• Korean Journal of Exercise Nutrition
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• v.25 no.1
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• pp.35-41
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• 2021

[Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R²) and 85.9% (adjusted R²), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R²) and 82.6% (adjusted R²), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R²) and 91.0% (adjusted R²), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.85-96
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• 2006

This study was conducted to suggest a method to determine weighting values of each parameter of the RMR system considered with geologic characteristics of a study area. This study reviewed the weighting values of the RMR system for the Cretaceous sedimentary rocks distributed in Ulsan area. Based on the data of field survey at the study area, a multiple regression analysis was used to set up an optimal weighting values of the RMR parameters. For the multiple regression analysis, each parameter of the RMR and the slope gradient were regarded as the independent variable and the dependent variable, respectively. The analysis result suggested a modified weighting values of the RMR parameters as follows; 30 for the intact strength of rock; 18 for RQD; 8 for spacing of discontinuities; 32 for the condition of discontinuities; and 12 for ground water.

• The Journal of Pediatrics of Korean Medicine
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• v.25 no.3
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• pp.57-69
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• 2011

Objectives: Purpose of this study is to analyze and to estimate which and how much genetic and environmental factors have affected on growth. Also, a method of final height prediction can be developed from this study results. Methods: Correlation analysis and categorical regression analysis were conducted between genetic and environmental factors correlated with the final adult height, through survey from 171 male. Results: Mid parental height, neonatal body weight, intake frequency of beef, chicken, milk, fruits and coffee, sleep quantity and quality during the elementary school and sleep quantity during the middle school have affected on the final adult height. And a regression equation with 0.494 for coefficient of determination was obtained. Conclusions: Mid-parental-height has the most affected on the final adult height. Among environmental factors, food and sleep have significantly affected, but exercise doesn't. Among foods, meal, beef, and milk intake have remarkably affected on the final height, and chicken and fruit also have affected in some degree, but coffee has affected badly. Among sleep habits, sleep quantity during the elementary school has the most affected, sleep quality during the elementary school and sleep quantity during the middle school also have affected in some degree on final height. The younger the age is, the more sleep have affected and sleep quantity have more affected than sleep quality. Neonatal weight also has remarkably affected on the final height. Through this analysis, the final adult height can be predicted using regression equation which covers 49.4% of genetic and environmental factors.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.120-126
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• 1999

;The consicErations for reminder life of transmission line is gradually higher. It is requisite for investigation of ACSR's life to test tensile load of ACSR as a fundamental data. It is vary important to analysis correlations between results of tensile load testing and elasped years. Estimation of ACSR's life can be obtained by statistics processing using mechanical experirrental results. It is a general method to use regression analysis as a statistics processing technique. In this paper, we did experiment on tensile strength of ACSR by using a new and old ACSR as sample experirrental materials. The limit of life estimation is decided by basic line using twenty percentage reduction of rate tensile strength. This basic line is like to results of Canada Ontario Hydro-research. There are $95[\textrm{mm}^2]$, $97[\textrm{mm}^2]$, $120[\textrm{mm}^2]$, $240[\textrm{mm}^2]$ ACSRs which are experimented on this study. 1be life estimation of these ACSR is presented by table 1 to be obtained through the linear regression and nonlinear regression analysis. SPSS and statistics toolbox of matlab is used for analysis.lysis.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1075-1083
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• 2009

The scientific research method went through construction of hypothesis and collection of data by experiment or observation and abstracting the hypothesis based on the experience which uses the data. The statistical methodology plays an important role in this process. The method which acquires a data becomes an initial process of abstraction and a survey research using structured questionnaires is a basic tool. After the data is acquired, the high-class statistical techniques such as the regression analysis and the linear structural equation model are used to abstract a hypothesis. By the way, from time to time the concepts which have become abstractive do not help us to understand an actual phenomena, rather it is need to extract some knowledge from questions themselves. In this article, we review the well known statistical methods providing the ways of finding core questions which possibly answer a researcher wants to know. We deal with course evaluation data as an example and try to set up the strategy for improving course evaluation.

