• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.2
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• pp.100-105
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• 1989

This paper presents an adaptive finite element method for magnetostatic force computation using Maxwell's stress tensor. Mesh refinements are performed automatically by interelement magnetic field intensity discontinuity errors and element force errors. In initial mesh, the computed forces for different integration paths give great differences, but converge to a certain value as mesh division is performed by the adaptive scheme, We obtained good agreement between analytic solutions and numerical values in typical examples.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.723-738
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• 2020

In this paper, we study a method to discriminate between trend stationary and difference stationary processes. Since a crucial ingredient of this discrimination is to determine the existence of unit root, we can use a unit root testing strategy. So, we introduce a discrimination based on unit root testing and propose the method using the adaptive lasso. Our Monte Carlo simulation experiments show that the adaptive lasso improves the discrimination accuracy when the process is trend stationary, but has lower accuracy than unit root strategy where the process is difference stationary.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.915-922
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• 2014

We propose an adaptive zoom motion estimation method where a picture is divided into two areas based on the distance information with a depth camera : the one is object area and the other is background area. In the proposed method, the zoom motion is only applied to the object area except the background area. Further, the block size of motion estimation for the object area is set to smaller than that of background area. This adaptive zoom motion estimation method can be reduced at the complexity of motion estimation and can be improved at the motion estimation performance by reducing the block size of the object area in comparison with the conventional zoom motion estimation method. Based on the simulation results, the proposed method is compared with the conventional methods in terms of motion estimation accuracy and computational complexity.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.539-551
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• 2018

Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.334-336
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• 2008

A novel adaptive mesh refinement (AMR) strategy based on the Moment-of-Fluid (MOF) method for volume-tracking dynamic interface computation is presented. The Moment-of-Fluid method is a new interface reconstruction and volume advection method using volume fraction as well as material centroid. The mesh refinement is performed based on the error indicator, the deviation of the actual centroid obtained by interface reconstruction from the reference centroid given by moment advection process. Using the AMR-MOF method, the accuracy of volume-tracking computation with evolving interfaces is improved significantly compared to other published results.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.334-336
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• 2008

A novel adaptive mesh refinement (AMR) strategy based on the Moment-of-Fluid (MOF) method for volume-tracking dynamic interface computation is presented. The Moment-of-Fluid method is a new interface reconstruction and volume advection method using volume fraction as well as material centroid. The mesh refinement is performed based on the error indicator, the deviation of the actual centroid obtained by interface reconstruction from the reference centroid given by moment advection process. Using the AMR-MOF method, the accuracy of volume-tracking computation with evolving interfaces is improved significantly compared to other published results.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.177-184
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• 2020

In this paper, we studied to direction of arrival (DoA) estimation to use DoA and optimum weight algorithms in coherent interference channels. The DoA algorithm have been considerable attention in signal processing with coherent signals and a limited number of snapshots in a noise and an interference environment. This paper is a proposed method for the desired signal estimation using MUSIC algorithm and adaptive beamforming to compare classical subspace techniques. Also, the proposed method is combined the updated weight value with LCMV beamforming algorithm in adaptive antenna array system for direction of arrival estimation of desired signal. The proposed algorithm can be used with combination to MUSIC algorithm, linearly constrained minimum variance beamforming (LCMV) and the weight value method to accurately desired signal estimation. Through simulation, we compare the proposed method with classical direction of in order to desired signals estimation. We show that the propose method has achieved good resolution performance better that classical direction arrival estimation algorithm. The simulation results show the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1614-1623
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• 1995

In this paper we propose a region-adaptive CELP image coder for still images at low bit rates below 0.5 bpp. The proposed method partitions the image into stochastically similar regions by the minimum spanning tree method and finds prediction coefficients for each region using a 2- dimensional linear prediction model. Coding is carried out on 8$\times$8 blocks and when there are several regions included in a block, an image is synthesized using the prediction coefficients of each region. Computer simulation results show that the proposed method allows improved synthesized image over conventional block-adaptive CELP methods, especially at edges. In addition, performance comparison with the JPEG DCT method shows that while the JPEG method shows block distortion and staircase effects (ragged edges) at bit rates below 0.5 bpp, the proposed CELP method shows improved synthesized images with such effects reduced.

• Journal of Mechanical Science and Technology
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• v.18 no.10
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• pp.1837-1848
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• 2004

Interaction behaviors of high-speed compressible viscous flow and thermal-structural response of structure are presented. The compressible viscous laminar flow behavior based on the Navier-Stokes equations is predicted by using an adaptive cell-centered finite-element method. The energy equation and the quasi-static structural equations for aerodynamically heated structures are solved by applying the Galerkin finite-element method. The finite-element formulation and computational procedure are described. The performance of the combined method is evaluated by solving Mach 4 flow past a flat plate and comparing with the solution from the finite different method. To demonstrate their interaction, the high-speed flow, structural heat transfer, and deformation phenomena are studied by applying the present method to Mach 10 flow past a flat plate.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.501-509
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• 2011

In this paper, we propose an edge profile adaptive bi-directional diffusion interpolation method which consists of shock filter and level set. In recent years many interpolation methods have been proposed but all methods have some degrees of artifacts such as blurring and jaggies. To solve these problems, we adaptively apply shock filter and level set method where shock filter enhances edge along the normal direction and level set method removes jaggies artifact along the tangent direction. After the initial interpolation, weights of shock filter and level set are locally adjusted according to the edge profile. By adaptive coupling shock filter with level set method, the proposed method can remove jaggies artifact and enhance the edge. Experimental results show that the average PSNR and MSSIM of our method are increased, and contour smoothness and edge sharpness are also improved.