• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2713-2716
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• 2003

This paper presents a dynamic manipulability analysis method of the limb moving in viscous fluid. The key idea of the presented method is that the boundary of joint velocity can be converted to the velocity-dependant dynamic manipulability polytope through the coriolis, centrifugal and drag terms in dynamic equation. The velocity-dependant dynamic manipulability polytope is added to the inertial and restoring force manipulability polytope to get overall manipulability polytope of the limb moving in the fluid Each of the torque and velocity bounds arc considered in the infinite norm sense in joint space, and the drag force of a limb moving in fluid viscous is modeled as a quadratic form An analysis example with proposed analysis scheme is presented to validate the method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.5
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• pp.173-178
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• 1985

The control of a linear system with random coefficients is discussed here. The cost function is of a quadratic form and the random coefficients are assumed to be completely observable by the controller. Stochastic Process involved in the problem by the controller. Stochastic Process involved in the problem formulation is presented to be the unique strong solution to the corresponding stochastic differential equations. Condition for the optimal control is represented through the existence of solution to a Cauchy problem for the given nonlinear partial differential equation. The optimal control is shown to be a linear function of the states and a nonlinear function of random parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.524-529
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• 1993

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called "component cost" to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. One possible use of component costs is for model reduction by deleting those components that have the smallest component cost. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. When the dynamics of this input are added to the plant, which is to be reduced by CCA, the algorithm for model reduction process will be called Weighted Component Cost Analysis (WCCA). Closed-form analytical expressions of component costs for continuous time case, are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems beyond Lyapunov solvable dimension. A numerical example for NASA's MINIMAST system is presented.presented.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.83-99
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• 2002

Optimality conditions are derived for a nonlinear program in which a support function appears in the objective as well as in each constraint function. Wolfe and Mond-Weir type duals to this program are presented and various duality results are established under suitable convexity and generalized convexity assumptions. Special cases that often occur in the literature are those in which a support function is the square root of a positive semi- definite quadratic form or an Lp norm. It is pointed out that these special cases can easily be generated from our results.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.75-106
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• 2008

In this paper, we derive necessary optimality conditions for a continuous programming problem in which both objective and constraint functions contain support functions and is, therefore, nondifferentiable. It is shown that under generalized invexity of functionals, Karush-Kuhn-Tucker type optimality conditions for the continuous programming problem are also sufficient. Using these optimality conditions, we construct dual problems of both Wolfe and Mond-Weir types and validate appropriate duality theorems under invexity and generalized invexity. A mixed type dual is also proposed and duality results are validated under generalized invexity. A special case which often occurs in mathematical programming is that in which the support function is the square root of a positive semidefinite quadratic form. Further, it is also pointed out that our results can be considered as dynamic generalizations of those of (static) nonlinear programming with support functions recently incorporated in the literature.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.736-742
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• 2008

This paper proposes new searching algorithm for the optimal PD gains of flexible rotor supported by active magnetic bearings. Under the assumption of linearized bearing parameters with respect to PD gains, the performance index in quadratic form is defined and steepest descent method is adopted for determining local minimum. Moreover, the eigenpair sensitivity concept is utilized to evaluate the sensitivity of performance index. To evaluate the effectiveness of suggested algorithm, the finite element model is constructed and its reduced model is retained in modal domain. Given starting gains, the optimal gains are successfully found and the control performance is demonstrated by simulation to show the efficiency of the proposed method.

• Journal of the Korean Statistical Society
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• v.35 no.2
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• pp.115-142
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• 2006

This paper studies the problem of option hedging when the underlying asset price process is a compound Poisson process. By adopting an asymptotic approach to let the security price converge to a continuous process, we find a closed-form hedging strategy that improves the classical Black-Scholes hedging strategy in a quadratic sense. We first show that the scaled Black-scholes hedging error has a limit in law, and that limit is decomposed into a part that can be traded away and a part that is purely unreplicable. The Black-Scholes hedging strategy is then modified by adding the replicable part of its hedging error and by adding the mean-variance hedging strategy to the nonreplicable part. Some results of simulation experiment s are also provided.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.583-589
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• 2019

Counterexamples of a skew-normal distribution are developed to improve our understanding of this distribution. Two examples on bivariate non-skew-normal distribution owning marginal skew-normal distributions are first provided. Sum of dependent skew-normal and normal variables does not follow a skew-normal distribution. Continuous bivariate density with discontinuous marginal density also exists in skew-normal distribution. An example presents that the range of possible correlations for bivariate skew-normal distribution is constrained in a relatively small set. For unified skew-normal variables, an example about converging in law are discussed. Convergence in distribution is involved in two separate examples for skew-normal variables. The point estimation problem, which is not a counterexample, is provided because of its importance in understanding the skew-normal distribution. These materials are useful for undergraduate and/or graduate teaching courses.

• Journal of Korea Technology Innovation Society
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• v.1 no.2
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• pp.192-207
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• 1998

This paper focuses on the relationship between innovation and export performance of technology-based firms in Korea. This study analyses the relationship between innovative activity and firm's performances using a sample of 760 technology-based firms in Korea. As for the firm's performance indicators, export is employed. The empirical results support that innovation has a positive effect on firm's export performance. However, for small and medium firms, the relationship between innovative activity and export performance is an U-shape quadratic form, which shows that small firms takes a minimum innovative expenditure in order to access the abroad market. Also, with product differentiation, innovative firms tends to devot more to domestic market than to abroad market. Therefore, it can be concluded that innovative activity builds market power and accelerates export performance. And product differentiation through advertising expenditure make innovative firms less exporting.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.163-178
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• 2001

We consider the experimental design problem of selecting values of design variables x for observation of a response y that depends on x and on model parameters $\theta$. The form of the dependence may be quite general, including all linear and nonlinear modeling situations. The goal of the design selection is to efficiently estimate functions of $\theta$. Three new criteria for selecting design points x are presented. The criteria generalized the usual Bayesian optimal design criteria to situations n which the prior distribution for $\theta$ amy be uncertain. We assume that there are several possible prior distributions,. The new criteria are applied to the nonlinear problem of designing to estimate the turning point of a quadratic equation. We give both analytic and computational results illustrating the robustness of the optimal designs based on the new criteria.