• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1372-1383
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• 2004

The purpose of this study was to analyze the differences in cosmetic purchase behavior according to clothing involvement, age, and face satisfaction. Subjects of this study were the females in Seoul and Kyonggi, who were 20's and 40$.$50's. Questionnaire was used as major method of gathering data. The data were collected from Sep. to Oct., 2003 and analyzed by using SPSS 10.0 with various techniques such as the factor analysis, reliability analysis, mean, percentage, cluster analysis, ANOYA, Duncan test, t-test. Cronbach's $\alpha$ and X$^2$-test. The results of this study were as follows: 1. The cosmetic purchase behaviors were categorized in 4 different factors by the factor analysis;'fashion pursuit' purchase, 'conspicuous pursuit' purchase, 'brand pursuit' purchase and 'rational pursuit' purchase. 2. The consumers were classified into four groups by clothing involvement; 'high clothing involvement' group, 'low fashion involvement' group, 'middle clothing involvement' group and 'low clothing involvement' group. 3.'High clothing involvement' group was the highest in 'fashion pursuit' and 'conspicuous pursuit' purchase factors, 'Low fashion involvement' group was the lowest in 'fashion pursuit' purchase factor. Conclusionally, 'fashion pursuit' and 'conspicuous pursuit' purchase behaviors were setting more aggressive as clothing involvement was getting higher. 4. The differences in cosmetic purchase behavior according to the age revealed that 40'$.$50s' basic cosmetic purchase behavior was more 'brand pursuit' oriented than 20's. 5. The result of differences in cosmetics purchase behavior according to the face satisfaction was no noticeable difference.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.7
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• pp.1053-1064
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• 2010

This study investigates the Korean loungewear market and the traditional culture values of consumers related to loungewear to examine the preference of Korean traditional details, sewing techniques in loungewear design, and purchasing intentions. A survey method was used in this study. A total of 230 self-administered questionnaires were obtained from female consumers and 214 data sets were used for analysis. For the analysis, factor analysis, cluster analysis, and ANOVA were executed with PASW Statistics 18.0 and a structural equation model was estimated by Amos 18.0. The results are as follows. Traditional culture values were classified into two dimensions, traditional succession value and traditional design preference value. In the structure equation model, the traditional design preference value had a significant effect on the preference and the traditional culture succession value had significant effect on purchase intention. The results proved that the preference on loungewear with Korean traditional elements is closely related to purchase intention. Consumer groups were divided into three groups by traditional culture values factor; traditional culture succession group, traditional design preference group, and traditional culture indifference group. Style preference images showed significant differences in relation to traditional culture groups. This study is for use as fundamental knowledge on traditional loungewear brand development and strategy planning by offering specific traditional culture aspects associated with preference and purchase intentions.

• Language and Information
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• v.14 no.1
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• pp.113-144
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• 2010

The primary goal of this paper is to find a feasible way to answer the question: Does the similarity in meaning between verbs relate to the similarity in their subcategorization? In order to answer this question in a rather concrete way on the basis of a large set of English verbs, this study made use of various language resources, tools, and statistical methodologies. We first compiled a list of 678 verbs that were selected from the most and second most frequent word lists from the Colins Cobuild English Dictionary, which also appeared in WordNet 3.0. We calculated similarity measures between all the pairs of the words based on the 'jcn' algorithm (Jiang and Conrath, 1997) implemented in the WordNet::Similarity module (Pedersen, Patwardhan, and Michelizzi, 2004). The clustering process followed, first building similarity matrices out of the similarity measure values, next drawing dendrograms on the basis of the matricies, then finally getting 177 meaningful clusters (covering 437 verbs) that passed a certain level set by z-score. The subcategorization frames and their frequency values were taken from the ICE-GB. In order to calculate the Selectional Preference Strength (SPS) of the relationship between a verb and its subcategorizations, we relied on the Kullback-Leibler Divergence model (Resnik, 1996). The SPS values of the verbs in the same cluster were compared with each other, which served to give the statistical values that indicate how much the SPS values overlap between the subcategorization frames of the verbs. Our final analysis shows that the degree of overlap, or the relationship between semantic similarity and the subcategorization frames of the verbs in English, is equally spread out from the 'very strongly related' to the 'very weakly related'. Some semantically similar verbs share a lot in terms of their subcategorization frames, and some others indicate an average degree of strength in the relationship, while the others, though still semantically similar, tend to share little in their subcategorization frames.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.101-109
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• 2011

