• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.181-185
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• 1996

Color image is largely corrupted by various ambient illumination. However, human perceives always white color as white under any illumination because of a characteristic of human vision, called color constancy. In the conventional algorithm which applied the constancy effect, after the RGB color space is transformed to the IHS(Intensity, Hue, and Saturation) color space, then the hue is preserved and the intensity or the saturation is properly enhanced. Then the enhanced IHS color is reversely transformed to the RGB color space. In this process, the color distortion is included due to the color gamut error. But in the proposed algorithm, there is not transformation. In that, the RGB color is considered as 3 dimensional color vector and we assume that white color is the natural daylight. As the color vector of the illumination can be calculated as the average vector of R, G, and B image, we can achieve the constancy effect by simply rotating the illumination vector to the white color vector. The simulation results show the efficiency of the vector rotating process for color image enhancement.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.56-65
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• 2009

Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.323-343
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• 2020

With the rapid development of computer and communication techniques, copyright protection of vector geographic data has attracted considerable research attention because of the high cost of such data. A novel adaptive watermark detection algorithm is proposed for vector geographic data that can be used to qualitatively analyze the robustness of watermarks against data addition attacks. First, a watermark was embedded into the vertex coordinates based on coordinate mapping and quantization. Second, the adaptive watermark detection model, which is capable of calculating the detection threshold, false positive error (FPE) and false negative error (FNE), was established, and the characteristics of the adaptive watermark detection algorithm were analyzed. Finally, experiments were conducted on several real-world vector maps to show the usability and robustness of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.10
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• pp.46-52
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• 2009

A Multi-Core/Multi-Thread architecture is adopted for the Shader processor to enhance the processing performance. The Shader processor is designed to utilize its processing core IP for multiple purposes, such as Vertex-Shading, Rasterization, Pixel-Shading, etc. In this paper, we propose a 'Rasterization based on Vector Algorithm' that makes parallel pixels processing possible with Multi-Core and Multi-Thread architecture on the Shader Core. The proposed algorithm takes only 2% operation counts of the Scan-Line Algorithm and processes pixels independently.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1061-1066
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• 2002

This study proposes an analytic method that determines an optimal arrangement of absorptive materials on an enclosure surface. Under the optimal arrangement, a quiet zone in the enclosure has the minimum $\varepsilon$$\sub$p/ (acoustic potential energy density). The proposed method has been implemented by using a BEM simulation and a genetic algorithm. The BEM simulation evaluates the $\varepsilon$$\sub$p/ under the prescribed arrangement of the absorptive materials. The genetic algorithm searches the optimal arrangement by referring the ep evaluated from the BEM simulation. In the BEM simulation, the absorptive material arrangement is expressed as a vector, which is denoted as in absorptive material arrangement (AMA) vector. Besides, an admittance vector of which elements are admittances of available absorptive materials and an AMA matrix that transforms the admittance vector into the AMA vector are defined. The AMA matrix is also used as a chromosome in the genetic algorithm so that it functions to relate the BEM simulation to the genetic algorithm. As a verification example, the proposed method is applied to make the quiet zone in a parallelepiped enclosure.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1027-1036
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• 2018

In this paper a new generalized space vector pulse width modulation scheme is proposed based on the principle of reverse mapping to drive the switches of multilevel inverters. This projected scheme is developed based on the middle vector of the subhexagon which holds the tip of the reference vector, which plays a major role in mapping the reference vector. A new approach is offered to produce middle vector of the subhexagon which holds tip of the reference vector in the multilevel space vector plane. By using middle vector of the subhexagon, reference vector is linked towards the inner two level sub-hexagon. Then switching vectors, switching sequence and dwell times corresponding to a particular sector of a two-level inverter are determined. After that, by using the two level stage findings, the switching vectors related to exact position of the reference vector are directly generated based on principle of the reverse mapping approach and do not need to be found at n level stage. In the reverse mapping principle, the middle vector of subhexagon is added to the formerly found two level switching vectors. The proposed generalized algorithm is efficient and it can be applied to an inverter of any level. In this paper, the proposed scheme is explained for a five-level inverter and the performance is analyzed for five level and three level inverters through MATLAB. The simulation results are validated by implementing the propose scheme on a V/f controlled three-level inverter fed induction motor using dSPACE control desk.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.41-47
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• 2011

This paper is concerned with the DW-MCMA(Dual Weight vector Modified Constant Modulus Algorithm) adaptive equalization algorithm using the dual weight vector in order to improve the convergence characteristic and residual inter-symbol interference which are used as the performance index for an adaptive equalizer. The equalizer is used to reduce the distortion caused by the inter-symbol interference on the wireless and the wired band-limited channel that connect the transmitting system and receiving system. The CMA is widely known as the representative algorithm for equalization. In order to transmitting the mass information with a high speed through the channels, a fast convergence speed in the equalizer performance that is able to minimize overhead needed for equalization is acquired. In this paper, By the computer simulation, we confirmed that the proposed DW-MCMA has the faster convergence speed and the smaller residual inter-symbol interference than the conventional CMA and MCMA.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.69-85
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• 2006

Transductive Support Vector Machine(TSVM) is one of semi-supervised learning algorithms which exploit the domain structure of the whole data by considering labeled and unlabeled data together. Although it was proposed several years ago, there has been no efficient algorithm which can handle problems with more than hundreds of training examples. In this paper, we propose an efficient branch-and-bound algorithm which can solve large-scale TSVM problems with thousands of training examples. The proposed algorithm uses two bounding techniques: min-cut bound and reduced SVM bound. The min-cut bound is derived from a capacitated graph whose cuts represent a lower bound to the optimal objective function value of the dual problem. The reduced SVM bound is obtained by constructing the SVM problem with only labeled data. Experimental results show that the accuracy rate of TSVM can be significantly improved by learning from the optimal solution of TSVM, rather than an approximated solution.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.27-36
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• 2010

The paper proposes RFB(Record Filtering using Bit-vector) join algorithm, an in-network strategy that uses bit-vector to drastically reduce the size of data and hence the communication cost. In addition, by eliminating data not involved in join result prior to actual join, communication cost can be minimized since not all data need to be moved to the join nodes. The simulation result shows that the proposed RFB algorithm significantly reduces the number of bytes to be moved to join nodes compared to the popular synopsis join(SNJ) algorithm.