• Proceedings of the Korea Society for Simulation Conference
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• 2000.04a
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• pp.91-95
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• 2000

The purpose of format conversion is to convert a wide range of personal computer video formats to a target format. Circuits for the conversion has been developed by means of interpolation techniques, such as zero-order interpolation, bilinear interpolation, and bisigmoidal interpolation. This paper proposes a scan converter using cubic splines. The converter was modeled in VHDL on Max+Plus II and implemented with an FPGA cpip. The circuit gives much better conversion performance than a scan converter with zero-order or linear interpolation.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.379-385
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• 2010

This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

• 한국전산유체공학회:학술대회논문집
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• 2002.10a
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• pp.84-87
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• 2002

When computing the flow around complex three dimensional configurations, the generation of grid is the sunt time consuming part of any calculation. The object of this study is to develop the grid duster techniques capable of resolving complex flows with shock waves, expansion waves, shear layers, and cursive shapes, The Dot insert method of Non-Uniform Rational B-Splines is described as a id control method.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.77-88
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• 1998

Smoothing spline estimators are modified to remove boundary bias effects using the technique proposed in Eubank and Speckman (1991). An O(n) algorithm is developed for the computation of the resulting estimator as well as associated generalized cross-validation criteria, etc. The asymptotic properties of the estimator are studied for the case of a linear smoothing spline and the upper bound for the average mean squared error of the estimator given in Eubank and Speckman (1991) is shown to be asymptotically sharp in this case.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.339-345
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• 2007

In this paper, a variational formulation for plane elasticity problems is derived based on an isogeometric approach. The isogeometric analysis is an emerging methodology such that the basis functions for response analysis are generated directly from NURBS (Non-Uniform Rational B-Splines) geometry. Furthermore, the solution space for the response analysis can be represented in terms of the same functions to represent the geometry, which enables to provide a precise construction method of finite element model to exactly represent geometry using B-spline base functions in CAD geometric modeling and analyze arbitrarily shaped structures without re-meshing. In this paper, a continuum-based adjoint sensitivity analysis method using the isogeometric approach is extensively derived for the plane elasticity problems. The conventional shape optimization using the finite element method has some difficulties in the parameterization of geometry In the isogeometric analysis, however, the geometric properties are already embedded in the B-spline basis functions and control points so that it has potential capability to overcome the aforementioned difficulties. Through some numerical examples, the developed isogeometric sensitivity analysis method is verified to show excellent agreement with finite difference sensitivity.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.38-48
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• 2007

In this paper, we propose an image-based method for modeling 3D objects with curved surfaces based on the NURBS (Non-Uniform Rational B-Splines) representation. Starting from a few calibrated images, the user specifies the corresponding curves by means of an interactive user interface. Then, the 3D curves are reconstructed using stereo reconstruction. In order to fit the curves easily using the interactive user interface, NURBS curves and surfaces are employed. The proposed surface modeling techniques include surface building methods such as bilinear surfaces, ruled surfaces, generalized cylinders, and surfaces of revolution. In addition to these methods, we also propose various advanced surface modeling techniques, including skinned surfaces, swept surfaces, and boundary patches. Based on these surface modeling techniques, it is possible to build various types of 3D shape models with textured curved surfaces without much effort. Also, it is possible to reconstruct more realistic surfaces by using proposed view-dependent texture acquisition algorithm. Constructed 3D shape model with curves and curved surfaces can be exported in VRML format, making it possible to be used in different 3D graphics softwares.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.1
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• pp.8-15
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• 2002

A two-dimensional higher order panel method using B-splines has been developed to overcome the disadvantages of the low order panel method and to obtain more accurate solution. The sources and the normal dipoles are distributed on both the body and the free surface. Instead of applying the upwind finite difference schemes to satisfy the linearized free surface and the radiation condition, the derivatives of the basis functions of the B-splines are directly applied to the linearized free surface condition. Numerical damping in the Dawson's method are avoided in the Present computations. In order to validate the present method, numerical computations are carried out for a submerged cylinder and a two-dimensional hydrofoil steadily moving beneath a free surface. The numerical results show that fast convergence and better accuracies have been achieved by the present method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.17-30
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• 2000

In this paper, we propose an efficient algorithm to produce 3-D surface model from a set of range data, based on NURBS (Non-Uniform Rational B-Splines) surface fitting technique. It is assumed that the range data is initially unorganized and scattered 3-D points, while their connectivity is also unknown. The proposed algorithm consists of three steps: initial model approximation, hierarchical representation, and construction of the NURBS patch network. The mitral model is approximated by polyhedral and triangular model using K-means clustering technique Then, the initial model is represented by hierarchically decomposed tree structure. Based on this, $G^1$ continuous NURBS patch network is constructed efficiently. The computational complexity as well as the modeling error is much reduced by means of hierarchical decomposition and precise approximation of the NURBS control mesh Experimental results show that the initial model as well as the NURBS patch network are constructed automatically, while the modeling error is observed to be negligible.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.1-16
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• 2016

In this paper, we propose and efficient curve reconstruction method based on the classical least-square fitting scheme. Specifically, given planar sample points equipped with normals, we reconstruct the objective curve as the zero set of a hierarchical implicit ZP(Zwart-Powell)-spline that can recover large holes of dataset without loosing the fine details. As regularizers, we adopted two: a Tikhonov regularizer to reduce the singularity of the linear system and a discrete Laplacian operator to smooth out the isocurves. Benchmark tests with quantitative measurements are done and our method shows much better quality than polynomial methods. Compared with the hierarchical bi-quadratic spline for datasets with holes, our method results in compatible quality but with less than 90% computational overhead.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.219-233
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• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.