• Bulletin of the Korean Mathematical Society
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• v.51 no.5
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• pp.1399-1409
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• 2014

In this article, we establish the $\mathfrak{F}_p$-uniform moderate deviation principles of the sample quantiles and order statistics for a sequence of independent and identically distributed samples.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.6
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• pp.70-76
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• 2011

This paper presents an optimization procedure for reducing warpage of injection molded part by using a volumetric shrinkage deviation as an objective function. A design of experiments based on orthogonal arrays was used in the optimization procedure, and the entire optimization was performed through a two stage process - a preliminary experimentation and a principal experimentation. Proposed optimization method was applied to the design of a CPU-base part in computer. With the moderate number of experiments, an optimal molding condition for uniform distribution of volumetric shrinkage was obtained, as a result, the warpage of the molded part was significantly reduced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.413-421
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• 2008

The paper derives asymptotic formulas for the MSE distortion and the signal-to-noise ratio of a mismatched fixed-rate minimum MSE Laplacian quantizer. These closed-form formulas are expressed in terms of the number N of quantization points, the mean displacement $\mu$, and the ratio $\rho$ of the standard deviation of the source to that for which the quantizer is optimally designed. Numerical results show that the principal formula is accurate in that, for rate R=$log_2N{\geq}6$, it predicts signal-to-noise ratios within 1% of the true values for a wide range of $\mu$, and $\rho$. The new findings herein include the fact that, for heavy variance mismatch of ${\rho}>3/2$, the signal-to-noise ratio increases at the rate of $9/\rho$ dB/bit, which is slower than the usual 6 dB/bit, and the fact that an optimal uniform quantizer, though optimally designed, is slightly more than critically mismatched to the source. It is also found that signal-to-noise ratio loss due to $\mu$ is moderate. The derived formulas can be useful in quantization of speech or music signals, which are modeled well as Laplacian sources and have changing short-term variances.