• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.350-353
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• 2001

This study proposes a new method for the transmission system expansion planning using the fuzzy integer programming. It presents stepwise cost characteristics analysis which is a practical condition of an actual systems. A branch and bound method which includes the network flow method and the maximum flow-minimum cut set theorem has been used in order to proceed the stepwise cost characteristics analysis. Uncertainties of the permission of the construction cost and not strict reserve rate and load forecasting of expansion planning have been included and also processed using fuzzy set theory in this study. In order to proceed the latter analysis, the solving procedure is illustrated in detail by branch and bound method which includes the network flow method and maximum flow-minimum cut set theorem. Finally, case studies on 21-bus test system show that the algorithm proposed is efficiently applicable to the practical expansion planning of transmission systems in future.

• Journal of Korean Academy of Nursing
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• v.17 no.3
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• pp.218-226
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• 1987

This descriptive-correlational study was undertaken in order to examine if there were relationships between family support, compliance and life satisfaction in chronic arthritis patients. The sampling method was a non-probability, purposive sampling technique. The participants of this study were 92 volunteer adults. 1) who have been diagnosed as having chronic arthritis and 2) who were at the medical out patient clinic of one university hospital in Seoul between April 27th to May 12th 1987. The instruments used for this study were the Family Support Scale developed by Kang Hyun Sook, a Compilance Scale developed by the researcher and the Life-Satisfaction Index-Z developed by Wood et.al. Analysis of data was done using t-test, ANOVA, Pearson Correlation Coefficient and Stepwise Multiple Regression Analysis. The results of study were as follows; Hypothesis I; “The higher the family support, the higher the compliance” was accepted. (r＝.2604, p＜.01) Hypothesis II; “The higher the compliance, the higher the life satisfaction,” was rejected. (r＝.1663, p＞0.5) Hypothesis III; “The higher the family support, the higher the life satisfaction” was accepted. (r＝.3914, p＜.01) In addition, by using Stepwise Multiple Regression Analysis it was determined that the main influencing factors on the life satisfaction were family support, the number of inflammatory joints, compliance and pain level. These 4 main variables made it possible to explain 30.8% of the variance in life satisfaction. In conclusion, this study revealed that family support is an important factor that can improve compliance and life satisfaction in chronic arthritis patients.

• Food Science and Biotechnology
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• v.16 no.1
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• pp.23-28
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• 2007

A linear correlation was found by stepwise multiple regression analysis between the sensory score of barley bran sauce aroma and the absolute gas chromatogram (GC) data transformed with square root. In spite of highly significant relationship between the quantity of the peak and the sensory score, it is difficult to estimate the aroma quality of barley bran sauce samples on the basis of only one peak. Peak 29 (methyl 9,12,15-octadecatrienoate) contributed most to the aroma of barley bran sauce. This was followed by 27 (methyl 9,12-octadecadienoate), 28 (ethyl 9,12-octadecadienoate), 12 (phenyl acetaldehyde), and 9 (methyl furfural) in terms of absolute value. When it was calculated using absolute value transformed by square root, peak 28 (ethyl 9,12-octadecadienoate) made the highest contribution to the aroma of barley bran sauce of among the peaks. It was followed by 31 (9,12-octadecadienoic acid), 27 (methyl 9,12-octadecadienoate), 12 (phenyl acetaldehyde), and 29 (methyl 9,12,15-octadecatrienoate).

• ETRI Journal
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• v.40 no.6
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• pp.802-812
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• 2018

Disease discrimination using an electronic nose is achieved by measuring the presence of a specific gas contained in the exhaled breath of patients. Many studies have reported the presence of acetone in the breath of diabetic patients. These studies suggest that acetone can be used as a biomarker of diabetes, enabling diagnoses to be made by measuring acetone levels in exhaled breath. In this study, we perform a chemical sensor array optimization to improve the performance of an electronic nose system using Wilks' lambda, sensor selection based on a principal component (B4), and a stepwise elimination (SE) technique to detect the presence of acetone gas in human breath. By applying five different temperatures to four sensors fabricated from different synthetic materials, a total of 20 sensing combinations are created, and three sensing combinations are selected for the sensor array using optimization techniques. The measurements and analyses of the exhaled breath using the electronic nose system together with the optimized sensor array show that diabetic patients and control groups can be easily differentiated. The results are confirmed using principal component analysis (PCA).

