• Journal of the Korean Ceramic Society
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• v.39 no.10
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• pp.1007-1010
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• 2002

Alpha alumina platelet particles were synthesized from the powder mixture of ${\gamma}-Al_2O_3and\;Na_2SO_4$ with the use of microwave heating. The characteristics of the particles such as particle size and particle size distribution were compared with those of particles obtained from the same mixture without the use of microwave. Sample with the use of microwave showed small particle size and narrow particle size distribution compared to that without the use of microwave.

• Journal of The Korean Astronomical Society
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• v.25 no.2
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• pp.111-128
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• 1992

Infrared emissions from spherical dust, clouds are calculated using quasi-diffusion method. We have employed graphite-silicate mixture with power-law size distribution for the dust model. The grains are assumed to be heated and cooled by radiative processes only. The primary heating source is diffuse interstellar radiation field. hut the cases with an embedded source are also considered. Since graphite grains have higher temperature than silicate grains, the observed IR emission is mainly due to graphite grains, unless the fraction of graphite grains is negligibly small. The color temperature of Bok globules obtained from IRAS 60 and $100{\mu}m$ data are found to be consistent with the dust cloud with graphite-silicate mixture exposed to average interstellar radiation field. The color temperature is sensitive to the external radiation field, but rather insensitive to the size distribution of the grains. We found that the density distribution can be recovered outside the beam size using the inversion technique that assumes negligible optical depth. However, the information within the beam size is lost for if beam convolved intensity distributions are used in deriving density profile.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.939-945
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• 2009

In this paper, we proposed a method which corresponds people under the structured spaces with multiple cameras. The correspondence takes an important role for using multiple camera system. For solving this correspondence, the proposed method consists of three main steps. Firstly, moving objects are detected by background subtraction using a multiple background model. The temporal difference is simultaneously used to reduce a noise in the temporal change. When more than two people are detected, those detected regions are divided into each label to represent an individual person. Secondly, the detected region is segmented as features for correspondence by a criterion with the color distribution and context information of human body. The segmented region is represented as a set of blobs. Each blob is described as Gaussian probability distribution, i.e., a person model is generated from the blobs as a Gaussian Mixture Model (GMM). Finally, a GMM of each person from a camera is matched with the model of other people from different cameras by maximum likelihood. From those results, we identify a same person in different view. The experiment was performed according to three scenarios and verified the performance in qualitative and quantitative results.

• Macromolecular Research
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• v.16 no.2
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• pp.108-112
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• 2008

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis of nonpolar polymeric materials is affected by the sample preparation as well as the matrix and cationizing agent. This study examined the influence of silver salt types on the MALDI analysis of polybutadiene (PB). Silver trifluoroacetate (AgTFA), silver benzoate (AgBz), silver nitrate ($AgNO_3$), and silver p-toluenesulfonate (AgTS) were used as the silver salts to compare the MALDI mass spectra of PB. The mixture solution of PB and 2,5-dihydroxybenzoic acid (DHB), as a matrix dissolved in THF, was spotted on the sample plate and dried. A droplet of the aqueous silver salt solution was placed onto the mixture. The mass spectrum with AgBz showed the clear $[M+Ag]^+$ ion distribution of PB while the mass spectrum with AgTFA did not show $[M+Ag]^+$ ions but only silver cluster ions. The mass spectra with $AgNO_3$ and AgTS did not show a clear $[M+Ag]^+$ ion distribution. The difference in the formation of $[M+Ag]^+$ ions of PB depending on the silver salts was attributed to the silver cation transfer reaction between the silver salt and the matrix (DHB). The mass spectrum showed a clear $[M+Ag]^+$ ion distribution of PB when the conjugate acid of the silver salt was less acidic than the matrix.

