• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.341-348
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• 2021

The aim of this study is to fill gaps in emerging empirical evidence and negative electronic word of mouth (NeWOM) in repurchase intention (RI) moderated by the roles of social network sites (SNS) and company mitigation response (CMR). This type of research is descriptive. The sample used in this study is online consumers who buy energy drinks, based on the questionnaire obtained by 145 respondents. Based on the results of testing the estimation of the structural equation model, it was found that the negative variable brand experience sharing had no significant effect on NeWOM; the negative variable electronic reviews had a significant effect on the electronic word of mouth variable, the negative variable electronic reviews had a significant effect on the negative electronic variable word of mouth, the variable intensity of the use of social networking sites can strengthen the direction of the causal influence between the negative variables sharing brand experiences on negative electronic words of mouth. The variable social networking sites usage intensity can strengthen the direction of the effect of causality between negative electronic review variables on negative electronic word of mouth, the negative brand experience sharing variable does not have a significant effect on the repurchase intention variable.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.251-261
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• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• Journal of the Korean Society of Safety
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• v.33 no.5
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• pp.101-108
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• 2018

This study was carried out to obtain baseline data on the causes of industrial accidents and their prevention by investigating structural models between the Shipyard workers' egogram ego-states (CP: Critical Parent, NP: Nurturing Parent, A: Adult, FC: Free Child, AC: Adapted Child), safe and unsafe behaviors, and industrial accidents (frequency/severity). In order to achieve this goal, 378 workers from 3 locations of major corporations in Geojedo Island and Ulsan took a questionnaire, which was then analyzed with a structural equation model using the SPSS 23.0 and AMOS 24 statistics package, and the main results of the study are as follows. First, NP and A's ego-states had a positive influence on safe behavior, AC's ego-state had a negative influence on safe behavior, and A's ego-state had the largest influence on safe behavior. Second, CP and AC's ego-states had a positive influence on unsafe behavior, and A's ego-state had a negative influence on unsafe behavior. AC's ego-state had the largest influence on unsafe behavior. Third, safe behavior did not have a significant influence on industrial accidents. However, unsafe behavior had a positive influence on industrial accident frequency and industrial accident severity, both sub-factors of industrial accidents. This study, despite its limitations, such as sampling limitations, has the following significance. First, this study verified that ego-state, a psychological characteristic, is an important factor for predicting unsafe behavior that induces industrial accidents. Second, in order to reduce industrial accidents, there is a need to stimulate the A ego-states, and promote continuous safety management and safety education to neutralize the AC ego-state. Third, previous studies were limited in the area of practical methods for reducing unsafe behaviors, but this study presents practical methods for reducing unsafe behaviors by verifying the structural relationship between safe/unsafe behaviors and industrial accidents by selecting ego-gram ego-states, variable personality theory, as an independent variable.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.137-145
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• 2008

Embedded industry has emerged as one of the important industry for u-IT based application service. Technology development related to embedded hardware and software provides the base for the development of U-IT convergence industry. This study intends to suggest a research model to investigate the influence of industry, organization, technology factors on technology performance in the embedded companies. This study adopted research variables such as global network, local network, industry intensity, and technology capability as independent variables, with technology performance as a dependent variable from the existing literatures. The purpose of this study is to analyze the influence of industrial and organizational factors on technology performance of embedded companies SCM systems, including the moderating effect of government support. 94 companies data were collected by survey. The result of this empirical study is summarized as follows. First, local network and technology capability are the important determinants to influence technology performance of embedded companies in direct effect model. Second, global network and industry intensity has more positive influence on technology performance of embedded companies through a moderating variable of government support.

