• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (B)
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• pp.388-390
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• 2005

최근 소프트웨어 가 점 점 복잡해 짐 에 따라 다양한 상황에 대한 테스트의 중요도도 함께 증가하지만, 다양한 상황을 모두 고려하여 테스트하는 것은 많은 시간과 비용을 요구한다. 본 논문에서는 이러한 복잡한 시스템의 테스트를 위해 Orthogonal Array와 Equivalence Class 기법을 이용하여 test suite의 중복성을 낮추는 효율적인 test set을 생성하는 기법을 제안한다. 이렇게 제안된 기법을 OMA DRM(Digital Rights Management) System에 적용한 사례를 통해 기법의 우수성을 보인다.

• 유통과학연구
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• 제11권12호
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• pp.71-81
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• 2013

Purpose - This study investigated the effects of consumers' selection criteria for environment-friendly agricultural products on purchase intention and the effects of consumers' attitudes and the reliability of environment-friendly agricultural products on purchase intention by using the theory of planned behavior. Subjective norms of variables of behavioral intention, attitudes toward behavior and control of the behavior were used to create selection criteria, consumers' attitudes and reliability of environment-friendly agricultural products. The study investigated the effects of consumers' selection criteria, attitudes, and reliability of environment-friendly agricultural products on purchase intention constructing models and hypotheses of mediation and moderation between selection criteria for agricultural products and purchase intention by consumers' attitudes and reliability. Research design, data, and methodology - The findings were as follows: first, consumers' selection criteria for environment-friendly agricultural products had a significantly affirmative influence upon purchase intention. Health was the most important factor of selection criteria convenience was more important than quality and familiarity was next. Consumers' attitudes and trust had a significant influence on purchase intention. Second, testing showed that consumers' attitude and trust partially mediated selection criteria: sub-factors and purchase intention were important in selection criteria. Third, testing showed that consumers' attitude and trust had a significant moderation effect between selection criteria and purchase intention. In the test of the moderation effect between sub-factors of selection criteria and purchase intention, consumers' attitude had a significantly positive influence upon health, convenience, and familiarity, and had no significant influence upon quality and purchase intention. Consumers' trust had no significant influence upon health, convenience, and quality. Results - The study provided several theoretical implications: first, an empirical analysis was undertaken with selection criteria for environmental-friendly agricultural products, consumers' attitude, and trust to investigate subjective norms, attitude toward behavior and control of behavior based on the theory of planned behavior. Second, this study investigated both the mediation effect and moderation effect of consumers' subjective norms on attitudes toward behavior, the mediating effects of perceived behavior control and changes of behavioral intention depending upon size and direction of the variables. This study also provided several practical implications. Conclusions - First, consumption of environment-friendly agricultural products did not increase despite rapid increase of production therefore, promotion of consumption and distribution was needed considering the supply and demand of the products. Second, definite standards for selection criteria were suggested to build up consumers' attitude and trust. Consumers' attitude could be improved by factors including the brand of environment-friendly agricultural products, consistent quality, solving physiological problems caused by adverse effects of environmental problems, supplementary approaches, treatment of adverse effects by eating food, and the development and supply of products in accordance with changes of lifestyle. Finally, consumers' demand for sub-factors of selection criteria could be much higher than health, convenience, and quality of the products. Therefore, a process was needed that could continuously check consumers' needs for the products. Limitations were described at the end of the study.

