• Korea Journal of Hospital Management
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• v.15 no.4
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• pp.43-62
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• 2010

This study provides an evidence on the determinants of the profitability of university hospital by analyzing university hospital-level data set of hospital performance during the year 2007 (32 university hospitals in total). For the study, a multiple regression model is employed in which profitability index obtained from the DEA computations, operating margin to total asset and gross revenue are used as the dependent variables, and a number of hospital operating characteristics are chosen as the independent variables such as ownership type, location, bed size, period of establishment, bed occupancy rate, admission ratio of outpatients, patients per medical specialist, personnel cost per patient, liabilities to total assets, current ratio, fixed ratio, total asset turnover, medical assistance rate and public indicator. First, the results indicate that the bed occupancy rate and liabilities to total assets are positively and significantly associated with operating margin to total asset. Second, number of beds, the bed occupancy rate and number of patients per medical specialist are positively and significantly associated with operating margin to gross revenue. Third, the bed occupancy rate, number of patients per medical specialist, liabilities to total assets, total asset turnover are positively and significantly associated with profitability index revealed from DEA.

• Physical Therapy Korea
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• v.17 no.3
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• pp.59-67
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• 2010

Mortality rates from stroke have been declining. Because of this, more people are living with residual disability. Rehabilitation plays an important role in functional recovery of stroke survivors. In stroke rehabilitation, early prediction of the obtainable level of functional recovery is desirable to deliver efficient care, set realistic goals, and provide appropriate discharge planning. The purpose of this study was to identify predictors of functional outcome after stroke using inpatient rehabilitation as measured by Functional Independence Measure (FIM) total scores. Correlation and stepwise multiple regression analyses were performed on data collected retrospectively from two-hundred thirty-five patients. More than moderate correlation was found between FIM total scores at the time of hospital admission and FIM total scores at the time of discharge from the hospital. Significant predictors of FIM at the time of discharge were FIM total scores at the time of hospital admission, age, and onset-admission interval. The equation was as follows: expected discharge FIM total score = $76.12+.62{\times}$(admission FIM total score)-$.38{\times}(age)-.15{\times}$(onset-admission interval). These findings suggest that FIM total scores at the time of hospital admission, age, and onset-admission interval are important determinants of functional outcome.

• Wind and Structures
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• v.10 no.2
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• pp.99-119
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• 2007

Estimations of wind flow over terrain are often needed for applications such as pollutant dispersion, transport safety or wind farm location. Whilst field studies offer very detailed information regarding the wind potential over a small region, the cost of instrumenting a natural fetch alone is prohibitive. Wind tunnels offer one alternative although wind tunnel simulations can suffer from scale effects and high costs as well. Computational Fluid Dynamics (CFD) offers a second alternative which is increasingly seen as a viable one by wind engineers. There are two issues associated with CFD however, that of accuracy of the predictions and set-up and simulation times. This paper aims to address the two issues by demonstrating, by way of an investigation of wind potential for the Askervein Hill, that a good level of accuracy can be obtained with CFD (10% for the speed up ratio) and that it is possible to automate the simulations in order to compute a full wind rose efficiently. The paper shows how a combination of script and session files can be written to drive and automate CFD simulations based on commercial software. It proposes a general methodology for the automation of CFD applied to the computation of wind flow over a region of interest.

• Journal of Korea Planning Association
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• v.54 no.4
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• pp.122-130
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• 2019

The purpose of this study is to analyze effect of climate and urban factors on energy resilience, and to explore policy alternatives to strengthen resilience of energy system. For this purpose, this study used extensive literature review on resilience studies and multiple regression analysis. In this study, blackout time was set as a dependent variable. And the independent variables were divided into climate and urban (robustness, countermeasure capacity) characteristics. As a result of the analysis, in terms of climate characteristics, maximum wind speed and cooling/heating degree-day have statistically significant impact on blackout time. With regard to urban characteristics, number of consumer, ratio of deteriorated housing and coast dummy variables have statistically significant impact on blackout time. And the ratio of government employees and road ratio were found to be the most influencing factors to shorten time taken to restore original level of electricity supply. Based on the study results, several policy suggestions to improve energy resilience were made such as continuous management of vulnerable areas and strengthening disaster response services. This study only considered engineering dimension of resilience. Further studies need to be approached on ecological & social-ecological dimension.

