• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.175-183
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• 2015

The proposed algorithm consists of two stages: the learning and synthesis stages. At the learning stage, we first collect various high-resolution (HR)-low-resolution (LR) text image pairs, and quantize the LR images, and extract HR-LR block pairs. Based on quantized LR blocks, the LR-HR block pairs are clustered into a pre-determined number of classes. For each class, an optimal 2D-FIR filter is computed, and it is stored into a dictionary with the corresponding LR block for indexing. At the synthesis stage, each quantized LR block in an input LR image is compared with every LR block in the dictionary, and the FIR filter of the best-matched LR block is selected. Finally, a HR block is synthesized with the chosen filter, and a final HR image is produced. Also, in order to cope with noisy environment, we generate multiple dictionaries according to noise level at the learning stage. So, the dictionary corresponding to the noise level of the input image is chosen, and a final HR image is produced using the selected dictionary. Experimental results show that the proposed algorithm outperforms the previous works for noisy images as well as noise-free images.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.835-842
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• 2008

The response surface method (RSM) is widely adopted for the structural reliability analysis because of its numerical efficiency. However, the RSM is still time consuming for large-scale applications and sometimes shows large errors in the calculation of sensitivity of reliability index with respect to random variables. Therefore, this study proposes a new RSM in which moving least squares (MLS) approximation is applied. Least squares approximation generally used in the common RSM gives equal weight to the coefficients of the response surface function (RSF). On the other hand, The MLS approximation gives higher weight to the experimental points closer to the design point, which yields the RSF more similar to the limit state at the design point. In the procedure of the proposed method, a linear RSF is constructed initially and then a quadratic RSF is formed using the axial experimental points selected from the reduced region where the design point is likely to exist. The RSF is updated successively by adding one more experimental point to the previously sampled experimental points. In order to demonstrate the effectiveness of the proposed method, mathematical problems and ten-bar truss are considered as numerical examples. As a result, the proposed method shows better accuracy and computational efficiency than the common RSM.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.1
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• pp.79-88
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• 1997

Very stiff floor system in a residential-commercial building causes some problems in the numerical analysis procedure due to significant difference in stiffness with adjacent elements. Static analysis of structure with a stiff transfer-floor can be performed approximately in two steps for upper and lower parts for the structure. However, it is impossible to perform dynamic analysis in two steps with separate models. An efficient method for dynamic analysis of a structure with a right floor system is proposd in this study. The matrix condensation technique is employed to reduce the degree of freedom for upper and lower parts of the structure and a beam elements with rigid bodies at both ends are introduce to model the rigid floor system. Efficiency and accuracy of the proposed method are verified through analysis of several example structures.

• Computational Structural Engineering
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• v.5 no.1
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• pp.75-82
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• 1992

In the h-version of F.E.M., all piecewisely smooth curved boundaries can be approximated by a sufficient number of straight-sided elements. However, in the p-version the size of the element is usually large and hence the probability of distortions is more. An attempt has been made to generate a curved boundary by using a transfinite interpolation technique to avoid the discretization errors. In the following sections, it will be shown how to construct transfinite interpolants both in h-version and in p-version over polygonal and nonpolygonal regions. Three numerical tests are shown to validate the applicability and superior capability of transfinite interpolation technique.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.12
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• pp.566-574
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• 2002

In this paper, the scattered field from a perfectly conducting fractal surface by the Monte-Carlo moment method was computed. An one-dimensional fractal surface was generated by using the fractional Brownian motion model. Back scattering coefficients are calculated with different values of the spectral parameter(S$\_$0/), and fractal dimension(D) which determine characteristics of the fractal surface. The number of surface realization for the computed field, the point number, and the width of surface realization are set to be 80, 2048, and 64L, respectively. In order to verify the computed results these results are compared with those of small perturbation methods, which show good agreement between them.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.214-221
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• 2015

In this paper, we present robust estimation and detection algorithms for discrete-time switched linear systems whose output measurements are corrupted by noises. First, a mode estimation algorithm is proposed based on the minimum distance criterion. Then, state variables are also observed under the active mode estimate. Second, a detection algorithm is constructed to detect the mode switching of the switched system. With the boundedness of measurement noise, the proposed estimation algorithm returns the exact active mode and approximate state information of the switched system. In addition, the detection algorithm can detect the switching time within a pre-determined time interval after the actual switching occurred.