• 대한지구과학교육학회지
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• 제8권3호
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• pp.259-266
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• 2015

This study aims to analyze a selective examination for the gifted and talented from a domain-general and special standpoint. For this, we analyzed gifted and talented test results carried out by Gifted and Talented Education institute affiliated with the university of Education located in the central region of South Korea. This test consisted of three sections which are giftedness in the first round, academic aptitude in the second round and interview in the last round. I conducted the analysis of variance of the giftedness test result to the gifted and talented group in each subject from the domain-general point of view. As a result, the each group was not significant. This means that the gifted and talented in each subject has giftedness from the domain-general viewpoint. Secondly, I implemented the analysis of correlation among three test such as giftedness, academic aptitude and interview conducted during the selective process for the gifted and talented. The result was that they had a low or no correlations between them and were not significant. This demonstrated that each test checked a different area. That is, we came to realize that the first, second and third test evaluates a different area and in particular, with the result that the first and second test had a low or no correlations between both of them we realized that they evaluated a different area from a domain-special standpoint. The purpose of this study is meaningful to investigate in terms of how the selective test for the gifted and talented is conducted from a domain-general and special standpoint as a recent study viewpoint about the gifted and talented along with creativity. It is too limited to generalize this result because this test was sampled by one region but, this study indicates that we should take a domain-general and special standpoint into account when it comes to selection for the gifted and talented.

• 정보처리학회논문지D
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• 제13D권7호
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• pp.923-930
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• 2006

본 논문에서는 무기체계 임베디드 소프트웨어의 시간 요소를 고려한 TFM(Time Factor Method) 기반의 시스템 테스트 모델을 설계하고, 적용사례를 통하여 결과를 제시한다. 이를 위해 무기체계 임베디드 소프트웨어의 특징과 시스템 테스트 그리고 객체지향 모델의 표현방법인 UML 표기법에 대하여 알아보고, 시스템 테스트 모델 설계를 위한 TFM 접근 방법으로 시간 요소를 고려한 테스트 방법과 시간 요소 측정 방법 그리고 테스트 케이스 선정 알고리즘을 제시한다. 무기체계 임베디드 소프트웨어의 TFM 기반 시스템 테스트 모델은 세 가지 요소 (X,Y,Z) 로 구성되며, 'X' 에서는 최대시간경로를 선정하는 알고리즘을 통해 테스트 케이스가 도출되고, 'Y' 에서는 Sequence Diagram과 관련된 객체를 식별하고, 'Z'에서는 Timing Diagram을 통하여 식별된 각 객체들의 실행시간을 측정한다. 또한 제안한 W:M 기반 시스템 테스트 모델을 '다기능 미사일 방어시스템'에 적용하여 테스트 케이스를 추출하는 방법을 제시한다.

• 한국식품영양학회지
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• 제27권6호
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• pp.1156-1162
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• 2014

The study is part of the Chinese beverage selection attributes according to dietary style purchases based on the different dietary styles among different factors and consumer behavior analysis of consumer characteristics. The subjects of study were for the people living in Tianjin China objects directly in the local implementation of the questionnaire survey. A statistical analysis of 455 was conducted using SPSS 19. Using the general statistical analysis and cause analysis and reliability analysis, ANOVA test and cross analysis. Investigation object types related dietary style 20 projects, selection attributes 14 exploratory analysis of the causes, according to the results of dietary style in five factors, respectively of the health oriented, convenience oriented, economy oriented, gourmet oriented, food safety oriented convenient type named pursuit. Selection attributes is to consider three items of the preference factors, production and functional factors, information factors named. Food safety oriented showed a high percentage, Gourmet oriented compared to other types of higher proportion of singles. Food safety oriented production and functional factors to purchase consideration magazine and newspaper has obtained the information. Gourmet oriented production and functional factors to purchase consideration TV and radio were obtained by using the information. Health oriented green tea beverages have been preferred.

• Interdisciplinary Bio Central
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• 제6권1호
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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.

• 응용통계연구
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• 제24권6호
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• pp.1149-1160
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• 2011

기존의 frequentist 추론에 비해 Bayesian 추론에서의 가설 검정 및 모형 선택 문제는 학자들 간에 일치된 견해를 보이지 못하고 있으며 아직도 논란이 되는 것들이 많다. Bayesian 추론에서 가설 검정 및 모형 선택의 기준으로 널리 쓰이는 Bayes factor는 이해하기 쉬우나 여러 경우에 구하기 어려운 단점이 존재한다. 그 외에 다른 기준으로 Spiegelhalter 등 (2002)가 제시한 DIC(Deviance Information Criterion)과 frequentist 추론에서의 P-value에 대비되는 Bayesian P-value가 있다. 본 논문에서는 Swiss banknote 자료를 Bayesian 로지스틱 회귀모형으로 분석하고 관련 기준들을 구하여 각 기준들이 일관성 있는 결론을 보이는지 확인하고자 한다.

