• Journal of Technology Innovation
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• v.12 no.2
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• pp.99-126
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• 2004

Japan's economic clusters are characterized by their high level of diversity. In essence, Japanese economic clusters are not limited to single industries; they comprise numerous manufacturing industries and firms which cluster in specific heterogeneous economic zones, vice political boundaries. Japanese manufacturing sectors are showing an increased level of diversity, resulting in the spread of experience and knowledge among clusters, and sustained growth at the point of industrial structural transformation. Japan's Ministry of Education, Culture, Sports, Science and Technology (MEXT) proposed the creation of intellectual clusters for the purpose of promoting research and development(R&D) activities resulting in the stimulation and development of new technologies. The Ministry of Economy Trade and Industry (METI) is also proposing the industrial cluster plan with the aim to promote the local rebirth and revitalization of the Japanese industrial sector. This paper proposes a methodological analysis which will result in the integration of the two policies currently implemented by the Japanese government. If the current policies are not coordinated and integrated, artificial firms and sectors will continue to hamper innovation and discourage competitiveness, which will ultimately result in Japan's loss of economic opportunities within Asia. In the worst case, failure to act on current economic deficiencies illuminated in this paper could cost Japan its position as an Asian economic leader.

• The Korean Journal of Community Living Science
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• v.21 no.2
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• pp.211-225
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• 2010

This research investigated the purchasing behaviors of fur clothing consumers to verify fur clothing consumption and to establish marketing strategies for the fur clothing market. Since fur clothing has clear characteristics distinguishing it from other clothes, there are many differences in customers' interest. Therefore, it is needed to identify some differences in the customers' interest by their own buying habits. A survey was conducted with a questionnaire and revised by using a theoretical background. Questionnaires were given to 322 ladies in their over 20s. SPSS 12.0 was used to analyse the result with analysis of frequency, a primary factor, crossing, cluster and ANOVA. There were several results as follows. First, purchase behaviors of fur clothing were significantly different between groups divided by demographic variables such as marital status, age, and income level of household. Second, factor analysis on sought clothing benefits resulted in 4 dimensions such as symbolic value, brand value, economical value and practical value. Cluster analysis on the 4 factors of clothing benefits being sought resulted in 3 groups such as one group pursuing symbolism, one group pursuing practicism/economism and a group pursuing brand. Third, purchase behaviors of fur clothing and demographic variables were significantly different between the groups divided by clothing benefits being sought.

• Fashion & Textile Research Journal
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• v.7 no.6
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• pp.650-656
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• 2005

The objective of this study is to analyze the formative attributes of face by measuring the shape and features of face. The faces of women in 20's were taken by digital camera and measured, then it has conducted a statistical analysis using a SPSS for factor analysis, correlation and cluster analysis. The findings are that it is consisted of six(6) different factors and it is responsible for 73.93%. In Factor 1 and Factor 2, it has explained the most significant factor to determine the shape of face. The result on cluster analysis is that it is classified into 5 groups and it is as follows. Attributes of each group is that Group 1 has a wide and long forehead, small and longish chin-line and chubby cheeks that represent polished and modern images, while Group 2 has small and longish forehead and chin-line that represent classical and mature images. On the other hand, Group 3 has a narrow forehead, small and longish chin-line and upward-style eyebrows that represents provocative images, whereas Group 4 has a shaped style that represent intellectual images and Group 5 has small and longish forehead and chin-line and cheekbones that represent polished and cute images.

• Fashion & Textile Research Journal
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• v.15 no.4
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• pp.554-564
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• 2013

We provide an empirical assessment that examines the differences in appearance management behavior, life satisfaction and demographic variables between groups classified by individual lifestyle. Questionnaires were administered to 513 female and male adults over 17 years of age in the Daegu and Kyungbok metropolitan regions. Descriptive statistics, cluster analysis, Cronbach's ${\alpha}$, ANOVA, Duncan test and ${\chi}^2$ test were applied to analyze data from 513 respondents. The results are as follows. First, we did a cluster analysis on the appearance management behavior of weight training, skin care, hair care, make-up and clothing selection. Four groups (passive, rational, fashion oriented, and active typed) where classified according to individual lifestyle. Second, the rational and active groups were more interested in the social life, environmental stability, health, fashion and economic seeking life. They were also more involved in appearance management behavior and in a higher level of life satisfaction. However, the differences of life satisfaction among the lifestyle group (male) were not statistically significant. Third, females with higher level of income and education (among the demographic variables) belonged to the active group. We found significant differences in appearance management behavior, life satisfaction and demographic variables among male and female groups classified by lifestyle.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.923-931
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• 2013