• Journal of Families and Better Life
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• v.27 no.1
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• pp.127-144
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• 2009

This study examines the factors that influence the subjective quality of life for Korean, Chinese-Korean, and Chinese women who are both married and employed, and it offers suggestions based on this examination for how to improve these women's quality of life. In particular, we employ both empirical and comparative research to explore the causal relationship in these three groups of women between variables such as cultural orientations, life satisfactions and the perceived quality of life. For these objectives, 263 Korean women, 265 Chinese-Korean women and 280 Chinese women were surveyed. The research can be summarized as follows: First, when we consider subjective quality of life as the dependent variable and factors such as self-esteem, cultural inclination and life satisfactions as independent variables, we find that most of variables record relatively higher than middle score. Comparisons among the three groups find that every variable shows meaningful differences among the groups except for the non-economic reasons for employment. Second, in examining the relative influence of the different variables on the subjective quality of life, we observe that both job satisfaction and family-life satisfaction have a significant influence on the quality of life for women in all groups. For Korean and Chinese women, job satisfaction has a greater influence on the quality of life than family-life satisfaction.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.117-126
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• 2016

The purpose of this study was to explain the influence of depression on the life satisfaction of the elderly with hypertension. Also, we were focusing whether there is a mediating effect of subjective health status between depression and life satisfaction of the elderly with hypertension. 2,198 persons with hypertension over 65 years of age were selected from the data of KLoSA(Korean Longitudinal Study of Ageing), administered by The Korea Employment Information Service in 2014. Life satisfaction was measured by 10-Likert. The depression measured by CES-D10. The mediating variable is subjective health status measured by 5-Likert. As the method of analysis, the multiple regressions were used with SPSS 19.0. The result of the study shows that depression has a negative influence on life satisfaction and a negative influence on subjective health status. It was also verified that the subjective health status variable has a mediating effect between depression and life satisfaction. These results present the importance of psychological approach for the health promotion experts intervening with the elderly with hypertension.

• Transactions of Materials Processing
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• v.15 no.1 s.82
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• pp.47-56
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• 2006

It is well known that the family-mold has an advantage to reduce the cost for production and mold. However, defects are frequently occurred by over packing the smaller volume cavity during molding, especially when the family-mold has a volumetric difference between two cavities. In this study, the cavity-filling imbalance was confirmed by the temperature and the pressure sensors, and a variable-runner system was developed for balancing the cavity-filling. Experiments of balancing the cavity filling was carried out in the family-mold with the variable-runner system, and balancing the cavity-filling was confirmed by changing the cross-sectional area of a runner in the variable-runner system with the temperature and pressure sensors. The influence of the injection speed to the balancing-capability of the variable-runner system was also examined in the experiment.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.195-205
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• 2005

In decision tree analysis, C4.5 and CART algorithm have some problems of computational complexity and bias on variable selection. But QUEST algorithm solves these problems by dividing the step of variable selection and split point selection. When input variables are continuous, QUEST algorithm uses ANOVA F-test under the assumption of normality and homogeneity of variances. In this paper, we investigate the influence of violation of normality assumption and effect of the transformation of variables in the QUEST algorithm. In the simulation study, we obtained the empirical powers of variable selection and the empirical bias of variable selection after transformation of variables having various type of underlying distributions.

• Journal of Korean Society of Steel Construction
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• v.10 no.4 s.37
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• pp.615-627
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• 1998

In order to determine the maximum shear force, the maximum bending moment, the maximum pure torsion. the maximum warping torsion, and the maximum bimoment for the curved girder grid bridges, it is important to find the location of live load applied to the curved girder grid bridges, so that the influence line can be estimated. The fundamental differential equation concerning the behaviour with warping effects for the curved girder is developed by Vlasov. In this paper, the influence line of shear force, bending moment, pure torsion, warping torsion, and bimoment due to unit vertical load and unit torsional moment for curved I-girder grid bridges with variable and constant cross section are obtained by using the finite difference method and compared with respectively.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.111-121
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• 2005

The purpose of this study was to analyze characteristics of experimental design and evidence choice of the elementary school students in problem solving process related to controlling variable. For this study, 96 6th grade students were selected and tested with Science Reasoning Task. This study revealed that the types of experimental design were categorized as variance of control variable, controlling of causal variable, perfect controlling variable, imperfect controlling variable, variance of all variable. Prior belief had a strong influence on student's experimental design. The types of evidence choice were categorized as perfect controlling variable, controlling causal variable, variance of causal variable. The degree of controlling variable in evidence choice process was much lower than that in experimental design. Most students tended to choose evidence according to prior belief without controlling variable. The results of this study implied that student's prior belief and characteristic of science process skills should be considered to develop program for promoting controlling variable ability.