• Journal of IKEEE
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• v.28 no.2
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• pp.187-198
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• 2024

Estimating the phase boundary in two-phase flow is crucial for designing and optimizing industrial processes. Electrical impedance tomography (EIT) is a promising technique for imaging phase distribution in such flows. This paper proposes using a cuckoo search (CS) optimization algorithm to estimate the phase boundary with EIT. The boundary is parameterized using the Fourier series, and the coefficients are determined by the CS algorithm. The CS algorithm iteratively seeks the phase boundary configuration by minimizing a cost function. Computer simulations and phantom experiments demonstrate the effectiveness of this method in estimating phase boundaries in two-phase flow.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.32-35
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• 2004

In boundary estimation in Electrical Impedance Tomography (EIT), conventional method is the modified Newton Raphson (mNR) method .The mNR is famous for good method since has good convergence and robustness against noisy data. But the mNR is low efficiency to get and update Jacobian matrix. So, the mNR become very slow algorithm. We propose the Quasi Newton (QN) method to improve efficiency which will lead to speed up in boundary estimation. The QN can improve a low efficiency by using estimated Jacobian matrix contrary to using exactly calculated Jacobian matrix, this used by the mNR. And finally, we propose the modified Quasi Newton (mQN) method because the QN has some problems such as bad early convergence rate and instability of 'divided by zero'. For the verification of the propose method, numerical experiments are conducted and the results show a good performance.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.114-116
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• 1989

A method has been proposed for the fully automatic detection of left ventricular endocardial boundary in 2D short axis echocardiogram using geometric model. The procedure has the following three distinct stages. First, the initial center is estimated by the initial center estimation algorithm which is applied to decimated image. Second, the center estimation algorithm is applied to original image and then best-fit elliptic model estimation is processed. Third, best-fit boundary is detected by the cost function which is based on the best-fit elliptic model. The proposed method shows effective result without manual intervention by a human operator.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• Journal of IKEEE
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• v.18 no.4
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• pp.463-470
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• 2014

In stratified flows of two immiscible liquids, due to the vibration in a pipe, the shape of the interface is not always periodic and it causes the different end points of the interfacial boundary. In this case the performance is not good. To solve this, in this paper, the hybrid-type Fourier series is proposed, which consists of both the polynomial and the trigonometric terms. Under the stationary interfacial boundary during acquiring a full set of voltage data, the performance of the proposed method is evaluated through the numerical experiments. The results show that the proposed method performs better than the conventional Fourier series in estimating the interfacial boundary.

• Journal of IKEEE
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• v.16 no.3
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• pp.211-216
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• 2012

In the phase boundary estimation problem, the estimation performance depends on the initial guess. However, there is no information on the number of bubbles and those positions for the initial guess in real flows. Therefore, it is very important to set appropriate initial guesses from prior information. In this paper, in order to set initial guesses for estimating the phase boundaries in two-phase flows, first, unknown resistivity distribution was estimated using the difference reconstruction method. After that, an adaptive threshold value was automatically computed using intermodes method. Based on this value, the number of bubbles and the initial position were determined. The numerical experiments have been performed to evaluate the estimation performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.40-45
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• 2004

This work presents a boundary estimation approach in electrical impedance imaging for binary-mixture fields based on a parallel structured multi-layer neural network. The interfacial boundaries are expressed with the truncated Fourier series and the unknown Fourier coefficients are estimated with the parallel structure of multi-layer neural network. Results from numerical experiments shows that the proposed approach is insensitive to the measurement noise and has a strong possibility in the visualization of binary mixtures for a real time monitoring.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.139-144
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• 2011

This paper presents a boundary element application to determine the optimal impressed current densities at defect position on the pipe line. In this protection paint, enough current must be impressed to lower the potential distribution on the metal surface to the critical values. The optimal impressed current densities are determined in order to minimize the power supply for protection. This inverse problem was formulated by employing the boundary element method. Since the system of linear equations obtained was ill-conditioned, including singular value decomposition, conjugate gradient method were applied and the accuracies of these estimation. Several numerical examples are presented to demonstrate the practical applicability of the proposed method.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1320-1326
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• 2002

In a one-dimensional heat conduction domain with heated and insulated walls, an integral approach is proposed to estimate time-dependent boundary heat flux without internal measurements. It is assumed that the expression of the heat flux is not known a priori. Hence, the present inverse heat conduction problem is classified as a function estimation problem. The spatial temperature distribution is approximated as a third-order polynomial of position, whose four coefficients are determined from the heat fluxes and the temperatures at both ends at each measurement. After integrating the heat conduction equation over spatial and time domain, respectively, a simple and non-iterative recursive equation to estimate the time-dependent boundary heat flux is derived. Several examples are introduced to show the effectiveness of the present approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.726-732
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• 2013

It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.