• International Journal of Costume and Fashion
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• 제4권
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• pp.47-61
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• 2004

This study analyzed the buying patterns of American and Korean female college students in terms of criteria for clothing selection； store preferences； criteria for store selection； fashion information sources； expressions of customer dissatisfaction； purchasing frequency and motivations for purchasing clothes. The study was implemented through self-administered questionnaires which were back translated for validity. The samples consisted of 730 female college students majoring in the fields related to clothing and textiles： 310 U.S. and 412 Korean students. Likert scales were used for most measures with 1＝never or very unimportant and 5＝always or very important. Data were analyzed by factor analysis, analysis of covariance, Duncans multiple comparison, and t-test. Results are as follows： 1) Design factor was the most important criteria in clothing selection with no differences between country groups. There were, however, significant differences for psychological exhibition factors, practical and economic factors. 2) Both groups preferred specialty and department stores, with department stores more popular in Korea. 3) Merchandise was the most important store selection criterion and fashion magazines and self-experience were rated as the most important information sources for the both groups. 4) Korean group expressed their dissatisfaction with and observable problem with a product before purchase more often than U.S. group, but the U.S. group was more vocal about color loss or shrinkage after care procedures. 5) Some clear differences between the two countries emerged. Marketers targeting American consumers should pay more attention to practicality and service； to Korean consumers more symbolic meaning of products.

• 한국경영과학회지
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• 제39권3호
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• pp.51-61
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• 2014

In this paper, we deal with developing a cost estimation relationships (CER) for Korean maneuverable weapons systems using historical production cost. To develop the CER, we collected the historical data of the production cost of four tanks and five armored vehicles. We also analyzed the Required Operational Capability (ROC) of the weapons systems and chose cost drivers that can compare operational capabilities of the weapons systems We used Forward selection, Backward selection, Stepwise Regression and $R^2$ selection as the cost drivers which have the greatest influence with the dependent variables. And we used Principle Component Regression, Robust Regression and Weighted Regression to deal with multicollinearity and outlier among the data to develop a more appropriate CER. As a result, we were able to develop a production cost CER for Korean maneuverable weapons systems that have the lowest cost errors. Thus, this research is meaningful in terms of developing a CER based on Korean original cost data without foreign data and these methods will contribute to developing a Korean cost analysis program in the future.

• Journal of Construction Engineering and Project Management
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• 제6권3호
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• pp.1-7
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• 2016

The purpose of this paper is to develop a model for selecting the best contractor in the Gaza Strip using the Artificial Neural Network (ANN). The contractor's selection methods and criteria were identified using a field survey. Fifty four engineers were asked to fill a questionnaire that covers factors related to the selection criteria of contractors practiced in Gaza Strip. The results shows that the dominant part of respondents (91%) confirmed that the current awarding method "the lowest bid price" is considered one of the major problems of the construction sector, "award the bid to the highest weight after combination of the technical and financial scores" represented 50% of the respondents. The criteria weights were determined based on Relative Importance Index (RII. Ninety-one tenders(13 projects) were used to train and test the ANN model after re-evaluating the contractors depend on the weights of factors to select the best contractor who achieves the highest score. Neurosolution software was used to train the models. The results of the trained models indicated that neural network reasonably succeeded in selection the best contractor with 95.96% accuracy. The performed sensitivity analysis showed that the profitability and capital of company are the most influential parameters in selection contractors. This model gives chance to the owner to be more accurate in selecting the most appropriate contractor.