The purpose of this study was to examine the effect of the type of masculinity on appearance-oriented and appearance management behavior. Questionnaires were administered to 201 males 20s to 50s living in Daegu. The SPSS 20.0 package was utilized for data analysis which included frequency analysis, Cronbach's ${\alpha}$, factor analysis, cluster analysis, regression analysis, t-test and logistic regression. First, factor analysis in a appearance management behavior and the type of masculinity, were cluster analysis in appearance-oriented. Were used to analyze the problem of the study by classified five factors and two groups. The results of this study were as follows: First, the masculinity of Retro sexual, Metro sexual, Techno sexual showed a negative influence on appearance-oriented. Second, the masculinity had a influence on appearance management behavior. M-ness showed a negative influence on skin care, Metro sexual showed a positive influence on skin care, hair/fashion, cosmetics, plastic surgery. And Retro sexual showed a influence on skin care, positive influence on hair/fashion, cosmetics. Techno sexual showed a positive influence on body management, skin care, hair/fashion. Uber sexual showed a positive influence on body management, cosmetics of appearance management. Third, the appearance-oriented had a differences on body management, hair/fashion, cosmetics, plastic surgery of appearance management behavior.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3427-3437
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• 2000

In this paper,we propose an method of core sciences extractionusing word cooccrrence graph in order to summarize a document. For automatic extraction of core sentenees, we construct a mean cluster from word cooccurrence graph, and find insistence which corresponds a porposed of author. And then we extract keywords by using relationship between mean cluster and isistence. Finally, core senrences are sclected based on keywords and insitances. The esults are evaluated by comparing with manual extraction, and show that the extraction performance is improved about 10%.

• Journal of Korean Society of Rural Planning
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• v.20 no.3
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• pp.45-53
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• 2014

This study classifies the types of visitors to experiential fishing villages and analyses the features and target marketing strategies by categorical groups. Seven factors are extracted by Factor Analysis and the results of Cluster Analysis indicate the classification of five groups. The first group puts emphasis on the family connection, so family centered facilities and programs are necessary. The second group is composed of surrounding area residents whose purpose of visit is unclear. So environmentally friendly village development programs to encourage local patriotism are necessary. The third group puts emphasis on the necessary facilities and programs for experiencing the fishing village and traditional play, etc. The fourth group emphasizes programs related with the region and the means to satisfy visitor's aesthetic desires. Finally, the fifth group aims at various desires that are generally felt in experiential fishing villages. So this group requires marketing strategies from the public point of view. The existing research mostly surveys rural tourism villages, but this study highlights the difference in dealing with fishing villages as opposed to rural villages, from the perspective of industry and settlement.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.91-102
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• 2016

This study classified the lower body types of female adults aged 18 to 69. The lower body was divided into front, lateral front, and lateral back. In order to understand the shape and somatotype of each segment, 592 people were analyzed based on girth, height, length, depth, width, angle and cross section distance for each segment. For data analysis, SPSS 18.0 was performed for descriptive statics, principal component analysis, K-means cluster analysis, ANOVA, and Duncan's test (as verification). Factor analysis was performed based on index values, calculation values, angles, and cross section distances. The measured items resulted in a.) 16 items were extracted to 5 factors in the case of the front factor (FF) of the lower body, and b.) 24 items were extracted to 6 factors in the case of lateral front factor (LFF) and lateral back factor (LBF). Each factor was put through K-means cluster analysis, classifying the lower bodies into one of four types of based on the front type (FT), the lateral front type (LFT), and the lateral back type (LBT) respectively. This study proposed an understanding of various lower body shapes by segmenting and classifying the lower body shapes for each type.

• Clean Technology
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• v.22 no.1
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• pp.62-72
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• 2016

These days, it seems to be a core time to build proactive prevention systems for small and medium sized enterprises due to the reinforced safety in the production process and the strong environmental regulations (ES) both at home and abroad. On the other hand, a network of experts that combines the industrial environment and production safety as well as even the knowledge services companies are not quite enough to prepare to support them. In this study, through a survey of experts the current statue of the convergence of industrial environment and production safety were reviewed, and the structure of knowledge ES cluster was proposed to overcome this current state. Detailed strategies such as the development and distribution of ES convergence methodology, ES efficiency analysis and an ES roundtable.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1470-1481
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• 2004

The purpose of this study was to research on facial shape to suggest a quantified data for the domestic apparel and beauty industry. Conducted a measurement research of 278 female college students, We took the photographs of front view and lateral view of the subjects by digital camera and obtained the 69 measurements through the facial measurement program. 264 ,subjects' measurement data were analyzed by various statistical methods such as descriptive analysis, factor analysis and cluster analysis. Using the 69 measurement items,4 factors were selected as key factors for the factor analysis of facial shape, the factors are: \circled1 Front face height \circled2 Side face radial length \circled3 Front face breadth \circled4 Ear height and Gnathion radial length. We categorized the facial shape into four types by cluster analysis. Type 4 is the most common facial shape in female college students: \circled1 Type 1: Round face \circled2 Type 2: Oval face \circled3 Type 3: Square face \circled4 Type 4: Heart shaped face According to the facial shape analysis, facial shape of female college students are consisting of Heart shaped face(34.8%), Round face(29.2%), Square face(23.5%), oval face(12.5%).