• Journal of Digital Convergence
• /
• v.14 no.1
• /
• pp.291-303
• /
• 2016

The purpose of this study has been done to identify the influencing factors on rehabilitation motive of stroke patients. A sample of 138 stroke patients in Long-term Care and rehabilitation hospitals completed questionnaires through face - to - face interviews. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and Stepwise multiple regression. Rehabilitation motive of stroke pacients was correlated with empowerment (r=.467, p<.001), but not with perceived stress(r=.-.186, p=.029). In a multiple regression, empowerment (${\beta}=.432$, p<.001) and primary care-giver (${\beta}=.175$, p=.023) were associated with rehabilitation motive. These factors attributed to 24% of the total variance in rehabilitation motive. Therefore, the study finding suggests that these significant factors should be considered when developing and implementing convergent care strategies for stroke patients in order to promote their rehabilitation motive.

• Journal of Digital Convergence
• /
• v.18 no.9
• /
• pp.229-237
• /
• 2020

The study was done to identify relations among moral sensitivity, self-leadership, fatigue and compliance with standard precautions and to identify the influencing factors on compliance with standard precautions for intensive care nurses. Data were collected from 153 intensive care nurses in March 2019 and were analyzed using Descriptive statistics, Pearson correlation coefficients, and Stepwise multiple regression with SPSS/WIN 24.0 version. The compliance with standard precautions has positive correlation with their self-leadership (r=.17, p=.042). The self-leadership (β=.17, p=.042) was a significant predictor of the compliance with standard precautions. It was statistically significant (R²=.03, F=4.21, p=.042). Based on the findings of this study, each institution needs to make efforts to strengthen the capacity of nurses for self-leadership.

• Journal of Digital Convergence
• /
• v.16 no.2
• /
• pp.243-250
• /
• 2018

The purpose of this study was to examine relationships among empowerment, awareness and performance on standard precautions and identify the factors that affect performance of standard precaution in the health care workers. The data were collected from 200 health care workers working in the general hospital located Y city. The data were analyzed by descriptive statistics, t-test, ANOVA, Scheffe, Pearson's correlation coefficient, and stepwise multiple regression. The result of the stepwise multiple regression indicates the awareness predict 49.0% (F=191.98, P<.001) in the performance of standard precaution. Therefore, it is necessary to develop awareness of the standard precaution strategy program for improving the performance of standard precautions in health care workers.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.481-489
• /
• 2016

This study examined the relationships among stress, childhood traumatic experience, ego-resilience, and life satisfaction of university students to explore the moderating effects of ego-resilience on those variables. The survey participants were 459 university students in Gyeonggi province. The collected data were analyzed using frequency, Pearson correlation coefficient, stepwise multiple regression, and moderated multiple regression by SPSS. The results were as follows. Stress, childhood traumatic experience and ego resilience had correlations with the life satisfaction. Ego resilience and stress were significant effective variables on the life satisfaction. Moderated multiple regression analysis also showed that a positive future orientation, which is a sub factor of ego-resilience, influenced the stress level. Based on these findings, it is important to lower the stress levels to increase the students' life satisfaction level. To do so, a strategy to enhance the positive future orientation is recommended.

• Journal of Wetlands Research
• /
• v.18 no.3
• /
• pp.301-312
• /
• 2016

This study has performed comparative analysis on characteristics of contaminated 35 tributaries on seasonal variation/point discharge load/pollutant distribution of water quality factors(8) in order to understand the effect of the watershed in Nakdong River Basin. As a results, the water quality of $BOD_5$(Biochemical Oxygen Demand), Chl-a(Chlorophyll a) and Fecal E. Coli shows II grade at tributaries of more than 50% without COD(Chemical Oxygen Demand), TP(Total Phosphate), TOC(Total Oxygen Carbon) and TN(Total Nitrogen) factors. The specific discharge(Q) were occupied about 54.4% (19 sites) as $0.05m^3/sec/km^2$ value. Among these results, the contaminant level of Dalseocheon, Hyeonjicheon, Seokkyocheon 1, Uriyeongcheon and Dasancheon was also high, which has to consider a discharged pollutant load(kg/day). The 35 major tributaries of Nakdong River were included in 7 mid-watershed, such as Nakdong Waegwan, Geumho River, Nakdong Goryung, Nakdong Changnyung, Nam River, Nakdong Milyang, Nakdong River Hagueon. Especially, the discharged pollutant load of Nam River and Geumho River also was high according to the amount of discharge such as Kachang dam, Gongsan dam and Nam river dam. Seasonal difference of the water quality factors such as $BOD_5$, TN, SS and Q was observed largely, on the other hand the TP and Chl-a was not. This is guessed due to the precipitation effect of site, biological and physicochemical degradation properties of pollutant and etc. The co-relationship between the seasonal difference and water quality factors was observed using a Pearson correlation coefficients. Besides, the Multiple Regression analysis using a Stepwise Regression method was conducted to understand the effect between seasonal difference and water quality factors/regression equations. As a result, the Multiple Regression analysis was adapted in the spring, summer and autumn without the winter, which was observed high at spring, summer and autumn in the order COD/TP, Chl-a/TOC, TOC/COD/$BOD_5$ water quality factors, respectively.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.4
• /
• pp.969-977
• /
• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model

