• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.891-907
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• 2014

This article is concerned with one of the most important prior distributions for Bayesian analysis of survival and event history data, called Beta processes, proposed in Hjort (1990). We review the current state of the art of beta processes and their application to survival analysis. Relevant methodological and practical areas of research that we touch on relate to constructions, posterior distributions, large-sample properties, Bayesian computations, and mixtures of Beta processes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.6
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• pp.988-995
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• 2001

Functionally graded materials(FGMs) are highlighted to be suitable for high temperature engineering due to their continuous distribution of material properties. In this paper, an optimal design is executed for determining the optimal material volume distribution pattern that minimizes the steady-state thermal stress of FGM heat-resisting composites. The interior penalty function method and the golden section method are employed as optimization techniques while the finite element method is used for thermal stress analysis. Through numerical simulations we suggest the volume fraction distributions that considerably improve initial thermal stress distributions.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.161-166
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• 2003

In this paper, a new form of generalized linear models is proposed. The proposed models consist of a distribution function of the mean response and a weighted linear combination of distribution functions of covariates. This form addresses a structural problem of the link function in the generalized linear models. Markov chain Monte Carlo methods are used to estimate the parameters within a Bayesian framework.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.225-233
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• 1996

In this paper, we propose Bayes estimators of the finite population mean based on heavy-tailed prior distributions using scale mixtures of normals. Also, the asymptotic optimality property of the proposed Bayes estimators is proved. A numerical example is provided to illustrate the results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.95-102
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• 2020

For the purpose of developing a PE fiber-reinforced highly ductile cementitious composite having high tensile strain capacity more than 2% under the condition of containing aggregates with large particle size, this study investigated the tensile behavior of composites according to the particle size and distribution of aggregates in the composite. Compared with the mixture containing silica sand of which particle size is less than 0.6 mm, mixtures containing river sand and/or gravel with the maximum particle size of 2.36 mm, 4.75 mm, 5.6 mm, 6.7 mm were considered in the experimental design. The particle size distributions of aggregates were adjusted for the optimized distribution curves obtained from modified A&A model by blending different sizes of aggregates. All the mixtures presented clear strain-hardening behavior in the direct tensile tests. The mixtures with the blended aggregates to meet the optimum curves of aggregate size distributions showed higher tensile strain capacity than the mixture with silica sand. It was also found that the tensile strain capacity was improved as the maximum size of aggregate increased which resulted in wider particle size distribution. The mixtures with the maximum size of 5.6 mm and 6.7 mm presented very high tensile strain capacities of 4.83% and 5.89%, respectively. This study demonstrated that it was possible to use coarse aggregates in manufacturing highly ductile fiber-reinforced cementitous composite by adjusting the particle size distribution.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.619-630
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• 2011

In order to estimate an appropriate threshold and evaluate its performance for the data mixed with two different distributions, nine kinds of well-known classification accuracy measures such as MVD, Youden's index, the closest-to- (0,1) criterion, the amended closest-to- (0,1) criterion, SSS, symmetry point, accuracy area, TA, TR are clustered into five categories on the basis of their characters. In credit evaluation study, it is assumed that the score random variable follows normal mixture distributions of the default and non-default states. For various normal mixtures, optimal cut-off points for classification measures belong to each category are obtained and type I and II error rates corresponding to these cut-off points are calculated. Then we explore the cases when these error rates are minimized. If normal mixtures might be estimated for these kinds of real data, we could make use of results of this study to select the best classification accuracy measure which has the minimum error rate.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.269-278
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• 2011

There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.6
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• pp.868-875
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• 2001

The objective of this study is to investigate the average droplet size distributions of a GDI spray by simultaneous fluorescence/scattering image technique. GDI engine is recently very popular because of high engine efficiency and low emissions. However, the injectors must have good spray characteristics because the fuel is directly injected into the cylinder. The fuel mixtures used in this study were 2% of fluorobenzene, 9% of DEMA(diethyl-methyl-amine) and 89% of hexane by volume. The system for obtaining 2-D fluorescence/scattering images of fuel spray was constituted of a laser sheet, a doubling prism, optical filters, and an ICCD camera. Using the ratio of the fluorescence to the scattering intensities, SMD distributions were obtained. SMD measured by the technique was compared with that obtained by PDA. It was found that average droplet size was bigger at spray center in the early stage of injection and at the outer periphery of the spray in the late stage of injection.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2734-2741
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• 2023

Brachytherapy is a special case of radiotherapy. It should be arranged according to some principles in medical radiation applications and radiation physics. The primary principle is to use as low as reasonably achievable dose in all ionizing radiation applications for diagnostic and therapeutic treatments. Dosimetric distributions are dependent on radioactive source properties and radiation-matter interactions in an absorber medium such as phantom or tissue. In this consideration, the geometrical structure and material of the seed capsule, which surrounds a radioactive material, are directly responsible for isodose profiles and dosimetric functions. In this study, the radiometric properties of capsule material were investigated on dose distribution in a water phantom by changing its nuclear properties using the EGSnrc Monte Carlo (MC) simulation code. Effective atomic numbers of hypothetic mixtures were calculated by using different elements with several fractions for capsule material. Model 6711 brachytherapy seed was modeled by EGSnrc/Dosrcnrc Code and dosimetric functions were calculated. As a result, dosimetric parameters of hypothetic sources have been acquired in large-scale atomic number. Dosimetric deviations between the data of hypothetic seeds and the original one were analyzed. Unit dose (Gy/Particle) distributions belonging to different types of material in seed capsule have remarkably differed from the original capsule's data. Capsule type is major variable to manage the expected dose profile and isodose distribution around a seed. This study shows us systematically varied scale of material type (cross section or effective atomic number dependent) offers selective material usage in production of seed capsules for the expected isodose profile of a specific source.

• Journal of Ginseng Research
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• v.43 no.3
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• pp.368-376
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• 2019

Background: In the current phytochemical research on ginseng, the differentiation and structural identification of ginsenosides isomers remain challenging. In this paper, a two-dimensional mass spectrometry (2D-MS) method was developed and combined with statistical analysis for the direct differentiation, identification, and relative quantification of protopanaxadiol (PPD)-type ginsenoside isomers. Methods: Collision-induced dissociation was performed at successive collision energy values to produce distinct profiles of the intensity fraction (IF) and ratio of intensity (RI) of the fragment ions. To amplify the differences in tandem mass spectra between isomers, IF and RI were plotted against collision energy. The resulting data distributions were then used to obtain the parameters of the fitted curves, which were used to evaluate the statistical significance of the differences between these distributions via the unpaired t test. Results: A triplet and two pairs of PPD-type ginsenoside isomers were differentiated and identified by their distinct IF and RI distributions. In addition, the fragmentation preference of PPD-type ginsenosides was determined on the basis of the activation energy. The developed 2D-MS method was also extended to quantitatively determine the molar composition of ginsenoside isomers in mixtures of biotransformation products. Conclusion: In comparison with conventional mass spectrometry methods, 2D-MS provides more direct insights into the subtle structural differences between isomers and can be used as an alternative approach for the differentiation of isomeric ginsenosides and natural products.