• Journal of Korea Water Resources Association
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• v.50 no.5
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• pp.289-302
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• 2017

DFB (Divergence Form for Bed slope source term) was rigorously derived and the error of mDFB using mean water depth at the cell face in DFB was clearly demonstrated. In addition, DFB technique turned out to be an exact method to the bed slope source term. The existing volume/free-surface relationship to the PSC (Partially Submerged Cell) has been corrected. It was discussed that treatment for the partially submerged edge is required to satisfy the C-property in PSC. It is expected that this study will provides a more accurate means in analyzing the shallow water equations with the approximate Riemann solver.

• The KSFM Journal of Fluid Machinery
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• v.16 no.1
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• pp.24-31
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• 2013

The motion of living organisms such as birds, fishes, and insects, has been analyzed for the purpose of the design of MAV(Micro Air Vehicle) and NAV(Nano Air Vehicle). In this research, natural motion was considered to be applied to the determination of the geometry and motion of AUV(Autonomous Underwater Vehicle). The flapping motion of a number of hydrofoil shapes in AUV was studied, and at the same time, the optimization of the hydrofoil shape and flapping motion was executed that allow the highest thrust and efficiency. The harmonic motion of plunging and pitching of NACA 4 digit series models, was used for the numerical analysis. The meta model was made by using the kriging method in Optimization method and the experimental points of 49 were extracted for the OA(Orthogonal array) in DOE(Design of experiments). Parametric study using this experimental points was conducted and the results were applied to MGA(Micro Genetic Algorithm). The flow simulation model was validated to be an appropriate tool by comparing with experimental data and the optimized shape and motion of AUV was turned out to produce highest thrust and efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1015-1023
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• 1999

We propose nonlinear processing schemes for robust acquisition of direct-sequence spread spectrum (DS/SS) signals in wideband pulse jamming. To mitigate the interference effect due to impulse-like wideband jamming signals, the received signal is preprocessed by using the median filter, a simple order statistic filter Since only parts of the PN sequence are used for rapid acquisition, it is indispensable for analytic design of an acquisition scheme to have an appropriate model of the partial PN signal. The partial correlation of the median filtered PN signal is approximated by a two-piecewise linear model using an approximate upper bound. The acquisition performance of the proposed schemes is compared to that of other schemes. Finally, the analytic design is verified by computer simulation.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.135-147
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• 1990

A nuclear power plant can be viewed as a large complex man-machine system where high system reliability is obtained by ensuring that sub-systems are designed to operate at a very high level of performance. The chance of severe accident involving at least partial core-melt is very low but once it happens the consequence is very catastrophic. The prediction of risk in low probability, high-risk incidents must be examined in the contest of general engineering knowledge and operational experience. Engineering knowledge forms part of the prior information that must be quantified and then updated by statistical evidence gathered from operational experience. Recently, Bayesian procedures have been used to estimate rate of accident and to predict future risks. The Bayesian procedure has advantages in that it efficiently incorporates experts opinions and, if properly applied, it adaptively updates the model parameters such as the rate or probability of accidents. But at the same time it has the disadvantages of computational complexity. The predictive distribution for the time to next incident can not always be expected to end up with a nice closed form even with conjugate priors. Thus we often encounter a numerical integration problem with high dimensions to obtain a predictive distribution, which is practically unsolvable for a model that involves many parameters. In order to circumvent this difficulty, we propose a method of approximation that essentially breaks down a problem involving many integrations into several repetitive steps so that each step involves only a small number of integrations.