• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.72-79
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• 2018

The purpose of this study was to analyze general characteristics and empathy factors of nursing student's major satisfaction. Participants in this study were 235 students from both located in J do and C do Universities. The research method was a cross-sectional survey and the survey period was from September 1 to 10, 2017. The questionnaire was used to investigate general characteristics, empathy, and major satisfaction. The analysis was based on frequency analysis, p value of t or F value, Pearson correlation, regression analysis, and hierarchical regression analysis using SPSS 18.0. The result of this study were as follows: (1) The C University showed higher satisfaction than J University(3.44), (2) the factors affecting major satisfaction were school location, grade, religion, cognitive empathy, and emotional empathy correlated, Regression analysis was used to examine factors that correlated with major satisfaction, followed by hierarchical regression analysis to identify the most influential factors. (3) The result of the analysis showed that the greatest influence factors on major satisfaction were the University location(${\beta}=.325$, p<.01), the cognitive empathy (${\beta}=.287$, p<.01), and the next order was negative grade(${\beta}=-.230$, p<.01). Based on the results of this stud, the following conclusions can be drawn. The most influential factor in the major satisfaction was the school location, but this was an irreversible factor. Therefore, if the cognitive empathy factor and grades are corrected, it can be said that it can increase the satisfaction of major in nursing University students. In this study, it was emphasized that cognitive empathy contained in the course of nursing education program and suggested guidance on major satisfaction in lower grades.

• Korean Security Journal
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• no.43
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• pp.99-120
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• 2015

This research aimed at analyzing health behavior of private security guards applying planned behavioral theory. In order to achieve the above purpose, this research conducted purposive sampling on the security guards who live in Seoul Gyeonggi region. Excluding unfaithful response and abnormal outlier, material of 187 persons was used for analysis. As the concrete analysis method, multiple regression analysis and logistic regression analysis to presume exploratory factory analysis(EFA), Polyserial Exploratory Factor Analysis(EFA), Polyserial correlation analysis, and causal relationship between each variable. The result can be summarized as follows. First, attachment, attitude subjective standard on behavior, perceived behavioral control appeared to positively influence affirmative(+) effect on health behavior continuance will. Second, attachment had no meaningful influence attitude toward behavior. Third, attachment had affirmative(+) influence on health behavior continuance will. Fourth, perceived behavioral control had affirmative(+) influence on realization of health behavior, possibility of practising health behavior increased by about 62.9% when perceived behavioral control increased by 1 unit.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.151-157
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• 2014

Purpose: In order to develop strategies to prevent farm-work accidents relating to agricultural machinery, influential factors were examined in this paper. The effects of these factors were quantified using logistic regression. Methods: Based on the results of a survey on farm-work accidents conducted by the National Academy of Agricultural Science, 21 tentative independent variables were selected. To apply these variables to regression, the presence of multicollinearity was examined by comparing correlation coefficients, checking the statistical significance of the coefficients in a simple linear regression model, and calculating the variance inflation factor. A logistic regression model and determination method of its goodness of fit was defined. Results: Among 21 independent variables, 13 variables were not collinear each other. The results of a logistic regression analysis using these variables showed that the model was significant and acceptable, with deviance of 714.053. Parameter estimation results showed that four variables (age, power tiller ownership, cognizance of the government's safety policy, and consciousness of safety) were significant. The logistic regression model predicted that the former two increased accident odds by 1.027 and 8.506 times, respectively, while the latter two decreased the odds by 0.243 and 0.545 times, respectively. Conclusions: Prevention strategies against factors causing an accident, such as the age of farmers and the use of a power tiller, are necessary. In addition, more efficient trainings to elevate the farmer's consciousness about safety must be provided.

