• Journal of Sport and Applied Science
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• v.5 no.3
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• pp.7-12
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• 2021

Purpose: The purpose of this study is to examine the relationship between the perfectionism tendency of amateur boxers and exercise exhaustion, to understand the perfectionism tendency of boxers in the sports of speculative sports, and to provide startigic insights for reducing exercise exhaustion. Research design, data, and methodology: In this study, adult boxers registered with the Korean Boxing Association of the Korea Sports Council in 2019 were selected as the research population. 280 boxers participated in the survey and responded the survey items, which were constructed by research variables, perfectionism and burnout. Data were analysed using SPSS version 18.0 for statistics. In details, frequency, correlations, exploratory factor analysis, multiple regressions were conducted to test the proposed relationship. Results: As a result of analysing the relationship between amateur boxers' perfectionism and athletic exhaustion, it was con-firmed that when the self-oriented perfectionism among amateur boxers' perfectionist tendencies was high, it had a significant effect on exercise burnout. Conclusions: In order to reduce the pressure of amateur boxers to win and the pressure to pass through the weight class, which is characteristic of weight control events, if the athlete manages himself well, the athlete's exercise exhaustion will decrease. If professional mental training is combined, it is judged that amateur boxing will be able to develop once again.

• Women's Health Nursing
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• v.25 no.1
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• pp.86-98
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• 2019

Purpose: The purpose of the study was to determine effect of incivility, resilience, and social support experienced by nursing students on burnout in clinical practice. Methods: Subjects were 140 nursing students who agreed to participate in this study. Collected data were analyzed using descriptive statistics, t-test, analysis of variance, Pearson's correlation and stepwise multiple regression with SPSS WIN 23.0 program. Results: Burnout showed significantly positive correlation with incivility but significantly negative correlations with resilience and social support. Factors affecting burnout were satisfaction with major-dissatisfaction, satisfaction with major-average, social support, grade, and relationship with peers. Satisfaction with major (dissatisfaction) had the greatest effect on burnout, explaining 41% of the total variance. Conclusion: According to this study, dissatisfaction with major was identified as the most significant factor influencing burnout of nursing students in clinical practice. Therefore, it is important to develop and implement programs that can reduce dissatisfaction with major and increase social support and relationship with peers in order to lower burnout of nursing students. In addition, a systemic management of fourth-grade students with a high level of clinical practice is necessary to reduce the level of clinical practice. The authors declared no conflict of interest.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.699-707
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• 2021

The objective of this study is to examine the determinants of the liquidity of 17 commercial banks listed on the Vietnamese Stock Exchanges, HOSE, HNX and UPCoM. The study uses the quarterly audited financial statements from the first quarter of 2006 to first quarter of 2020; it includes 496 observations. Data on GDP and inflation are compiled from the International Monetary Fund and the General Statistics Office of Vietnam. Once collected, the data were organized along the line of unbalanced panel data. The results show that total asset size, return on total assets, and credit growth are positively associated with the liquidity of the listed banks; whereas the interaction between the bank size and the return on total assets has a negative impact on the liquidity of commercial banks listed on the HNX, HOSE, UPCoM. In order to maintain good liquidity, commercial banks need to focus on effective credit growth, ensure a high rate of profit over total assets, and at the same time focus on developing the scale of total assets. However, the development of the size of the total assets should be noted in the balance between the total assets and the rate of return on the total assets.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.99-110
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• 2021

This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.

• Journal of East-West Nursing Research
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• v.28 no.2
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• pp.83-90
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• 2022

Purpose: The purpose of this study was to investigate the educational needs and knowledge level of traditional Korean nursing among nurses in Korean medicine hospitals. Methods: A survey design was used. A total of 180 nurses working for more than six months at 10 Korean medicine participated in this study. Data were collected in September of 2019. All data were analyzed by t-test, ANOVA, Scheffé, and paired t-test using SPSS Statistics 25.0 program. Results: The six sub-areas of educational needs for traditional Korean nursing were knowledge of treatments, direct nursing care, types of acupuncture, manipulative therapy, diagnosis, and herbal medicine in order. Average score of the educational needs for nurses in Korean medicine hospitals was 3.77 points out of 5 points. All six sub-areas of the knowledge level were statistically significant. Average score of knowledge level about Korean medicine among nurses was 3.03 out of 5. Conclusion: As a result of this study, it was found that a high level of knowledge is required or Korean medicine education. Knowledge of Korean medicine should be improved through education on thetypes of acupuncture, manipulative therapy, diagnosis, and treatment with relatively low scores. The results of this study can be used as basic data for preparing an educational system to improve the knowledge level of nurses in Korean medicine hospitals.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.

• Journal of Wind Energy
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• v.14 no.3
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• pp.25-33
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• 2023

In order to secure the safety of increasing offshore activities such as offshore wind farm maintenance and fishing, IMPACT, a mid-term marine weather forecasting system, was established by predicting marine weather up to 7 days in advance. Forecast data from the Korea Hydrographic and Oceanographic Agency (KHOA), which provides the most reliable marine meteorological service in Korea, was used, but wind speed and wave height forecast errors increased as the leading forecast period increased, so improvement of the accuracy of the model results was needed. The Model Output Statistics (MOS) method, a post-correction method using statistical machine learning, was applied to improve the prediction accuracy of wave height, which is an important factor in forecasting the risk of marine activities. Compared with the observed data, the wave height prediction results by the model before correction for 6 to 7 days ahead showed an RMSE of 0.692 m and R of 0.591, and there was a tendency to underestimate high waves. After correction with the MOS technique, RMSE was 0.554 m and R was 0.732, confirming that accuracy was significantly improved.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1201-1212
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• 2016

Value at Risk (VaR) for market risk management is a favorite method used by financial companies; however, there are some problems that cannot be explained for the amount of loss when a specific investment fails. Conditional Tail Expectation (CTE) is an alternative risk measure defined as the conditional expectation exceeded VaR. Multivariate loss rates are transformed into a univariate distribution in real financial markets in order to obtain CTE for some portfolio as well as to estimate CTE. We propose multivariate CTEs using multivariate quantile vectors. A relationship among multivariate CTEs is also derived by extending univariate CTEs. Multivariate CTEs are obtained from bivariate and trivariate normal distributions; in addition, relationships among multivariate CTEs are also explored. We then discuss the extensibility to high dimension as well as illustrate some examples. Multivariate CTEs (using variance-covariance matrix and multivariate quantile vector) are found to have smaller values than CTEs transformed to univariate. Therefore, it can be concluded that the proposed multivariate CTEs provides smaller estimates that represent less risk than others and that a drastic investment using this CTE is also possible when a diversified investment strategy includes many companies in a portfolio.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.315-329
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• 2014

In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.21-28
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• 2017

This study aims to identify individual and familial factors associated with youth sexual experience by using the nationally representative sample data in South Korea. Specifically, we select 68,043 students in middle and high schools participating in the 2015 Korea Youth Risk Behavior Web-based Survey. Considering the complex survey design, we conduct a descriptive analysis and multiple logistic regression for sexual experience. The main results identify factors on sexual experience such as age, type of school, stress level, drinking, smoking, economic status, and cohabiting parents. In particular, the drinking and smoking behaviors are positively associated with sexual experience and the youth living with neither parent is more likely to have a sexual experience than those who lived two parents. In conclusion, the plan of sex education should consider the risk factors and the quality of sex education should be enhanced in order to build more appropriate sexual culture and behaviors among the youth.