• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.751-759
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• 2007

We have developed several methods for the optimization problem having large-scale and highly nonlinear system. First, step by step method in optimization process was employed to improve the convergence. In addition, techniques of furnishing good initial guesses for analysis using sensitivity information acquired from optimization iteration, and of manipulating analysis/optimization convergency criterion motivated from simultaneous technique were used. We applied them to flow control problem and verified their efficiency and robustness. However, they are based on quasi-Newton method that approximate the Hessian matrix using exact first derivatives. However solution of the Navier-Stokes equations are very cost, so we want to improve the efficiency of the optimization algorithm as much as possible. Thus we develop a true Newton method that uses exact Hessian matrix. And we apply that to the three-dimensional problem of flow around a sphere. This problem is certainly intractable with existing methods for optimal flow control. However, we can attack such problems with the methods that we developed previously and true Newton method.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.71-82
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• 2012

In this paper, we propose a license plate detection method with improved Adaboost learning and MCT (Modified Census Transform). The MCT represents the local structure patterns as integer numbered feature values which has robustness to illumination change and memory efficiency. However, since these integer values are discrete, a lookup table is needed to design a weak classifier for Adaboost learning. Some previous research efforts have focused on minimization of exponential criterion for Adaboost optimization. In this paper, a method that uses MCT and improved Adaboost learning based on Newton's optimization to exponential criterion is proposed for license plate detection. Experimental results on license patch images and field images demonstrate that the proposed method yields higher performance of detection rates with low false positives than the conventional method using the original Adaboost learning.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.675-691
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• 2002

The focus of this work is on the development of large-scale numerical optimization methods for optimal control of steady incompressible Navier-Stokes flows. The control is affected by the suction or injection of fluid on portions of the boundary, and the objective function of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. We develop reduced Hessian sequential quadratic programming. Both quasi-Newton and Newton variants are developed and compared to the approach of eliminating the flow equations and variables, which is effectively the generalized reduced gradient method. Optimal control problems we solved for two-dimensional flow around a cylinder. The examples demonstrate at least an order-of-magnitude reduction in time taken, allowing the optimal solution of flow control problems in as little as half an hour on a desktop workstation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.4
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• pp.661-674
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• 2002

The objective of this study is to develop efficient numerical method to enable solution of optimal control problems of Navier-Stokes flows and to apply these technique to the problem of viscous drag minimization on a bluff body by controlling boundary velocities on the surface of the body. In addition to the industrial importance of the drag reduction problem, it serves as a model for other more complex flow optimization settings, and allows us to study, modify, and improve the behavior of the optimal control methods proposed here. The control is affected by the suction or injection of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. This study shows how reduced Hessian successive quadratic programming method, which avoid converging the flow equations at each iteration, can be tailored to these problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.95-101
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• 2007

Recently, two phase scheme for removing impulse noise in images is proposed. This algorithms first detect the noise candidates based on the adaptive median filter, and then apply optimizing techniques recursively only to those noise candidates to restore image. Thus the noise detector with high accuracy is important role on this algorithm, In this paper, novel noise detector is proposed, which can detect impose noise with high accuracy while reducing the probability of false detecting image details as impulses. And the method for reducing computational cost of regularization phase is presented also.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.661-669
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• 2007

Eyer since the Prandtl's experiment in 1934 and X-21 airjet test in 1950 both attempting to reduce drag, it was found that controlling the velocities of surface for extremely fast-moving object in the air through suction or injection was highly effective and active method. To obtain the right amount of suction or injection, however, repetitive trial-and error parameter test has been still used up to now. This study started from an attempt to decide optimal amount of suction and injection of incompressible Navier-Stokes by employing optimization techniques. However, optimization with traditional methods are very limited, especially when Reynolds number gets high and many unexpected variables emerges. In earlier study, we have proposed an algorithm to solve this problem by using step by step method in analysis and introducing SQP method in optimization. In this study, we propose more effective and robust algorithm and techniques in solving flow optimization problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.1-16
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• 2022

The location of the bus stop on urban roads should be installed at a point where it is convenient for users and the impact of bus stops on the traffic flow is minimized. However, the location of the bus stops is determined indiscriminately due to the lack of related research. Therefore, this study developed a traffic accident prediction model and calculated the proper separation distance for the bus stops through an optimization technique. The result of the study indicates that the bus stop can be installed in the form of a mid-block approximately 87 to 166 m away from the intersection in the road section. This result is valid if the number of main road lanes in the road section is 2 to 4 with a level of traffic from 1,000 to 3,000 v/h. In the section with 5 to 6 lanes, it is desirable to install a bus stop close to the intersection by about 42 to 97 m.