• Computers and Concrete
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• v.24 no.1
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• pp.1-6
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• 2019

Within the scope of this study, the foam solution was prepared by properly mixing sulfonate based foam agent with water. Furthermore, this solution was mixed with the mixture of fine sand, cement, and water to produce foamed concrete. The mixture ratios which are the percentage of foam solution used in foam concrete were chosen as 0, 20, 40 and 60% by vol. After these groups reached 28 days of strength, they were heated to 20, 100, 400 and $700^{\circ}C$ respectively. Afterward, high-temperature effects on the foamed concrete were obtained by employing physical and mechanical properties tests. Additionally, SEM (scanning electron microscope) and EDX (energy-dispersive X-ray spectroscopy) tests were employed to analyze the microstructure, and ${\mu}-CT$ (micro computed tomography) images were used to reconstruct 3-D models of the heat-treated specimens. Then, these models are analyzed to examine the void structures and the changes in these structures due to the high temperatures. The study has shown that the void structures reduce the high-temperature effects and the foam solution could be mixed with concrete up to 40 % by vol. where the high strength of foamed concrete is non-mandatory.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.335-342
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• 2015

Joint hierarchical generalized linear models proposed by Molas et al. (2013) extend the simple longitudinal model into multiple models fitted jointly. It can easily handle the correlation of multivariate longitudinal data. In this paper, we apply this method to analyze KoGES cohort dataset. Fixed unknown parameters, random effects and variance components are estimated based on a standard framework of h-likelihood theory. Furthermore, based on the conditional Akaike information criterion the correlated covariance structure of random-effect model is selected rather than an independent structure.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.957-981
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• 2017

A generalized linear mixed model is an extension of a generalized linear model that allows random effect as well as provides flexibility in developing a suitable model when observations are correlated or when there are other underlying phenomena that contribute to resulting variability. We describe maximum likelihood estimation methods for logistic regression models that include random effects - the Laplace approximation, Gauss-Hermite quadrature, adaptive Gauss-Hermite quadrature, and pseudo-likelihood. Applications are provided with social science problems by analyzing the effect of mental health and life satisfaction on volunteer activities from Korean welfare panel data; in addition, we observe that the inclusion of random effects in the model leads to improved analyses with more reasonable inferences.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1055-1067
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• 2017

Most previous works to study for the depression of the disabilities in Korea have analyzed the repeated measured data of each individual under the mutually independent assumption. In this study, Korea Welfare Panel data of the disabilities surveyed additionally every three years are analyzed to detect the significant exploratory variables by the linear mixed models. A suitable correlation matrix is considered for the dependency of repeated measurement of each individual. The random effect to reflect the characteristics of the individuals as well as the fixed effect is included in the fitted linear mixed model. By the residual plot of the fixed effect model, the problem that the averages of residuals of each individual do not seem to be around zero is described. Further, the residual plot and the Q-Q plot coming from the selected final model are shown that the problem is modified well.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.385-392
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• 2012

Logistic regression is a well known binary classification method in the field of statistical learning. Mixed-effect regression models are widely used for the analysis of correlated data such as those found in longitudinal studies. We consider kernel extensions with semiparametric fixed effects and parametric random effects for the logistic regression. The estimation is performed through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of optimal hyperparameters, cross-validation techniques are employed. Numerical results are then presented to indicate the performance of the proposed procedure.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.73-81
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• 2014

This study dealt with the impacts of geometric structure on traffic accidents occurring on the interstates. There are standard values for the case of geometric structure which are recommended in the design guideline/policy; however, in the previous models, geometric variables were adapted as integrated ones as opposed to mixed ones in the real world so that derived models had a weakness to reflect the real. Therefore, using subdivided geometric variables, this study tried to derive the model which reflects the real world. In addition, by calculating elasticity, each variables' effect to the accidents are estimated. Hopefully, this study will help to establish the future guideline/policy of geometrics considering traffic safety.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.787-796
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• 2009

