• Journal of the Korean GEO-environmental Society
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• v.18 no.12
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• pp.65-75
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• 2017

Flowability and strength with curing time of controlled low-strength material (CLSM) are required differently according to the construction purpose. In this paper, the flowability and strength were estimated from the mixing ratio of CLSM using multiple regression analysis to design the CLSM. The flow values and strength at 12 hrs and 7days were measured in accordance with the mixing ratio of CLSM which consists of 7 different materials, such as CSA expansive agent, ordinary Portland cement, fly ash, sand, silt, water, and accelerator. The multiple regression was performed with the proportions of each material of CLSM as independent variables and the measured properties as dependent variables using SPSS Statistics 23 which is a statistical analysis program. The regression coefficients were estimated from the first to third order equation models for the materials. From the results, the third order model for the flow values and the first order models for 12hrs and 7days strength are the most appropriate models. This study suggests that the mixing ratio required for constructions may be effectively estimated from the regression models about the characteristics of CLSM, before performing experimental tests.

• 한국기계연구소 소보
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• s.11
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• pp.95-101
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• 1984

The MAU-series propellers were designed and tested in japan. This report presents the polynomial coefficients of open water Characteristics for each standard MAU-series propellers, obtained by multiple polynomial regression analysis in terms of pitch-diameter ratio and advance coefficient. The limitation of applicability and the accuracy of the regression polynomial are also discussed.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.375-383
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• 2009

This study examined hydraulic characteristics on diagonal weirs with hydraulic experiment and presented a discharge coefficient equation utilizing multiple regression analysis for various design conditions. This study had a object in designing efficiently diagonal weirs utilizing this equation. Diagonal weirs maintained uniformly upstream water level than rectangular suppressed weirs. Also, as installation degrees of diagonal weirs increased, diagonal weirs increased maintenance effects of a upstream water level. Because of these characteristics, diagonal weirs were suitable to canal system. This study presented discharge coefficient equations for diagonal weirs utilizing simple regression analysis. But, these equations are some restrictions on degrees. Therefore, this study presented an equation to estimate directly discharge coefficients to various degrees utilizing multiple regression analysis. This equation was verified by making use of analyses of $R^2$, the sum of residuals, MAPE. Therefore, this equation is enable to make good use of a design in diagonal weirs.

• The Korean Journal of Emergency Medical Services
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• v.17 no.3
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• pp.169-179
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• 2013

Purpose: The performance rate to perform Cardiopulmonary Resuscitation (CPR) by witness in out-of-hospital Cardiac Arrest (OHCA) is very low in South Korea. To prevent the death caused by OHCA, it is important to encourage the witness to perform CPR actively. The purpose of the study is to investigate the influencing factors to affect bystander CPR rate. Methods: I conducted a questionnaire survey from 25 February to 4 March, 2013, receiving responses from 517 people in Korea. The questionnaire included social demographic factors, history of heart disease, knowledge of CPR, and the reliability of emergency medical service (EMS). A logistic regression analysis was conducted. Results: Among the 517 respondents, 294 (57.4%) had intention of performing CPR. Multiple logistic regression analysis found the following significant predictors of CPR intention: gender (odds ratio [OR] = 0.390), age (OR = 1.024), religion (OR = 0.843), and knowledge of CPR (OR = 4.734). Conclusion: This study indicated that the strongest predictor is knowledge of CPR. Therefore, it would be helpful to teach CPR nationwide to encourage performing CPR. In addition, effect of CPR education in religious facilities is necessary.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.2
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• pp.184-190
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• 2010

Recently, the polishing process using magnetorheological fluids(MR fluids) has been focused as a new ultra-precision polishing technology for micro and optical parts such as aspheric lenses, etc. This method uses MR fluid as a polishing media which contains required micro abrasives. In the MR polishing process, the surface roughness and material removal rate of a workpiece are affected by the process parameters, such as the properties of used nonmagnetic abrasives(particle material, size, aspect ratio and density, etc.), rotating wheel speed, imposed magnetic flux density and feed rate, etc. The objective of this research is to predict MRR according to the polishing conditions based on the multiple regression analysis. Three polishing parameters such as wheel speed, feed rates and current value were optimized. For experimental works, an orthogonal array L27(313) was used based on DOE(Design of Experiments), and ANOVA(Analysis of Variance) was carried out. Finally, it was possible to recognize that the sequence of the factors affecting MRR correspond to feed rate, current and wheel speed, and to determine a combination of optimal polishing conditions.