• The korean journal of orthodontics
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• v.51 no.6
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• pp.397-406
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• 2021

Objective: The purpose of this study was to evaluate the effects of self-ligating brackets (SBs) and other factors that influence orthodontic treatment outcomes. Methods: This two-armed cohort study included consecutively treated patients in a private practice. The patients were asked to choose between SBs and conventional brackets (CBs); if any patient did not have a preference, he or she was randomly allocated to the CB or SB group. All patients were treated using an identical archwire sequence. Evaluated parameters were as follows: treatment duration, number of bracket failures, poor oral hygiene, poor elastic wear, extraction, use of orthodontic mini-implants (OMI), OMI failure, American Board of Orthodontics (ABO) Discrepancy Index (DI), arch length discrepancy, and ABO Cast-Radiograph Evaluation (CRE) score. Stepwise regression analysis was performed to generate the equation for prediction of the CRE. Results: The final sample comprised 134 patients with an average age of 22.73 years. The average DI, CRE, and treatment duration were 21.81, 14.25, and 28.63 months, respectively. Analysis of covariance showed a significant difference in CRE between the CB and SB groups after adjusting for the effects of confounding variables. Stepwise regression analysis using four variables, namely extraction, SB use, poor elastic wear, and additional appliance use, could explain only 25.2% of the variance in the CRE. Conclusions: Although the CRE was significantly better for CBs than for SBs, the clinical significance of this result seems to be limited. Extraction, SB use, poor elastic wear, and additional appliance use may have significant effects on treatment outcomes.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.881-889
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• 2021

The purpose of this study is to descriptively reveal the demographic and business profile and personal-entrepreneurial characteristics in Manado, the capital of North Sulawesi, and secondly to associate these profiles and characters to their business progress. A sample size of 21 respondents was drawn - selected from those who warmly welcomed the interviewers for an open-ended structured questionnaire. SPSS 24 has been employed to descriptively reveal the sample distribution according to demographic factors and business entities and to determine the dominant factors affecting the progress of the business by testing the hypothesis on the association of variables under study using specified statistical analytical tools, such as regression analysis, especially stepwise regression formula, between specified dependent variables and independent variables and /or between all variables. The stepwise regression analysis has enabled the researcher to determine which variables are the most important reflecting the personal characteristics theorized as "locus of control": self-efficacy, needs for achievement, personal traits, and barriers to business progress The analysis reveals that the progress of business does have an association and is dependent on the source of capital and education, needs for achievement and locus of control.

• Child Health Nursing Research
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• v.28 no.1
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• pp.82-90
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• 2022

Purpose: The aim of this study was to examine the relationships among parenting role sharing, parenting stress, happiness, and parenting behavior of mothers with 6-year-old children. Methods: This study used data from the seventh Panel Study of Korean Children, which began collecting longitudinal data on a sample of newborn households nationwide in 2008 and will continue yearly until 2027. The participants were 1,560 mothers of children aged 6 years. We conducted statistical analyses using descriptive statistics, the t-test, analysis of variance, Pearson correlation coefficients, and stepwise multiple regression. Results: The mean age of the mothers was 36.8±3.7 years. The mothers' perceived parenting role sharing (r=.07, p=.007), parenting stress (r=-.54, p<.001), and happiness (r=.38, p<.001) were significantly correlated with warm parenting behavior. Stepwise multiple regression analysis revealed that parenting stress (β=-.47, p<.001), happiness (β=.15, p<.001), and parenting role sharing (β=.11, p<.001) were significant predictors for warm parenting behavior by mothers. Conclusion: It is essential to reduce mothers' stress and increase their positive emotions (happiness). Fathers should actively share parenting roles in raising children to enhance mothers' warm parenting behavior.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.39-50
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• 2006

The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.

• Journal of Korean Public Health Nursing
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• v.14 no.1
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• pp.161-171
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• 2000

The purpose of this study was to investigate the factors influencing health promoting behavior and quality of life in the nursing students, to provide the basic data for health promoting intervention in order to improve quality of life. The subjects of this study were 199 nursing students, living in M city, during the period from May 18 to 25, 1999. The instruments for this study were the health promoting behavior scale developed by Walker et al.(1987), the quality of life scale by Ro(1988), the self efficacy scale by Sherer(1982), the health locus of control scale by Wallston et al. (1978) and the self esteem scale by Rogenberg(1965). The data were analyzed using descriptive statistics, Pearson correlation coefficients, stepwise multiple regression, t-test, ANOVA. The results of this study are as follows; 1. The health promoting behavior showed significant positive correlation with self efficacy, self esteem, internal health locus of control and quality of life. 2. The quality of life showed significant positive correlation with self efficacy, self esteem, internal health locus of control. 3. Stepwise multiple regression analysis revealed that the most powerful predictor of health promoting behavior was self efficacy. A combination of self efficacy, self esteem, health locus of control and quality of life accounted for $41\%$ of the variance in health promoting behavior. 4. Stepwise multiple regression analysis revealed that the most powerful predictor of quality of life was self esteem. A combination of self esteem, self efficacy and health promoting behavior accounted for $40\%$ of the variance in quality of life. Based on the above findings, it is suggested to develop nursing intervention to improve Self Efficacy, Self Esteem of nursing students enhance health promoting lifestyle.