• Honam Mathematical Journal
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• v.36 no.4
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• pp.831-852
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• 2014

The obstacle shape reconstruction problem has been known to be difficult to solve since it is highly nonlinear and severely ill-posed. The use of local or locally supported basis functions for the problem has been addressed for many years. However, to the authors' knowledge, any research report on the proper usage of local or locally supported basis functions for the shape reconstruction has not been appeared in the literature due to many difficulties. The aim of this paper is to introduce the general concepts and methodologies for the proper choice and their implementation of locally supported basis functions through the two-dimensional Helmholtz equation. The implementations are based on the complex nonlinear parameter estimation (CNPE) formula and its robust algorithm developed recently by the authors. The basic concepts and ideas are simple. The derivation of the necessary properties needed for the shape reconstructions are elementary. However, the capturing abilities for the local geometry of the obstacle are superior to those by conventional methods, the trial and errors, due to the proper implementation and the CNPE algorithm. Several numerical experiments are performed to show the power of the proposed method. The fundamental ideas and methodologies described in this paper can be applied to many other shape reconstruction problems.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.276-284
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• 2000

Usual practice of the transformation of a B-spline curve into a set of piecewise polynomial curves in a power form is done by either a knot refinement followed by basis conversions or applying a Taylor expansion on the B-spline curve for each knot span. Presented in this paper is a new algorithm, called a direct expansion algorithm, for the problem. The algorithm first locates the coefficients of all the linear terms that make up the basis functions in a knot span, and then the algorithm directly obtains the power form representation of basis functions by expanding the summation of products of appropriate linear terms. Then, a polynomial segment of a knot span can be easily obtained by the summation of products of the basis functions within the knot span with corresponding control points. Repeating this operation for each knot span, all of the polynomials of the B-spline curve can be transformed into a power form. The algorithm has been applied to both static and dynamic curves. It turns out that the proposed algorithm outperforms the existing algorithms for the conversion for both types of curves. Especially, the proposed algorithm shows significantly fast performance for the dynamic curves.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.5 no.2
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• pp.38-41
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• 1999

This study was carried out to investigate improvement of kraft paper sack mixed with recycled paper for sugars and assorted feeds. Four Plies of kraft paper mixed with recycled paper(basis weight : $80g/m^2$) were taken place of two plies of kraft paper made from all pulp(basis weight : $98g/m^2$) and one ply of kraft paper mixed with recycled paper(basis weight : $80g/m^2$) for sugar 30kg. Three Plies of kraft paper mixed with recycled paper(basis weight : $80g/m^2$) were taken place of two plies of kraft paper made from all pulp(basis weight $98g/m^2$) for sugar 15kg and assorted feed 25kg. Physical properties, tensile strength, internal tearing strength and bursting strength, were improved by exchanging kraft paper mixed with recycled paper for kraft paper from all pulp and so kraft paper sacks made from all pulp were no damage in handling. They had so high friction coefficient that there was no danger of collapse on pallet by slipperiness in transportation and handling. And they had high printability so disappearance of printing by the contact with other paper sack in transportation was not found.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1660-1668
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• 2004

This paper proposes a Voice Activity Detection (VAD) algorithm based on Radial Basis Function (RBF) network using dual threshold. The k-means clustering and Least Mean Square (LMS) algorithm are used to upade the RBF network to the underlying speech condition. The inputs for RBF are the three parameters in a Code Exited Linear Prediction (CELP) coder, which works stably under various background noise levels. Dual hangover threshold applies in BRF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental result show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.135-142
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• 2012

In this paper, we proposed a new architecture called radial basis function-based polynomial neural networks classifier that consists of heterogeneous neural networks such as radial basis function neural networks and polynomial neural networks. The underlying architecture of the proposed model equals to polynomial neural networks(PNNs) while polynomial neurons in PNNs are composed of Fuzzy-c means-based radial basis function neural networks(FCM-based RBFNNs) instead of the conventional polynomial function. We consider PNNs to find the optimal local models and use RBFNNs to cover the high dimensionality problems. Also, in the hidden layer of RBFNNs, FCM algorithm is used to produce some clusters based on the similarity of given dataset. The proposed model depends on some parameters such as the number of input variables in PNNs, the number of clusters and fuzzification coefficient in FCM and polynomial type in RBFNNs. A multiobjective particle swarm optimization using crowding distance (MoPSO-CD) is exploited in order to carry out both structural and parametric optimization of the proposed networks. MoPSO is introduced for not only the performance of model but also complexity and interpretability. The usefulness of the proposed model as a classifier is evaluated with the aid of some benchmark datasets such as iris and liver.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.988-1003
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• 2021

Existing elastic analysis methods cannot be adhered to in order to assess the structural integrity of a reactor vessel and internals for a beyond design basis earthquake. Elasto-plastic analysis methods are required, and the factors that affect the elasto-plastic behavior of reactor materials should be taken into account. In this study, a material behavior model was developed that considers the irradiation embrittlement effect, which affects the elasto-plastic behavior of the reactor material. This was used to perform the elasto-plastic time history analyses of the reactor vessel and its internals for beyond design basis earthquake. For this investigation, appropriate beyond design basis earthquakes and reliable finite element models were used. Based on the analysis results, consideration was given to the load reduction effect and the margin change. These were transferred to the internals due to the plastic deformation of the reactor vessel.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.196-220
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• 2021

This study formulates a new geometric parameterization scheme to effectively address numerical analysis subject to the variation of the fiber radius of a square unit cell. In particular, the proposed mesh-morphing approach may lead to a parameterized weak form whose bilinear and linear forms are affine in the geometric parameter of interest, i.e. the fiber radius. As a result, we may certify the reduced basis analysis of a square unit cell model for any parameters in a predetermined parameter domain with a rigorous a posteriori error bound. To demonstrate the utility of the proposed geometric parameterization, we consider a two-dimensional, steady-state heat conduction analysis dependent on two parameters: a fiber radius and a thermal conductivity. For rapid yet rigorous a posteriori error evaluation, we estimate a lower bound of a coercivity constant via the min-θ method as well as the successive constraint method. Compared to the corresponding finite element analysis, the constructed reduced basis analysis may yield nearly the same solution at a computational speed about 29 times faster on average. In conclusion, the proposed geometric parameterization scheme is conducive for accurate yet efficient reduced basis analysis.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.470-472
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• 1999

Sparse coding은 최소한의 active한 (non-orthogonal) basis vector를 이용하여 데이터를 표시하는 하나의 방법이다. Sparse coding에서 basis coefficient들이 statistically independent 하다는 constraint를 주기에 sparse coding은 independent component analysis(ICA)와 밀접한 관계를 가지고 있다. 본 논문에서는 sparse representation을 위하여 super-Gaussian prior를 이용한 ICA, 즉 sparse ICA 방법을 제시한다. Sparse ICA 방법을 이용하여 natural scenes의 basis vector를 찾고 이와 sparse coding과의 관계를 고찰한다. 여러 가지 super-Gaussian prior들을 고려하지 않고 이들이 ICA에 미치는 영향에 대해 살펴본다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.233-236
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• 1996

A new method of blocking effects reduction is proposed in this paper for use in low bitrate image coding. We use 28 DCT kernel functions of which boundary values are linearly independent, and Gram-Schmidt process is applied to the boundary values in order to obtain 28 boundary-orthonormal basis images. Then we use these basis images to obtain the correction terms for blocking artifacts reduction. A threshold of block discontinuity is introduced for improvement of visual quality by reducing image blurring. We also investigate the number of basis images needed for efficient blocking artifacts reduction when the compression ratio changes.