• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.82-90
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• 2020

This study investigated the effects of empathy, self-control, and smartphone dependency on the interpersonal relationships of nursing students. The survey participants were 157 students in A city. The data was collected through self-report questionnaires that were obtained from May 27 2019 to May 31 2019. The data was analyzed using descriptive statistics and Independent t-tests, One-way ANOVA, Pearson correlation coefficients, and Stepwise multiple regression analysis of the SPSS 14.0 program. As a result, self-control (F=5.319, p=.006) and smartphone dependency (F=4.854, p=.009) showed significant differences according to the school records. Smartphone dependency (t=-3.381, p<.001) showed significant differences according to smartphone use. Age was found to have a statistically positive correlation with self-control (r=.194, p=.015) and it had a negative correlation with smartphone dependency (r=-.223, p=.005). Self-control was found to have a statistically positive correlation with empathy (r=.244, p<.01), interpersonal relationship (r=.540, p<.001). and negative correlation with smartphone dependency (r=-.432, p<.001). Empathy was found to have a statistically positive correlation with interpersonal relationships (r=.476, p<.001). Stepwise multiple regression analysis revealed that the predictors of interpersonal relationships were self-control (β=.477, p<.001), empathy (β=.359, p<.001), and smartphone use (β=.208, p<.01) which accounted for 45.0% of all the variance (F=12.029 p<.01). An enhancement program of nursing students' interpersonal relationships is needed that considers their self-control, empathy, and smartphone use.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.246-254
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• 2021

The purpose of this study was to investigate the effects of knowledge and risk perception of coronavirus disease-2019 on preventive health behavior among nursing students. The survey participants were 291 students in A city. Data were collected using self-report questionnaires between August 1 and 20, 2020. Data were analyzed using descriptive statistics, the independent t-test, one-way ANOVA, Pearson's correlation coefficients, and stepwise multiple regression in SPSS ver. 18.0. Knowledge of COVID-19 was significantly dependent on age and school records. Risk perceptions were significantly dependent on educational grades. Age, health status, knowledge, and risk perception had significant effects on preventive health behavior, which was found to be positively correlated with knowledge and risk perception. Stepwise multiple regression analysis revealed that age significantly predicted preventive health behavior (β=.188, p<.01), health status (β=-.245, p<.001), knowledge (β=.254, p<.001), and risk perception (β=.191, p<.001) that it accounted for 18.9% (F=17.904, p<.001) of the variance. An educational program is required to enhance the preventive health behavior of nursing students in a background of COVID-2019 that considers student age, health level, knowledge, and perception of risk.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.553-561
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• 2019

This study examined the relationship between professional self-concept, interpersonal relationship, coping, and clinical practice satisfaction of nursing college students. This was a descriptive study. The survey participants were 355 students in M city and I city. The data were collected from May 29 to June 16, 2017 and self-report questionnaires, including the Professional Self-concept Scale, Interpersonal Relationship Scale, Coping Scale, and Clinical Practice Satisfaction Scale. The data were analyzed by descriptive statistics, independent-samples t-test, ANOVA, and stepwise multiple regression. Professional self-concept showed significant differences according to religion, income, and school records. Interpersonal relationships showed significant differences according to gender, income, and school records. Coping showed significant differences according to the school records. Professional self-concept had a statistically positive correlation with interpersonal relationship, clinical practice satisfaction, and approach coping. Stepwise multiple regression analysis showed that the predictor of professional self-concept was interpersonal relationships, approach coping, religion, school records, and avoidant coping, which accounted for 45.2% of the variance. These results highlight the need for enhancement programs of nursing college students' professional self-concept that consider their interpersonal relationships, coping, religion, and school records.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.743-750
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• 2021

Purpose: The purpose of this study was to analyze factors affecting the meaning of life in patients on hemodialysis. Methods: The sample consisted of 176 adults diagnosed with chronic kidney disease at hospitals in Seoul and Gyeonggi-do who had been receiving hemodialysis for more than three months. The patients volunteered to participate in the study. Data collection instruments used were the Meaning in Life (ML) scale, Resilience scale, Beck Depression Inventory-II (BDI-II) and Fatigue scale questionnaire. The SAS9.2 version was used for descriptive analysis, independent t-test, one-way ANOVA, Pearson's correlation coefficients and stepwise multiple regression. Results: The mean total item score on the meaning of life scale was 133.68 (total score:180), which was low. There was a significant relationship between the ML scale and resilience, depression, and fatigue. Stepwise multiple regression analysis showed that resilience, religion, depression, and fatigue were predictors of the meaning of life. Conclusion: These results indicate a need to develop nursing interventions to increase resilience and reduce depression and fatigue to promote the meaning of life in patients on hemodialysis.

• Korean Journal of Exercise Nutrition
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• v.25 no.1
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• pp.35-41
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• 2021

[Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R²) and 85.9% (adjusted R²), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R²) and 82.6% (adjusted R²), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R²) and 91.0% (adjusted R²), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• The Research Journal of the Costume Culture
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• v.1 no.2
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• pp.113-130
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• 1993

The purpose of this study was to investigate the role of perceived attributes of innovation in predicting the fashion innovativeness of female college students and to compare results with the predictive efficacy of selected psychographic variables. The data were analyzed by factor analysis and stepwise multiple regression. Frequency, percentage and man values were used to evaluate the descriptive data. The major findings derived from analysis are as follows: 1. Of the psychographic variables used to predict fashion innovativeness fashion interest was the most predictive of fashion innovativeness followed by venturesomeness. 2. So only perceived attributes variables found to be predictive of fashion innovativeness was perceived risk.

• International Journal of Human Ecology
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• v.10 no.1
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• pp.75-86
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• 2009

The direct impacts of individual materialism on price perceptions and price perceptions on patronage behavior have been limited in previous research. This study examined the impact of materialism on consumer perceptions of clothing price and the influence that price perceptions have on store patronage by consumers. Using factor analysis and stepwise regression analysis, results indicated that materialistic values revealed four factors (pursuit of happiness, acquisition centrality, success, and practical-consuming). Materialistic four values influence consumer attitudes toward the positive and negative roles of price. In turn, patronage is predicted by positive and negative price-perception. Implications and future research directions are also discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.67
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• pp.83-92
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• 2001

This paper is to measure and evaluate the degree of customer satisfaction for internet search engines. The service quality scale is developed after testing validity and reliability through the result of inquiring into the literature and the interview of university students. The stepwise regression analysis using MINITAB is used to analyze the survey results.