• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.193-197
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• 2004

In this paper, a combination problem of controllers which are the same type of $H_{\infty}$ controllers designed with different weighting functions. This approach can remove the difficulty in the selection of the weighting functions. As a sub-controller, the Youla type of $H_{\infty}$ controller is used. In the $H_{\infty}$ controller, Youla parameterization is used to minimize $H_{\infty}$ norm of mixed sensitivity function by using polynomial approach. Computer simulation results show the robustness improvement and the performance improvement.

• Honam Mathematical Journal
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• v.45 no.2
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• pp.285-299
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• 2023

In the present paper, we establish some perturbed Newton-type inequalities in the case of twice differentiable convex functions. These inequalities are established by using the well-known Riemann-Liouville fractional integrals. With the aid of special cases of our main results, we also give some previously obtained Newton-type inequalities.

• Management Science and Financial Engineering
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• v.22 no.1
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• pp.5-12
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• 2016

We consider a time-cost tradeoff problem with multiple milestones under a chain precedence graph. In the problem, some penalty occurs unless a milestone is completed before its appointed date. This can be avoided through compressing the processing time of the jobs with additional costs. We describe the compression cost as the convex or the concave function. The objective is to minimize the sum of the total penalty cost and the total compression cost. It has been known that the problems with the concave and the convex cost functions for the compression are NP-hard and polynomially solvable, respectively. Thus, we consider the special cases such that the cost functions or maximal compression amounts of each job are identical. When the cost functions are convex, we show that the problem with the identical costs functions can be solved in strongly polynomial time. When the cost functions are concave, we show that the problem remains NP-hard even if the cost functions are identical, and develop the strongly polynomial approach for the case with the identical maximal compression amounts.

• Kyungpook Mathematical Journal
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• v.63 no.4
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• pp.577-591
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• 2023

In this paper we establish the L^p boundedness of Marcinkiewicz integral operators on product domains with rough kernels satisfying a weak size condition. We assume that our kernels are supported on surfaces generated by curves more general than polynomials and convex functions. This generalizes and extends previous results.

• Korean Journal of Mathematics
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• v.24 no.3
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• pp.369-374
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• 2016

In this paper, we study the hereditary convex radius of convex harmonic mapping $f(z)=f_1(z)+{\bar{f_x(z)}}$ under the integral operator $I_f(z)={\int_{o}^{z}}{\frac{f_1(u)}{u}}du+{\bar{{\int_{o}^{z}}{\frac{f_x(u)}{u}}}}$ and obtain the sharp constant ${\frac{{\sqrt[4]{6}}-{\sqrt[]{15}}}{9}}$, which generalized the result corresponding to the class of analytic functions given by Nash.

• Bulletin of the Korean Mathematical Society
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• v.36 no.4
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• pp.763-770
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• 1999

The purpose of this paper is to give sufficient coefficient conditions for a class of univalent harmonic functions that map each $$\mid$z$\mid$$ = r >1 onto a curve that bounds a domain that is starlike with respect to origin. Furthermore, it is shown that these conditions are also necessary when the coefficients are negative. Extreme points for these classes are also determined. Finally, comparable results are given for the convex analgo.

• Journal of the Chungcheong Mathematical Society
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• v.4 no.1
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• pp.55-59
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• 1991

We consider perturbation problems and Lagrangians for convex set function optimization problems. In particular, we prove that the Lagrangian $L({\Omega},y)$ is a convex set function in ${\Omega}$ for each y if the perturbation function is convex.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1395-1408
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• 2010

In this paper, a pair of Wolfe type second-order nondifferentiable multiobjective symmetric dual program over arbitrary cones is formulated. Weak, strong and converse duality theorems are established under second-order (F, $\alpha$, $\rho$, d)-convexity assumptions. An illustration is given to show that second-order (F, $\alpha$, $\rho$, d)-convex functions are generalization of second-order F-convex functions. Several known results including many recent works are obtained as special cases.

• Communications of the Korean Mathematical Society
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• v.37 no.4
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• pp.1025-1039
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• 2022

For given non-negative real numbers 𝛼_k with ∑^m_k=1 𝛼_k = 1 and normalized analytic functions f_k, k = 1, …, m, defined on the open unit disc, let the functions F and Fn be defined by F(z) := ∑^m_k=1 𝛼_kf_k(z), and F_n(z) := n^-1 ∑^n-1_j=0 e^-2j𝜋i/nF(e^2j𝜋i/nz). This paper studies the functions f_k satisfying the subordination zf'_k(z)/F_n(z) ≺ h(z), where the function h is a convex univalent function with positive real part. We also consider the analogues of the classes of starlike functions with respect to symmetric, conjugate, and symmetric conjugate points. Inclusion and convolution results are proved for these and related classes. Our classes generalize several well-known classes and the connections with the previous works are indicated.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.79-88
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• 1999

This work aims to establish an algorithm for solving the problem of convex programming with several objective-functions with linear constraints. Starting from the idea of Rosen's algorithm for solving the problem of convex programming with linear con-straints and taking into account the solution concept from multi-dimensional programming represented by a program which reaches "the best compromise" we are extending this method in the case of multidimensional programming. The concept of direction of min-imization is introduced and a necessary and sufficient condition is given for a s∈Rn direction to be a direction is min-imal. The two numerical examples presented at the end validate the algorithm.