• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.83-90
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• 2017

Electrical impedance tomography is a relatively new nondestructive imaging modality in which the internal conductivity distribution is reconstructed based on the injected currents and measured voltages through electrodes placed on the surface of a domain. In this paper, a fast iterative Gauss-Newton method is proposed to increase the spatial resolution as well as reduce the inverse computational time in the inverse problem, which could be applied to online binary mixture flow applications. To evaluate the reconstruction performance of the proposed method, numerical experiments have been carried out and the results are analyzed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

When the sensor geometry is poor, the user position estimate obtained by of GN (Gauss-Newton) method is often diverged in radio navigation. In other to avoid divergence problem QCLS (Quadratic Correction Least Square) method using TDOA (Time Difference of Arrival) measurements is introduced, but the estimation error is somewhat large. This paper presents the modified QCLS method using weighted least square. Since the weighting matrix is influenced by the unknown user position, two-step approach is employed in the proposed method. The weighting matrix is estimated in the first step using least square, and then find user position is obtained using weighted least square. Simulation results show that the performance of the proposed method is superior to the conventional QCLS all over the workspace.

• 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 IKEEE
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• v.19 no.1
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• pp.33-40
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• 2015

Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.3
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• pp.227-232
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• 1995

A new evaluation procedure for calculating the Jacobian elliptic parameter is presented. This procedure is useful in calculating the trajectory for cnoidal wave generation. Upon specification of water depth, the wave height and either the wave period or the wavelength, the presented algorithm uses the Newton-Raphson method and the arithmetic and geometric-mean scales to calculate the profile directly, without trial and error procedures or look-up in tables. It is shown that the algorithm provides equally accurate result as the ad hoc methods previously used.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.565-568
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• 2011

NURBS는 매개변수를 이용하여 3차원에서 곡면을 표현한 방법으로서 노트벡터, 조정점, 가중치로 구성된다. 레벨셋은 공간을 음함수로 정의된 장으로 형성하여 음함수의 일정한 값을 추적하여 곡면을 표현한 방법이다. 본 논문에서는 스캔 데이터를 NURBS 형태로 추출한 뒤 이를 정밀한 레벨셋 모델로 변환하였다. 레벨셋 모델을 구성하기 위해서 형성된 음함수는 부호를 갖는 거리함수를 사용하였고, 거리함수를 정밀하게 나타내기 위해 Newton 순환법을 이용하였다. 변환된 레벨셋 모델을 이용하여 형상의 몰핑을 수행하였다. 몰핑은 초기 형상을 목표 형상으로 변화시켜 나가는 과정으로서 레벨셋 모델을 이용한 몰핑은 용이성과 질적인 측면에서 우수하다. 수치 예제에서는 스캔 데이터의 레벨셋 모델 변환과 변환된 형상이 자연스럽게 목표형상으로 변화하는지를 확인한다.

• Nuclear Engineering and Technology
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• v.4 no.1
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• pp.11-22
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• 1972

Determination of a two-point boundary value problem is the key of finding the control function u(t) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial costate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's Sequential method is examined about a number of engineering problems and found available.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.4-4
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• 1994

미분방정식은 많은 학문에서 현실 세계의 대상을 모형화하고 시뮬레이션하는 데에 매우 유용하게 사용되는 도구이다. 그 중에서도 현실 세계에서 적용되는 물리적 법칙에 근거해서 가상 세계를 만드는 컴퓨터 애니메이션이나 과학적 가시화등의 분양에서는 미분방정식으로 다루고자하는 대상을 모형화하고 시뮬레이션을 통해서 필요한 자료를 추출하는 과정이 필수적이다. 본 연구에서는 현실 세계에 근거한 가상세계를 만들기 위해서 요구되는 물리적 시뮬레이션을 수행하기 위한 방법을 연구하고, 그 소프트웨어를 개발한다. 현실세게를 모형화하는데에 많이 쓰이는 물리학적 방법은 역학에 근거한 미분방정식들이다. 그 중에서도 연립 상미분방정식의 형태로 많이 나타나는 Newton 방정식은 거시적인 물체들간의운동ㅇㄹ 표현하는데에 많이 사용도니다. 그리고 편미분방정식의 형태로 나타나는 Lagrange 방정식은 Hamilton의 원리를 운동방정식에 적용하여 얻은 것으로 Newton 방정식과 관계가 없는 광버무이한 물리적 현상을 표현하는데에 사용된다. 본 연구에서 개발하는 시물레이션 소프트웨어는 연립 상미분방정식으로 모형화되는 대상을 시뮬레이션할 수 있는 방법과 2c, 편미분방정식으로 모형화되는 대상을 시뮬레이션 할 수 있는 방법을 제공한다.

• Nuclear Engineering and Technology
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• v.1 no.2
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• pp.79-85
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• 1969

Determination of a two-point boundary value problem is the key of finding the control function u(f) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial testate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's sequential method is examined in this paper.

• 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.