• International Journal of Contents
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• v.1 no.1
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• pp.1-5
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• 2005

This paper presents the development and application of electrical resistance imaging techniques for the visualization of two-phase flow fields. Two algorithms, the so-called the mesh grouping and the boundary estimation, are described for potential applications of electrical resistance tomography (ERT) and results from extensive numerical simulations are also presented. In the electrical resistance imaging for two-phase flows, numerical meshes fairly belonging to each phase can be grouped to improve the reconstruction performance. In many cases, the detection of phase boundary is a key subject and a mathematical model to estimate phase boundary can be formulated in a different manner. Our results indicated that the mesh grouping algorithm is effective to enhance computational performance and image quality, and boundary estimation algorithm to determine the phase boundary directly.

• 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.

• 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.

• Journal of the Korean Ceramic Society
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• v.39 no.9
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• pp.818-821
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• 2002

The grain boundary resistivity of a 1-mol%-$Al_2O_3$-dopedd CaO-Stabilized Zirconia(CSZ) specimen was determined by impedance spectroscopy using sub-millimeter-scale electrodes. At the initial stage of sintering, the grain-boundary resistivity of the specimen interior was observed to be higher than that of the surface. However, upon further sintering the boundary resistivity of the specimen interior became lower than that of the surface. The results were explained in terms of a redistribution of the intergranular liquid phase. The liquid phase was predicted to initially coagulate at the interior of the specimen then spread outward during sintering.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.553-558
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• 2003

The boundary estimation problem is used to estimate the shape of organic depend on the phase of the cardiac cycle or interested in the detection of the location and size of anomalies with resistivity values different from the background tissues such as nuclear reactor. And we can use the method to solve the optimal solution such as modified Newton raphson, kalman filter, extended kalman filter, etc. But, this method consumes much time and is sensitive to the initial value and noise in the estimation of the unknown shape. In the paper, we propose that multi-layer neural networks estimate the boundary of the unknown object using Fourier coefficient. This method can be used at the real time estimation and have strong characteristics at the noise and initial value. It uses voltage change; difference the homogeneous voltage to the non-homogeneous voltage, and change of Fourier coefficient change to train multi-layer neural network. After train, we can have real time estimation using this method.

• 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 Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.162-170
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• 1996

A numerical study on the Stefan problem occurred in cryosurgery is performed. Crank-Nicholson type finite difference algorithm based on the enthaly method is adapted to solve the phase change problem in this study. As it is a moving boundary problem, special emphasis is put on the estimation of the freezing front location. Two cases selected here are freezings of human tissue by disk type cryoprobe and by hemispherical one. In both cases, the heat flows are considered to be one dimensional. The calculated results using enthalpy method are compared with those using the program TRUMP and with Neumann's solution. These results agree guite well with each other. While it is pretty difficult to get accurate freezing front location by TRUMP due to the so- called "phase change knee" occured during the phase change, the algorithm based on the enthalpy method is proved to be very powerful to cope with this kind of problem.f problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.453-459
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• 2017

Users tend to check in and post their statuses in location-based social networks (LBSNs) to describe that their interests are related to a point-of-interest (POI). While previous studies on discovering area-of-interests (AOIs) were conducted mostly on the basis of density-based clustering methods with the collection of geo-tagged photos from LBSNs, we focus on estimating a POI boundary, which corresponds to only one cluster containing its POI center. Using geo-tagged tweets recorded from Twitter users, this paper introduces a density-based low-complexity two-phase method to estimate a POI boundary by finding a suitable radius reachable from the POI center. We estimate a boundary of the POI as the convex hull of selected geo-tags through our two-phase density-based estimation, where each phase proceeds with different sizes of radius increment. It is shown that our method outperforms the conventional density-based clustering method in terms of computational complexity.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.33-41
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• 2017

We present a region-based approach for accurate pose estimation of small mechanical components. Our algorithm consists of two key phases: Multi-view object co-segmentation and pose estimation. In the first phase, we explain an automatic method to extract binary masks of a target object captured from multiple viewpoints. For initialization, we assume the target object is bounded by the convex volume of interest defined by a few user inputs. The co-segmented target object shares the same geometric representation in space, and has distinctive color models from those of the backgrounds. In the second phase, we retrieve a 3D model instance with correct upright orientation, and estimate a relative pose of the object observed from images. Our energy function, combining region and boundary terms for the proposed measures, maximizes the overlapping regions and boundaries between the multi-view co-segmentations and projected masks of the reference model. Based on high-quality co-segmentations consistent across all different viewpoints, our final results are accurate model indices and pose parameters of the extracted object. We demonstrate the effectiveness of the proposed method using various examples.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.423-428
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• 2013

This paper investigates a boundary tracking problem using multiple quadrotor UAVs to detect and track the boundary of physical events. We set the boundary estimation problem as a classification problem of the region in which the physical events occur, and employ SVL (Support Vector Learning). We also demonstrate a velocity vector field which is globally attractive to a desired closed path with circulation at the desired speed and a virtual phase for stabilizing the collective configuration of the multiple quadrotors. Experimental results with multiple quadrotors show that this study provides good performance of the collective boundary tracking.