• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.703-713
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• 2002

Recently, an improved EFG(Element-Free Galerkin) crack analysis technique, which includes a discontinuous approximation and a singular basis function on the auxiliary supports, was developed. The technique is able to accurately analyze the crack propagation problem without any modification of the analysis model; however, it shows some dependency on the analysis parameters used. In this study, the effect of analysis parameters such as the size of compact support, dilation parameter, the smoothness of shape function around the crack tip, and the number of node using auxiliary supports on the accuracy of solution has been investigated. Through a patch test with a crack, relative L₂ error norm of stresses and the stress intensity factor were computed and compared for various analysis parameters and the results were presented as guidelines for adequate choice of analysis parameters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.963-969
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• 2000

In this paper, we define two input-output gains of linear periodic time-varying systems. One is the ratio of output with worst-case l2-norm over all inputs with unit 12-norm. It denotes G($\iota_2,\iota_2$.The other is the ratio of output with worst-case RMS value over all inputs with unit RMS value. It denotes G(RMS, RMS) .It is fact that these two gains are equivalent for linear time-invariant system. In this paper, we prove these two gains are also equivalent for linear periodic time-varying system. In addition, the relationship between two method of obtaining the generalized frequency responses for linear periodic time-varying system is derived. Finally, we apply the defined input-output gains to M-channel filter-bank which is multi-rate signal Processing system, used to speech coding. In the filter-bank, generally, aliasing distortion, magnitude distortion, and phase distortion are present. It is shown that these are kept small if the filter-bank is designed by a method that optimizes the gain G($\iota_2,\iota_2$ of an error system.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.733-745
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• 2017

Local composite quantile regression is a useful non-parametric regression method widely used for its high efficiency. Data smoothing methods using kernel are typically used in the estimation process with performances that rely largely on the smoothing parameter rather than the kernel. However, $L_2$-norm is generally used as criterion to estimate the performance of the regression function. In addition, many studies have been conducted on the selection of smoothing parameters that minimize mean square error (MSE) or mean integrated square error (MISE). In this paper, we explored the optimality of selecting smoothing parameters that determine the performance of non-parametric regression models using local linear composite quantile regression. As evaluation criteria for the choice of smoothing parameter, we used mean absolute error (MAE) and mean integrated absolute error (MIAE), which have not been researched extensively due to mathematical difficulties. We proved the uniqueness of the optimal smoothing parameter based on MAE and MIAE. Furthermore, we compared the optimal smoothing parameter based on the proposed criteria (MAE and MIAE) with existing criteria (MSE and MISE). In this process, the properties of the proposed method were investigated through simulation studies in various situations.