• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.24.1-24.1
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• 2007

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.06b
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• pp.282-290
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• 1998

• Proceedings of the Zoological Society Korea Conference
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• 1996.10a
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• pp.66.1-66
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• 1996

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.155-156
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• 2005

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.585-591
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• 2014

An improved numerical scattering model with the 2-dimensional moment method including roof-top basis and a modified window-function to reduce edge-effect is presented in this study. The roof-top basis function is used to depict randomly positioned surface currents and increase an efficiency of the moment method. To reduce the edge-effect which occurs at the end of numerically generated surfaces, an enhanced window-function which is weighted by incident angle variable is proposed. To validate an proposed 2-dimensional scattering model and numerical analysis techniques for randomly rough surfaces, computational results are compared and analyzed to SPM(Small Perturbation Model) as well.

• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• Journal of the Korean Mathematical Society
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• v.45 no.6
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• pp.1613-1622
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• 2008

Let G be a graph with vertex set V(G) and edge set E(G), and let g, f be two nonnegative integer-valued functions defined on V(G) such that $g(x)\;{\leq}\;f(x)$ for every vertex x of V(G). We use $d_G(x)$ to denote the degree of a vertex x of G. A (g, f)-factor of G is a spanning subgraph F of G such that $g(x)\;{\leq}\;d_F(x)\;{\leq}\;f(x)$ for every vertex x of V(F). In particular, G is called a (g, f)-graph if G itself is a (g, f)-factor. A (g, f)-factorization of G is a partition of E(G) into edge-disjoint (g, f)-factors. Let F = {$F_1$, $F_2$, ..., $F_m$} be a factorization of G and H be a subgraph of G with mr edges. If $F_i$, $1\;{\leq}\;i\;{\leq}\;m$, has exactly r edges in common with H, we say that F is r-orthogonal to H. If for any partition {$A_1$, $A_2$, ..., $A_m$} of E(H) with $|A_i|=r$ there is a (g, f)-factorization F = {$F_1$, $F_2$, ..., $F_m$} of G such that $A_i\;{\subseteq}E(F_i)$, $1\;{\leq}\;i\;{\leq}\;m$, then we say that G has (g, f)-factorizations randomly r-orthogonal to H. In this paper it is proved that every (0, mf - (m - 1)r)-graph has (0, f)-factorizations randomly r-orthogonal to any given subgraph with mr edges if $f(x)\;{\geq}\;3r\;-\;1$ for any $x\;{\in}\;V(G)$.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.413-420
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• 2013

The design rule depending on total transmission length is induced in the optical links with residual dispersion per span (RDPS) of the random distribution, which is adopted for implementing the flexible systems of wavelength division multiplexing (WDM) transmission with dispersion management (DM) and optical phase conjugation. DM parameters used for the analysis of the design rule are the effective net residual dispersion (NRD) and the effective launch power. It is confirmed that the flexible optical network configuration with the total transmission length lower than 1,000 km is possible, because the system performance difference between the randomly distribution and the uniform distribution of RDPS is small. And, in the optical links with the randomly distributed RDPS, the wide NRD can be applied for transmitting WDM channels of the relatively wide launch power.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.883-891
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• 2011

For survival data we sometimes want to test a log normality hypothesis that can be changed into normality by transforming the survival data. Hence the Shapiro-Wilk type statistic for normality is generalized to randomly censored data based on the Kaplan-Meier product limit estimate of the distribution function. Koziol and Green (1976) derived Cram$\acute{e}$r-von Mises statistic's randomly censored version under the simpl hypothesis. These two test statistics are compared through a simulation study. As for the distribution of censoring variables, we consider Koziol and Green (1976)'s model and other similar models. Through the simulation results, we can see that the power of the proposed statistic is higher than that of Koziol-Green statistic and that the proportion of the censored observations (rather than the distribution of censoring variables) has a strong influence on the power of the proposed statistic.

• Journal of Ginseng Research
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• v.17 no.2
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• pp.153-158
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• 1993

The study was carried out for comparison of variants and development of genetic markers using Randomly Amplified Polymorphic D사A (RAPD) analysis method. The ginseng variants used were as follows: Chungkyung-Chong, Hwangskoog-Chong, KG101 selected by the pureline selection method, and 6 kinds of Jakyung-Chong strains Uinjakyung, Jakyung-Chong 81783, Jakyung-Chong 847913, Jaky tong-Chong 79742, Jinjakyung of USSR, and Mimaki of Japan). Four of 10 RAPD primers showed the distinctive polymorphism among 9 ginseng variants and lines, and were selected for more detailed polymorphic analysis. The sequences of 4 selected primers were TGCCGAGCTG (Primer#2), AATCGGGCTG (#4), GAAACGGGTG (U7), and GTGACGTAGG (#8). All primers produced several common bands among the strains. However, when primer # 2 was applied, the electrophoregram showed the specific band at 1.8 kb region in Chungkyung-Chong, Hwangskoog- chong, and KG101, and 1 kb in the Jakyung-Chong 847913. In primer #4, 1.1 kb band was shown in Chungkyung-Chong, Hwangskoog-Chong, KG101, and Jakyung-Chong 79742. In primer # 7, 700 bp band was appeared in Jakyung-Chong 81783 and Jinjakyung of USSR In primer # 8, 800 bp band was observed only in Mimaki, comparing to another strains. When Similarity Index (SI) was calculated, Chungkyung-Chong and Hwngskoog-Chong, and Jakyung- chong 81783 and Jinjakyung of USSR showed the most close SI, 0.11 and 0.08, respectively. The data of KG101, which showed the SI of 0.13 with the group of Chungkyung-Chong and Hwangskoog-Chong, coincided with the fact that it was released from Hwangskoog-Chong by breeding process. The data of Jakyung strains indicated the significant variation among the strains. From these results, RAPD analysis method could be succesively applied to the classification and genetic analysis for breeding of Korean ginseng.