• Korean Journal of Applied Biomechanics
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• v.17 no.2
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• pp.83-91
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• 2007

This experiment studied the change in a human's control of his or her static posture by analyzing the stabilogram diffusion and, by using the said study, evaluated the control ability of different groups with different experiences. The postures had a rising requirement of heel-rise according to three conditions: heel-toe, ball, toe; the groups were divided into dance major student and non-dance majors. The results of the critical points according to posture did not show a direct relation with the change in postures that had a rising requirement of heel-rise. The diffusion coefficient(D) had greater stochastic activity for short-term regions that utilize open-loop controls without feedback than for long-term regions that used closed-loop controls with feedback to maintain balance. The directional results of the body undergoing disturbance showed that A/P direction's diffusion coefficient (D) was larger than that of M/L direction. Both feet's planar diffusion coefficients were a linear combination of the diffusion coefficients calculated for the x and y axis. In studying the different abilities to control posture between a dance major student and a non-dance majors, a comparison of open-loop control's diffusion coefficient(D) was effective, and dance major student had superior control ability to that of non-dance majors.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.519-536
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• 2005

The purpose of this paper is to propose several approximating methods to obtain the American option prices under jump-diffusion processes. The first method is to extend an approximating method to the optimal exercise boundary by a multipiece exponential function suggested by Ju [17]. The second approach is to modify the analytical methods of MacMillan [20] and Zhang [25] in a discrete time space. The third approach is to apply the simulation technique of Ibanez and Zapareto [14] to the problem of American option pricing when the jumps are allowed. Finally, we compare the numerical performance of each suggesting method with those of the previous numerical approaches.

• Journal of Mechanical Science and Technology
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• v.17 no.3
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• pp.440-448
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• 2003

In the present paper, numerical simulations of buoyant plume dispersion in a neutral and stable atmospheric boundary layer have been carride out. A Lagrangian Stochastic Model (LSM) with a Non-Linear Eddy Viscosity Model (NLEVM) for turbulence is used to generate a Reynolds stress field as an input condition of dispersion simulation. A modified plume-rise equation is included in dispersion simulation in order to consider momentum effect in an initial stage of plume rise resulting in an improved prediction by comparing with the experimental data. The LSM is validated by comparing with the prediction of an Eulerian Dispersion Model (EDM) and by the measured results of vertical profiles of mean concentration in the downstream of an elevated source in an atmospheric boundary layer. The LSM predicts accurate results especially in the vicinity of the source where the EDM underestimates the peak concentration by 40% due to inherent limitations of gradient diffusion theory. As a verification study, the LSM simulation of buoyant plume dispersions under a neutral and stable atmospheric condition is compared with a wind-tunnel experiment, which shows good qualitative agreements.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.801-811
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• 2008

Modeling financial phenomena with diffusion processes is a commonly used methodology in the area of modern finance. Recently, various types of diffusion models have been suggested to explain the specific financial processes, and their related inference methodology have been also developed. In particular, likelihood methods for the efficient and accurate inference have been explored in various ways. In this paper, we review the mathematical properties of an approximated likelihood method, which is obtained by linearizing the drift coefficient of a diffusion process.

• Journal of Korea Water Resources Association
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• v.37 no.11
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• pp.889-896
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• 2004

The fractal advection-diffusion equation (ADE) is a generalization of the classical AdE in which the second-order derivative is replaced with a fractal order derivative. While the fractal ADE have been analyzed with a stochastic process In the Fourier and Laplace space so far, in this study a fractal ADE for describing solute transport in rivers is derived with a finite difference scheme in the real space. This derivation with a finite difference scheme gives the hint how the fractal derivative order and fractal diffusion coefficient can be estimated physically In contrast to the classical ADE, the fractal ADE is expected to be able to provide solutions that resemble the highly skewed and heavy-tailed time-concentration distribution curves of contaminant plumes observed in rivers.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2788-2802
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• 2021