• Journal of Korea Trade
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• v.23 no.7
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• pp.83-95
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• 2019

Purpose - This study analyzed the effect of the Trump Government's protectionist trade policies on foreign ownership. Specifically, this study empirically analyzes the hypothesis that foreign ownership will decrease after the Trump Government rather than before the Trump Government. Design/methodology - The hypothesis of this study is based on the expectation that US protection trade policy will negatively affect the profitability of Korean companies. The dependent variable in this study is the foreign ownership ratio, and the independent variable is a dummy variable representing before and after the Trump Government. Multiple regression analysis was performed, including the control variables suggested in previous studies related to foreign ownership. Findings - As a result, foreign ownership increased after the Trump Government rather than before the Trump Government. This study further analyzes whether the main variables affecting foreign investor's decision-making are differences before and after Trump Government. The export ratio, profitability and dividends did not differ before and after Trump Government. However, the level of information asymmetry decreased after the Trump Government than before the Trump Government. This suggests that US protection trade policies do not adversely affect the profitability of Korean companies. However, Korean firms are improving their information environment because US protectionist trade policies can lower profitability and negatively impact capital raising. In this regard, the foreign ownership ratio seems to differ before and after the Trump Government. Originality/value - This study contributes in that it presents data that US protectionist policies can affect Korean corporate governance. This study has implications from the short-term analysis of US protection trade policy.

• Journal of Technologic Dentistry
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• v.45 no.1
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• pp.14-20
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• 2023

Purpose: This study was conducted to provide basic data for a health promotion program by analyzing the effects of high school students' mental health-related factors on oral symptom experiences. Methods: This study included 24,833 high school students who participated in the screening and health survey in the "17th (2021) Adolescent Health Behavior Survey." SPSS software (SPSS Statistics ver. 21.0; IBM) was used for statistical analysis. Multiple sample logistic regression analysis was performed. The significance level was set to 0.05. Results: The result of the analysis on the effect of mental health revealed that oral symptom experience was low in students without depression and suicidal thoughts. Oral symptom experience was high in students with stress perception. Additionally, the experience of oral symptoms was low when there was sufficient subjective sleep. Conclusion: Therefore, it is necessary to develop a customized oral health education program for early detection of oral symptoms and oral health promotion in high school students. Furthermore, it suggests the need for strategies and continuous oral health guidance to practice proper oral health habits to maintain healthy oral conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.219-220
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• 2022

In order to meet the trend, construction public data are already disclosing not only data generated at the construction site but also various data ranging from inspection reports and public construction contracts through multiple portals. However, unlike the excellence of the open performance evaluated by the number of data, it is difficult to evaluate the specific level of disclosure because there is no case of analyzing the quality, ease of use, and possibility of further opening of the public construction data set. On the other hand, performance measurement is already performed using an internationally agreed evaluation method in different fields such as real estate, population, and environment. So it is essential to analyze the current status of public data openings in the construction field and to derive improvement tasks. Therefore, this study conducted a survey of researchers with the highest system utilization targeting representative public data open systems in the construction field, such as E-AIS(세움터) and KISCON. To ensure fairness and increase comparability, the questionnaire was composed using evaluation items on implementing public data conducted annually by the World Wide Web Foundation, an international non-profit organization. With these responses, we investigated the status of public data disclosure and opinions on data quality and derived tasks to improve public data disclosure in construction through the analysis of the results.

• The Journal of Korean Medicine
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• v.44 no.3
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• pp.47-58
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• 2023

Objectives: This study aimed to investigate the epidemiological characteristics of COVID-19 in Chungju City from July to December 2021. Methods: The authors processed and analyzed the epidemiological analysis report written by researcher. The estimated reproduction rate was analyzed using web-based software that calculates time-varying reproduction numbers. The results were analyzed through univariate multiple regression analysis, with a maximum significance level set at 0.05. Results: During the study period, a total of 1,188 patients were identified, with 7.9% of them progressing to a severe status. The maximum reproduction rate recorded was 3.48. Factors associated with the transition to a severe status included the presence of symptoms at the time of diagnosis, lack of vaccination, and belonging to the age group over 40. Conclusion: Based on the findings of this study, it can be strongly supported that the measures implemented in Chungju City, such as social distancing, vaccination, and preemptive diagnostic tests, were appropriate. Furthermore, it demonstrates that Chungju City effectively managed the impact of COVID-19. Korean Medicine Doctors made significant contributions to the epidemiological investigations of COVID-19. To comprehensively manage infectious diseases, it is crucial to provide administrative and legal support and encourage active research to expand the role of Korean Medicine Doctors in this area.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.419-429
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• 2015

We investigate how the regional prevalence of hyperlipidemia is affected by health-related and socioeconomic factors with a special emphasis on geographic variations. We focus on the likelihood of hyperlipidemia as function of various region-specific attributes. We analysis a data set at the level of 249 small administrative districts collected from 2012 Korean Community Health Survey by Korea Centers for Disease Control and Prevention. To estimate, we use several methods including correlation analysis, multiple regression and decision tree model. We find that the average prevalence of hyperlipidemia in 249 small districts is 9.6% and its coefficient of variation is 28.3%. Prevalence of hyperlipidemia in continental and capital regions is higher than in southeast coastal regions. Further findings using decision tree model suggest that variations of hyperlipidemia prevalence between regions is more likely to be associated with rate of employee, level of stress, prevalence of hypertension, angina pectoris, and osteoarthritis in their regions.