• Journal of applied mathematics & informatics
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• 제30권3_4호
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• pp.381-393
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• 2012

In this paper, we show two ways of the time reparametrization of piecewise Pythagorean-hodograph $C^1$ Hermite interpolants. One is the time reparametrization with no shape change, and the other is that with shape change. We show that the first reparametrization does not depend on the boundary data and that it is uniquely determined by the size of parameter domain, up to the general cases. We empirically show that the second parametrization can cause the change of the shape of interpolant.

• International Journal of Reliability and Applications
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• 제2권2호
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• pp.117-130
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• 2001

Consider the problem of estimating the system reliability using noninformative priors when both stress and strength follow generalized gamma distributions. We first treat the orthogonal reparametrization and then, using this reparametrization, derive Jeffreys'prior, reference prior, and matching priors. We next provide the suffcient condition for propriety of posterior distributions under those noninformative priors. Finally, we provide and compare estimated values of the system reliability based on the simulated values of the parameter of interest in some special cases.

• 한국CDE학회논문집
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• 제3권2호
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• pp.87-102
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• 1998

Given a sequence of cross-sectional curves, the skinning method generates a freeform surface that interpolates the given curves in that sequence. This thesis presents a construction method of a B-spline skinning surface that is fair and satisfies volume constraints. The fairness metric is based on the parametric energy functional of a surface. The degrees of freedom in surface control are closely related lo control points in the skinning direction. The algorithm fur finding a skinning surface consists of two step. In the first step, an initial fair surface is generated without volume constraints and one coordinate of each control point is fixed. In the second step, a final surface that meets all constraints is constucted by rearranging the other coordinates of each control point that defines the initial surface A variational Lagrange optimization method produces a system of nonlinear equations, which can be solved numerically. Moreover, the reparametrization of given sectional curves is important for the construction of a reasonable skinning surface. This thesis also presents an intuitive metric for reparametrization and gives some examples that are optimized with respect to that metric.

• Journal of applied mathematics & informatics
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• 제28권1_2호
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• pp.131-141
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• 2010

In this paper, we propose a new method to obtain $C^1$ MPH quartic Hermite interpolants generically for any $C^1$ Hermite data, by using the speed raparametrization method introduced in [16]. We show that, by this method, without extraordinary processes ($C^{\frac{1}{2}}$ Hermite interpolation introduced in [13]) for non-admissible cases, we are always able to find $C^1$ Hermite interpolants for any $C^1$ Hermite data generically, whether it is admissible or not.

• 한국신뢰성학회지:신뢰성응용연구
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• 제11권2호
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• pp.151-165
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• 2011

We consider the problem of estimating the system reliability using noninformative priors when both stress and strength follow generalized gamma distributions with index, scale, and shape parameters. We first derive group-ordering reference priors using the reparametrization. We next provide the sufficient condition for propriety of posterior distributions and provide marginal posterior distributions under those noninformative priors. Finally, we provide and compare estimated values of the system reliability based on the simulated values of parameter of interest in some special cases.

• Journal of the Korean Statistical Society
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• 제28권2호
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• pp.183-193
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• 1999

In the problem of estimating estimable functions in classification linear models, we propose a method of obtaining least squares estimators of estimable functions. This method is based on the hierarchical Bayesian approach for estimating a vector of unknown parameters. Also, we verify that estimators obtained by our method are identical to least squares estimators of estimable functions obtained by using either generalized inverses or full rank reparametrization of the models. Some examples are given which illustrate our results.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 추계학술대회
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• pp.27-34
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• 2005

We consider the problem of estimating the system reliability noninformative priors when both stress and strength follow generalized gamma distributions. We first derive Jeffreys' prior, group ordering reference priors, and matching priors. We investigate the propriety of posterior distributions and provide marginal posterior distributions under those noninformative priors. We also examine whether the reference priors satisfy the probability matching criterion.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.395-411
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• 2005

In this paper, we develop the Jeffreys' prior, reference prior and the the probability matching priors for the difference of intraclass correlation coefficients in familial data. e prove the sufficient condition for propriety of posterior distributions. Using marginal posterior distributions under those noninformative priors, we compare posterior quantiles and frequentist coverage probability.

• 통합자연과학논문집
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• 제5권1호
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• pp.38-41
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• 2012

In this paper we show that for any triangle and any point on the circumcircle the envelope of the Wallace-Simson lines with signed angle ${\alpha}$ is a parabola. The proof is obtained naturally using polar coordinates. We also present the reparametrization of the envelope which is a linear normal curve.

• 대한수학회지
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• 제55권3호
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• pp.593-604
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• 2018

Recently, a new version of expansiveness which is closely attached to some certain weak version of hyperbolicity was given for $C^1$ vector fields as following: a $C^1$ vector field X will be called rescaling expansive on a compact invariant set ${\Lambda}$ of X if for any ${\epsilon}$ > 0 there is ${\delta}$ > 0 such that, for any $x,\;y{\in}{\Lambda}$ and any time reparametrization ${\theta}:{\mathbb{R}}{\rightarrow}{\mathbb{R}}$, if $d({\varphi}_t(x),\,{\varphi}_{{\theta}(t)}(y)){\leq}{\delta}{\parallel}X({\varphi}_t(x)){\parallel}$ for all $t{\in}{\mathbb{R}}$, then ${\varphi}_{{\theta}(t)}(y){\in}{\varphi}_{(-{\epsilon},{\epsilon})}({\varphi}_t(x))$ for all $t{\in}{\mathbb{R}}$. In this paper, some equivalent definitions for rescaled expansiveness are given.