• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.895-906
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• 2015

Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.329-341
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• 2008

Knowledge management has garnered attention due to its role of maintaining competitive advantage. Creating and sharing knowledge is an essential part of managing knowledge. However, the best knowledge is underutilized because employees tend to seek knowledge through their informal networks, not reach out to other sources for obtaining the best knowledge. Prior studies on informal networks pointed out a negative influence of heavy reliance on learning through informal networks but they paid little attention to a structure of informal networks and its impacts on diffusion of knowledge. The aim of our study is to show impacts of informal network on knowledge management by employing a network structure and investigating diffusion of knowledge within it. Our study found out that performance of learning becomes lower in a highly clustered network. Creating random links such as serendipitous learning can improve performance of knowledge management. When employees rely on a knowledge management system, creating random links is not necessary. Costs of adopting knowledge affect performance of knowledge management.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.523-528
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• 2004

This study proposed an anisotropic diffusion restoration fer image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.2
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• pp.194-200
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• 2002

A method for simulating flow of extremely low Reynolds number in a vortex-in-cell (VIC) was studied. The viscous diffusion was represented by the random walk method. The validity of this method was proven by applying it to the flows passing over a fence placed vertically at an extremely low Reynolds number. The effects of parameters of the VIC method on the random walk method, such as the number of point vortices, the mesh density and the time increment, were investigated by numerical analysis using a one-dimensional diffusion equation. Changes in the relative error of vorticity depending on those parameters were clarified.

• Bulletin of the Korean Chemical Society
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• v.35 no.10
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• pp.3089-3091
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• 2014

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• Bulletin of the Korean Chemical Society
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• v.32 no.9
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• pp.3521-3523
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• 2011

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.979-982
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• 2007

The effect of a scattering wall surfaces on sound diffusion can be assessed by determining the scattering and diffusion coefficients in the laboratory. However, the sound field in a concert hall including scattered reflections is different from the laboratory measurement condition. Therefore, there is a need for objective investigation of diffusion in real sound fields. In this paper, possible acoustical parameters of in-situ measurements are discussed.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.415-421
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• 2014

In this paper, we proposed problem and improvement of halftoning using random space filling curve. Random space filling curve is developed as a solution for shortcoming which space filling curve has self-similarity. It is used to reduce regular pattern can be occurred in constant brightness area in order that randomness apply to scanning path. But there is a problem that some area along scanning path can show too bright result in halftoning using random space filling curve. In this paper, we analyzed cause of problem and proposed single pixel error diffusion as a solution method. This method can avoid over-accumulated error and show better result in halftoning.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.43-47
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• 2000

We studied experimentally a discrete random phase-code multiplexing technique for holographic data storage, which we believe can overcome some disadvantages of conventional random phase-code multiplexing adopting either a diffusion plate or a multimode fiber. Experimental demonstration is presented to show the potential usefulness and some characteristics of the discrete random phase-code multiplexing technique.