• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.534-538
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• 2003

Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed knowledge of the natures and quantities of radionuclides in waste package. Many of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the Indirect method by which the concentrations of DTM (Difficult-to-Measure) nuclide is decided using the relation of concentrations (Scaling Factor) between Key (Easy-to-Measure) nuclide and DTM nuclide with measured concentrations of Key nuclide. In general, scaling factor is determined by using of log mean average (LMA) and regression. These methods are adequate to apply most corrosion product nuclides. But in case of fission product nuclides and some corrosion product nuclides, the predicted values aren't well matched with the original values. In this study, the models using artificial neural network (ANN) for C-14 and Sr-90 are compared with those using LMA and regression. The assessment of models is executed in the two parts divided by a training part and a validation part. For all of two nuclides in the training part, the predicted values using ANN are well matched with the measured values compared with those using LMA and regression. In the validation part, the accuracy of the predicted values using ANN is better than that using LMA and is similar to or better than that using regression. It is concluded that the predicted values using ANN model are better than those using conventional model in some nuclides and ANN model can be used as the complement of LMA and regression model.

• KDI Journal of Economic Policy
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• v.24 no.1
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• pp.113-190
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• 2002

The purpose of this paper is to perform empirical studies on the impact of pollution intensity on international competitiveness using 1993 and 1998 data, and to estimate the change in environmental regulation level faced by the firms during 1993~1998. Collecting relevant data and providing them for further studies in the area are another purposes of the paper. The first method is the regression of various indices of international competitiveness on factor costs, such as labor, capital, R&D and pollution abatement costs. Goal of the regression analysis is to estimate the scarcity and comparative advantage effect of each production factor, especially environmental resource. Regression results show that those industries which employ more environmental resource have higher comparative advantage in both years, which implies that Korean firms are endowed with abundant environmental resource compared to other countries. The second method is to compute the relative scarcity indices(HOVL indices) of production factors, proposed by Leamer based on Vanek's generalized Hecksher-Ohlin Theorem. This method estimates the relative scarcity of production factors by computing factor costs embodied in import and export of commodities. This method shows similar results as the regression method; i.e., trade pattern of production factors implies that the manufacturing sector in Korea is endowed with abundant environmental resource compared to other countries. Considering population density, water resource endowment, intensity of economic activity per unit area and current air and water pollution levels, it is evident that Korea is never endowed with abundant environmental resource compared to other countries. Then the abundance of environmental resource revealed by the trade patterns of commodities and production factors implies that Korea's environmental regulation level is excessively generous compared to environmental capacity, and that this increased the environmental resource endowment supplied to firms and thus distorted the inter-industry comparative advantages. Both regression and HOVL methods, on the other hand, show that overall environmental regulation level faced by the firms has been strengthened during 1993~1998.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.151-157
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• 2014

Purpose: In order to develop strategies to prevent farm-work accidents relating to agricultural machinery, influential factors were examined in this paper. The effects of these factors were quantified using logistic regression. Methods: Based on the results of a survey on farm-work accidents conducted by the National Academy of Agricultural Science, 21 tentative independent variables were selected. To apply these variables to regression, the presence of multicollinearity was examined by comparing correlation coefficients, checking the statistical significance of the coefficients in a simple linear regression model, and calculating the variance inflation factor. A logistic regression model and determination method of its goodness of fit was defined. Results: Among 21 independent variables, 13 variables were not collinear each other. The results of a logistic regression analysis using these variables showed that the model was significant and acceptable, with deviance of 714.053. Parameter estimation results showed that four variables (age, power tiller ownership, cognizance of the government's safety policy, and consciousness of safety) were significant. The logistic regression model predicted that the former two increased accident odds by 1.027 and 8.506 times, respectively, while the latter two decreased the odds by 0.243 and 0.545 times, respectively. Conclusions: Prevention strategies against factors causing an accident, such as the age of farmers and the use of a power tiller, are necessary. In addition, more efficient trainings to elevate the farmer's consciousness about safety must be provided.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.65.1-65.1
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• 2010

