• The Korean Journal of Franchise Management
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• v.7 no.1
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• pp.21-29
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• 2016

Purpose - The primary purpose of this study is to employ effective marketing methods using market segmentation of coffee shops by determining how motivations to visit coffee shops have different impacts on demographic profile of visitors and characteristics of coffee shop visits, so as to draw out a better understanding of customers of coffee market. Research design, data, and methodology - Data were collected using surveys of self-administered questionnaires toward coffee shop users in Daejeon, Korea. A number of samples used in data analysis were 253 excluding unusable responses. The data were analyzed through frequency, reliability, and factor analysis using SPSS 20.0. Factor analysis was conducted through the principal component analysis and varimax rotation method to derive factors of one or more eigen values. In addition, the cluster analysis, multivariate ANOVA, and cross-tab analysis were used for the market segmentation based on the types of motivation for coffee shop visits. The process of the cluster analysis is as follows. Four clusters were derived through hierarchical clustering, and k-means cluster analysis was then carried out using mean value of the four clusters as the initial seed value. Result - The factor analysis delineated four dimensions of motivation to visit coffee shops: ostentation motivation, hedonic motivation, esthetic motivation, utility motivation. The cluster analysis yielded four clusters: utility and esthetic seekers, hedonic seekers, utility seekers, ostentation seekers. In order to further specify the profile of four clusters, each cluster was cross tabulated with socio-demographics and characteristics of coffee shop visits. Four clusters are significantly different from each other by four types of motivations for coffee shop visits. Conclusions - This study has empirically examined the difference in demographic profile of visitors and characteristics of coffee shop visits by motivation to visit coffee shops. There are significant differences according to age, education background, marital status, occupation and monthly income. In addition, coffee shops use pattern characterization in frequency of visits to coffee shops, relationships with companion, purpose of visit, information sources, brand type, average expense per visit, important elements of selection attribute were significantly different depending on motivations for coffee shop visits.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.47-56
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• 2023

The Quercus variabilis and Quercus dentata, which are said to be relatively drought tolerant among the important genus Quercus that represent deciduous broad-leaved forests in Korea. These two species are widely distributed worldwide in Korea, Japan and China (northern, central, western and eastern subtropical regions). This study compared the ecological niche breadth and overlap according to growth response in 4 soil moisture gradients for the two species and tried to reveal degree of competition and ecological niche characteristics. The ecological niche breadth was 0.977±0.020 for Q. variabilis and 0.979±0.014 for Q. dentata, the latter being slightly wider. And they were similar in 5 traits (stem length, leaf lamina length, leaf width length, stem weight, leaf petiole weight), Q. variabilis was more dominant in 4 traits (leaves number, stem diameter, leaf area, leaf petiole length), and Q. dentata was more dominant in 7 traits (root length, shoot length, plant weight, root weight, shoot weight, leaf weight, leaf petiole weight). The ecological niche overlap for soil moisture between the two species overlapped most in plant structure-related traits and least in photosynthetic organ-related traits such as petiole length. As a result of principal component analysis, degree of competition between the two species for soil moisture was more severe when the soil moisture condition was low than high. Among the measured traits that affect the two-dimensional distribution, 8 traits (Leaves number, Shoot length, Stem length, Plant weight, Root weight, Shoot weight, Stem weight, Leaves weight) were correlated with the factor 1, and 2 traits (Leaf width length, Leaf petiole weight) were correlated with the factor 2 (r>0.5). These results show that the ecological response of the two species to soil moisture is not a few traits involved, but several traits are involved simultaneously.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.6
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• pp.1096-1106
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• 1996

This study was to identify the dimensions of consumers' attitudes toward imported casual brands. Another objectives were to examine consumers' attitude according to the preference group, and to ascertain the imported casual brand images. The 55 Likert type questions were selected through the results of self-questionnaire analyses. 520 females aged between 20 to 29 in Pusan responded to the second questionnaire of consumers' attitudes and brand images toward imported casual brands. The results were as follows: 1. For final factor analysis, 56 selected from 85 questions were subjected to the principal component analyses with orthogonal rotation after extraction of 5 major factors. 2. Five dimensions are brand's uniqueness and good quality, high prestige, incongruity with native emotion and ethnocentrism, conspicuous consumption, and reasonable purchasing advantages. These factors explained 45.0% of total variance. 3. Five dimensions were different according to the degree of preference. For preference group, they purchased the imported casual brands by uniqueness, good quality and reasonable purchasing advantages. For non-preference group, they disliked the imported brands by incongruity with native emotion, ethnocentrism, and conspicuous consumption. 4. Preference group had 5.47, whereas non-preference group had 1.76 pieces of imported casual brands for this 2 years. This result suggests that to develop the domestic brands with international uniqueness, good quality, and high prestige, and to improve according to preference group are necessary.

