• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.335-342
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• 2001

In this paper, an improved Element-Free Galerkin (EFG) method is proposed by adding enrichment function to the standard EFG approximation and a discontinuity function is implemented in constructing the shape function across the crack surface. In this method, the singularity and the discontinuity of the crack are efficiently modeled by using initial node distribution to evaluate reliable stress intensity factor, though the standard EFG method requires placing additional nodes near the crack tip. The proposed method enables the initial node distribution to be kept without any additional nodal d.o.f. and expresses the asymptotic stress field near the crack tip successfully. Numerical example verifies the improvement and the effectiveness of the method.

• Journal of the Chungcheong Mathematical Society
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• v.28 no.3
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• pp.491-497
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• 2015

In this paper, we have suggested an extended double Newton's method with sixth-order convergence by considering a control parameter ${\gamma}$ and a weight function H(s, u). We have determined forms of ${\gamma}$ and H(s, u) in order to induce the greatest order of convergence and established the main theorem utilizing related properties. The developed theory is ensured by numerical experiments with high-precision computation for a number of test functions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.194-198
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• 1998

A novel fuzzy basis function vector- based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the paramenters of the compensator in the sense that both the robustness and the asymptotic error convergence can be obtained for the closed loop nonlinear control system.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.47-64
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• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1225-1231
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• 2000

This paper proposes a V-shaped Lyapunov function approach for the model-based control of flexible-joint robots, in which a new model-based nonlinear control scheme is designed based on a V-shaped Lyapunov function. The proposed control guarantees global asymptotic stability for link trajectory control while keeping all internal signals bounded. Since joint flexibility is used as a control parameter, the proposed control is not restricted by the degree of joint flexibility and be applied to flexibility-joint, partly-flexibility, or rigid-joint robots without modification. the effectiveness of the proposed control has been by computer simulation.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.471-487
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• 1996

In this paper we propose an efficient scoring type one-step GM-estimator, which has a bounded influence function and a high break-down point. The main point of the estimator is in the weighting scheme of the GM-estimator. The weight function we used depends on both leverage points and residuals So we construct an estimator which does not downweight good leverage points Unider some regularity conditions, we compute the finite-sample breakdown point and prove asymptotic normality Some simulation results are also presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.341-345
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• 1997

A novel fuzzy basis function vector-based adaptive control approach for Multi-input and Multi-output(MIMO) system is presented in this paper, in which the nonlinear plants is first linearised, the fuzzy basis function vector is then introduced to adaptively learn the upper bound of the system uncertainty vector, and its output is used as the parameters of the compensator in the sense that both the asymptotic error convergence can be obtained for the colsed loop nonlinear control system.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.219-228
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• 2004

In this paper we construct prediction intervals for nonlinear time series models using the bootstrap. We compare these prediction intervals to traditional asymptotic prediction intervals using quasi-score estimation function and M-quasi-score estimating function comprising bounded functions. Simulation results show that the bootstrap method leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the consumer price index.

• Korean Journal of Mathematics
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• v.21 no.4
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• pp.365-374
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• 2013

Let $k=\mathbb{F}_q(T)$ be a rational function field over the finite field $\mathbb{F}_q$, where q is a power of an odd prime number, and $\mathbb{A}=\mathbb{F}_q[T]$. Let ${\gamma}$ be a generator of $\mathbb{F}^*_q$. Let $\mathcal{H}_n$ be the subset of $\mathbb{A}$ consisting of monic square-free polynomials of degree n. In this paper we obtain an asymptotic formula for the mean value of $L(1,{\chi}_{\gamma}{\small{D}})$ and calculate the average value of the ideal class number $h_{\gamma}\small{D}$ when the average is taken over $D{\in}\mathcal{H}_{2g+2}$.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.433-444
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• 1996

In contrast to the multiplicative risk model, the additive risk model specifies that the hazard function with covariates is the sum of, rather than product of, the baseline hazard function and the regression function of covariates. We, in this paper, propose a method for checking the adequacy of the additive risk model based on partial-sum of matingale residuals. Under the assumed model, the asymptotic properties of the proposed test statistic and approximation method to find the critical values of the limiting distribution are studied. Several real examples are illustrated.