• East Asian mathematical journal
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• v.29 no.3
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• pp.279-292
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• 2013

It is well known that each kernel function defines a primal-dual interior-point method(IPM). Most of polynomial-time interior-point algorithms for linear optimization(LO) are based on the logarithmic kernel function([2, 11]). In this paper we define a new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has ${\mathcal{O}}((log\;p){\sqrt{n}}\;log\;n\;log\;{\frac{n}{\epsilon}})$ and ${\mathcal{O}}((q\;log\;p)^{\frac{3}{2}}{\sqrt{n}}\;log\;{\frac{n}{\epsilon}})$ iteration bound for large- and small-update methods, respectively. These are currently the best known complexity results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.286-292
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• 2006

Both composition and XOR are operations widely used to enhance security of cryptographic schemes. The more number of random permutations we compose (resp. XOR), the more secure random permutation (resp. random function) we get. Combining the two methods, we consider a generalized form of random function: $SUM^s - CMP^c = ({\pi}_{sc} ... {\pi}_{(s-1)c+1}){\oplus}...{\oplus}({\pi}_c...{\pi}_1)$ where ${\pi}_1...{\pi}_{sc}$ are random permutations. Given a fixed number of random permutations, there seems to be a trade-off between composition and XOR for security of $SUM^s - CMP^c$. We analyze this trade-off based on some upper bound of insecurity of $SUM^s - CMP^c$, and investigate what the optimal number of each operation is, in order to lower the upper bound.

• Tunnel and Underground Space
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• v.25 no.3
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• pp.284-292
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• 2015

The generalized Hoek-Brown failure criterion, the strength parameters of which are determined by using the GSI index, is an empirical nonlinear failure criterion of rock mass and has been widely employed in various rock engineering practices. Many rock engineering practitioners, however, are still familiar with the description of the strength of rock mass in terms of friction angle and cohesion. In addition, almost all rock mechanics softwares incorporate the simple linear Mohr-Coulomb function. Therefore, it is necessary to provide a tool to implement the Hoek-Brown function in the framework of the Mohr-Coulomb criterion. In this study, the use of upper-bound solution of limit analysis for bearing capacity of a strip footing resting on the ground surface is proposed for the estimation of the equivalent friction angle and cohesion of rock mass incorporating the generalized Hoek-Brown failure criterion. The upper-bound bearing capacity is expressed in terms of friction angle by use of the relationship between tangential friction angle and tangential cohesion implied in the generalized Hoek-Brown function. The friction angle minimizing the upper-bound bearing capacity is taken as the equivalent friction angle. Through the illustrative implementations of the proposed method, the influences of GSI, $m_i$ and D on the equivalent friction angle and cohesion are investigated.

• Structural Engineering and Mechanics
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• v.33 no.1
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• pp.109-112
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• 2009

• Journal of applied mathematics & informatics
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• v.2 no.2
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• pp.3-12
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• 1995

Evaluation of permanents of some(0,1) circulants is known to be of major importance for designers of certain speech scrambling systems. In this paper we gicve a lower bound for the number of scaram-bling patterns we deal with by minimizing the permanent function over some matrix polyhedra.

• Bulletin of the Korean Mathematical Society
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• v.41 no.2
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• pp.213-220
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• 2004

In this paper, we generalize the Bishop-Gromov volume comparison theorem by considering an integral bound for the part of the radial Ricci curvature which lies below a given smooth function. We also establish a compactness theorem from this result.

• Communications of the Korean Mathematical Society
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• v.35 no.4
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• pp.1193-1202
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• 2020

We consider the integral ${{\int}_{0}^{\infty}}(\frac{sin\;x}{x})^n\;dx$ as a function of the positive integer n. We show that there exists an asymptotic series in ${\frac{1}{n}}$ and compute the first terms of this series together with an explicit error bound.

• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

• Korean Management Science Review
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• v.33 no.2
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• pp.75-87
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• 2016

Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by analyzing customer requirements. It is a main activity in QFD planning process to determine the optimal values of the technical attributes (TAs) so as to achieve the customer requirements (CRs) from the House of Quality (HoQ). In most of the previous research, all the TAs in QFD are assumed to have either continuous or discrete values. In the real world applications, the continuous TAs and the discrete TAs are often mixed in QFD. In this paper, a mixed integer linear programming model is formulated to obtain the optimal values for the continuous TAs and the discrete TAs in QFD planning as well as Branch and Bound (B and B) algorithm is proposed as the solution approach. Finally, the proposed model and solution approach are illustrated with an office chair under multi-segment market, and the sensitivity analysis is performed to study how the proposed model and its solutions respond to the variation for the two elements which are budget and CRs' weights.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.225-234
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• 1999

We consider the following semi-parametric non-linear mixed effect regression model : y\ulcorner=f($\chi$\ulcorner;$\beta$)+$\sigma$$\mu$($\chi$\ulcorner)+$\sigma$$\varepsilon$\ulcorner,i=1,…,n,y*=f($\chi$;$\beta$)+$\sigma$$\mu$($\chi$) where y'=(y\ulcorner,…,y\ulcorner) is a vector of n observations, y* is an unobserved new random variable of interest, f($\chi$;$\beta$) represents fixed effect of known functional form containing unknown parameter vector $\beta$\ulcorner=($\beta$$_1$,…,$\beta$\ulcorner), $\mu$($\chi$) is a random function of mean zero and the known covariance function r(.,.), $\varepsilon$'=($\varepsilon$$_1$,…,$\varepsilon$\ulcorner) is the set of uncorrelated measurement errors with zero mean and unit variance and $\sigma$ is an unknown dispersion(scale) parameter. On the basis of finite-sample, small-dispersion asymptotic framework, we derive an absolute lower bound for the asymptotic mean squared errors of prediction(AMSEP) of the regular-consistent non-linear predictors of the new random variable of interest y*. Then we construct an optimal predictor of y* which attains the lower bound irrespective of types of distributions of random effect $\mu$(.) and measurement errors $\varepsilon$.