• Korean Journal of Human Ecology
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• v.18 no.2
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• pp.363-379
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• 2009

The purpose of this study is to provide a meaningful thought to professionals and administrators of Korea working for Consumer General Education development at their Universities. Also, tips for organizing and meaning Consumer General Education Curriculum effectively are provided. Finally, the study suggests essential elements to improve qualities of Consumer General Education in Korea Universities. This study's method are content analysis through web site and survey. The subjects of this survey were 257 students. The data were collected by questionnaire developed by researcher and analyzed by frequencies, correlation Analysis, One Way Anova, Duncan Test, Factor Analysis, Multiple Regression Analysis. The major findings were as follows: University students's satisfaction level about General Education was low and the needs level about Consumer General Education was high. And the education service quality showed factors to be administrative service element, professor service element, classroom environment element, communication element. And Multiple Regression Analysis on each of the education service quality factors had been significant effects for find out the differences in the degree of satisfaction.

• Journal of Korean Biological Nursing Science
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• v.24 no.4
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• pp.209-218
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• 2022

Purpose: This study aimed to investigate the relationships between the characteristics of nurses' work schedules, health outcomes, and work-life balance. Methods: This was a secondary data analysis that included 422 nurses in Korean hospitals. Descriptive analysis, independent sample t-test, one-way ANOVA, Pearson correlation analysis, and multiple linear regression analysis were used to identify the associated factors. Results: Multiple linear regression analysis showed that work-life balance was lower when atypical work was performed (β=-.14, p=.010). Nurses who did not work overtime showed a higher level of work-life balance than those who worked overtime infrequently (β=-.11, p=.002) or frequently (β=-.28, p<.001). The work-life balance level increased when nurses had better subjective health status (β=.16, p<.001) or higher sleep quality (β=.29, p<.001). It was verified that the work-life balance level was higher for single-person households than for households with two (β=-.18, p=.003), three to four (β=-.16, p=.022), or five or more (β=-.21, p<.001) persons. Conclusion: This study suggests that government and hospital organizations should provide high-quality care and consideration to nurses who do atypical or overtime work as well as their subjective health status and sleep quality. Further research should focus on the development of a policy that improves the work-life balance of nurses, especially for those who work during atypical hours.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.121-133
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• 2021

This study set up the estimates of leakage management efficiency evaluation and leakage management goal that could be used in local water distribution networks efficiency business and modernization business. The data were analyzed using data envelopment analysis and multiple regression analysis. To this end, with leakage management input indices concerning leakage reduction activities (e.g., aged pipe replacement, water meter replacement, leakage restoration, and leakage detection) and leakage management calculation indices (e.g., the increase of revenue water ratio and the reduction of leakage ratio), the data on 22 K-water consignment local water supply systems were analyzed for the years from 2004 through 2018. Using the results of efficiency analysis by data envelopment analysis, the other DMUs (Decision Making Unit) benchmarked the DMU with the highest efficiency to maximize the leakage management efficiency for all DMUs. Through this, leakage management goal estimates were drawn with the input indices of four leakage reduction activities and calculation indices of the increase of revenue water ratio and the reduction of leakage ratio by multiple regression analysis for each group based on the revenue water ratio and leakage ratio. The correlation coefficients of the leakage management goal estimate for the criteria for the revenue water ratio amounted to 0.553 and 0.771. The correlation coefficients of the leakage management goal estimate for the criteria for leakage ratio were 0.397 and 0.865. Accordingly, we estimated the quantity and priority of four leakage reduction activities for the target leakage ratio and revenue water ratio.

• Journal of Bio-Environment Control
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• v.17 no.2
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• pp.124-131
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• 2008

To investigate main air temperature factors correlated to difference of fruit characteristics according to cultivating areas, fruit and air temperature characteristics of eight cultivating areas of 'Fuyu' persimmon were analyzed by principle components and multiple regression analysis. The first principal components extracted from 16 air temperature factors was annual mean temperature, mean temperature during October, annual mean minimum extreme temperature, mean temperature during growing period, and so forth. The second principal components was mean temperature during May and June and so forth. And cumulative contribution was 91.4%. The five of eight cultivating area had clearly the difference of main factors or the correlated direction among cultivating areas. In multiple regression analysis between the extracted main factors and fruit characteristics, fruit hight were highly correlated with mean temperature during growing period ($X_8$) and cumulative temperature ($X_6$), and the regression equation was $Y=150.55-5.375X_8+ 0.014X_6(r^2=0.843)$. Also this regression equation was affected by mean minimum temperature during growing period, cumulative temperature, and mean temperature during August. Fruit diameter was negatively correlated with mean temperature during growing period, flesh browning rate and Hunter a value of peel color were positively correlated with mean minimum temperature during growing period and annual minimum air temperature, respectively.