• Safety and Health at Work
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• v.6 no.2
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• pp.77-84
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• 2015

Background: A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods: To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results: The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion: The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

• Journal of Korean Academy of Nursing
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• v.35 no.6
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• pp.1063-1071
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• 2005

Purpose: This study was done to develop and test validity and reliability of on instrument for predicting nursing intention for SARS patient care. Method: The psychometric properties of a SARS patient care attrition prediction tool, based on the Theory of Planned Behavior, were examined in this study. The Three-phase design involved a) salient beliefs generated from clinical nurses (n=43) b) content validation by expert panel evaluations(n=5) c) face validation by plot testing (n=10) d) and instrument validation in a cross sectional survey (n=299). Psychometric analysis of survey data provided empirical evidence of the construct validity and reliability of the instrument. Result: Principal component analysis verified the hypothesized 6-factor solution, explaining $68.2\%$ of variance, and Alpha coefficients of .7538 to .9389 indicated a high internal consistency of the instrument. Conclusion: The instrument can be used by nurse administrators and researcher to assess clinical nurses' salient beliefs about caring for SARS patients, guide tailored intervention strategies to effective caring, and evaluate the effectiveness of interventions.

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2009-2016
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• 2020

A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety.

• Journal of Families and Better Life
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• v.27 no.6
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• pp.95-109
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• 2009

This study focused on the development of a scale to measure the ability of consumers to use credit cards. The purposes of this study were to develop a tool which would be able to measure consumer knowledge, consumer skills and consumer attitudes. Data were collected from 313 credit card using consumers and were analyzed by employing a goodness of fit test, principal component analysis & confirmatory factor analysis(Amos 5.0), multiple regression. The results from this study were as follows: 1) Six factors of consumer knowledge(16-items) were identified: damage salvation; credit delinquency; personal credit information; credit provision period; credit & credit card issuance; credit delinquent striking out a record & credit rating. The total variance was 55.86%. 2) Three factors of consumer skills(17-items) were identified: credit delinquency & over-consumption; credit card management; and loss & damage salvation. The total variance was 62.90%. 3) Three factors of consumer attitudes(16-items) were identified: credit delinquency & credit; credit card issuance & use; and credit card management. The total variance was 58.75%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1194-1202
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• 2002

A study on the topology optimization of a multi-spectral camera for space-use is presented. The optimization is carried out under self-weight and polishing pressure loading. A multi-spectral camera for space-use experiences degradation of optical image in the space, which can not be detected on the optical test bench on the earth. An optical surface deformation of a primary mirror, which is a principal component of the camera system, is an important factor affecting the optical performance of the whole camera system. In this study, topology optimization of the primary mirror of the camera is presented. As an objective function, a measure of Strehl ratio is used. Total mass of the primary mirror is given as a constraint to the optimization problem. The sensitivities of the objective function and constraint are calculated by direct differentiation method. Optimization procedure is carried out by an optimality criteria method. For the light-weight primary mirror design, a three dimensional model is treated. As a preliminary example, topology optimization considering a self-weight loading is treated. In the second example, the polishing pressure is also included as a loading in the topology optimization of the mirror. Results of the optimized design topology for the mirror with various mass constraints are presented.

• Interdisciplinary Bio Central
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• v.6 no.1
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• pp.1.1-1.6
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• 2014

A growing body of evidence shows that most psychological traits are polygenic, that is they involve the action of many genes with small effects. However, the study of selection has disproportionately been on one or a few genes and their associated sweep signals (rapid and large changes in frequency). If our goal is to study the evolution of psychological variables, such as intelligence, we need a model that explains the evolution of phenotypes governed by many common genetic variants. This study illustrates simple statistical tools to detect signals of recent polygenic selection: a) ANOVA can be used to reveal significant deviation from random distribution of allele frequencies across racial groups. b) Principal component analysis can be used as a tool for finding a factor that represents the strength of recent selection on a phenotype and the underlying genetic variation. c) Method of correlated vectors: the correlation between genetic frequencies and the average phenotypes of different populations is computed; then, the resulting correlation coefficients are correlated with the corresponding alleles' genome-wide significance. This provides a measure of how selection acted on genes with higher signal to noise ratio. Another related test is that alleles with large frequency differences between populations should have a higher genome-wide significance value than alleles with small frequency differences. This paper fruitfully employs these tools and shows that common genetic variants exhibit subtle frequency shifts and that these shifts predict phenotypic differences across populations.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1462-1466
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• 2009

우리나라 가뭄의 지역적 특성은 수문학적으로 동질한 지역의 구분 결과에 따라 달라진다. 지역의 구분에는 가뭄에 영향을 미치는 다양한 변수들이 사용될 수 있다. 가뭄을 특징짓는 요소로서 지속기간, 심도, 이외의 통계적 특성들이 있으며, 이 변수들을 정보화하여 변수의 유형을 구분지어 모든 변수들을 요약된 정보로 활용하여 가뭄의 특성을 구분할 수 있다. 본 연구에서는 우리나라 기상청 강우자료 75개 관측지점 중 30년 미만의 강우기록이 있는 17개의 지점을 제외한 58개 강우 관측 지점을 대상으로 가뭄지수(SPI)를 산정하여 가뭄사상의 특성을 정량화 과정으로 남한지역 가뭄특성을 분류하였다. SPSS를 활용한 다변량 분석기법인 주성분 분석(principal component analysis)을 통해 가뭄특성인자의 상관관계가 높은 변수들을 조합하여 그 변수들 중 가뭄정보를 가능한 많이 함축하고 있는 새로운 특성 변수를 만들어 내었으며, 선정된 변수들을 바탕으로 요인분석(factor analysis)의 직각회전 방식(Varimax)을 이용하여 변수들의 표준화를 통해 가뭄특성요인을 찾아내었다. 이를 통해 지역간 동질성을 파악하여 K-means기법을 적용하여 군집해석(clustering analysis)을 실시하였다.