• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.422-425
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• 2004

This paper develops an octree-based algorithm for machining simulation. Most commercial machining simulators are based on the Z map model, which has several limitations in terms of achieving a high level of precision in five-axis machining simulation. Octree representation being a three-dimensional (3D) decomposition method, an octree-based algorithm is expected to be able to overcome such limitations. With the octree model, storage requirement is reduced. Moreover, recursive subdivision is processed in the boundaries, which reduces useless computations. The supersampling method is the most common form of antialiasing and is typically used with polygon mesh rendering in computer graphics. The supersampling technique is being used to advance the efficiency of the octree algorithm..

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.9-15
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• 2012

Thermal model reduction algorithms and techniques are introduced to condense a huge satellite panel thermal model into the simplified model on the purpose of calculating the thermal responses of a satellite on orbit. Guyan condensation algorithm with the substitution matrix manipulation is developed and the mathematical procedure is depicted step by step. A block-form LU decomposition method is also invited to compare the developed algorithm. The constructed reduced thermal model induced from the detailed model based on a real satellite panel is satisfying the correlation criterion of ${\pm}2^{\circ}C$ for the validity accuracy. Guyan condensation algorithm is superior to the block-form LU decomposition method on computation time.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.405-416
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• 2011

An efficient two-level domain decomposition parallel algorithm is suggested to solve large-DOF structural problems with nonlinear material models generating unsymmetric tangent matrices, such as a group of plastic-damage material models. The parallel version of the stabilized bi-conjugate gradient method is developed to solve unsymmetric coarse problems iteratively. In the present approach the coarse DOF system is solved parallelly on each processor rather than the whole system equation to minimize the data communication between processors, which is appropriate to maintain the computing performance on a non-supercomputer level cluster system. The performance test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF nonlinear structural problems on a cluster system.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.3
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• pp.171-178
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• 2013

In this paper, we implement the Faddev-Leverier algorithm using GPGPU (General-Purpose Graphics Processing Unit) to accelerate singular value decomposition. In addition, we compare the performance of the algorithm using CPU and CPU plus GPGPU for eleven ${\times}n$ matrix sizes in order to decompose singular values, where =4, 8, 16, 32, 64, 128, 256, 512, 1,024, 2,048, and 4,096. Experimental results indicate that CPU achieves better performance than CPU plus GPGPU for $n{\leq}64$ because of a large number of read and write operations between CPU and GPGPU. However, CPU plus GPGPU outperforms CPU exponentially in the execution time for $n{\geq}64$.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.204-211
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• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1167-1174
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• 1999

In this paper, we present a new technique for the local decomposition of convex structuring elements for morphological image processing. Local decomposition of a structuring element consists of local structuring elements, in which each structuring element consists of a subset of origin pixel and its eight neighbors. Generally, local decomposition of a structuring element reduces the amount of computation required for morphological operations with the structuring element. A unique feature of our approach is the use of linear integer programming technique to determine optimal local decomposition that guarantees the minimal amount of computation. We defined a digital convex polygon, which, in turn, is defined as a convex structuring element, and formulated the necessary and sufficient conditions to decompose a digital convex polygon into a set of basis digital convex polygons. We used a set of linear equations to represent the relationships between the edges and the positions of the original convex polygon, and those of the basis convex polygons. Further. a cost function was used represent the total processing time required for computation of dilation/erosion with the structuring elements in a decomposition. Then integer linear programming was used to seek an optimal local decomposition, that satisfies the linear equations and simultaneously minimize the cost function.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1046-1057
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• 2004

An image enhancement method using both homomorphic transformation and multiscale decomposition is proposed. The original image is first transformed to homomorphic domain by taking the logarithm, is then separated to multiscales. These multiscales are combined with weighting. The combined signal is exponentially transformed back into intensity domain. In homomorphic domain, the magnitude control of low frequency component make change the dynamic range, and the magnitude control of the other frequency components contribute to enhancement of the contrast. The "${\AA}$ trous" algorithm, which has a simple and efficient scheme, is used for multiscale decomposition. The performance of proposed method is verified by simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1419-1424
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• 1999

In order to implement morphological filters on image processing systems, the size of structuring element must be small due to the architectural constraints of the systems, which requires the decomposition of structuring element into small elements for the filters with large structuring elements. In this paper, an algorithm for decomposition of structuring element with no restriction on the shape and size is developed which enables sub-optimal implementation of any morphological filter on 3X3 pipeline machine. The given structuring element is first decomposed into the union of elements using sequential search procedure, then each element is further decomposed optimally into 3X3 elements, resulting in final sub-optimal 3$\times$3 hybrid decomposition. The proposed algorithm is applied to some structuring elements and the results close to the optimum are obtained.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.29-36
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• 2012

The existing solar tracking sensor for 2 axial control system to trace latitude and longitude is made of four phototransistor. The phototransistor-making is difficult and it's manufacturing is more high-priced than a wide use phototransistor because they have to the same characteristics of each phototransistor output signal. This paper described the algorithm for supplement these weakness. The algorithm applied to signal normalizing method and vector decomposition law. The deviations of each a wide use phototransistor output signal are resolved by signal normalizing method and it is able to make a solar tracking sensor using three phototransistor by vector decomposition law. Therefore, in this paper, it is reduced the number of phototransistor that is composed of solar tracking sensor and possible to use a wide use phototransistor by the proposed algorithm.