• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.12
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• pp.1608-1615
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• 2004

CFD data compression methods based on Full-3D and Quasi-1D supercompact multiwavelets are presented. Supercompact wavelets method provide advantageous benefit that it allows higher order accurate representation with compact support. Therefore it avoids unnecessary interaction with remotely located data across singularities such as shock. Full-3D wavelets entails appropriate cross-derivative scaling function & wavelets, hence it can allow highly accurate multi-spatial data representation. Quasi-1D method adopt 1D multiresolution by alternating the directions rather than solving huge transformation matrix in Full-3D method. Hence efficient and relatively handy data processing can be conducted. Several numerical tests show swift data processing as well as high data compression ratio for CFD simulation data.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.7-9
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• 2002

위치 기반 서비스가 무선 인터넷의 새로운 이슈로 떠오르고 있다. 이동 객체의 패턴 마이닝은 이동 객체의 시간 패턴을 탐사함으로써 이동 객체에 위치에 기반한 유용한 서비스를 제공할 수 있게 해준다. 이동 객체는 시간에 따라 빈번하게 이동하기 때문에 패턴도 최근의 경향을 반영하기 위해 빈번하게 탐사되어야 한다. 따라서 점진적으로 시간 패턴을 탐사하는 접근법이 요구된다. 이 논문에서는 이동 객체의 시간 패턴을 탐사하는데 있어서 측정된 위치 데이터가 가질 수 있는 모호성을 제시했다. 또한 모호성을 고려한 시간 패턴 마이닝를 위해 패턴 탐사 단계에서의 모호성의 처리를 위해 모호성을 원인에 따라 세 가지 임계치를 정의하였다. 그리고 이러한 임계치를 고려한 시간 패턴 마이닝 프로시저 구조를 제시하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.150-155
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• 2012

POC(Phase-Only Correlation) is a useful method that can conduct face recognition without using feature extraction or eigenface, but uses Fourier transformation for square areas. In this paper, we propose an effective face area to increase the performance of face recognition using POC. Specifically, three areas are experimented for POC. The frist area is the square area that includes head and space. The second area is the square area from ear to ear horizontally and from the end of chin to the forehead vertically. The third area is the square area from the line under the lips to the forehead vertically and from cheek to cheek horizontally. Experimental results show that the second face area has the best advantage among the three types of areas to define the threshold for POC.

• Composites Research
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• v.36 no.6
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• pp.388-394
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• 2023

In composites manufacturing, increasing resin impregnation is a key way to speed up the manufacturing process and improve product quality. While resin improvement is important, simple fiber surface treatments can also improve resin flowability. In this study, different plasma treatment times were applied to carbon fiber fabrics to improve the impregnation between resin and fiber. Electrical resistivity measurements were used to evaluate the dispersion of resin in the fibers, which changed with plasma treatment. The effect of fiber surface treatment on resin spreadability could be observed in real time. When inserting a carbon fiber tow into the resin, the amount of resin that soaked into the tow was measured to objectively compare resin impregnation. Five minutes of plasma treatment improved the tensile and compressive strength of the composite by more than 50%, while reducing the void content and increasing the fire point impregnation flow rate. Finally, a dynamic flexural fatigue test was conducted using a portion of the composite used as an architectural composite part, and the composite part did not fail after one million cycles of a 3 kN load.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.27-35
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• 2003

Because of the lack of translation invariance of wavelet basis, traditional wavelet thresholding denoising leads to pseudo-Gibbs phenomena in the vicinity of discontinuities of signal. In this paper, in order to reduce the pseudo-Gibbs phenomena, wavelet coefficients are thresholded and reconstruction algorithm is implemented through minimizing the total variation of denoising signal using subgradient descent algorithm. Most of experiments were performed under the non-real-time and real-time environments. In the case of non-real-time experiments, the algorithm that this paper proposes was found more effective than that of wavelet hard thresholding denoising by 2.794㏈(SNR) based on the signal to noise ratio. And lots of pseudo-Gibbs phenomena was removed visually in the vicinity of discontinuities. In the case of real-time experiments, the number of iteration was restricted to 60 times considering the performance time. It took 0.49 seconds and most of the pseudo-Gibbs phenomena were also removed.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.585-594
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• 2004

When several service providers want to work together with only one master key, they need to properly distribute the key to participants who come in for the co-work business and then securely manage the distributed keys. This paper describes the system that can efficiently and securely manage the master key on the basis of the secret sharing scheme that can reconstruct original secret information as the necessity of reconstructing original secret arises. The proposed system can distribute secret information to several groups and also redistribute the secret to subgroup in proportion to the participant's security level using smart card-based (t, t)-(k, n)-threshold secret scheme for securely keeping secret information and authentication of participant's identification.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.128-134
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• 2014

In this paper, we propose a detection method of the leukocyte motions in a microvessel by using spatiotemporal image analysis. The leukocyte motions that adhere to blood vessel walls can be visualized to move along the blood vessel wall's contours in a sequence of images. In this proposal method, we use the constraint that the leukocytes move along the blood vessel wall's contours and detect the leukocyte motions by using the spatiotemporal image analysis method. The generated spatiotemporal image is processed by a special-purpose orientation-selective filter and then subsequent grouping processes are done. The subsequent grouping processes select and group the leukocyte trace segments among all the segments obtained by simple thresholding and skeletonizing operations. Experimental results show that the proposed method can stably detect the leukocyte motions even when multiple leukocyte traces intersect each other.

• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.124-130
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• 2007

Least squares ($l^2$ norm) solutions of seismic inversion tend to be very sensitive to data points with large errors. The $l^1$ norm minimization gives more robust solutions, but usually with higher computational cost. Iteratively reweighted least squares (IRLS) method gives efficient approximate solutions of these $l^1$ norm problems. I propose an efficient implementation of the IRLS method for a hybrid $l^1/l^2$ minimization problem that behaves as $l^2$ norm fit for small residual and $l^1$ norm fit for large residuals. The proposed algorithm shows more robust characteristics to the decision of the threshold value than the l1 norm IRLS inversion does with respect to the threshold value to avoid singularity.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.70-76
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• 2012

In this paper, an automatic extraction method of glomerulus region from human renal tissue image is presented. The important information reflecting the state of kidneys richly included in the glomeruli, so it should be the first step to extract the glomerulus region from the renal tissue image for the further quantitative analysis of the renal condition. Especially, there is no clear difference between the glomerulus and other tissues, so the glomerulus region can not be easily extracted from its background by the existing segmentation methods. The outer edge of a glomerulus region is regarded as a common property for the regions of this kind ; a two- dimensional Gaussian distribution is used to convolve with an original image first and then the image is thresholded at this blurred image ; a closed curve corresponding to the outer edge can be obtained by usual pattern processing skills like thinning, branch-cutting, hole-filling etc., Finally, the glomerulus region can be obtained by extracting the area in the original image surrounded by the closed curve. The glomerulus regions are correctly extracted by 85 percentages and experimental results show the proposed method is effective.