• Water for future
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• v.24 no.3
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• pp.71-82
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• 1991

Methods of predicting water resources availiability of a river basin can be classified as empirical formula, water budget analysis and regression analysis. The purpose of this study is to develop a method to estimate the monthly runoff required for long-term water resources development project. Using the monthly runoff data series at gaging stations alternative multiple regression models were constructed and evaluated. Monthly runoff volume along with the meteorological and physiographic parameters of 48 gaging stations are used, those of 43 stations to construct the model and the remaining 5 stations to verify the model. Regression models are named to be Model-1, Model-2, Model-3 and Model-4 developing on the way of data processing for the multiple regressions. From the verification, Model-2 is found to be the best-fit model. A comparison of the selected regression model with the Kajiyama's formula is made based on the predicted monthly and annual runoff of the 5 watersheds. The result showed that the present model is fairly resonable and convinient to apply in practice.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.215-224
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• 2021

This article emphasizes the consequences of exploring the relationship between sustainable development practices and non-financial performing factors. Also, it investigates the combined effects of the transformational leadership style on the relationship between sustainable development practices and non-financial performing factors. Using primary data sources, this study reviews the literature on the relationship between the factors of the effectiveness of sustainable development practices of Jordanian contractors and non-financial performance. A total of 290 questionnaires were personally distributed to contractors in the Amman district in Jordan. Only 253 questionnaires were returned and usable for further analysis, which represents a response rate of 87%. Data was collected from October 2020 until April 2020. Hypotheses were tested through multiple regression analysis, and hypotheses for interacting effect were examined through hierarchical multiple regression analysis. Based on the results of the analysis obtained there is a significant effect on the relationship between sustainable development and non-financial performances. It shows that construction companies involved in sustainability practices will able to improve their performance, which contributed significantly toward the overall firm's performance. Whereas, results from hierarchical multiple regressions showed that transformational leadership had no moderation effect on the non-financial performance in such a way that reaches a higher firm performance level.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.453-469
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• 2022

The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.

• Korean Journal of Human Ecology
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• v.11 no.2
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• pp.107-121
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• 2002

The purpose of His research was to investigate the effect of grandchildren's solidarity with their grandparents on their caring attitude for the elderly. The participants were 311 college students in Chollabuk-Do province. Such statistical methods as factor analysis, ANOVA, Duncan's multiple range test, t-Test, pearson's correlation analysis, and multiple regression analysis were performed for this research. The results showed that the solidarity with grandparents was significantly different according to the college grade, birth order, mother's and grandparents' educational levels, economic status of grandparent, relationship with parents, and grandparents' ages. It was also found that there were significant differences in the levels of grandchildren's caring attitude for the elderly according to the college grade, occupational status of mother, relationship with parent, parents' educational levels, and family atmosphere. Finally, multiple regression analysis results indicated that grandchildren's caring attitude for the elderly was significantly influenced by grandchildren's affectional and contact solidarity with grandparents, relationship with parent, and grandparents' economic status.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.217-223
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• 2019

A study in predicting defects of spot welding in real time in automotive field is essential for cost reduction and high quality production. Welding quality is determined by shear strength and the size of the nugget, and results depend on different independent variables. In order to develop the real-time prediction system, multiple regression analyses were conducted and the two dependent variables were obtained with sufficient statistical results with three independent variables, however, the quality prediction by the regression formula could not ensure accuracy. In this study, a multi-layer neural network circuit was constructed. The neural network by 10 dynamic resistance variables was constructed with three hidden layers to obtain execution functions and weighting matrix. In this case, the neural network was established with three independent variables based on regression analysis, as there could be difficulties in real-time control due to too many input variables. As a result, all test data were divided into poor, partial, and modalities. Therefore, a real-time welding quality determination system by three independent variables obtained by multiple regression analysis was completed.