A random coefficient model is applied when times of the repeated measurements are not fixed in experiments with respect to the subjects. The procedures of the inference of a random coefficient model are same as those of a mixed model. Diet experimental data was used for applying the random coefficient model. Various random coefficient models are investigated for the experimental data, and are compared each other. Finally, optimal random coefficient model would be selected. It resulted from the analysis that for the fixed effect factor, the baseline, treatment, height, and time effect were very significant. The treatment effect of the diet foods and exercises were more effective in losing weight than the effect of the diet foods only. The fixed cubic time effect was very significant. The variance components corresponding to the subject effect, linear time effect, quadratic time effect, and cubic time effect of the random coefficients are all positive. When quartic time effect was added as random coefficients the model did not converge. Thus random coefficients up to the cubic terms was considered as the optimal model.

• Environmental Engineering Research
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• v.18 no.3
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• pp.163-168
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• 2013

In this study, an innovative media, iron mixed ceramic pellet (IMCP) has been developed for arsenic (As) removal from groundwater. A porous, solid-phase IMCP (2-3 mm) was manufactured by combining clay soil, rice bran, and Fe(0) powder at $600^{\circ}C$. Both the As(III) and As(V) adsorption characteristics of IMCP were studied in several batch experiments. Structural analysis of the IMCP was conducted using X-ray absorption fine structure (XAFS) analysis to understand the mechanism of As removal. The adsorption of As was found to be dependent on pH, and exhibited strong adsorption of both As(III) and As(V) at pH 5-7. The adsorption process was described to follow a pseudo-second-order reaction, and the adsorption rate of As(V) was greater than that of As(III). The adsorption data were fit well with both Freundlich and Langmuir isotherm models. The maximum adsorption capacities of As(III) and As(V) from the Langmuir isotherm were found to be 4.0 and 4.5 mg/g, respectively. Phosphorus in the water had an adverse effect on both As(III) and As(V) adsorption. Scanning electron microscopy results revealed that iron(III) oxides/hydroxides are aggregated on the surface of IMCP. XAFS analysis showed a partial oxidation of As(III) and adsorption of As(V) onto the iron oxide in the IMCP.

• Particle and aerosol research
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• v.5 no.2
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• pp.45-52
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• 2009

Black carbon, which is a by-product of combustion of fossil fuel and biomass burning, is the component that imposes the largest uncertainty on quantifying aerosol climate effect. The direct, indirect and semi-direct climate effects of black carbon depend on its state of the mixing with other water-soluble aerosol components. The process that transforms hydrophobic externally mixed black carbon particles into hygroscopic internally mixed ones is called "aging". In most climate models, simple parameterizations for the aging time scale are used instead of solving detailed dynamics equations on the aging process due to the computation cost. In this study, a new parameterization for the black carbon aging time scale due to condensation and coagulation is presented as a function of the concentration of hygroscopic atmospheric components and the black carbon particle size. It is shown that the black carbon aging time scale due to condensation of sulfuric acid vapors varies to a large extent depending on the sulfuric acid concentration and the black carbon particle size. This result indicates that the constant aging time scale values suggested in the literature cannot be directly applied to a global scale modeling. The aging time scale due to coagulation with internally mixed aerosol particles shows an even stronger dependency on particle size, which implies that the use of a particle-size-independent aging time scale may lead to a large error when the aging is dominated by coagulation.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1401-1406
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• 2004

In this paper, we present the theoretical and numerical results of scavenge characteristics in a small prechamber of an HCCI(Homogeneous Charge Compression Ignition) engine. Two theoretical models are proposed in prediction of the scavenge time and the efficiency ; one is the non-mixing models in which it is assumed that the input gas($CH_{4}$) and the existing gas(air) do not mix with each other, and the other is the fully-mixed model in which the two gases are assumed to mix completely before ejecting to the ambient air. Focus is also given to the effect on the scavenge performance of the size of the chamber oulet.