• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.13-22
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• 2000

We consider local likelihood method with a smoothed version of the model density in stead of an original model density. For simplicity a model is assumed as the log-linear density then we were able to show that the proposed local density estimator is less affected by changes among observations but its bias increases little bit more than that of the currently used local density estimator. Hence if we use the existing method and the proposed method in a proper way we would derive the local density estimator fitting the data in a better way.

• Journal of the Korean Ceramic Society
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• v.34 no.11
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• pp.1139-1150
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• 1997

A model for predicting the relative density and the compressive strength of open-cell ceramics with three-dimensional network structure was proposed through the interpretation of their macrostructure and fracture mechanics. The equation predicting the relative density was derived under the assumption that the open-cell structure was a periodic array of the tetrakaidecahedron unit cell consisting of cylindrical struts containing the internal hollow with the shape of a triangular prism. The model for compressive strength of open-cell ceramics with the hollow strut was also developed by modifying conventional model which based on fracture behavior of them subjected to the compressive stress. Both the relative density and the compressive strength were expressed in terms of the ratio of the strut diameter to the length together with the ratio of the hollow size to the strut diameter. The proposed model for the relative density and the compressive strength of the alumina-zirconia composite with open-cell structure were accorded well with the experimental values, whereas Gibson-Ashby and Zhang's model did not show such a good agreement.

• Korean Management Science Review
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• v.32 no.3
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• pp.29-36
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• 2015

In this research, we analyze the sensitivity of the network density to the estimates for the Bass model parameters with both theoretical model and a simulation. Bass model describes the process that the non-adopters in the market potential adopt a new product or an innovation by the innovation effect and imitation effect. The imitation effect shows the word of mouth effect from the previous adopters to non-adopters. But it does not divide the underlying network structure from the strength of the influence over the network. With a network based Bass model, we found that the estimate for the imitation coefficient is highly sensitive to the network density and it is decreasing while the network density is decreasing. This finding implies that the interpersonal influence can be under-looked when the network density is low. It also implies that both of the network density and the interpersonal influence are important to facilitate the diffusion of an innovation.

• Korean Journal of Mathematics
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• v.17 no.4
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• pp.399-409
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• 2009

We study the weak convergence of various models to Fractional Brownian motion. First, we consider arima process and ON/OFF source model which allows for long packet trains and long inter-train distances. Finally, we figure out power spectrum density as a Fourier transform of autocorrelation function of arima model and binary signal model.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.507-514
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• 1998

The minimum distance estimation based on the L$_2$ distance between a model density and a density estimator is studied from M-estimation point of view. We will show that how a model density and a density estimator are incorporated in order to create an M-estimation function. This method enables us to create an M-estimating function reflecting the natures of both an assumed model density and a given set of data. Some new types of M-estimation functions for estimating a location and scale parameters are introduced.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• Economic and Environmental Geology
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• v.27 no.5
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• pp.479-489
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• 1994

In this paper, the iterative least-squares inversion method is used to determine shapes and density contrasts of 2-D structures from the gravity data. The 2-D structures are represented by their cross-sections of N-sided polygons with density contrasts which are constant or varying with depth. Gravity data are calculated by theoretical formulas for the above structure models. The data are considered as observed ones and used for inversions. The inversions are performed by the following processes: I) polygon's vertices and density contrast are initially assumed, 2) gravity are calculated for the assumed model and error between the true (observed) and calculated gravity are determined, 3) new vertices and density contrast are determined from the error by using the damped least-squares inversion method, and 4) final model is determined when the error is very small. Results of this study show that the shape and density contrast of each model are accurately determined when the density contrast is constant or vertical density gradient is known. In case where the density gradient is unknown, the inversion gives incorrect results. But the shape and density gradient of the model are determined when the surface density contrast is known.

• Proceedings of the Korean System Dynamics Society
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• 2003.08a
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• pp.1-24
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• 2003

The purpose of this paper was developing a development density control model for urban growth management, using system dynamics modeling. The density control model was developed to see how urban growth, transition, and decay occur depending on the interaction among population, houses, industry structure, land and urban infrastructure such as road, water supply, and sewage treatment facilities. Suggesting adequate level of development density control using the model was another purpose of this paper. The model was applied to An'yang city to estimate the maximum number of population, industry structures, houses, and cars that can be adequately sustained with the current An'yang city's infrastructur capacity. The computer simulation results shows that the city is overpopulated by some 90,000 people. To reduce the population to the adequate level that the current urban infrastructure can sustain, the current city regulation on floor area ratio are needed to be strengthened at least 20 to 35%.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.493-502
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• 2020

The prediction of soil response under repetitive mechanical loadings remains challenging in geotechnical engineering applications. Modeling the cyclic soil response requires a robust model validation with an experimental dataset. This study proposes a unique method adopting linearity of model constant with the number of cycles. The model allows the prediction of the terminal density of sediments when subjected to repetitive changes in pore-fluid pressure based on the two-surface plasticity. Model simulations are analyzed in combination with an experimental dataset of sandy sediments when subjected to repetitive changes in pore fluid pressure under constant deviatoric stress conditions. The results show that the modified plastic moduli in the two-surface plasticity model appear to be critical for determining the terminal density. The methodology introduced in this study is expected to contribute to the prediction of the terminal density and the evolution of shear strain at given repetitive loading conditions.

• Bulletin of the Korean Chemical Society
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• v.24 no.12
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• pp.1742-1750
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• 2003

In order to characterize the hydrophobic parameters of N-acetyl amino acid amides in 1-octanol/water, a theoretical calculation was carried out using a solvation free energy density model. The hydrophobicity parameters of the molecules are obtained with the consideration of the solvation free energy over the solvent volume surrounding the solute, using a grid model. Our method can account for the solvent accessible surface area of the molecules according to conformational variations. Through a comparison of the hydrophobicity of our calculation and that of other experimental/theoretical works, the solvation free energy density model is proven to be a useful tool for the evaluation of the hydrophobicity of amino acids and peptides. In order to evaluate the solvation free energy density model as a method of calculating the activity of drugs using the hydrophobicity of its building blocks, the contracture of Bradykinin potentiating pentapeptide was also predicted from the hydrophobicity of each residue. The solvation free energy density model can be used to employ descriptors for the prediction of peptide activities in drug discovery, as well as to calculate the hydrophobicity of amino acids.