Multigroup cross section (MG XS) generation by the UNIST in-house Monte Carlo (MC) code MCS for fast reactor analysis using nodal diffusion codes is reported. The feasibility of the approach is quantified for two sodium fast reactors (SFRs) specified in the OECD/NEA SFR benchmark: a 1000 MW_th metal-fueled SFR (MET-1000) and a 3600 MW_th oxide-fueled SFR (MOX-3600). The accuracy of a few-group XSs generated by MCS is verified using another MC code, Serpent 2. The neutronic steady-state whole-core problem is analyzed using MCS/RAST-K with a 24-group XS set. Various core parameters of interest (core k_eff, power profiles, and reactivity feedback coefficients) are obtained using both MCS/RAST-K and MCS. A code-to-code comparison indicates excellent agreement between the nodal diffusion solution and stochastic solution; the error in the core k_eff is less than 110 pcm, the root-mean-square error of the power profiles is within 1.0%, and the error of the reactivity feedback coefficients is within three standard deviations. Furthermore, using the super-homogenization-corrected XSs improves the prediction accuracy of the control rod worth and power profiles with all rods in. Therefore, the results demonstrate that employing the MCS MG XSs for the nodal diffusion code is feasible for high-fidelity analyses of fast reactors.

• Journal of the Korean Society of Combustion
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• v.15 no.4
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• pp.15-21
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• 2010

The transported probability density function(PDF) model has been applied to simulate the turbulent nonpremixed piloted jet flame. To realistically account for the mixture fraction PDF informations on the turbulent non-premixed jet flame, the present Lagrangian PDF transport approach is based on the joint velocity-composition-turbulence frequency PDF formulation. The fluctuating velocity of stochastic fields is modeled by simplified Langevin model(SLM), turbulence frequency of stochastic fields is modeled by Jayesh-Pope model and effects of molecular diffusion are represented by the interaction by exchange with the mean (IEM) mixing model. To validate the present approach, the numerical results obtained by the joint velocity-composition-turbulence frequency PDF model are compared with experimental data in terms of the unconditional and conditional means of mixture fraction, temperature and species and PDFs.

• Publications of The Korean Astronomical Society
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• v.7 no.1
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• pp.51-61
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• 1992

The nonlinear stochastic behavior of chaotic inflation is characterized by the 'scaling' effect. Using a simple criterion for the appearance of scaling behavior in the ${\lambda}{\phi}^4$ inflation model, we show explicitly that in this limit the onset of the scaling regime does not require any special initial conditions and that it is independent of the self-coupling constant ${\lambda}$. Non-Gaussian statistics in adiabatic fluctuations are important only for super-horizon scales and the scaling regime does not lead to any significant statistical properties on currently observable scales. However, the scaling effect gives some cosmological consequences very different from what we expect in the naive diffusion approximation for quantum fluctuations. The classical (deterministic) treatment of the inflation field (essentially a quantum mechanical object.) becomes valid towards the end of inflation.

• Bulletin of the Korean Chemical Society
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• v.27 no.10
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• pp.1659-1663
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• 2006

A many-body master equation is constructed by incorporating stochastic terms responsible for chemical reactions into the many-body Smoluchowski equation. Two forms of Langevin-type of memory equations describing the time evolution of dynamical variables under the influence of time-independent perturbation with an arbitrary intensity are derived. One form is convenient in obtaining the dynamics approaching the steady-state attained by the perturbation and the other in describing the fluctuation dynamics at the steady-state and consequently in obtaining the linear response of the system at the steady-state to time-dependent perturbation. In both cases, the kinetics of statistical averages of variables is found to be obtained by analyzing the dynamics of time-correlation functions of the variables.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1344-1346
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• 1996

In this paper, we discuss an informal analysis of diffusion, global optimization properties of Langevine competitive learning neural network. In the view of the stochastic process, it is important that competitive learning gurantee an optimal solution for pattern recognition. We show that the binary reinforcement function in Langevine competitive learning is a brownian motion as Gaussian process, and construct the Fokker-Plank equation for the proposed neural network. Finally, we show that the informal analysis of the proposed algorithm has a possiblity of globally optimal. solution with the proper initial condition.