In most of the urbanized cities, socio-economic attributes tend to cluster as patterns of similarity in space, namely spatial autocorrelation, by agglomeration forces. The classical linear regression model, the most frequently adopted in the trip generation step, cannot sufficiently represent this effect. In order to take into account the effect properly, we need a model which adequately deals with the spatial dependence patterns. In this study, the Geographically Weighted Regression (GWR) model is adopted as an alternative method for the local analysis of relationships in multivariate data sets; that is GWR extends this traditional regression framework by estimating local rather than global parameters. This study shows the existence of spatial effects in the production and attraction of home base/non-home based trips through the GWR model using travel data collected in Daegu metropolitan area. Furthermore, LISA is employed to verify the fact that the local spatial autocorrelation exists.

• Research in Community and Public Health Nursing
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• v.19 no.1
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• pp.36-45
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• 2008

Purpose: This study was to estimate the prevalence of dementia in order to estimate the associations of dementia with its risk factors in the community elderly. Methods: The multistage random cluster sampling method was used to select the subjects. The response rate was 94.3%. For the 1st stage screening survey, the Korean-version Mini-Mental State Examination (K-MMSE) and the Bathel Index of activities of daily living (ADL) and instrumental activities of daily living (IADL) were used as primary screening tools. At the 2nd stage. diagnoses were confirmed according to the Clinical Dementia Rating Scale (CBR) and Computer Tomogram (CT). Results: Age-sex adjusted prevalence (%) [95% CI] of dementia was 6.25% [4.47-7.83] (male 4.21% [2.40-6.02]; female 8.28% [5.71-10.85]). Four statistically significant risk factors of the dementia were identified: age 70-74 (OR=1.367), age 75-79 (OR=1.712), age 80-84 (OR=2.465), age 85 over (OR=7.363) illiteracy (OR=3.827); unconsciousness after head injury (OR=3.383), and no exercise (OR=2.188). Hosmer and Lemeshow goodness-of-fit index of dementia risk model was E (legit of dementia)= -4.337+$0.312^*Age(70{\sim}74)+0.538^*Age(75{\sim}79)+0.902^*Age(80{\sim}84)+1.996^*Age$(85over)+$1.342^*$Illiteracy+$1.219^*$Unconsciousness after head trauma+$0.783^*$No exercise. We confirmed that the overall prevalence of dementia in adults aged 65 and older was 94.3%. The risk factors of dementia were explained by age, illiteracy unconsciousness after head trauma and no exercise. Conclusion: These data have been used to estimate the incidence of dementia in elderly community population and to manage the possible role of risk factors as predictors of dementia.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.10
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• pp.1180-1187
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• 2012

In this paper, joint transmission space division multiple access(JT-SDMA) scheme is proposed to mitigate inter-cell interference(ICI) in cooperative wireless communications system with limited feedback. We propose a systematic design method for a codebook consisting of a finite number of unitary matrices suitable for network multiple-input multiple-output( MIMO) channel characteristics. A centralized cluster scheduling scheme is proposed to both mitigate ICI and maximizes multiuser diversity gain with limited feedback. It is shown that the proposed JT-SDMA scheme outperforms a existing coordinated SDMA scheme even in wireless network environments where sufficient multiuser diversity order can not be provided through efficient ICI mitigation.

