• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.2
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• pp.82-89
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• 1985

A new non-inferior solution is obtained by investigating method of weight p- norm to explain the conception of MCO (multiple criterion optimization) problem. And then the optimum non-inferior solution is obtained by the weight minimization method applied to objective function of MOSFET NAND rATEAlso this weight minimization method using weight P- norm methods can be applied to non-convex objective function. The result of this minimization method shows the efficiency in comparison with that of Lightner.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.240-242
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• 2007

The game theoretic analysis in wireless networks can be classified into the jamming game of the physical layer, the multiple access game of the medium access layer, the forwarder's dilemma and joint packet forwarding game of the network layer, and etc. In this paper, the game theoretic analysis about the multiple access game that selfish nodes exist in the IEEE 802.11 DCF(Distributed Coordination Function) wireless networks is addressed. In this' wireless networks, the modeling of the CSMA/CA protocol based DCF, the utility or payoff function calculation of the game, the system optimization (using optimization theory or convex optimization), and selection of Pareto-optimality and Nash Equilibrium in game strategies are the important elements for analyzing how nodes are operated in the steady state of system. Finally, the main issues about the game theory in the wireless network are introduced.

• Bulletin of the Korean Mathematical Society
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• v.33 no.1
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• pp.1-16
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• 1996

Earlier in 1935[12], M. S. Robertson introduced the class of quadrant preserving functions. More precisely, let Q be the class of all functions f(z) analytic in the unit disk $D = {z : $\mid$z$\mid$ < 1}$ such that f(0) = 0, f'(0) = 1, and the range f(z) is in the j-th quadrant whenever z is in the j-th quadrant of D, j = 1,2,3,4. This class Q contains the subclass of normalized, odd univalent functions which have real coefficients. On the other hand, this class Q is contained in the class T of odd typically real functions which was introduced by W. Rogosinski [13]. Clearly, if $f \in Q$, then f(z) is real when z is real and therefore the coefficients of f are all real. Recently, it was observed by Y. Abu-Muhanna and T. H. MacGregor [1] that any function $f \in Q$ is odd. Instead of functions "preserving quadrants", the authors [1] have introduced the notion of "preserving sectors".

• Bulletin of the Korean Mathematical Society
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• v.29 no.2
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• pp.193-200
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• 1992

This paper uses a piecewise ratonal cubic interpolant to solve the problem of shape preserving interpolation for plane curves; scalar curves are also considered as a special case. The results derived here are actually the extensions of the convexity preserving results of Delbourgo and Gregory [Delbourgo and Gregory'85] who developed a $C^{1}$ shape preserving interpolation scheme for scalar curves using the same piecewise rational function. They derived the ocnstraints, on the shape parameters occuring in the rational function under discussion, to make the interpolant preserve the convex shape of the data. This paper begins with some preliminaries about the rational cubic interpolant. The constraints consistent with convex data, are derived in Sections 3. These constraints are dependent on the tangent vectors. The description of the tangent vectors, which are consistent and dependent on the given data, is made in Section 4. the convexity preserving results are explained with examples in Section 5.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2005.04a
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• pp.79-82
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• 2005

In this study, we have tested the feasibility of the convex non-linear objective model and the line search optimization method for the fluence map optimization (FMO). We've created the convex nonlinear objective function with simple bound constraints and attained the optimal solution using well-known gradient algorithms with an Armijo line search that requires sufficient objective function decrease. The algorithms were applied to 10 head-and-neck cases. The numbers of beamlets were between 900 and 2,100 with a 3 mm isotropic dose grid. Nonlinear optimization methods could efficiently solve the IMRT FMO problem in well under a minute with high quality for clinical cases.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.620-623
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• 1997

This paper is concerned with the design of a suboptimal Kalman filter with robust state estimation performance for system models represented in the state space, which are subjected to parameter uncertainties in both the state and measurement matrices. Under the assumption that the uncertain system is quadratically stable, if the augmented system composed of the uncertain system and the filter is controllable, the proposed filter can provide the upper bound of the estimation error variance for all admissible uncertain parameters. This upper bound can be represented as the convex function of a parameter introduced in the design procedure, and the optimized upper bound of the estimation error variance can also be found via the optimization of this convex function.

• Honam Mathematical Journal
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• v.37 no.3
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• pp.317-323
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• 2015

The purpose of the present paper is to study certain radii problems for the function $$f(z)=\[{\frac{z^{1-{\gamma}}}{{\gamma}+{\beta}}}\(z^{\gamma}[D^nF(z)]^{\beta}\)^{\prime}\]^{1/{\beta}}$$, where ${\beta}$ is a positive real number, ${\gamma}$ is a complex number such that ${\gamma}+{\beta}{\neq}0$ and the function F(z) varies various subclasses of analytic functions with fixed second coefficients. Relevant connections of the results presented herewith various well-known results are briefly indicated.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1003-1007
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• 2015

Depth calibration is a procedure for finding the conversion function that maps disparity data from a depth-sensing camera to actual distance information. In this paper, we present an optimal depth calibration method for Kinect$^{TM}$ sensors based on an experimental design and convex optimization. The proposed method, which utilizes multiple measurements from only two points, suggests a simplified calibration procedure. The confidence ellipsoids obtained from a series of simulations confirm that a simpler procedure produces a more reliable calibration function.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2405-2407
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• 2001

In this paper, we apply and evolutionary computation(EC), probabilistic optimization algorithm, to active contour. A number of problems exist associated with such as algorithm initialization, existence of local minima, non-convex search space, and the selection of model parameters in conventional models. We propose an adequate fitness function for these problems. The determination of fitness function adequate to active contour using EC is important in search capability. As a result of applying the proposed method to non-convex object shape, we improve the unstability and contraction phenomena, in nature, of snake generated in deformable contour optimization.

• Kyungpook Mathematical Journal
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• v.61 no.3
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• pp.661-669
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• 2021

For a simple, undirected graph G = (V, E), a perfect Roman dominating function (PRDF) f : V → {0, 1, 2} has the property that, every vertex u with f(u) = 0 is adjacent to exactly one vertex v for which f(v) = 2. The weight of a PRDF is the sum f(V) = ∑_v∈V f(v). The minimum weight of a PRDF is called the perfect Roman domination number, denoted by γ_R^P(G). Given a graph G and a positive integer k, the PRDF problem is to check whether G has a perfect Roman dominating function of weight at most k. In this paper, we first investigate the complexity of PRDF problem for some subclasses of bipartite graphs namely, star convex bipartite graphs and comb convex bipartite graphs. Then we show that PRDF problem is linear time solvable for bounded tree-width graphs, chain graphs and threshold graphs, a subclass of split graphs.