• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.5
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• pp.231-238
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• 2006

This paper analysed the induced current density inside human body of hot-line worker for 765kV double circuit transmission line according to locations of human body. Human model was composed of several organs and other parts, whose shapes were expressed by spheroids or cylinders. Organs such as the brain, heart, lungs, liver and intestines were taken into account. Applying the 3 dimensional boundary element method, we calculated induced current density in case a worker was located inside and outside a lowest phase of 765 kV transmission line in which a 60% current of maximum load flowed. As results of study, we found a maximum induced current density in all organs was less than $10mA/m^2$ when a wonder was outside. As one in brain and heart was higher than $10mA/m^2$ when a worker was inside, we propose a method for lowering current density.

• 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.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.813-826
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• 2005

Regarding all particles at a fixed site as a cluster, the size of the largest cluster under the zero range invariant measures is well studied by Jeon et al.[5] for the case of density one. Here, the density of the finite zero-range process is given by the ratio between the number m of particles and the number n of sites. In this paper, we study the lower density case, i.e., the case m = o(n). Especially, when m ~ $n^{\beta}$,0 < ${\beta}$ < 1, we show that there is an interesting cutoff point around $\beta$ = 1/2.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.583-592
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• 2007

Given the moments of a symmetric random variable, its density and distribution functions can be accurately approximated by making use of the algorithm proposed in this paper. This algorithm is specially designed for approximating symmetric distributions and comprises of four phases. This approach is essentially based on the transformation of variable technique and moment-based density approximants expressed in terms of the product of an appropriate initial approximant and a polynomial adjustment. Probabilistic quantities such as percentage points and percentiles can also be accurately determined from approximation of the corresponding distribution functions. This algorithm is not only conceptually simple but also easy to implement. As illustrated by the first two numerical examples, the density functions so obtained are in good agreement with the exact values. Moreover, the proposed approximation algorithm can provide the more accurate quantities than direct approximation as shown in the last example.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1201-1206
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• 2004

This paper deals with the numerical analysis of natural convection flow induced by the density inversion effect of water inside horizontal pipe. The numerical method is based on SIMPLE/PWIM in general coordinate for its wide applicabilities. The numerical tool was validated through the comparison with the previous results concerning the density inversion effect of water It is shown that the developed numerical tool could predict the flow pattern and the heat transfer phenomena qualitatively And it is also found that the density inversion effect of water has significant effects on the flow pattern.

• Bulletin of the Korean Chemical Society
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• v.32 no.10
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• pp.3618-3623
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• 2011

This paper presents a stable isotope chemistry of bone collagen and carbonate. Bone carbonate has the potential to provide additional isotopic information. However, it remains controversial as to whether archaeological bone carbonate retains its original biogenic signature. I used a novel application of bone density fractionation and checked the integrity of ${\delta}^{13}C_{apa}$ values using radiocarbon dating. Diagenesis in archaeological bone carbonate still remains to be resolved in extracting biogenic information. The combined use of bone density fractionation and differential dissolution method shows a large shift in the ${\delta}^{13}C_{apa}$ values. Although ${\delta}^{13}C_{apa}$ values are improved in lighter density fractions, a large percentage of contamination in bone carbonate was reported via $^{14}C$ dating compared to that noted with bone collagen.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.461-465
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• 2004

This paper analysed the induced current density by electric field of human body under the 765 kV transmission line considering permittivity and conductivity. As permittivity of human body is very high as $10^6$ at 60 Hz, special numerical computation technique in Surface Charge Method(SCM) for composite media with extremely different properties is applied to reduce calculation error of induced current density and electric field inside the human body. Calculation results show that the average of the induced current density inside human body is about 3mA/$m^2$, which is less than ICNIRP criterion (10mA/$m^2$).

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.145-154
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• 2020

Maximum likelihood (ML) is the best estimator asymptotically as the number of training samples approaches infinity. This paper deduces an adaptive algorithm for blind signal processing problem based on gradient optimization criterion. A parametric density model is introduced through a parameterized generalized distribution family in ML framework. After specifying a limited number of parameters, the density of specific original signal can be approximated automatically by the constructed density function. Consequently, signal separation can be conducted without any prior information about the probability density of the desired original signal. Simulations on classical biomedical signals confirm the performance of the deduced technique.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.449-453
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• 2005

Electrochemical systems find widespread technical application. Industrial electrolytic process include electroplating, electroforming, and electropolishing. Electroforming and electroplating is widely used in the manufacture of metal parts. This paper based on the basic equations of electrics and electrochemical kinetics, was employed for a theoretical explanation of the current density distribution on electroforming process. We calculated current density distribution and potential distribution on cathode. Also, calculated current density distribution of vertical direction. It was shown that current density is related with distance of between anode and cathode and mass transfer process. And make an experiment on its relation and electroformed thickness. It shows that it is useful method using FEM with multi-physics to estimate electroformed thickness.

• 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.