• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.174-184
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• 2006

In order to fill the holes with complex shapes in the large polygon model, a new approach which is based on the implicit surface interpolation method combined with domain decomposition method is presented. In the present study, a surface is constructed by creating smooth implicit surface from the incomplete polygon model through which the surface should pass. In the method an implicit surface is defined by a radial basis function, a continuous scalar-valued function over the domain $R^3$ The generated surface is the set of all points at which this scalar function takes on the value zero and is created by placing zero-valued constraints at the vertices of the polygon model. In this paper the well-known domain decomposition method is used in order to treat the large polygon model. The global domain of interest is divided into smaller domains where the problem can be solved locally. LU decomposition method is used to solve a set of small local problems and their local solutions are combined together using the weighting coefficients to obtain a global solution. In order to show the validity of the present study, various hole fillings are carried out fur the large and complex polygon model of arbitrary topology.

• Journal of Korean Ophthalmic Optics Society
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• v.6 no.2
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• pp.121-127
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• 2001

While SVD and Gaussian elimination method were applied to the additive damped least squares(DLS), the convergence and the stability of the optimization process were examined in a triplet-type camera lens-system where the condition number is well conditioned. DLS with SVD method generated a suitable merit function but this merit function may be trapped in a local minimum by the nonlinearity of error function. Therefore, the least camera lens-system was further designed by the global optimization method is grid method, and this method is adopted to get merit function that convergent to global minimum without local minimum trapping.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.19-27
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• 2001

Seismic parameters fur computation of ground motions in Southern Korea are obtained from recently recorded data, and site-independent regional and site-dependent local strong ground motions are predicted using efficient computational techniques. For the computation of ground motions, we devised an efficient procedure to compute site-independent $x_{q}$ and dependent $x_{s}$ values separately. The first step of this procedure is to use the coda normalization method far computation of site independent Q or corresponding $x_{q}$ value. The next step is the computation of $x_{s}$, values fur each site separately using the given $x_{q}$ value. For computation of ground motions the empirical Green's function (EGF) is modified to account fur the depth and distance variations of subevents on a finite fault plane using the theoritical Green's function. It is computed using wavenumber integration technique in layered media. The site dependent ground motions at seismic stations in southeastern local area were properly simulated using the modified empirical Green's function method in layered medium. The proposed method and procedures fur estimation of site dependent seismic parameters and ground motions could be efficiently used in the low and moderate seismicity regions.ons.s.ons.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2418-2425
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• 1994

Although the error backpropagation(EBP) algorithm based on the gradient descent method is a widely-used learning algorithm of neural networks, learning sometimes takes a long time to acquire accuracy. This paper develops a novel learning method to alleviate the problems of EBP algorithm such as local minima, slow speed, and size of structure and thus to improve performance by adopting other new networks. Gaussian Potential Function networks(GPFN), in parallel with multilayer neural networks. Empirical simulations show the efficacy of the proposed algorithm in function approximation, which enables us to train networks faster with the better generalization capabilities.

• Korean System Dynamics Review
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• v.15 no.2
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• pp.75-96
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• 2014

The purpose of this paper is to analyze the functional changes of local educational authority policy based on the systems thinking perspective using causal loop diagrams. In the past, the main function of the local educational authority was to manage and supervise schools. Through this policy, local educational authority would be transformed into a support agency. However, this policy did not achieve the goal, was to cause confusion and require improvement. This study shows structured causes of the problem based on systems thinking. These diagrams make it possible for educational policy makers to provide ideas, although they have some complicated environment. The findings indicate that based on systems thinking in this policy can help those who related to policy decision than existing diagnosis method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1008-1015
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• 2002

This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.159-162
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• 2008

This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.228-234
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the local rationalized Haar transform, local operational matrix and local delay operational matrix. This approach let a general sampling time be used by introducing a scaling factor. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method is suitable for the analysis of linear systems. The proposed method is expected to the applicable to the adaptive control which demanded to the real-time applications.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.333-336
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• 2000

In this paper, a profile management system consisting of global and local range finders is presented for the automat ion of material pile handling. A global range finder detects range data of the front part of the piles of material and a profile map is obtained from a 3D profile detection algorithm. A local range finder attached on the side of the arm of the reclaimer detects range data with the handling function dynamically, and a local profile patch is acquired from the range data A yard profile map manager constructs a map by using the 3D profile of the global range finder and revises the map by replacing it with the local profile patch obtained Iron the local range finder. The developed vision system was applied to a simulator and the results of test show that it is appropriate to use for automating the material handling.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.