• Structural Engineering and Mechanics
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• v.14 no.6
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• pp.713-732
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• 2002

A local radial point interpolation method (LRPIM) based on local residual formulation is presented and applied to solid mechanics in this paper. In LRPIM, the trial function is constructed by the radial point interpolation method (PIM) and establishes discrete equations through a local residual formulation, which can be carried out nodes by nodes. Therefore, element connectivity for trial function and background mesh for integration is not necessary. Radial PIM is used for interpolation so that singularity in polynomial PIM may be avoided. Essential boundary conditions can be imposed by a straightforward and effective manner due to its Delta properties. Moreover, the approximation quality of the radial PIM is evaluated by the surface fitting of given functions. Numerical performance for this LRPIM method is further studied through several numerical examples of solid mechanics.

• Structural Engineering and Mechanics
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• v.11 no.2
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• pp.221-236
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• 2001

A local point interpolation method (LPIM) is presented for the stress analysis of two-dimensional solids. A local weak form is developed using the weighted residual method locally in two-dimensional solids. The polynomial interpolation, which is based only on a group of arbitrarily distributed nodes, is used to obtain shape functions. The LPIM equations are derived, based on the local weak form and point interpolation. Since the shape functions possess the Kronecker delta function property, the essential boundary condition can be implemented with ease as in the conventional finite element method (FEM). The presented LPIM method is a truly meshless method, as it does not need any element or mesh for both field interpolation and background integration. The implementation procedure is as simple as strong form formulation methods. The LPIM has been coded in FORTRAN. The validity and efficiency of the present LPIM formulation are demonstrated through example problems. It is found that the present LPIM is very easy to implement, and very robust for obtaining displacements and stresses of desired accuracy in solids.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.3
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• pp.49-58
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• 2020

Image interpolation, a technology that converts low resolution images into high resolution images, has been widely used in various image processing fields such as CCTV, web-cam, and medical imaging. This technique is based on the fact that the statistical distributions of the white Gaussian noise and the difference between the interpolated image and the original image is similar to each other. The proposed algorithm is composed of three steps. In first, the interpolated image is derived by random image interpolation. In second, we derive weighting functions that are used to apply non-local mean filtering. In the final step, the prediction error is corrected by performing non-local mean filtering by applying the selected weighting function. It can be considered as a post-processing algorithm to further reduce the prediction error after applying an arbitrary image interpolation algorithm. Simulation results show that the proposed method yields reasonable performance.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.27 no.2
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• pp.120-124
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• 1991

An interaction of turbulent boundary layer and local roughness effects was evaluated to investigate the shear frictional coefficient in diffuser. Clauser roughness function was applied to Karman's integral equation for governing equation. The roughness of overall and local diffuser surfaces were calculated using Cole's wall and wake law and Clauser's roughness function for turbulent boundary layer characteristics. The calculating results were compared with the experimental results of other paper. It shows some significant improyements for shear frictional coefficient. Computer code was then used to confirm the behavior of local frictional coefficient along with diffuser roughness surface for some reduction of shear flow stress.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.173-180
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• 2012

This paper proposes a novel optimization algorithm inspired by water flowing and shaking behaviors in a vessel. Water drops in our algorithm flow to the gradient descent direction and are sometimes shaken for getting out of local optimum areas when most water drops fall in local optimum areas. These flowing and shaking operations allow our algorithm to quickly approach to the global optimum without staying in local optimum areas. We experimented our algorithm with four function optimization problems and compared its results with those of particle swarm optimization. Experimental results showed that our algorithm is superior to the particle swarm optimization algorithm in terms of the speed and success ratio of finding the global optimum.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.579-590
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• 2012

Local linear jump detection in a discontinuous regression function involves the choice of the bandwidth and the performance of a local linear jump detector depends heavily on the choice of the bandwidth. However, little attention has been paid to this important issue. In this paper we propose two fully data adaptive bandwidth selection methods for a local linear jump detector. The performance of the proposed methods are investigated through a simulation study.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.87-95
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• 2014

In the regression model, Kang and Huh (2006) studied the estimation of the discontinuous variance function using the Nadaraya-Watson estimator with the squared residuals. The local linear estimator of the log-variance function, which may have the whole real number, was proposed by Huh (2013) based on the kernel weighted local-likelihood of the ${\chi}^2$-distribution. Chen et al. (2009) estimated the continuous variance function using the local linear fit with the log-squared residuals. In this paper, the estimator of the discontinuous log-variance function itself or its derivative using Chen et al. (2009)'s estimator. Numerical works investigate the performances of the estimators with simulated examples.

• Kyungpook Mathematical Journal
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• v.32 no.1
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• pp.31-43
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• 1992

• Structural Engineering and Mechanics
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• v.44 no.5
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• pp.663-680
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• 2012

Previous major earthquakes revealed that most damage of the buried segmented pipelines occurs at the joints of the pipelines. It has been proven that the differential motions between the pipe segments are one of the primary reasons that results in the damage (Zerva et al. 1986, O'Roueke and Liu 1999). This paper studies the combined influences of ground motion spatial variations and local soil conditions on the seismic responses of buried segmented pipelines. The heterogeneous soil deposits surrounding the pipelines are assumed resting on an elastic half-space (base rock). The spatially varying base rock motions are modelled by the filtered Tajimi-Kanai power spectral density function and an empirical coherency loss function. Local site amplification effect is derived based on the one-dimensional wave propagation theory by assuming the base rock motions consist of out-of-plane SH wave or combined in-plane P and SV waves propagating into the site with an assumed incident angle. The differential axial and lateral displacements between the pipeline segments are stochastically formulated in the frequency domain. The influences of ground motion spatial variations, local soil conditions, wave incident angle and stiffness of the joint are investigated in detail. Numerical results show that ground motion spatial variations and local soil conditions can significantly influence the differential displacements between the pipeline segments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1167-1174
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• 1999

In this paper, we present a new technique for the local decomposition of convex structuring elements for morphological image processing. Local decomposition of a structuring element consists of local structuring elements, in which each structuring element consists of a subset of origin pixel and its eight neighbors. Generally, local decomposition of a structuring element reduces the amount of computation required for morphological operations with the structuring element. A unique feature of our approach is the use of linear integer programming technique to determine optimal local decomposition that guarantees the minimal amount of computation. We defined a digital convex polygon, which, in turn, is defined as a convex structuring element, and formulated the necessary and sufficient conditions to decompose a digital convex polygon into a set of basis digital convex polygons. We used a set of linear equations to represent the relationships between the edges and the positions of the original convex polygon, and those of the basis convex polygons. Further. a cost function was used represent the total processing time required for computation of dilation/erosion with the structuring elements in a decomposition. Then integer linear programming was used to seek an optimal local decomposition, that satisfies the linear equations and simultaneously minimize the cost function.