Thermal performance tests of solar thermal collectors include determination of coefficient parameters in an efficiency equation. The parameters can be estimated using regression method to minimize an objective function as sum of differences between measured efficiency data and regressed efficiency equation. However, this conventional approach doesn't consider measurement uncertainties. In this presentation, a method to determine regression parameters in the efficiency equation and uncertainties of the parameters is described with mainly mathematical expressions based on literature reviews. In the method, parameters in the equation for collector efficiency can be determined using regression analysis with a weighting factor in the objective function. The weighting factor can be uncertainties of the differences between measured and fitted efficiencies. To evaluate the approach, performance estimation of a solar collector using the efficiency equation with uncertainties is compared to the result using the conventional efficiency equation by a simulated way for a case in one of previous studies.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.339-344
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• 2006

Slope failures are happen to natural disastrous when they occur in mountainous areas adjoining highways in Korea. The accidents associated with slope failures have increased due to rapid urbanization of mountainous areas. Therefore, Regular maintenance is essential for all slope and conducted to maintain road safety as well as road function. In this study, we take priority of making a database of risk factor of the failure of a slope before assesment and analysis. The purpose of this paper is to recommend a standard of Slope Management Information Sheet(SMIS) like as Hazard Map. The next research, we suggest to pre-estimated model of a road slope using Logistic Regression Model.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.199-202
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• 2001

This paper presents the correlation on the contamination degree and weather conditions using the multiple regression of the statistic method. The cotamination is a significant factor in the insulation system. The major factor is natural contamination, and the most is the salt. The salt contamination is occured by the weather conditions. The weather contaminations are wind, precipitation, temperature, relative humidity, etc. The effects of those are different, and the correlation is showed numerically by using the multiple regression method of the statistic method. With this, the estimation of the equivalent salt deposit density(ESDD) becomes possible by the changes of the weather conditions.

• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.94-98
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• 2002

This study aimed to search for the fundamental accident causes using a categorical analysis, a kind of statistical methods. As the analysis methods, correlation analysis, independence test and logistic regression analysis were used. And the SPSS package, a general-purpose mathematical library, was used to obtain statistical characteristics. As the result of this study, the accident causes associated with factor of 'lost working days' were factors such as 'employed periods', 'sex', 'type of accident', 'month'. In case of applying independence test method, the most important cause was the factor of 'month'. In case that logistic regression analysis method was applied, the cause contributed to the increase structure'. 'less than 6 month'. On the basis of these results, the plan for accident prevention and the proper investment for accident prevention expenditure could be carried out in each workshop.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.719-729
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• 2003

We propose a Bayesian model selection procedure for nonlinear regression models under noninformative prior. For informative prior, Na and Kim (2002) suggested the Bayesian model selection procedure through MCMC techniques. We extend this method to the case of noninformative prior. The difficulty with the use of noninformative prior is that it is typically improper and hence is defined only up to arbitrary constant. The methods, such as Intrinsic Bayes Factor(IBF) and Fractional Bayes Factor(FBF), are used as a resolution to the problem. We showed the detailed model selection procedure through the specific real data set.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.143-151
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• 2021

This study was a cross-sectional descriptive research to analyze the effects of sub-factors of cognitive emotional control on happiness levels. The participants of the study were 201 men and women in their 20s, and data were collected online from January 1 to 15 collected data were, 2001 using structured cognitive control and happiness level questionnaires. The collected data were conducted Independent t-test, Pearson correlation analysis, simple regression analysis, multiple regression Analysis, hierarchical regression analysis using SPSS 18.0 statistic program. As a result, the study appeared that the level of happiness by gender does not differ, and cognitive emotional control affected 58.5%. The average of cognitive emotional control was higher for all men, but women were higher than men in criticized others. Also, acceptance was the sub-factor of emotional control that most affected the level of happiness (β=-.587, p<0.01). Based on the results of this study, it is suggested that a systematic program on subject of acceptance, a sub-factor of cognitive emotional control, should be developed to improve the level of happiness.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.190-206
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• 1996

In case measurements are made on units of production in time order, it is reasonable to expect that the measurement errors will sometimes be first order autocorrelated, and a technique to test such autocorrelation is required to give good control of the productive process. Tool-wear process provide an example for which regression model can sometimes be useful in modeling and controlling the process. For the control of such process, we present a simple method for testing first order autocorrelation in regression errors. The method is based on Bayesian test method via Bayes factor and derived by observing that in general, a Bayes factor can be written as the product of a quantity called the Savage-Dickey density ratio and a correction factor ; both terms are easily estimated from Gibbs sampling technique. Performance of the method is examined by means of Monte Carlo simulation. It is noted that the test not only achieves satisfactory power but eliminates the inconvenience occurred in using the well-known Durbin-Watson test.