• Journal of KIISE:Computer Systems and Theory
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• v.32 no.3
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• pp.133-147
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• 2005

Various types of ray-tracing methods are used to predict the quantity measures of radiation illumination, the uniformity of illumination, radiation performance of LCD BLU(Hack-Light Unit). The uniformity of radiation illumination is one of the most important design factor of BLU and is usually controlled by the diffusive-ink pattern printed on the bottom of light-guide panel of BLU. Therefore it is desirable to produce an improved (ideally, the optimal) ink pattern to achieve the best uniformity of radiation illumination. In this paper, we applied the Welder-Mead simplex-search method among various direct search method to compute the optimal ink pattern. Direct search methods are widely used to optimize the functions which are often highly nonlinear, unpredictably discontinuous, and nondifferentiable, The ink-pattern controlling the uniformity of radiation illumination is one type of these functions. In this paper, we found that simplex search methods are well suited to computing the optimal diffusive-ink pattern. In extensive numerical testing, we have found the simplex search method to be reasonably efficient and reliable at computing the optimal diffusive-ink pattern. The result also suggests that optimization can improve the functionality of simulation tools which are used to design LCD BLU.

• Korean Management Science Review
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• v.17 no.2
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• pp.13-20
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• 2000

In this research, we compare and analyze the two initial basis construction procedures: LPAKO’s procedure proposed by Seo et. al. and symbolic crash procedure proposed by Maros et. al.. Based on the analysis, we present a new procedure which complements the previous procedures. The new procedure shows superiority to the previous procedures with respects to the optimality of initial basis. Also, the linear basis Also. the initial basis constructed by the new procedure reduces the number of simplex iterations.

• Korean Management Science Review
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• v.19 no.1
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• pp.67-75
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• 2002

This paper deals with the visualization method of solutions of the linear programming Problem. We used the revised simplex method for the LP algorithm. To represent the solutions at each iteration, we need the informations of feasible legion and animated effect of solutions. For the visualization in high dimension space, we used the method of Projection to the three dimensions if the decision variable vector is over three dimensions, and we studied the technique of preserving original Polyhedral information such as the number of vertices. In addtion, we studied the method of visualizing unbounded feasible region and the adjacency relationship of the vortices welch is Indispensable to cisualize feasible legion.

• Journal of electromagnetic engineering and science
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• v.10 no.4
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• pp.199-205
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• 2010

This paper presents a tumor detection system for breast cancer that utilizes two-dimensional (2D) image reconstruction with microwave tomographic imaging. The breast cancer detection system under development consists of 16 transmit/receive antennas, and the microwave tomography system operates at 900 MHz. To solve a 2D inverse scattering problem, the method of moments (MoM) is employed for forward problem solving, and the simplex method employed as an optimization algorithm. The results of the reconstructed image show that the method accurately shows the position of a breast tumor.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.539-551
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• 2021

With the continuous increase of computational capacity, more and more complex nonlinear elastoplastic constitutive models were developed to study the mechanical behavior of elastoplastic materials. These constitutive models generally contain a large amount of physical and phenomenological parameters, which often require a large amount of computational costs to determine. In this paper, an inverse parameter determination method is proposed to identify the constitutive parameters of elastoplastic materials, with the consideration of both strain rate effect and temperature effect. To carry out an efficient design, a hybrid optimization algorithm that combines the genetic algorithm and the Nelder-Mead simplex algorithm is proposed and developed. The proposed inverse method was employed to determine the parameters for an elasto-viscoplastic constitutive model and Johnson-cook model, which demonstrates the capability of this method in considering strain rate and temperature effect, simultaneously. This hybrid optimization algorithm shows a better accuracy and efficiency than using a single algorithm. Finally, the predictability analysis using partial experimental data is completed to further demonstrate the feasibility of the proposed method.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.71-76
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• 1994

In the source localization using single dipole model, the influence of the number of electrodes, the position and direction of a single dipole on the relation between S/W ratio and dipole parameter estimation errors is important. Monte Carlo simulation was used to investigate this influence. The forward problem was calculated using three spherical shell model, and dipole parameters were optimized by means of simplex method. As the number of electrodes became large, as the dipole went from midbrain to cortex, and as the direction of dipole changed from radial to tangential, the average and standard deviation of estimation errors became small.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.14-30
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• 1985

Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design as interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputer for solving goal programming problems.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1334-1339
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• 2003

An efficient method is developed for the shape optimization of 2-D structures. The sequential linear programming is used for minimization problems. Selected set of master nodes are employed as design variables and assigned to move towards the normal direction. After adapting the nodes on the design boundary, the B-spline curves and mesh smoothing schemes are used to maintain the finite element in good quality. Finally, a numerical implementation of optimum design of an automobile torque converter piston subjected to pressure and centrifugal loads is presented. The results shows additional weight up to 13% may be saved after the shape optimization.

• Tuberculosis and Respiratory Diseases
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• v.46 no.1
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• pp.82-88
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• 1999

Herpes simplex virus pneumonia in immunocompromised host is difficult to diagnose with non-invasive method, and has high mortality rate. Because early diagnosis and early treatment can significantly decrease the mortality rate, the enthusiastic efforts for the early diagnosis should be done. A 41-year-old woman who took prednisolone due to mixed connective tissue disease developed gradually increasing dyspnea with radiological features of interstitial lung disease. Initially, we treated her with empirical antibiotics, but failed to improve her dyspnea. So we performed bronchoalveolar lavage and open lung biopsy. Open lung biopsy specimen showed herpes simplex virus pneumonia. Herpes simplex virus was also isolated from bronchoalveolar lavage fluid. There was both clinical and radiological improvement after treatment with acyclovir for 14 days.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.509-516
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• 2013

Since traditional linear feature extraction methods are unable to handle nonlinear characteristics often exhibited in hyperspectral imagery, nonlinear feature extraction, also known as manifold learning, is receiving increased attention in hyperspectral remote sensing society as well as other community. A most widely used manifold Isomap is generally promising good results in classification and spectral unmixing tasks, but significantly high computational overhead is problematic, especially for large scale remotely sensed data. A small subset of distinguishing points, referred to as landmarks, is proposed as a solution. This study proposes a new robust and controllable landmark selection method based on the maximum volume of the simplex spanned by landmarks. The experiments are conducted to compare classification accuracies with standard deviation according to sampling methods, the number of landmarks, and processing time. The proposed method could employ both classification accuracy and computational efficiency.