• The Korean Journal of Applied Statistics
• /
• v.30 no.1
• /
• pp.41-55
• /
• 2017

This study predicts the average scores of top 150 PGA golf players on 132 PGA Tour tournaments (2013-2015) using data mining techniques and statistical analysis. This study also aims to predict the Top 10 and Top 25 best players in 4 different playoffs. Linear and nonlinear regression methods were used to predict average scores. Stepwise regression, all best subset, LASSO, ridge regression and principal component regression were used for the linear regression method. Tree, bagging, gradient boosting, neural network, random forests and KNN were used for nonlinear regression method. We found that the average score increases as fairway firmness or green height or average maximum wind speed increases. We also found that the average score decreases as the number of one-putts or scrambling variable or longest driving distance increases. All 11 different models have low prediction error when predicting the average scores of PGA Tournaments in 2015 which is not included in the training set. However, the performances of Bagging and Random Forest models are the best among all models and these two models have the highest prediction accuracy when predicting the Top 10 and Top 25 best players in 4 different playoffs.

• Journal of Digital Convergence
• /
• v.19 no.9
• /
• pp.393-400
• /
• 2021

Purpose: The purpose of this study was to provide basic data for intervention development programs that could improve the attachment of first-time mothers. Methods: Data were collected from 148 Primipara Women in S city from April 1 to May 31, 2021. Data were processed using descriptive statistics, t-test, ANOVA, correlation analysis, and stepwise regression analysis. Results: As a result of the study, mother-to-infant attachment was negatively correlated with maternal fatigue(r=-.65, p<.001) and anxiety level(r=-.62, p<.001). Maternal fatigue(β=-.52), anxiety level(β=-.48), Child care assistant(β=.10) affect the attachment of first-time mothers. Mother-to-infant attachment the total explanation power was 64.3%(F=89.19, p<.001). It is necessary to develop programs that reduce maternal fatigue and anxiety level based on factors affecting the mother-to-infant attachment of first-time mothers and improve the ability of the mother-to-infant attachment.

• The Korean Journal of Franchise Management
• /
• v.15 no.1
• /
• pp.61-78
• /
• 2024

Purpose: Dining out at restaurants was limited during the COVID-19 period. In order to confirm the impact of COVID-19 on the chicken market, this study selected three chicken companies, Kyochon, BBQ, and BHC, and conducted financial statement analysis and regression analysis. Research design and methodology: Each company's financial statements were divided into before and after COVID-19, and the rate of change and financial ratio for each item were calculated to see if there were any significant changes, and the impact of COVID-19 on each company's sales was identified through regression analysis. Result: As a result of the study, the increase in sales and assets of each company continued, and the influence of COVID-19 could be confirmed through regression analysis. It can be inferred that COVID-19 indeed affected the expansion of the chicken market. Conclusion: Therefore, it was confirmed through this study that COVID-19 had a significant effect on the growth of the chicken market. While individual chicken small business owners are grappling with declining sales per outlet, the decline of commercial areas, and a surge in closures, the broader chicken franchise industry is witnessing a surge in demand and business expansion prompted by the pandemic.

• Journal of Digital Convergence
• /
• v.10 no.1
• /
• pp.385-389
• /
• 2012

This study was performed to determine the effect of patients with colon polypectomy on health behavior practices. Data were surveyed using interview and questionnaires by 112 patients with colon polypectomy in a general hospital who were located in Seoul from December 6, 2010 to January 31, 2011. Data were evaluated with t-test, ANOVA, Pearson correlation coefficient, and Stepwise multiple regression. The results were as follows: First, the higher control of life habit was, the more positive attitude(r=.350, p<.01) and the less inconvenience was significant correlation(r=-.263, p<.05). Secondly, in the stepwise multiple regression analysis, the most important factors influencing health behavior practices were control of life habit(${\beta}$=.392, p=.000), and then inconvenience of life(${\beta}$=-.265, p=.007), weight gain(${\beta}$=-.248, p=.024). In conclusion, positive attitude and control of life habit are necessary to improve the health behavior of patient with colon polypectomy.