• Journal of Korean Public Health Nursing
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• v.15 no.1
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• pp.13-26
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• 2001

Today's health care environment is rapidly changing and nurse administrators' transformational leadership needs to practice in nursing organization to achieve organizational objectives. Transformational leadership is related to the job satisfaction, productivity, and organizational commitment. This study investigated the effect of transformational leadership and carreer characterics on nurses' organizational commitment. The sample for this study consisted of 594 nurse from 8 large Korean hospitals. The factor analysis Cronbach's alpha analysis, Pearson correlation analysis, multiple regression analysis and hierarchical multiple regression analysis were used for the statistical method. The results of this study were found that (1) charisma dimension of transformational leadership has positive influence on nurses' organizational commitment; but another two dimensions (intellectual stimulation and individualized consideration) did not showed significant effect on organizational commitment (2) nurses' career characteristic(age, marital status, education level. work duration, status) moderated the effect of transformational leadership on organizational commitment.

• Fashion & Textile Research Journal
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• v.4 no.1
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• pp.11-18
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• 2002

The purpose of this study was to investigate the characteristic and composition factor of Japanese costume design. The stimulus were 25 contemporary costume design which represented the traditional image of Japanese. The main survey of questionary consisted of their evaluation of the Japanese costume image by 26 semantic differential bipolar scales and the subjects were 99 female students majoring in clothing and textiles. The data were analyzed by Factor analysis, Multidimensional Scaling Method and Regression Analysis. The major findings were as follows. As a result of design analysis, contemporary Japanese costume design which represented the traditional image had traditional form, color, texture, pattern, etc. Through factor analysis about Japanese costume image 7 factors were identified; Attractiveness, Attention, Cool and warm, Neatness, Activeness, Maturity, Classics. According to image positioning, Japanese costume design was classified by simple-decorative, soft-hard. As the result of regression analysis, The preference of Japanese costume image was related to attractive factor.

• Journal of Korean Academy of Nursing
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• v.31 no.4
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• pp.598-609
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• 2001

Purpose: This study investigated the effect of transformational leadership and individual characteristics on nurses' job involvement. Method: The sample for this study consisted of 594 nurses from 8 large Korean hospitals. The factor analysis was drawn from the Cronbach's alpha analysis, the Pearson correlation analysis, the multiple regression analysis, and the hierarchical multiple regression analysis. Result: This study found that; (1) charisma dimension of transformational leadership has positive influence on job involvement; but intellectual stimulation and individualized consideration did not showed significant effects on job involvement (2) nurse individual characteristics (age, marital status, educational level, tenure, position) moderated the effect of transformational leadership on job involvement. Conclusion : Therefore, to improve job involvement nurses are required to apply the charisma dimension of transformational leadership in hospital organization.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.475-485
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• 2015

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretable compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern of the change.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.2
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• pp.49-56
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• 2003

The welding deformation of a hull structure in the shipbuilding industry is Inevitable at each assembly stage. The geometric inaccuracy caused by the welding deformation tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurateprediction method which can explicitly account for the influence of various factors on the welding deformation. The validity of the prediction method must be also clarified through experiments. This paper is aimed at deriving the simple prediction model for fillet welding deformations. For this purpose, the thermal elasto-plastic analysis varying the welding conditions and plate thickness has been performed. On the basis of numerical results, the formulae for angular distortion and transverse shrinkage have been derived through the regression analysis. Experimental work has been also carried out to clarify the validity of numerical results. It has been found that the numerical results show a good agreement with those of experiments

• Journal of the Ergonomics Society of Korea
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• v.19 no.3
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.

• Steel and Composite Structures
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• v.38 no.6
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• pp.637-656
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• 2021

The component-based method is widely used to analyze the initial stiffness of joint in steel structures. In this study, an analytical component model for determining the column face stiffness of square or rectangular hollow section (SHS/RHS) subjected to tension was established, focusing on endplate connections. Equations for calculating the stiffness of the SHS/RHS column face in bending were derived through regression analysis using numerical results obtained from a finite element model database. Because the presence of bolt holes decreased the bending stiffness of the column face, this effect was calculated using a novel plate-spring-based model through numerical analysis. The developed component model was first applied to predict the bending stiffness of the SHS column face determined through tests. Furthermore, this model was incorporated into the component-based method with other effective components, e.g., bolts under tension, to determine the tensile stiffness of the T-stub connections, which connects the SHS column, and the initial rotational stiffness of the joints. A comparison between the model predictions, test data, and numerical results confirms that the proposed model shows satisfactory accuracy in evaluating the bending stiffness of SHS column faces.