• 제목/요약/키워드: region embedding

검색결과 48건 처리시간 0.027초

스펙트럴 영역분할 격자 삽입법을 이용한 채널유동의 큰 에디 모사 (Large-eddy simulation of channel flow using a spectral domain-decomposition grid-embedding technique)

  • 강상모;변도영;백승욱
    • 대한기계학회논문집B
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    • 제22권7호
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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.

곡선 부-분할 보간과 Neighbor Embedding 기반의 복합 초고해상도 기법 (Hybrid Super Resolution Based on Curve Subdivision Interpolation and Neighbor Embedding)

  • 오의열;이용건;이지은;최윤식
    • 전기학회논문지
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    • 제64권9호
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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.

비만치료를 위한 매선요법의 중복시술 효과 5례 (The Duplicate Effect of Thread-embedding Therapy on 5 Patients with Obesity)

  • 신화영;임성철;이윤규;권효정;정태영;이봉효;김재수
    • Journal of Acupuncture Research
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    • 제29권1호
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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.

Adaptive Watermark Detection Algorithm Using Perceptual Model and Statistical Decision Method Based on Multiwavelet Transform

  • Hwang Eui-Chang;Kim Dong Kyue;Moon Kwang-Seok;Kwon Ki-Ryong
    • 한국멀티미디어학회논문지
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    • 제8권6호
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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.

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A Generalized Image Interpolation-based Reversible Data Hiding Scheme with High Embedding Capacity and Image Quality

  • Tsai, Yuan-Yu;Chen, Jian-Ting;Kuo, Yin-Chi;Chan, Chi-Shiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권9호
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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.

방사선 검출신호의 시계열 분석에 관한 연구 (A Study on Time Series Analysis for the Detector Pulses of Radiation)

  • 홍석붕;정종은;김용균;문병수;권기호
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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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.

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의료 영상을 위한 추정오차 히스토그램 기반 가역 워터마킹 알고리즘 (Reversible Watermarking based on Predicted Error Histogram for Medical Imagery)

  • 오기태;장한별;도엄지;이해연
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제4권5호
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    • pp.231-240
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    • 2015
  • 의료 영상은 원본 콘텐츠의 품질을 유지하는 것이 중요한 동시에 사생활 보호의 요구가 증가함에 따라서 가역 워터마킹 기술에 대한 필요성이 증가하고 있다. 기존의 가역 워터마킹 알고리즘은 의료 영상이 아닌 일반 영상에서는 고용량 고품질을 유지할 수 있으나 영상 전체에 왜곡을 야기한다. 따라서 촬영 대상물의 품질 유지가 중요한 의료 영상에 직접적으로 적용하기에는 부적합하다는 단점을 가진다. 본 논문에서는 의료 영상의 촬영 대상물 영역의 영상 품질을 유지하며, 워터마크를 효율적으로 삽입할 수 있는 가역 워터마킹 알고리즘을 제안한다. 먼저 대상물과 배경 영역을 분할하기 위한 알고리즘을 설계하고, 그 후에 분할된 대상물과 배경에 대해 추정오차 히스토그램에 기반하여 가역 워터마킹 기법을 적용한다. 대상물 영역에는 삽입 레벨을 낮게 설정하고, 배경 영역에 삽입 레벨을 높게 설정함으로써 대상물의 화질은 최소한으로 변형을 하며 효율적인 삽입이 가능하도록 하였다. 실험에서 다양한 의료 영상에 대하여 제안한 알고리즘을 기존 추정오차 히스토그램 기반 가역 워터마킹 기술과 삽입 용량 및 영상 품질에 대한 비교를 수행하였고, 그 결과 제안하는 알고리즘이 기존 알고리즘에 비해 높은 영상 품질을 유지하면서 우수한 삽입 용량을 얻을 수 있었다.

Algorithm for stochastic Neighbor Embedding: Conjugate Gradient, Newton, and Trust-Region

  • Hongmo, Je;Kijoeng, Nam;Seungjin, Choi
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (2)
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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.

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Adaptive Image Watermarking Using a Stochastic Multiresolution Modeling

  • Kim, Hyun-Chun;Kwon, Ki-Ryong;Kim, Jong-Jin
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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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.

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Content Adaptive Watermarkding Using a Stochastic Visual Model Based on Multiwavelet Transform

  • Kwon, Ki-Ryong;Kang, Kyun-Ho;Kwon, Seong-Geun;Moon, Kwang-Seok;Lee, Joon-Jae
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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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.

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