• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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• pp.742-752
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• 2006

The purpose of this study were to classify the door to door selling consumers's according to their cosmetics lifestyles and to analyze the cosmetics a purchase behavior and satisfaction of classified groups. subject were 424 women living in chung-cheong and kyung-gi. The statistical methods to analyze the data were frequency, t-test, factor analysis. cluster analysis, and ANOVA(LSD) using SPSSWIN package. Considering that there were significant differences in the behavior of uses, purchase propensity according to cosmetics lifestyles for door to door selling, it is reasonable that the consumer market should be subdivided by their cosmetics lifestyles and the quality improvement and distinguished sales strategies should be required.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.923-929
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• 2002

We discuss scheduling analysis for a discrete event system with time windows of which firing or holding time delays are subject to random variation within some finite range. To do this, we propose a modified p-lime Petri net, named p+-time Petri net. We develop a condition for which a synchronized transition does not have a dead token, that is, the firing epochs do not violate the time window constraints. We propose a method of computing the feasible range of the token sojourn time at each place based on a time difference graph. We also discuss an application for analyzing wafer residency times within the process chambers for a dual-armed cluster tool for chemical vapor deposition.

• The Research Journal of the Costume Culture
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• v.7 no.1
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• pp.154-164
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• 1999

The purpose of this study is to provide total information for elderly women\`s clothing construction by classifying and analyzing the characteristics of their lower body types. Three hundred three subjects, between the ages of 60 and 82, were chosen. The data were collected from 37 anthropometric measurements of each subject and analyzed by the multivariate method. Through the factor analysis of principal component model, eight factors were extracted from anthropometric measurements. The most important factors were obesity, vertical size, and shape of below waistline to hip. The subjects were classified into 5 types according to cluster analysis by Ward\`s minimum variance method. The dominent types were type 1, 2. The chracteristics of type 1 are average height and sized tyoes, a greater difference between hip and waist. The charateristics of type 2 are shorter height and comparatively fat types, fatness of the waist and abdomen.

• Fashion & Textile Research Journal
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• v.13 no.3
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• pp.364-372
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• 2011

The primary purposes of this study were to classify consumer's type according to narcissistic orientation of consumer and then to reveal consumer's perception differences on consumption value of apparel products and cosmetics subject to the types. Data were collected from 194 female college students in Ulsan. It was analyzed by frequency analysis, factor analysis, cluster analysis and MANOVA, ANOVA using SPSS Win 12.0. The results were as follows: First, consumer's types classified according to narcissistic orientation were non-narcissist, high-narcissist, leadership and self-absorption. Second, in the consumption value of apparel products case, there were significant differences in effective value, symbolic value and sensitive value among the types. Third, in the consumption value of cosmetics case, there were significant differences in sensitive value and effective value among the types.

• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.6
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• pp.995-1007
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• 1995

The purpose of this study is to examine on breast shapes of elderly women and provide fundamental data for developing brassiere. Numerous anthropometric measurements and other related data from 398 subjects were analyzed by various statistical methods such as ANOVA, Correlation analysis, Factor analysis and Cluster analysis. 1. Analysis of Breast Measurements The subjects were categorized into three groups(Group I; aged 55 to 64, Group II; aged 65 to 74, Group III; aged more than 75). 1) The results of the comparative analysis of anthropometric data from three groups show that by getting older: - $\circled1$ Breast lengths, widths, heights and bust girths are decreased significantly $\circled2$ Various length measurements related to the drooping degree of breast are increased $\circled3$ Some measurements related to the volume of breast are decreased. 2) The results of the correlation analysis among measurement show that there are no directs linear relationships between under bust girth and bust drooping. Further it turned out that the cup size could be used as a factor explaining the volume of breast due to large subject variation, Thus it is required to have more specific information about the breast volume. 2. Analysis of Breast Shapes 1) From 17 measurements, 5 factor were selected as key factors for the factor analysis of breast analysis of breast shapes. The 5 factors are: $\circled1$ Drooping degree of breast $\circled2$ slope between breast and chest, width of bust point $\circled3$ Contours and prominence of breast at the point of front and side $\circled4$ Breast volume $\circled5$ Breast width. 2) We categorized the breast shapes into three types by Cluster analysis. Type 1 is the most common breast shape in elderly women. $\circled1$ Type L: Not too droopy and large breast $\circled2$ Type 2: A little droopy and small breast $\circled3$ Type 3; Very droopy and wide breast

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.4
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• pp.427-439
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• 2014

This study identifies the foot side shapes of elderly men by classifying foot types according to 3D foot shapes and analyzing individual characteristics. The subjects were 284 elderly men over 60 years of age who lived in Gwangju and did not have foot related diseases. They were measured with a scanner (Nexcan$^{(R)}$ of K&I Technology) to obtain three dimensional feet shapes. Anthropometric measuring items consisted of 28 items estimated on the right foot of each subject. 3D scan data were analyzed by various statistical methods such as factor analysis, ANOVA and cluster analysis using the statistical program SPSS 19.0. A total of 7 factors were extracted through a factor analysis and these factors represent 77.56% of total variance. The 8 factors were: inside height and side gradient, ankle thickness, size from foot center to ankle, lateral malleolus height, forefoot height, instep and heel height and gradient. A total of 3 clusters (as foot type) were categorized using 7 factor scores by cluster analysis. Type 1 was classified as high forefoot and low midfoot compared to the length. Type 2 was classified as low forefoot and high midfoot, and type 3 was classified as low forefoot and low midfoot.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.399-408
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• 2011

The purpose of this study was to investigate the relationship between internal marketing and job satisfaction and organizational commitment of secondary physical education teachers. The subject who 286 people worked for secondary physical education teachers in Busan, using cluster random sampling. Finally 258 questionnaires were analyzed using SPSS 15.0 and the results were as follows. First, internal marketing had an effect on job satisfaction of secondary physical education teacher. Second, internal marketing had an effect on organizational commitment of secondary physical education teacher. Third, job satisfaction of secondary physical education teacher had an effect on organizational commitment.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.11-16
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• 2019

People are subject to time sanctions in a busy modern society. Therefore, people find it difficult to eat simple junk food and even exercise, which is bad for their health. As a result, the incidence of chronic diseases is increasing. Also, the importance of making accurate and appropriate inferences to individual characteristics is growing due to unnecessary information overload phenomenon. In this paper, we propose a knowledge reasoning model using association rules and cluster analysis of multi-contexts. The proposed method provides a personalized healthcare to users by generating association rules based on the clusters based on multi-context information. This can reduce the incidence of each disease by inferring the risk for each disease. In addition, the model proposed by the performance assessment shows that the F-measure value is 0.027 higher than the comparison model, and is highly regarded than the comparison model.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.252-258
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• 2022

In this study, we propose a method for analyzing students' understanding of probability and statistics in small lectures at universities. A computer-based test for probability and statistics was performed on 95 science and engineering college students. After dividing the students' responses into 7 clusters using the Robust PCA and the Gaussian mixture model, the achievement of each subject was analyzed for each cluster. High-ranking clusters generally showed high achievement on most topics except for statistical estimation, and low-achieving clusters showed strengths and weaknesses on different topics. Compared to the widely used PCA-based dimension reduction followed by clustering analysis, the proposed method showed each group's characteristics more clearly. The characteristics of each cluster can be used to develop an individualized learning strategy.