• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.391-400
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• 2019

This study was conducted to investigate the connections between life stress and smartphone addiction of nursing college students. The subjects included nursing college students in some areas. Data were collected in November and December, 2018 from a total of 240 subjects. Collected data were subjected to frequency, percentage, t-test, ${\chi}^2$-test, and ANOVA analyses to identify differences in smartphone addiction level and stress characteristics according to general characteristics. Correlations between smartphone addiction and stress characteristics were investigated by Pearson's correlation analysis, and factors influencing smartphone addiction were examined by hierarchical multiple regression analysis. The findings showed that independent variables had explanatory powers of 14.8% and 32.7% in Models 1 and 2, respectively. The study examined differences in smartphone addiction level according to the general characteristics of the subjects and found that female college students had a higher level of smartphone addiction than their male counterparts. The smartphone addiction level was high in those who were not satisfied with college life, used a smartphone for five hours or more a day, and spent many hours on SNS. Evaluation of differences in stress characteristics according to their general characteristics revealed female college students scored higher for stress characteristics. The means of the stress characteristics were also high for those who were not satisfied with college life, used a smartphone for many hours, and had a high risk of smartphone addiction. In conclusion, female gender, hours of smartphone usage and SNS, academic stress, and value stress were important factors influencing the smartphone addiction of nursing college students. These findings indicate the need to reinforce a stress management program for nursing college students and thus provide them with multifaceted support for stress management.

• Journal of Embryo Transfer
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• v.26 no.4
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• pp.229-235
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• 2011

Sloan-Kettering virus gene product of a cellular protooncogene c-Ski is an unique nuclear pro-oncoprotein and belongs to the Ski/Sno proto-oncogene family. Ski plays multiple roles in a variety of cell types, it can induce both oncogenic transformation and terminal muscle differentiation when expressed at high levels. Ski protein is implicated in proliferation/differentiation in a variety of cells. The alternative fate of granulosa cells other than apoptosis is to differentiate to luteal cells, however, it is unknown whether Ski is expressed and has a role in granulosa cells undergoing luteinization. Thus, the aim of this study was, by means of immunohistochemical methods, to locate Ski protein in the rat ovaries during ovulation and corpora lutea (CL) formation to predict the possible involvement of Ski in luteinization. In addition, we performed to examine whether the initiation of luteinization with luteinizing hormone (LH) directly regulates expression of Ski in the luteinized granulosa and luteal cells after ovulation by in vivo models. In order to examine the expression pattern of Ski protein along with the progress of luteinization, follicular growth was induced by administration of equine chorionic gonadtropin to immature female rat, and luteinization was induced by human chorionic gonadtropin treatment to mimic luteinizing hormone (LH) surge. While no Ski-positive granulosa cells were present in preovulatory follicle, Ski protein expression was induced in response to LH surge, and was maintained after the formation of corpus luteum (CL). These results indicate that Ski is profoundly expressed in the luteinized granulosa cells and luteal cells of CL during luteinization, and suggest that Ski may play a role in luteinization of granulosa cells.

• Korean Journal of Occupational Health Nursing
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• v.27 no.4
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• pp.203-214
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• 2018

Purpose: The purpose of this study was to identify factors influencing the quality of working life of cancer survivors (QWL-CS) after return to the workplace. Methods: Data were collected from 154 cancer survivors from May 16 to June 23, 2018. Participants were selected as candidates from two different hospitals in the metropolitan area and snowball sampling was used in parallel. The data were analyzed by SPSS 21.0 using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple linear regression. Results: Mean score of QWL-CS was $4.39{\pm}0.59$. QWL-CS was negatively correlated with fatigue, and job stress: however, it was positively correlated with workplace spirituality. The factor that had the greatest influence on the QWL-CS was job stress (${\beta}=-.36$, p<.001), followed by fatigue (${\beta}=-.35$, p<.001), workplace spirituality (${\beta}=.35$, p<.001), number of currently cancer treatment (${\beta}=-.15$, p=.009), and number of children (${\beta}=.12$, p=.031). The explanatory power of models was 54%. Conclusion: Effective and practical intervention programs for increasing the quality of working life are required to be provided to cancer survivors after return to the workplace in accordance with job stress, fatigue, workplace spirituality, and general characteristics of cancer survivors such as number of currently cancer treatments and number of children.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.67-72
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• 2020

