• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.403-410
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• 2014

Binary logistic regression analysis is a statistical technique that explains binary response variable by quantitative or qualitative explanatory variables. In the binary logistic regression model, the probability that the response variable equals, say 1, one of the binary values is to be explained as a transformation of linear combination of explanatory variables. This is one of big barriers that non-statisticians have to overcome in order to understand the model. In this study, an educational tool is developed that explains the need of the binary logistic regression analysis using Excel VBA. More precisely, this tool explains the problems related to modeling the probability of the response variable equal to 1 as a linear combination of explanatory variables and then shows how these problems can be solved through some transformations of the linear combination.

• Journal of Labour Economics
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• v.23 no.1
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• pp.81-101
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• 2000

This paper tests the economic effects of employee participation programs. We suggest framework that emphasizes the mutual gains through the interaction of employee participation programs with complementary practices-employment security, training, rational wage systems, information sharing and empowerment-. In regression analysis, we find positive effects on the productivity. And also we test significant differences of participation level and complementary level between win-win group(high productivity and low turnover) and lose-lose group(low productivity and high turnover) through the t-test and discriminant analysis. This facts suggest that employee participation programs contribute to mutual gains.

• Explosives and Blasting
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• v.31 no.1
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• pp.33-40
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• 2013

Carinthian cut and cover tunnelling method which combines cut & cover and NATM tunnel excavation method has increased the interest. Design and construction of arch concrete have been increased, but there is no applicable standards for arch concrete. Therefore, in this study numerical analysis was performed to propose standards for the Carinthian tunnelling method considering a variety of conditions such as ground conditions, tunnel overburden thickness, thickness of backfill, and overburden surface slope angle changes, linear regression equations derived to classify and organize a rational, economical, and safe Carinthian cut and cover tunneling method based proposed.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.899-907
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• 2010

Several non-response imputation methods are suggested, however, mainly cross-sectional imputations are studied and applied to this analysis. A simple and common imputation method for panel data is the cross-wave regression imputation or carry-over imputation as a special case of cross-wave regression imputation. This study suggests a multiple imputation method combined time series analysis and cross-sectional multiple imputation method. We compare this method and the cross-wave regression imputation method using MSE, MAE, and Bias. The 2008 monthly labor survey data is used for this study.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.1
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• pp.18-24
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• 2013

Recently, the interest is increasing about the eco-friendly concrete. Accordingly, the blast furnace slag(BFS), a by-product of industry is known for improving the durability through compaction in concrete and is expanding the use. The research about BFS in concrete be accomplished frequently. In this study, we should know the hydration characteristic of BFS concrete the through the adiabatic temperature rise test due to the replacement of a variety of BFS. In addition, we produced the regression analysis factors through the test result and analyzied the effect for the replacement of BFS. According to test results, the compressive strength showed a slight degradation or equal and the the adiabatic temperature rise figure and rising factors are went down for rising replacment of BFS. In the future, the study about the adiabatic temperature rise equation for the various replacement of BFS and binder is considered necessary.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.598-604
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• 2014

In this paper, we develop stepwise regression data envelopment model to select important variables. We formulate null hypothesis to understand the importance of each variable and use Kruskal-Wallis test for this purpose. If the Kruskal-Wallis test does reject the null hypothesis this will imply there is significant fluctuation in the efficiency score relative to base model. And therefore we have to further check the pair of variables that causes the fluctuation in order to determine its importance using Conover-Inman test. The proposed models helps understand the extent of misclassification decision making units as efficient/inefficient when variables are retained or discarded alongside provides useful managerial prescription to make improvement strategies.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.21-28
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• 2006

In a face detection system based on template matching, histogram equalization or log transform is applied to an input image for the intensity normalization and the image improvement. It is known that they are noneffective in improving an image with intensity distortion by illumination variation. In this paper, we propose an efficient image improvement method using a simple regression analysis combined with a bilateral symmetry average for images with intensity distortion by illumination variation. Experimental results show that our method delivers the detection performance better than previous methods and also remarkably reduces the number of face candidates.

• Journal of the Korean Magnetics Society
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• v.12 no.4
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• pp.143-148
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• 2002

We report an experimental evidence of coexistence of the strong and weak exchange couplings in unidirectional NiO/NiFe (antiferromagneticlferromagnetic) bilayer thin films. The exchange bias was measured by VSM and AMR techniques and then, analyzed into the strong and weak exchange couplings by means of a regression method. In NiO(60nm)/NiFe(10nm) film, the ratio of the weak exchange coupling field over the average exchange coupling field was found to be almost unchanged within it range from 0.2 to 0.4 irrespective to the strength of an applied field. However, the ratio increased among the samples with decreasing the average exchange coupling field due to the increment of the weak exchange coupling area.

• Journal of the Korea Concrete Institute
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• v.20 no.2
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• pp.147-156
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• 2008

In an uniaxial compressive test of a concrete standard specimen (150$\times$300 mm) the crack initiation and extension with the stress increase are the major reason of the failure, which is similar to the breakage of the particle bonding in the simulation by using particle bonded model, especially particle flow code in 3 dimensions (PFC3D) developed by Itasca Consulting Group Inc. That is the main motive to study the possibility of an uniaxial compressive strength test simulation. It is important to investigate the relationship between the micro-parameters and the macro-properties because the 3-dimensional particle bonded model uses the spherical particles to analyze the physical phenomena. Contact bonded model used herein has eight micro-parameters and there are five macro-properties; Young's modulus, Poisson's ratio, uniaxial compressive strength and the crack initiation stress and the ratio concerning the crack propagation with the stress. To simulate the compressive test we made quantitative relationships between the micro-parameters and the macro-properties by using the fractional factorial design and various sensitivity analyses including regression analysis, which result in the good agreement with the previous studies. Also, the stress-stain curve and the crack distribution over the specimen given by PFC3D showed the mechanical behavior of the concrete standard specimen under the uniaxial compression. It is concluded that the particle bonded model can be a good tool for the analyzing the mechanical behavior of concrete under the uniaxial compressive load.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.203-213
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• 2017

We study estimation and inference of joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. We consider a class of time-varying transformation models and combine the two marginal models using Gaussian copulas to estimate the joint models. Our models and estimation method can be applied in many situations where the conditional mean-based models are inadequate. Gaussian copulas combined with time-varying transformation models may allow convenient and easy-to-interpret modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.