• 대한기계학회논문집B
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• 제27권5호
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• pp.635-643
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• 2003

Parametric study for the analysis of performance characteristics of a planar -type solid oxide fuel cell(SOFC) using computational flow analysis is conducted. A planar -type SOFC, which is composed by two gas channels (fuel and ai.) and one set of anode-electrolyte-cathode assembly, is modeled as a two -dimensional isothermal case. Results of computational analysis of flow field including distributions of mass fractions in gas channels are used to the performance analysis of the fuel cell. Flow analysis makes it possible to consider current density distributions along the length of the cell in the process of performance analysis of the SOFC. As results of parametric study, it is found that the mole fraction of fuel at the inlet of fuel channel, operating pressure and temperature are closely related to the performance characteristics of SOFC.

• 한국게임학회 논문지
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• 제8권3호
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• pp.23-30
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• 2008

게임 완성도 향상 및 수출 증가 등 게임산업 경쟁력 강화를 위해서 수요자들의 게임만족도가 일정한 수준에 도달해야 되며 이를 위하여 기존 또는 향후 개발되는 게임들의 만족도가 어느 정도 되는지를 평가할 수 있는 연구가 필요하다. 본 논문에서는 게임산업의 경쟁력과 부가가치를 높이기 위한 방안으로 게임만족도 요소들의 점수분포를 추정하는 방법을 연구하였다. 그리고 온라인 RPG 게임을 대상으로 얻은 설문자료에 근거하여 SAS/INSIGHT의 모수적 밀도함수 추정방법을 이용하여 만족도 요소들의 점수분포를 각각 정규분포로 추정하였다. 제안된 방법을 활용하여 기존 또는 향후 개발되는 게임들의 만족도 수준과 기준을 예측할 수 있는 기대효과를 얻을 수 있다.

• 한국멀티미디어학회논문지
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• 제19권11호
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• pp.1900-1908
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• 2016

Recent times have seen the introduction of modeling technologies using implicit surface and marching cubes algorithm in the field of computer graphics. Implicit surface modeling is used to express characters or fluid. This study presents a calculation method for the density of curve skeletal primitives using parametric curve and implements an implicit surface modeling tool by utilizing Maya API. Skeletal primitives can be assembled and utilized in character modeling using the implemented modeling tool. Results could be obtained more effectively compared to existing particle-based methods.

• Computers and Concrete
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• 제5권4호
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• pp.359-373
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• 2008

The present parametric study deals with the meso-scale modelling of concrete subjected to cyclic compression, which exhibits hysteresis loops during unloading and reloading. Concrete is idealised as a two-dimensional three-phase composite made of aggregates, mortar and interfacial transition zones (ITZs). The meso-scale modelling approach relies on the hypothesis that the hysteresis loops are caused by localised permanent displacements, which result in nonlinear fracture processes during unloading and reloading. A parametric study is carried out to investigate how aggregate density and size, amount of permanent displacements in the ITZ and the mortar, and the ITZ strength influence the hysteresis loops obtained with the meso-scale modelling approach.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2004년도 제29회 KOSCI SYMPOSIUM 논문집
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• pp.62-69
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• 2004

Zone conditional formulations for the Reynolds average reaction progress variable are used to derive an asymptotic expression for turbulent burning velocity. New DNS runs are performed for validation in a statistically one dimensional steady state configuration. Parametric study is performed with respect to turbulent intensity, integral length scale, density ratio and laminar flame speed. Results show good agreement between DNS results and the asymptotic expression in terms of measured maximum flame surface density and estimated turbulent diffusivity in unburned gas.

• 한국연소학회지
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• 제9권4호
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• pp.1-8
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• 2004

Zone conditional formulation for the Reynolds average reaction progress variable is used to derive an asymptotic expression for turbulent burning velocity. New DNS runs are performed for validation in a statistically one dimensional steady state configuration. Parametric study is performed with respect to turbulent intensity, integral length scale, density ratio and laminar flame speed. Results show good agreement between DNS results and the asymptotic expression in terms of measured maximum flame surface density and estimated turbulent diffusivity in unburned gas.

• 응용통계연구
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• 제25권6호
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• pp.1049-1058
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• 2012

Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

• Journal of the Korean Statistical Society
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• 제30권3호
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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.

• Journal of Information Processing Systems
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• 제16권1호
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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.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.607-617
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• 2003

This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.