• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.978-986
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• 2005

The color of apparel products have a close relationship with the face skin colors of consumers. In order to extract the favorable colors which flatter to consumer's face skin colors, this study was carried our to classify the face skin colors of Korean females. The criteria that select new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 324 Korean females and other new 10 college girls. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 324 subjects who have YR colors were clustered into 3 face skin color groups. 2. Discriminant variables of face skin colors were 5 variables : b value of cheek, V value of forehead, L value of cheek, C value of forehead and H value of cheek by the standardized canonical discriminant function coefficient 1. 3. Hit ratio of type 1 was $96.8\%$, of type 2 was $94.9\%$, of type 3 was $100.0\%$ and mean of hit ratio was $96.9\%$ by canonical discriminant function of 5 variables. 4. With the unstandardized canonical discriminant function coefficient and constant, canonical discriminant function equation 1 and 2 were calculated. And cutting score and range of score of the classified types were computed. The criteria that select the new subjects were decided.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.79-100
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• 2017

This study provides the insight into the aged employment provision issue for the aged-low growth era. For the purpose, we analyze the national trend of the age demographic and occupational employment in first. And then we investigate the spatial characteristics of employment of the aged in the Seoul Metropolitan area which has the highest elderly population by utilizing location quotient, factor analysis, and K-means cluster analysis. As the result, we found that the spatial distribution patterns of the residence and workplace of the elderly were nearly coincided with each other. Furthermore, five clusters of the aged distribution have been determined according to the industrial-occupational-demographic attributes. The result revealed clear spatial segrmentation: Most of elderly population of the research area have been engaged in the low-level service jobs, while elderly population employed to the educated-knowledged based high-level jobs has been distributed at a few cores. The results could be applied to the practical use for regional employment planning for the aged.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.449-460
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• 2019

Purpose: This study aims to provide base data for designing education and counseling programs for child-raising by identifying the types, characteristics and predictors of parenting behaviors of married immigrant women. Methods: We used a self-report questionnaire to survey 126 immigrant mothers of young children, who agreed to participate, and who could speak Korean, Vietnamese, Chinese, Filipino, or English, at two children's hospitals and two multicultural support centers. Statistical analysis was conducted using descriptive analysis, K-means clustering, ${\chi}^2$ test, Fisher's exact test, one-way ANOVA, $Sch{\acute{e}}ffe^{\prime}s$ test, and multinominal logistic regression. Results: We identified three clusters of parenting behaviors: 'affectionate acceptance group' (38.9%), 'active engaging group' (26.2%), and 'passive parenting group' (34.9%). Passive parenting and affectionate acceptance groups were distinguished by the conversation time between couples (p=.028, OR=5.52), ideology of motherhood (p=.032, OR=4.33), and parenting stress between parent and child (p=.049, OR=0.22). Passive parenting was distinguished from active engaging group by support from spouses for participating in multicultural support centers or relevant programs (p=.011, OR=2.37), and ideology of motherhood (p=.001, OR=16.65). Ideology of motherhood was also the distinguishing factor between affectionate acceptance and active engaging groups (p=.041, OR=3.85). Conclusion: Since immigrant women's parenting type depends on their ideology of motherhood, parenting stress, and spousal relationships in terms of communication and support to help their child-raising and socio-cultural adaptation, it is necessary to provide them with systematic education and support, as well as interventions across personal, family, and community levels.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.71-81
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• 2010

The problem of finding clusters is widely used in numerous applications, such as pattern recognition, image analysis, market analysis. The important factors that decide cluster quality are the similarity measure and the number of attributes. Similarity measures should be defined with respect to the data types. Existing similarity measures are well applicable to numerical attribute values. However, those measures do not work well when the data is described by categorical attributes, that is, when no inherent similarity measure between values. In high dimensional spaces, conventional clustering algorithms tend to break down because of sparsity of data points. To overcome this difficulty, a subspace clustering approach has been proposed. It is based on the observation that different clusters may exist in different subspaces. In this paper, we propose a new similarity measure for clustering of high dimensional categorical data. The measure is defined based on the fact that a good clustering is one where each cluster should have certain information that can distinguish it with other clusters. We also try to capture on the attribute dependencies. This study is meaningful because there has been no method to use both of them. Experimental results on real datasets show clusters obtained by our proposed similarity measure are good enough with respect to clustering accuracy.

