• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.214-219
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• 2007

Both the bubble rising in a fully filled container and the droplet splash are simulated by a solution code(PowerCFD). This code employs an unstructured cell-centered method based on a conservative pressure-based finite-volume method with interface capturing method (CICSAM) in a volume of fluid(VOF) scheme for phase interface capturing. The present results are compared with other numerical solutions found in the literature. It is found that the present code simulate complex free surface flows such as multi phase flows due to large density difference efficiently and accurately.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.2
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• pp.112-119
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• 2021

This study proposes a design method of high-power-density and high-efficiency low-voltage DC-DC converters using SiC MOSFET and the optimized planar transformer design procedure based on the figure-of-merit. The secondary rectifying circuit of the phase-shifted full-bridge converter is compared to achieve high power density and high efficiency, and the phase-shifted full bridge converter with a current-doubler rectifier is selected. The planar transformer is designed by the proposed optimized design procedure and verified by FEA simulation. To validate the proposed design method, experimental results from a 3 kW prototype are provided. The prototype achieved 95.28% maximum efficiency and a power density of 2.98 kW/L.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1912-1921
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• 2020

Objective: This study assessed genomic prediction accuracies based on different selection methods, evaluation procedures, training population (TP) sizes, heritability (h²) levels, marker densities and pedigree error (PE) rates in a simulated Korean beef cattle population. Methods: A simulation was performed using two different selection methods, phenotypic and estimated breeding value (EBV), with an h² of 0.1, 0.3, or 0.5 and marker densities of 10, 50, or 777K. A total of 275 males and 2,475 females were randomly selected from the last generation to simulate ten recent generations. The simulation of the PE dataset was modified using only the EBV method of selection with a marker density of 50K and a heritability of 0.3. The proportions of errors substituted were 10%, 20%, 30%, and 40%, respectively. Genetic evaluations were performed using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with different weighted values. The accuracies of the predictions were determined. Results: Compared with phenotypic selection, the results revealed that the prediction accuracies obtained using GBLUP and ssGBLUP increased across heritability levels and TP sizes during EBV selection. However, an increase in the marker density did not yield higher accuracy in either method except when the h² was 0.3 under the EBV selection method. Based on EBV selection with a heritability of 0.1 and a marker density of 10K, GBLUP and ssGBLUP_0.95 prediction accuracy was higher than that obtained by phenotypic selection. The prediction accuracies from ssGBLUP_0.95 outperformed those from the GBLUP method across all scenarios. When errors were introduced into the pedigree dataset, the prediction accuracies were only minimally influenced across all scenarios. Conclusion: Our study suggests that the use of ssGBLUP_0.95, EBV selection, and low marker density could help improve genetic gains in beef cattle.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.453-465
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• 2001

It is often the case that one wants to estimate parameters of the distribution which follows certain parametric model, while the dta are contaminated. it is well known that the maximum likelihood estimators are not robust to contamination. Basuet al.(1998) proposed a robust method called the minimum density power divergence estimation. In this paper, we investigate data-driven selection of the tuning parameter $\alpha$ in the minimum density power divergence estimation. A criterion is proposed and its performance is studied through the simulation. The simulation includes three cases of estimation problem.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.11
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• pp.566-571
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• 2004

Pulse modulation technique provide additional controling method for electron temperature and density in rf and microwave processing plasma. Transient characteristics of electron density and temperature have been measured in pulse modulated rf inductively coupled argon plasma using simple probe circuit. Electron temperature relaxation is clearly identified in the after glow stage. Controllability of average electron temperature and density depends on the modulation frequency and duty ratio. Numerical calculation of time-dependent electron density and temperature have been performed based on the global model. It has been shown that simple langmuir probe measurement method used for continuous plasma is also applicable to time-dependent measurement of pulse modulated plasma.

• Wind and Structures
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• v.2 no.2
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• pp.105-117
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• 1999

The various spectral density functions of wind are applied in the wind process simulation by the spectral representation method. In view of the spectral density functions, the characteristics of the simulated processes are compared. The ensemble spectral density functions constructed from the simulated sample processes are revealed to have the similarity not only in global shape but also in the maximum values with the target spectral density functions with a high accuracy. For the correlation structure to be satisfied in the circumferential direction on the cooling tower shell, a new formula is suggested based on the mathematical expression representing the circumferential distribution of the wind pressure on the cooling tower shell. The simulated wind processes are applied in the dynamic analysis of cooling tower shell in the time domain and the fluctuating stochastic behavior of the cooling tower shell is investigated.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.161-169
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• 2022

With the development of mobile devices and global positioning systems, various location-based services can be utilized, which collects user's location information and provides services based on it. In this process, there is a risk of personal sensitive information being exposed to the outside, and thus Geo-indistinguishability (Geo-Ind), which protect location privacy of LBS users by perturbing their true location, is widely used. However, owing to the data perturbation mechanism of Geo-Ind, it is hard to accurately obtain the density distribution of LBS users from the collection of perturbed location data. Thus, in this paper, we aim to develop a novel method which enables to effectively compute the user density distribution from perturbed location dataset collected under Geo-Ind. In particular, the proposed method leverages Expectation-Maximization(EM) algorithm to precisely estimate the density disribution of LBS users from perturbed location dataset. Experimental results on real world datasets show that our proposed method achieves significantly better performance than a baseline approach.

• Journal of the Korean School Mathematics Society
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• v.23 no.4
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• pp.509-521
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• 2020

This study began with the discovery of the concept of frequency density in Singapore textbooks and in a set of subject contents of the UK's General Certificate of Secondary Education. To understand the mathematical meaning of frequency density, the mathematical connection of frequency density was considered in terms of mathematics internal connections and mathematics external connections. In addition, the teaching method of frequency density was introduced. In terms of mathematical internal connections, the connections among the probability density function, relative frequency density, and frequency density in high school statistics were examined. Regarding mathematical external connections, the connection with the density concept in middle school science was analyzed. Based on the mathematical connection, the study suggested the need to introduce the frequency density concept. For the teaching method of frequency density, the Singapore secondary mathematics textbook was introduced. The Singapore textbook introduces frequency density to correctly represent and accurately interpret data in histograms with unequal class intervals. Therefore, by introducing frequency density, Korea can consistently teach probability density function, relative frequency density, and frequency density, emphasizing the mathematical internal connections among them and considering the external connections with the science subject. Furthermore, as a teaching method of frequency density, we can consider the method provided in the Singapore textbook.

• Proceedings of the KIEE Conference
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• summer
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• pp.1058-1060
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• 2004

This paper presents a characteristic analysis method for an air gap flux density of axial-flux type brushless dc (BLDC) motor. The magnetic flux density for the torque, and vertical force characteristics is calculated by using analytical method, based on the concept of magnetic charge. The calculated results by the presented method is compared with those by 3 dimensional finite element method (3D FEM). Using the presented method, the characteristics of single and double sided axial-flux type BLDC motors are investigated through distributions of air gap flux density.