• Journal of the korean Society of Automotive Engineers
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• v.15 no.1
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• pp.73-80
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• 1993

In this study, 3-dimensional linear and non-linear vehicle models are proposed to improve ride quality. The simulations of a vehicle passing over a bump were performed with those two vehicle models. The dynamic responses of the models were analyzed in time-domain and frequency-domain. Then, discomforts in each vibration axis and the combined-axes were evaluated based on the vibrations of the proposed models. The actual vehicle test results in time domain and frequency domain. Also, the discomfort values were compared. Then the validity of those two models were verified. Also, the design parameters of the suspension system are proposed for improving the ride quality.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1249-1253
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• 2005

This paper presents a method to model the path loss characteristics in microwave urban line-of-sight (LOS) propagation. We propose new upper- and lower-bound models for the LOS path loss using fuzzy linear regression (FLR). The spread of upper- and lower-bound of FLR depends on max and min value of a sample path loss data while the conventional upper- and lower-bound models, the spread of the bound intervals are fixed and do not depend on the sample path loss data. Comparison of our models to conventional upper- and lower-bound models indicate that improvements in accuracy over the conventional models are achieved.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.265-275
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• 2004

In this paper, multi-objective models for designing 3D trajectory of horizontal wells are developed in a fuzzy environment. Here, the objectives of minimizing the length of the trajectory and the error of entry target point are fuzzy in nature. Some parameters, such as initial value, end value, lower bound and upper bound of the curvature radius, tool-face angle and the arc length of each curve section, are also assumed to be vague and imprecise. The impreciseness in the above objectives have been expressed by fuzzy linear membership functions and that in the above parameters by triangular fuzzy numbers. Models have been solved by the fuzzy non-linear programming method based on Zimmermann [1] and Lee and Li [2]. Models are applied to practical design of the horizontal wells. Numerical results illustrate the accuracy and efficiency of the fuzzy models.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.19-25
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• 2001

Random effects models which describe the dependence via random effects in various correlated data have recently received considerable attention in the biomedical literature. They include mixed linear models (MLMs), generatized linear mixed models (GLMMS) and hierarchical generalized linear models (HGLMs). For the inference Lee and Nelder (2000) proposed the first-and second-order REML (restricted maximum likelihood) methods based on hierarchical-likelihood of tee and Welder (1996). In this paper, for Poisson-gamma HGLMs the new methods are theoretically compared with marginal likelihood methods and both methods are illustrated by two practical examples.

• Journal of the Korean Society of Safety
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• v.24 no.2
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• pp.94-99
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• 2009

This study deals with the traffic accidents at the 3-legged signalized intersections in Cheongu. The goals are to analyze the geometric, traffic and operational conditions of intersections and to develop a various functional forms that predict the accidents. The models are developed through the correlation analysis, the multiple linear, the multiple nonlinear, Poisson and negative binomial regression analysis. In this study, two multiple linear, two multiple nonlinear and two negative binomial regression models were calibrated. These models were all analyzed to be statistically significant. All the models include 2 common variables(traffic volume and lane width) and model-specific variables. These variables are, therefore, evaluated to be critical to the accident reduction of Cheongju.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1367-1375
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• 2015

Consider the linear growth models for longitudinal data analysis. Several kind of linear growth models are selected such as time-effect and random-effect models as well as a dummy variable included model. In this work, simulation data are generated with normality assumption, and both binormal ROC curve and AUC are obtained and compared for various linear growth models. It is found that ROC curves have different shapes and AUC increase slowly, as values of the covariance increase and the time passes for random-effect models. On the other hand, AUC increases very fast as values of covariance decrease. When the covariance has positive value, we explored that the variances of random-effect models increase and the increment of AUC is smaller than that of AUC for time-effect models. And the increment of AUC for time-effect models is larger than the increment for random-effect models.

• Journal of Welding and Joining
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• v.17 no.4
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• pp.85-92
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• 1999

In GMAW, the spatter is generated because of the variation of the arc state. If the arc state is quantitatively assessed, the control method to make the spatter be reduced is able to develop. This study was attempted to develop the optimal model that could estimate the arc state quantitatively. To do this, the generated spatters was captured under the limited welding conditions, and the waveforms of the arc voltage and of the welding current were collected. From the collected waveforms, the waveform factors and their standard deviations were produced, and the linear and non-linear regression models constituted using the factors and their standard deviations are proposed to estimate the arc state. the performance test to the proposed models was practiced. Obtained results are as follow. From the results of correlation analysis between the factors and the amount of the generated spatters, the standard deviations of the waveform factors have more the multiple regression coefficients than the waveform factors. Because the correlation coefficient between T and {TEX}$T_{a}${/TEX}, and s[T] and s[{TEX}$T_{a}${/TEX}] was nearly one, it was found that these factors have the same effect to the spatter generation. In the regression models to estimate the arc state, it was fond that the linear and the non linear models were also consisted of similar factors. In addition, the linear regression model was assessed the optimal model for estimating the arc state because the variance of data was narrow and multiple regression coefficient was highest among the models. But in the welding conditions which the amount of the generated spatters were small, it was found that the non linear regression model had better the estimation performance for the spatter generation than the linear.

• Korean Journal of Geomatics
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• v.4 no.1
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• pp.31-37
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• 2004

The aim of this research is comparing the existing approximation models (e.g. Affine Transformation and Direct Linear Transformation) with Rational Function Model as a substitute of rigorous sensor model of linear array scanner, especially push-broom sensor. To do so, this research investigates the mathematical model of each approximation method. This is followed by the assessments of accuracy of transformation from object space to image space by using simulated data generated by collinearity equations which incorporate or depict the physical aspects of linear array sensor.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.295-308
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• 2015

We have experienced a substantial improvement in and cost-drop for genotyping that enables genetic epidemiological studies with large-scale genetic data. Genome-wide association studies have identified more than ten thousand causal variants. Many statistical methods based on linear mixed models have been developed for various goals such as estimating heritability and identifying disease susceptibility locus. Empirical results also repeatedly stress the importance of linear mixed models. Therefore, we review the statistical methods related with to linear mixed models and illustrate the meaning of their estimates.