• Mass Spectrometry Letters
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• v.8 no.2
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• pp.29-33
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• 2017

Understanding the mechanisms that control and concentrate the observed electrospray ionisation (ESI) response from peptides is important. Controlling these mechanisms can improve signal-to-noise ratio in the mass spectrum, and enhances the generation of intact ions, and thus, improves the detection of peptides when analysing mixtures. The effects of different mixtures of aqueous: organic solvents (25, 50, 75%; v/v): formic acid solution (at pH 3.26) compositions on the ESI response and charge-state distribution (CSD) during mass spectrometry (MS) were determined in a group of biologically active peptides (molecular wt range 1.3 - 3.3 kDa). The ESI response is dependent on type of organic solvent in the mobile phase mixture and therefore, solvent choice affects optimal ion intensities. As expected, intact peptide ions gave a more intense ESI signal in polar protic solvent mixtures than in the low polarity solvent. However, for four out of the five analysed peptides, neither the ESI response nor the CSD were affected by the volatility of the solvent mixture. Therefore, in solvent mixtures, as the composition changes during the evaporation processes, the $pK_b$ of the amino acid composition is a better predictor of multiple charging of the peptides.

• Steel and Composite Structures
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• v.43 no.3
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• pp.389-401
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• 2022

This study investigated the flowability and mechanical properties of cost-effective steel fiber reinforced ultra-high performance concrete (UHPC) by using locally available materials for field-cast application. To examine the effect of mixture constituents, five mixtures with different fractions of silica fume, silica powder, ground granulated blast furnace slag (GGBS), silica sand, and crushed natural sand were proportionally prepared. Comprehensive experiments for different mixture designs were conducted to evaluate the fresh- and hardened-state properties of self-consolidating UHPC. The results showed that the proposed UHPC had similar mechanical properties compared with conventional UHPC while the flow retention over time was enhanced so that the field-cast application seemed appropriately cost-effective. The self-consolidating UHPC with high flowability and low viscosity takes less total mixing time than conventional UHPC up to 6.7 times. The X-ray computed tomographic imaging was performed to investigate the steel fiber distribution inside the UHPC by visualizing the spatial distribution of steel fibers well. Finally, the tensile stress-strain curve for the proposed UHPC was proposed for the implementation to the structural analysis and design.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.725-730
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• 2007

Gray-level histogram-based threshold selection methods such as Otsu's method, Huang and Wang's method, and etc. have been widely used for the threshold selection in image processing. They are simple and effective, but take too much time to determine the optimal multilevel threshold values as the number of thresholds are increased. In this paper, we measure correlation between gray-levels by using the Gaussian function and define a Gaussian-type finite mixture distribution which is combination of the Gaussian distribution function with the gray-level histogram, and propose a fast and effective threshold selection method using it. We show the effectiveness of the proposed through experimental results applied it to three images and the efficiency though comparison of the computational complexity of the proposed with that of Otsu's method.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.505-519
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• 2006

We consider zero-inflated count data, which is discrete count data but has too many zeroes compared to the Poisson distribution. Zero-inflated data can be found in various areas. Despite its increasing importance in practice, appropriate statistical inference on zero-inflated data is limited. Classical inference based on a large number theory does not fit unless the sample size is very large. And regular Poisson model shows lack of St due to many zeroes. To handle the difficulties, a mixture of distributions are considered for the zero-inflated data. Specifically, a mixture of a point mass at zero and a Poisson distribution is employed for the data. In addition, when there exist meaningful covariates selected to the response variable, loglinear link is used between the mean of the response and the covariates in the Poisson distribution part. We propose a Bayesian inference for the zero-inflated Poisson regression model by using a Markov Chain Monte Carlo method. We applied the proposed method to a Korean oral hygienic data and compared the inference results with other models. We found that the proposed method is superior in that it gives small parameter estimation error and more accurate predictions.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.109-121
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• 2007

In this study, an imputation model using circular probability distribution was developed in order to overcome problems of missing data from a traffic survey. The existing ad-hoc or heuristic, model-based and algorithm-based imputation techniques were reviewed through previous studies, and then their limitations for imputing missing traffic volume data were revealed. The statistical computing language 'R' was employed for model construction, and a mixture of von Mises probability distribution, which is classified as symmetric, and unimodal circular probability were finally fitted on the basis of traffic volume data at survey stations in urban and rural areas, respectively. The circular probability distribution model largely proved to outperform a dummy variable regression model in regards to various evaluation conditions. It turned out that circular probability distribution models depict circularity of hourly volumes well and are very cost-effective and robust to changes in missing mechanisms.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.