• Journal of Global Scholars of Marketing Science
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• v.16 no.1
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• pp.73-91
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• 2006

This study was conducted for market segmentation of cruise tourist according to launching the "T" in Busan. Benefit segmentation was used to identify attributes of cruise services; importance of ship's physical appearance and importance of service and activities. 24 attributes were distilled to 5 factors: 'Facility & Service', 'Atmospherics of cruise ship', 'Escape', 'Choice', 'Safety'. A K-means cluster analysis identified three clustered segments for five importance factors in which high loyalty customers were found to be the most important segment. Based on the findings, three distinct groups were formed: 'Moderators', 'High Loyalty', 'Spurious'. The most important factors by high loyalty groups were identified 'Safety', 'Facility & Service', 'Atmospherics of cruise ship', 'Choice', 'Escape' in order. The results of the study showed statistically significant differences among the three groups in terms of demographic and behavioral variables. Especially, the target market should be considered by 'High Loyalty' group and 'Moderators' group in order. Positioning strategies and marketing mix strategies for effectively targeting the segments were discussed.

• Korean Journal of Environmental Biology
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• v.23 no.3 s.59
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• pp.238-249
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• 2005

The present study was carried out to apprehend that the pollutants originating from Jinhae Industrial Complex affect benthic polychaetous community in the northern Jinhae bay. An investigation on the macrobenthic community in Jinhae bay was conducted in September, December of 2002 and March of 2003. The benthic fauna showed mean density of 2,151 ind. $m^{-2}$ in September of 2002, 2,427 ind. $m^{-2}$ in December of 2002 and 2,394 ind. $m^{-2}$ in March of 2003. Major faunal groups are polychaetes, crustaceans and mollusks, corresponding to $73.7\%,\;12.0\%\;and\;11.7\%,$ in total mean density during all of the sampling season, respectively. The most abundant species was Lumbrineris longifolia $(24.85\%),$ followed by Tharyx sp. $(21.70\%),$ Mesochaetopterus sp. $(6.20\%),$ Heteromastus filiformis $(5.39\%),$ Prionospio sp. $(5.18\%),$ Clycinde sp. $(4.29\%),$ etc. Tharyx sp. was the highest abundant species in September of 2002, and Lumbrineris longifolia was the dominant species in another sampling seasons. The density and the species number of polychaetes were high around Chori Is. and poor near Jinhae Industrial Complex area. Cluster analysis based on the species composition showed that Jinhae bay could be divided into three regions except in March of 2003. In December of 2002, there are very distinct regions by the cluster analysis. The density of benthic polychaetes in Jinhae bay was higher than that in the other coastal area of Korea, due to the predominance by some of opportunistic species, such as Lumbrineris longifolia, Tharyx sp. and Heteromastus filiformis, etc. It means that the study area were in the process of organic enrichment.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.959-967
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• 2005

The color of apparels has the interaction of the face skin colors of the wearers. This study was carried out to classify the face skin colors of Korean males into several similar face skin colors in order to extract favorable colors which flatter to their face skin colors. The criterion that select the new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured quantitatively and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 418 Korean males and other 15 of new males subjects. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 418 subjects who have YR colors were clustered into 3 kinds of face skin color groups. 2. Discriminant variables of face skin colors was 4 variables : L value of forehead, v value of cheek, c value of forehead, and b value of cheek from standardized canonical discriminant function coefficient 1 and c value of forehead, L value of forehead, b value of cheek. and L value of cheek from standardized canonical discriminant function coefficient 2. 3. Hit ratio of type 1 was $92.3\%$, of type 2 was $96.5\%$ and of type 3 was $92.6\%$ by the canonical discriminant function of 4 variables. 4. The canonical discriminant function equation 1 and 2 were calculated with the unstandardized canonical discriminant function coefficient and constant, the cutting score, and range of the score were computed. 5. The criterion that select the new subjects who have the classified face skin colors was decided.

• Journal of the Korean Home Economics Association
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• v.46 no.1
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• pp.63-72
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• 2008

The purpose of this study was to investigate the appearance management behaviors and motives differentiated by the body image of college men. A questionnaire was designed for the survey and the subjects were 228 college in Pusan and the Kyongnam province, Korea. The statistical analyses were carried out in the forms of frequency, factor analysis, cluster analysis, ANOVA and Duncan's multiple range test. The findings throughout the research are as follows; First, according to the multidimensional body image of the subjects, the college men were classified into three groups, i.e. the appearance concerning and satisfied group, the weight concerning group, and the appearance indifferent group. The appearance management behaviors of the college men consist of innovative appearance management, weight reduction, appearance management through apparel and fashion products, body shape care, skin care, hair care and health care. Second, the weight concerning group showed a higher BMI than those of the other groups. The means of the monthly income and the expenses for the appearance management of the appearance indifferent group were lower than those of the other groups. Third, the college men were generally shown to pursue the motive improving sociality. The appearance concerning and satisfied group and the weight concerning group indicated higher pursuing motives than the appearance indifferent group in the appearance management motives. Finally, there were significant differences in the appearance management behaviors among the three groups. While the weight concerning group showed the more concerning appearance management behaviors, the appearance indifferent group had the least appearance concerning tendency.