The fifth generation (5G) mobile communication has an impact on the human life over the whole world, nowadays, through the artificial intelligence (AI) and the internet of things (IoT). The low latency of the 5G new radio (NR) access is implemented by the state-of-the art technologies, such as non-orthogonal multiple access (NOMA). This paper investigates a practical issue that in NOMA, for the practical channel models, such as fading channel environments, the successive interference cancellation (SIC) should be performed on the stronger channel users with low power allocation. Only if the SIC is performed on the user with the stronger channel gain, NOMA performs better than orthogonal multiple access (OMA). Otherwise, NOMA performs worse than OMA. Such the superiority requirement can be easily implemented for the channel being static or slow varying, compared to the block interval time. However, most mobile channels experience fading. And symbol by symbol channel estimations and in turn each symbol time, selections of the SIC-performing user look infeasible in the practical environments. Then practically the block of symbols uses the single channel estimation, which is obtained by the training sequence at the head of the block. In this case, not all the symbol times the SIC is performed on the stronger channel user. Sometimes, we do perform the SIC on the weaker channel user; such cases, NOMA performs worse than OMA. Thus, we can say that by what percent NOMA is better than OMA. This paper calculates analytically the percentage by which NOMA performs better than OMA in the practical mobile communication systems. We show analytically that the percentage for NOMA being better than OMA is only the function of the ratio of the stronger channel gain variance to weaker. In result, not always, but almost time, NOMA could perform better than OMA.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.673-679
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• 2017

In this paper a method for estimating the 'service life' and 'residual life' of a water pipe based on the Water Pipe Network Performance Evaluation(WPNPE) results of Water Supply Technical Diagnosis was developed for efficient maintenance of water pipes. The residual life of a pipe was defined as the difference between the service life and elapsed time since installation. The service life was defined as the time when a pipe reaches the reference score for determining deteriorated pipes that was used in the WPNPE. The pipe evaluation criteria and deterioration scores used in the WPNPE for the case study area were considered as independent variables in the multiple regression model for estimating the service life and residual life of the pipes in the area. To estimate the service life for the pipes the reference scores for determining deteriorated pipes were used as the values of the variables that represent the deterioration scores in the constructed regression models. Subsequently, the statistics of the service life and residual life of the pipes in the case study area were presented and analyzed in comparison with the service life defined by the Local Public Enterprizes Act.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1342-1349
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• 2013

This study was performed to investigate the factors which impact on the health-related quality of life of young-old(65-69 yr), old-old(70-79 yr), and oldest-old(80 yr or above) women in vulnerable elderly received home care service from public health centers in B city. The data were collected from 383 elderly women using structured questionnaires from September to November, 2010. Multiple regression with the SPSS WIN 18.0 program were used to analyze the data. There were statistically significant differences among young-old, old-old, and oldest-old women regarding the health-related quality of life, life satisfaction, cognitive function, frail condition. The models including life satisfaction, frail condition, cognitive function, perceived health status, number of chronic diseases were explained variance of the health-related quality of life elderly women differently like 42.8% of young-old, 28.9% of old-old, and 31.5% of oldest-old. Finally, frail condition and life satisfaction were predictors in explaining the level of health-related quality of life among vulnerable old women regardless of age. Based on the findings of the study, health promotion programs should be developed to improve health-related quality of life of vulnerable aged women according to age differences.

• Journal of Korean Society of Rural Planning
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• v.16 no.2
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• pp.47-55
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• 2010

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

• Safety and Health at Work
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• v.2 no.2
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• pp.169-175
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• 2011

Objectives: The questionnaire of occupational stress index (OSI) has been popular in the workplace, and it has been tailored for bus drivers in Taiwan. Nevertheless, its outcomes for participants are based on self-evaluations, thus validation by their physiological stress biomarker is warranted and this is the main goal of this study. Methods: A cross-sectional study of sixty-three city bus drivers and fifty-four supporting staffs for comparison was conducted. Questionnaire surveys, 24-hour urine cortisol testing, and blood draws for dehydroepiandrosterone-sulfate (DHEA-S) testing were performed. The measured concentrations of these biological measures were logarithmically transformed before the statistical analysis where various scores of stressor factors, moderators, and stress effects of each OSI domain were analyzed by applying multiple linear regression models. Results: For drivers, the elevated 24-hour urine cortisol level was associated with a worker's relationship with their supervisor and any life change events in the most recent 3 months. The DHEA-S level was higher in drivers of younger age as well as drivers with more concerns relating to their salary and bonuses. Non-drivers showed no association between any stressor or satisfaction and urine cortisol and blood DHEA-S levels. Conclusion: Measurements of biomarkers may offer additional stress evaluations with OSI questionnaires for bus drivers. Increased DHEA-S and cortisol levels may result from stressors like income security. Prevention efforts towards occupational stress and life events and health promotional efforts for aged driver were important anti-stress remedies.