• Korean Journal of Health Education and Promotion
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• v.21 no.3
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• pp.1-17
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• 2004

The purpose of this study is to evaluate the roles of expected self-control and expected self-control results in explaining adolescents' Internet addiction. In the study model, expectations of self-control and self-control results directly determine Internet addiction and Internet use time meditates the impacts of expectations of self-control and self-control results on Internet addiction. The study subjects are 1,080 middle and high school students in Busan. Stratified cluster sampling is applied by school type and school year. The response rate is 96%(l,037cases). This study develops the scales of expected self-control and expected self-control results. The scales of Internet addiction are devised by using the concept of functional dependency such as salience, withdrawal symptoms, mood modification, tolerance, relapse, and conflict. For verifying the study model, path analysis and multiple regression models are applied for identifying path significants and evaluating confounding effects of control variables, respectively. Moreover, multi partial F-test is performed for selecting the best regression model. Expected self-control is a significant determinant of Internet addiction and Internet use time that also significantly explains Internet addiction. The total effect of expected self-control towards Internet addiction is -.95. The total effect is comprised with the direct effect (-.71) and the indirect effect(-.24). In this result, the direct effect refers a curative effect since expected self-control directly reduces the level of Internet addiction, and the indirect effect refers a preventive effect because self-control can reduce time of Internet use that is a direct determinant of Internet addiction. In the test of the confounding effects of control variables, there are no confounding effects in the models of multiple regression. It implies a robustness of the study model as regards control variables. In conclusion, improving adolescents' expected self-control can control Internet addiction level. This finding implies that a health promotion program for improving expected self-control can be a cost effective method compared to other approaches.

• Korean Journal of Health Education and Promotion
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• v.27 no.1
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• pp.71-80
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• 2010

Objectives: This study furthers the currents understanding of mental health status and stress level among Seoul citizens and to identify differences according to socio-demographic variables for developing mental health programs. Methods: The study subjects using cluster-stratified sampling method were 1234 adults over 19 years old from 17 dong, S-Ku in Seoul City. A cross-sectional study with face-to-face interview was used to collect data. A questionnaire measuring socio-demographic variables, Symptom Checklist-90-Revised (SCL-90-R) and psychosocial wellbeing index-short form (PWI-SF) was utilized. Results: Three findings in this study were discussed: (1) The rate of clinical mental health was low in contrary to that of border group which was high and the rate of high risk group of stress was 68.1% (men 67.0%, women 69.0%); (2) The mental health and the stress level was significantly higher among female, elderly, lower education level, divorced, and lower family income; and (3) In Pearson correlation analysis, stress were correlated to all 9 symptoms of SCL-R. Conclusion: The findings suggest that the future intervention of Mental Health programs should be carefully designed and tailored by socio-demographic variables.

• Korean Journal of Health Education and Promotion
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• v.27 no.4
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• pp.141-152
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• 2010

Objectives: This study was conducted to estimate the health-related quality of life using EQ5-D by socio-demographic characteristics and mental health among Seoul citizens for developing health promotion programs. Methods: The study subjects using cluster-stratified sampling method were 1234 adults over 19 years old from 17 dong, S-Ku in Seoul City. A cross-sectional study with face-to-face interview was used to collect data. A questionnaire measuring socio-demographic variables, Symptom Checklist-90-Revised (SCL-90-R) and Euroqol EQ-5D instrument. The Difference on the EQ-5D index among groups were tested with Mann-Whitney U test and Kruskal Wallis test. Results: The mean EQ-5D index for all subjects was 0.946(${\pm}0.105$). The EQ-5D index were significantly different by sex, age, marital status, eduction level and income. The EQ5-D indexes among clinical mental health groups were the lowest scores and significantly different from other groups. Conclusion: The findings suggest that the future intervention of health promotion programs should be carefully designed and tailored by socio-demographic variables. Especially, the mental health programs need to be developed.

• Convergence Security Journal
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• v.13 no.3
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• pp.17-23
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• 2013

Clustering is required to configure clustering interdependent structural technology. Clustering handles variable workloads or impede continuity of service to continue operating in the event of a failure. Long as high-availability clustering feature focuses on server operating systems. Active-standby state of two systems when the active server fails, all services are running on the standby server, it takes the service. This function switching or switchover is called failover. Long as high-availability clustering feature focuses on server operating systems. The cluster node that is running on multiple systems and services have to duplicate each other so you can keep track of. In the event of a node failure within a few seconds the second node, the node shall perform the duties broken. Structure for high-availability clustering efficiency should be measured. System performance of infrastructure systems performance, latency, response time, CPU load factor(CPU utilization), CPU processes on the system (system process) channels are represented.