quantify sound color of rustling sounds of fabrics and investigate the characteristics of specimens classified by sound color factors through cluster analysis, rustling sounds of selected 65 commercial fabrics were produced by the sound generator developed for this study. ΔL, Δf, and LPT values were calculated form sound spectra forms presented by FFT analysis. Specimens were classified into four clusters with ΔL, Δf, and LPT by use of cluster analysis. Means for ΔL and Δf showed significant differences among clusters. Specimens of cluster 1 had higher ΔL and Δf than those of specimens of other cluster. Specimens of cluster 3 lower ΔL and Δf. These indicated that specimen of cluster 1 has deep and less steep curve in sound spectra and those of cluster 3 had shallow and steep curves. It was supposed that specimens of cluster 1 and 3 would generate sounds of unlike color due to the differences of ΔL and Δf.

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Cluster Analysis of the Foliose Lichens in Mt. Duckyoo (덕유산 엽상지의식물의 집락분석)

  • Park, Seung Tai
    • 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.

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The Assessment of Patient Satisfaction in Accordance with Hospital Patients Food Service Cluster Groups (병원입원환자의 서비스. 영양관리. 식단 만족 요인집단에 따른 만족도 분석)

  • 장은재;김혜진;홍완수
    • 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.

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