• Transactions of Materials Processing
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• v.26 no.5
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• pp.271-276
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• 2017

A tee is the most common pipefitting used to combine or divide fluid flow. Tees can connect pipes of different diameters or change the direction of a pipe run. To manufacture tee type of stainless steel pipe, combinations of punch piercing and burr forming have been widely used in the industry. However, such method is considerably time consuming with regard to performing empirical work necessary to attain process conditions to prevent upper end tearing of the tee product and meet target tee height. Numerous experiments have shown that the piercing profile is the main cause of defects mentioned above. Furthermore, the mold design is formed through trial and error according to pipe diameters and changes in requirements. Thus, the objective of this study was to perform piercing and burring process analysis via finite element analysis using DYNAFORM to resolve problems mentioned above. An optimization design method was used to determine the piercing punch profile. Three radii of the piercing punch (i.e., large, small, and joined radii) were selected as design variables to minimize thinning of a tee pipe. Based on results of correlation and multiple regression analyses, we developed a predictive approximation model to satisfy requirements for both thickness reduction and target height. The new piercing punch profile was then applied to actual tee forming using the developed prediction equation. Model results were found to be in good agreement with experimental results.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.151-160
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• 2019

Korea has the highest suicide rate among the OECD countries, and the suicide rate is highest among young adults in their 20s, most of whom are university students. Therefore, suicide among Korean university students is a public health issue that is of interest to us. The purpose of this study is to investigate the factors affecting the suicidal ideation of university students in Korea, and to use them as a basis to establish effective intervention for university suicide prevention through it. This was a cross-sectional descriptive study using convenience sampling method. The participants were 344 university students at universities in S and G cities. Data were collected with a structured questionnaire and analyzed using descriptive analysis, t-test, ANOVA, Pearson correlation coefficients, and hierarchical regression analysis using with the SPSS/Win 23.0 program. There was a significant correlation between depression (r=.45, p<.001), drinking alcohol (r=.14, p=.008), social support (r=-.26, p<.001), quality of life (r=-.46, p<.001), and suicidal ideation. In the first step of hierarchical regression analysis, satisfaction of school life (${\beta}=.198$, p<.001) was the significant factor influencing the suicidal ideation. Explanatory power was 25.2%. In the second step of the hierarchical regression analysis, absence of parents (${\beta}=-.095$, p=.044), depression (${\beta}=.247$, p<.001), quality of life (${\beta}=-.280$, p<.001), and explanatory power were increased to 42.0%. The results of the study indicate the need to actively identify the group of university students in their 20s with high risk of suicide through continuous evaluation of depression, and to improve the quality of life as a method of preventing suicide. In addition, the effect of absence of parents on the suicidal ideation among Korean university students suggests that parental support may play an important role in suicide prevention.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.483-494
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• 2023

Recently, gas turbine generators are widely used for frequency control of power systems. Although the inlet temperature of a gas turbine is a key factor related to the performance and lifespan of the device, the inlet temperature is not measured directly for reasons such as the turbine structure and operating environment. In particular, the inlet temperature of the reheating gas turbine is very important for stable operation management, but field workers are experiencing a lot of difficulties because the manufacturer does not provide information on the calculation formula. Therefore, in this study, we propose a method for estimating the inlet temperature of a gas turbine using a machine learning-based linear regression analysis method based on a polytropic process equation. In addition, by proposing an inlet temperature calculation algorithm through the usefulness analysis and verification of the inlet temperature calculation model obtained through linear regression analysis, it is intended to help to improve the level of reheat gas turbine combustion tuning technology.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• Analytical Science and Technology
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• v.21 no.5
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• pp.438-441
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• 2008

We have developed an alternative to the internal chemical reference based on a calibrated reference signal which is not a real NMR line but an electronically produced signal (HERETIC) and determined the phosphorus concentration using this method. The area ratio of HERETIC and sample peaks obtained from the standard samples was used to measure the concentrations of different samples directly. The analysis of phosphorus by this method showed the excellent linear regression coefficient ($R^2=0.9999$) for the concentration range from 20 ppm to 500 ppm with HERETIC peak as reference.