• Journal of Korean Society of Rural Planning
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• v.15 no.3
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• pp.23-32
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• 2009

The purpose of this research was to evaluate rural housing environment through evaluation of the two parties, public officials, the interest group and residents, the beneficiaries surveying general understanding and measuring difference in understanding between public officials and residents. Through the difference in understanding, this study was to propose effective promotion method and desirable direction of rural housing environment. For progress hereafter, by seeking active involvement of residents, this study proposed possible renewal plan of residential environment. Process of this study was first, research documents to examine several rural housing environment related promotions, and several analysis techniques like principal component analysis, multiple regression analysis used to understand different ideas Opinion of Public Officials and Inhabitants. Then take surveys of residents living in renewal zone, and surveys of public officials of borough, which already performed renewal projects to evaluate comprehensively as either residents' or administrators' view.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.5
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• pp.314-326
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• 2016

The purpose of variable selection techniques is to select a subset of relevant variables for a particular learning algorithm in order to improve the accuracy of prediction model and improve the efficiency of the model. We conduct an empirical analysis to evaluate and compare seven well-known variable selection techniques for multiple linear regression model, which is one of the most commonly used regression model in practice. The variable selection techniques we apply are forward selection, backward elimination, stepwise selection, genetic algorithm (GA), ridge regression, lasso (Least Absolute Shrinkage and Selection Operator) and elastic net. Based on the experiment with 49 regression data sets, it is found that GA resulted in the lowest error rates while lasso most significantly reduces the number of variables. In terms of computational efficiency, forward/backward elimination and lasso requires less time than the other techniques.

• IE interfaces
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• v.19 no.4
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• pp.291-299
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. The input variables of IDEA models were selected by stepwise multiple regression analysis. With the regression model, we could choose the number of soldiers, officers, and ammunition warehouses as input variables that have significant effects on the output performance. Then, we applied the IDEA-BCC model with the concept of potential efficiency. The results of the model indicate that 8 out of 16 ammunition companies are efficient, 7 are inefficient, and 1 is potentially efficient. We could also identify the possible input excesses and output shortfalls to reach the efficient frontier using the IDEA-Additive model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1707-1714
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• 2006

In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

• Korean Journal of Family Social Work
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• no.55
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• pp.31-58
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• 2017

This study aims to explore the longitudinal reciprocal relationship between family conflict and depression level of household head. Using the Korean Welfare Panel study (KOWEPS) of 2006-2009, the study applied multiple regression analysis and autoregressive cross-lagged model to test the hypothesis. Results of multiple regression analysis indicate that single direction of the impact of family conflict on a head of household's levels of depression and the vise versa were statistically significant. That is, higher level of family conflict in 2006 caused an increased levels of depression of household head in 2009, controlling gender, age and depression level in 2006. Also, the higher level of depression of household head in 2006 increased the level of family conflict in 2009 fixed with same control variables. The autoregressive and cross-lagged coefficients of family conflict and a head of household's levels of depression were statistically significant during the 4 years. The findings support the family system theory, indicating that there are reciprocal causal relationships between the whole family conflict and individual depression level. The strategies of social welfare practice and policy should thus aim to decrease individual's levels of depression and improve positive family function simultaneously to break the vicious circle.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.229-239
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• 2015

In light of the significant increase in the quantities of goods transported and the development of the shipping industry, the frequency of usage of port structures has increased; yet, the government's budget for the shipping & port of SOC has been reduced. Port structures require systematically effective maintenance and management trends that address their growing frequency of usage. In order to construct a productive maintenance system, it is essential to develop deterioration models of port structures that consider various characteristics, such as location, type, use, constructed level, and state of maintenance. Processes for developing such deterioration models include examining factors that cause the structures to deteriorate, collecting data on deteriorating structures, and deciding methods of estimation. The techniques used for developing the deterioration models are multiple regression analysis and Markov chain theory. Multiple regression analysis can reflect changes over time and Markov chain theory can apply status changes based on a probabilistic method. Along with these processes, the deterioration models of open-type and gravity-type wharfs were suggested.