• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.355-360
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• 2000

This paper presents properties of piecewise cubic B-spline function and Rayleigh-Ritz method to compute the smallest eigenvales. In order to compute the smallest eigenvalues, Rayleigh quotient approach is used and four different types of finite element approximating functions corresponding to the statical deflection curve, spanned by the linearly independent set of piecewise cubic B-spline functions with equally spaced 5 knots from a partion of [0, 1], each satisfying homogeneous boundary conditions with constraining effects are used to compute the smallest eigenvalues for a Sturm-Lionville boundary equations of u"＋ λ²u＝0, u(0.0)＝u(0.0)＝0, 0≤x≤1.0.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.320-322
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• 2008

We present efficient algorithms for solving the piecewise-cubic approximation problems in the plane. Given a set D of n points in the plane, we find a piecewise-cubic polynomial curve passing through only the points of a subset S of D and approximating the other points using the uniform metric. The goal is to minimize the size of S for a given error tolerance $\varepsilon$, called the min-# problem, or to minimize the error tolerance $\varepsilon$ for a given size of S, called the min-$\varepsilon$ problem. We give algorithms with running times O($n^2$ logn) and O($n^3$) for both problems, respectively.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.83-85
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• 2003

This paper presents a correction technique of missing load data. In this paper, the ARIMA(Autoregressive Integrated Moving Average) model and Piecewise Cubic Interpolation are applied to seek the missing parameters. The new model has been tested under a variety of conditions and it is shown in this paper to produce excellent results. It is helpful for operators to designed the load duration curve.

• The Journal of Information Technology
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• v.5 no.1
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• pp.99-111
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• 2002

Due to non-linear characteristics of color spaces, color corrections using linear conversions for real image near color reappearance causes color distortions. In order to overcome this problem, the Bezier Curve, constructed with a set of arbitrary plane in the linear theory, has been used. However, the Bezier Curve increases in proportion to the number of data points, resulting in higher computational complexities. This paper attempts to use a Triplicated Piecewise Bezier Cubic-Curve (TPBC-Curve) of which the degree is cubic on the whole interval while keeping the characteristics of Bezier Curves. By Comparing the TPBC-Curve with Bezier Curve of 20 degree, the paper not only reduces the distortion during color correction but also lessens the relative increase of workload that is caused by the color correction in a small zone.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1289-1297
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• 2006

Before other statistical data analysis the preprocessing steps should be performed adequately to have meaningful results. These steps include processes such as baseline correction, normalization, denoising, and multiple alignment. In this paper an algorithm for baseline correction is proposed with using the piecewise cubic Hermite interpolation with block-selected points and local minima after denoising for SELDI or MALDI mass spectrometry data.

• Bulletin of the Korean Mathematical Society
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• v.29 no.2
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• pp.193-200
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• 1992

This paper uses a piecewise ratonal cubic interpolant to solve the problem of shape preserving interpolation for plane curves; scalar curves are also considered as a special case. The results derived here are actually the extensions of the convexity preserving results of Delbourgo and Gregory [Delbourgo and Gregory'85] who developed a $C^{1}$ shape preserving interpolation scheme for scalar curves using the same piecewise rational function. They derived the ocnstraints, on the shape parameters occuring in the rational function under discussion, to make the interpolant preserve the convex shape of the data. This paper begins with some preliminaries about the rational cubic interpolant. The constraints consistent with convex data, are derived in Sections 3. These constraints are dependent on the tangent vectors. The description of the tangent vectors, which are consistent and dependent on the given data, is made in Section 4. the convexity preserving results are explained with examples in Section 5.

• Journal of Welding and Joining
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• v.27 no.5
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• pp.42-48
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• 2009

Pipe welding is used in various ranges such as civil engineering and ship building engineering. Until now, many technicians work for pipe welding manually under harmful, dangerous and difficult conditions. So it is necessary to install automation process. For automation pipe welding, relation between welding parameters & bead shape should be considered. Using this relation, bead shape could be expected from welding parameters. FCAW was used in this study. Instead of pipe workpiece, fillet joint plate is used, which were inclined 0,45,90,135,180 degree. By analyzing between welding parameters (current, welding speed, voltage) and bead shape parameters with non-linear multiple regression, bead shape parameters could be expected. Piecewise Cubic Hermite Interpolation was used to expect smooth curved bead shape with bead shape parameters. From these processes, bead shape could be expected from welding parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.16-22
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• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

• Kyungpook Mathematical Journal
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• v.24 no.1
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• pp.55-61
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• 1984

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.233-240
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• 2016

This paper describes a three-dimensional reference trajectory generation method for giving commands to an unmanned air vehicle (UAV). The trajectory is a set of consecutive curves with constant acceleration during each interval and passing through via-points at specified times or speeds. The functional inputs are three-dimensional positions and times (or speeds) at via-points, and velocities at both boundaries. Its output is the time series of position values satisfying the piecewise constant acceleration condition. To be specific, the shape of the trajectory, known as the path, is first represented by splines using third degree polynomials. A numeric algorithm is then suggested, which can overcome the demerits of cubic spline method and promptly generate a piecewise constant acceleration trajectory from the given path. To show the effectiveness of the present scheme, trajectory generation cases were treated, and their speed calculation errors were evaluated.