• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.7
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• pp.1030-1040
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• 1998

One of the main unresolved issues in large-eddy simulation(LES) of wall-bounded turbulent flows is the requirement of high spatial resolution in the near-wall region, especially in the spanwise direction. Such high resolution required in the near-wall region is generally used throughout the computational domain, making simulations of high Reynolds number, complex-geometry flows prohibitive. A grid-embedding strategy using a nonconforming spectral domain-decomposition method is proposed to address this limitation. This method provides an efficient way of clustering grid points in the near-wall region with spectral accuracy. LES of transitional and turbulent channel flow has been performed to evaluate the proposed grid-embedding technique. The computational domain is divided into three subdomains to resolve the near-wall regions in the spanwise direction. Spectral patching collocation methods are used for the grid-embedding and appropriate conditions are suggested for the interface matching. Results of LES using the grid-embedding strategy are promising compared to LES of global spectral method and direct numerical simulation. Overall, the results show that the spectral domain-decomposition grid-embedding technique provides an efficient method for resolving the near-wall region in LES of complex flows of engineering interest, allowing significant savings in the computational CPU and memory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1369-1373
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• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.

• Journal of Acupuncture Research
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• v.29 no.1
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• pp.61-66
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• 2012

Objectives : The purpose of this study was to examine the duplicate effect of thread-embedding therapy against obesity. Methods : 5 women from 20 to 30 with obesity were treated with thread-embedding therapy and compared the results with physical measurement, body composition tests and fat thickness measured by ultrasound. Results : The thread-embedding therapy locally reduced body size and fat thickness and had a cumulative effect, but showed the greatest effect in the abdominal region. It didn't affect to the overall change of body composition. Conclusions : The duplicate procedure of thread-embedding therapy for obesity had a cumulative effect, but it depended on the treatment region.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.783-789
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• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3286-3301
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• 2014

Jung and Yoo proposed the first image interpolation-based reversible data hiding algorithm. Although their algorithm achieved superior interpolation results, the embedding capacity was insufficient. Lee and Huang proposed an improved algorithm to enhance the embedding capacity and the interpolation results. However, these algorithms present limitations to magnify the original image to any resolution and pixels in the boundary region of the magnified image are poorly manipulated. Furthermore, the capacity and the image quality can be improved further. This study modifies the pixel mapping scheme and adopts a bilinear interpolation to solve boundary artifacts. The modified reference pixel determination and an optimal pixel adjustment process can effectively enhance the embedding capacity and the image quality. The experimental results show our proposed algorithm achieves a higher embedding capacity under acceptable visual distortions, and can be applied to a magnified image at any resolution. Our proposed technique is feasible in reversible data hiding.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.282-282
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• 2000

The analysis of the radiation effect on matter has been performed using stochastic methods. Recently, It was discovered that the detector pulses of radiation can be analysed using deterministic method that utilizes the chaotic behaviour with an attractor found in a noise region. We acquired a time series for pulse tram of Am-241 using scintillation detector and reconstructed a phase space, then performed new analysis for the radiation detection signal by applying embedding theory, Lyapunov exponent, correlation dimension, autocorrelation dimension, and power spectrum.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.231-240
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• 2015

Medical imagery require to protect the privacy with preserving the quality of the original contents. Therefore, reversible watermarking is a solution for this purpose. Previous researches have focused on general imagery and achieved high capacity and high quality. However, they raise a distortion over entire image and hence are not applicable to medical imagery which require to preserve the quality of the objects. In this paper, we propose a novel reversible watermarking for medical imagery, which preserve the quality of the objects and achieves high capacity. First, object and background region is segmented and then predicted error histogram-based reversible watermarking is applied for each region. For the efficient watermark embedding with small distortion in the object region, the embedding level at object region is set as low while the embedding level at background region is set as high. In experiments, the proposed algorithm is compared with the previous predicted error histogram-based algorithm in aspects of embedding capacity and perceptual quality. Results support that the proposed algorithm performs well over the previous algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.697-699
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• 2004

Stochastic Neighbor Embedding(SNE) is a probabilistic method of mapping high-dimensional data space into a low-dimensional representation with preserving neighbor identities. Even though SNE shows several useful properties, the gradient-based naive SNE algorithm has a critical limitation that it is very slow to converge. To overcome this limitation, faster optimization methods should be considered by using trust region method we call this method fast TR SNE. Moreover, this paper presents a couple of useful optimization methods(i.e. conjugate gradient method and Newton's method) to embody fast SNE algorithm. We compared above three methods and conclude that TR-SNE is the best algorithm among them considering speed and stability. Finally, we show several visualizing experiments of TR-SNE to confirm its stability by experiments.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.172-175
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• 2002

This paper presents perceptual model with a stochastic rnultiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the SSQ(successive subband quantization). The watermark embedding is based on the computation of a NVF(noise visibility function) that have local image properties. This method uses non-stationary Gaussian model stationary Generalized Gaussian model because watermark has noise properties. In order to determine the optimal NVF, we consider the watermark as noise. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model use the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark benchmark test.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1511-1514
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• 2002

This paper presents content adaptive image watermark embedding using stochastic visual model based on multiwavelet transform. To embedding watermark, the original image is decomposed into 4 levels using a discrete multiwavelet transform, then a watermark is embedded into the JND(just noticeable differences) of the image each subband. The perceptual model is applied with a stochastic approach fer watermark embedding. This is based on the computation of a NVF(noise visibility function) that have local image properties. The perceptual model with content adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the JND. This method uses stationary Generalized Gaussian model characteristic because watermark has noise properties. The experiment results of simulation of the proposed watermark embedding method using stochastic visual model based on multiwavelet transform techniques was found to be excellent invisibility and robustness.