• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.1-9
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• 2016

Linear interpolation is a basic sampling method for volume visualization. This method generates good images but sometimes it is inferior to our high expectation because it is encouraged to produce high quality images in the medical applications. In this paper, B spline based tri-cubic interpolation is used for the re-sampling step. The conventional B spline is an approximation method which does not cross control points so that we moved the control points and the curve crosses the original control points. In the rendering step, the empty space leaping is applicable to increase rendering speed. We have to calculate the maximum and minimum values for each block to detect empty space. The convex hull property of B spline enables the values of control points to be used as the maximum and minimum values. As a result, tri-cubic interpolated volume rendering is possible in interactive speed.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.97-108
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• 2005

In this paper a method of reconstructing a desired image through the geometrical transformation and the interpolation techniques is presented by comparing different interpolation schemes. Several different interpolation schemes are compared with respect to the amount of error that is the difference between the original and the reverse-projective transformed images. Higher ordered B-spline interpolation turned to be superior to other techniques in reconstructing the image which is desired to be close to the unskewed image as much as possible. In the results, this paper demonstrates that the reverse projection using the higher ordered B-spline interpolation is superior to those conventional interpolation methods, linear, cubic spline for reconstructing image. In experiments, the error decreases as the order of B-spline increases. The proposed technique is useful for various practical and theoretical applications in the area of satellite, medical, and commercial image processing.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.921-931
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• 2011

This paper presents a data-fitting technique in which a B-spline hypervolume is used to approximate a given data set of scattered data samples. We describe the implementation of the data structure of a B-spline hypervolume, and we measure its memory size to show that the representation is compact. The proposed technique includes two algorithms. One is for the determination of the knot vectors of a B-spline hypervolume. The other is for the control points, which are determined by solving a linear least-squares minimization problem where the solution is independent of the data-set complexity. The proposed approach is demonstrated with various data-set configurations to reveal its performance in terms of approximation accuracy, memory use, and running time. In addition, we compare our approach with existing methods and present unconstrained optimization examples to show the potential for various applications.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.691-694
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• 1999

This paper presents a performance improvement technique of 2-D towed array shape estimation using Kalman filters. The proposed algorithm by linear model approximation corrects the position errors caused by the Kalman filter results. However, since the assumed linear model makes errors at bending parts, the spline interpolation algorithm based on curve is proposed to reduce the errors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.3
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• pp.305-313
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• 2000

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current methods used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). Generally speaking. the nonlinear profile formulas provide better accuracy than the linear profile formulas. However, all the formulas mentioned have a common drawback to ground profile, such as sharp corners or the grid points of any two straight lines. In this paper, mathematical model for a searching examination the drawbacks of the current methods is presented. Also, the presented formular, the spot height method, and chamber formulas, chen and lin method are compared with the volumes of the pits in these examples. As a result of this study, algorithm of a proposal area formula by spline method should provide a better accuracy than the spot height method, chamber formulas, chen and lin method. The mathematical model mentioned make an offer maximum accuracy in estimating the volume of a pit excavation.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.72-76
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• 2000

A calibration technique is proposed to improve the performance of 2-D towed array shape estimation using the Kalman filter. In the case of using displacement sensors, 2-D hydrophone positions estimated by the Kalman filter are calculated by assuming that the adjacent hydrophones are horizontally equi-spaced so that maximum distance is equal to the array length. The assumption causes errors in estimating hydrophone positions. The proposed technique using linear model approximation or spline interpolation can reduce the errors by exploiting the fact that the whole length of array is preserved whatever the array shape is. The numerical experiments show that the proposed method is very effective.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.65-85
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• 1999

Objectives: To determine the effect of interpolation functions when processing the digital periapical images. Material and Methods: The digital images were obtained by Digora and CDR system on the dry skull and human subject. 3 oral radiologists evaluated the 3 portions of each processed image using 7 interpolation methods, and ROC curves were obtained by trapezoidal methods. Results: The heighest Az value(0.96) was obtained with cubic spline method and the lowest Az value(0.03) was obtained with facet model method in Digora system. The heighest Az value (0.79) was obtained with gray segment expansion method and the lowest Az value(0.07) was obtained with facet model method in CDR system. There was significant difference of Az value in original image between Digora and CDR system at a=0.05 level. There were significant differences of Az values between Digora and CDR images with cubic spline method, facet model method, linear interpolation method and non-linear interpolation method at α=0.1 level.

• Journal of Korean Port Research
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• v.15 no.1
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• pp.87-97
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• 2001

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current method used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). In this paper the spot height method, least square method, and chamber formulas, Chen and Lin method are compared with the volumes of the pits in these examples. As a result of this study, algorithm of chen and Lin me쇙 by spline method should provide a better accuracy than the spot height method, least square method, chamber formulas. The Chen and Lin formulas can be used for estimating the excavation volume of a pit divide into a grid with unequal intervals. From the characteristics of the cubic spline polynomial, the modeling curve of the Chen and Lin method is smooth and matches the ground profile well. Generally speaking, the nonlinear profile formulas provide better accuracy than the linear profile formulas. The mathematical model mentioned make an offer maximum accuracy in estimating the volume of a pit excavation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.85-92
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• 2002

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current methods used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). Generally speaking, the nonlinear profile formulas provide better accuracy than the linear profile formulas. However, all the formulas mentioned have a common drawback to ground profile, such as sharp corners or the grid points of any two straight lines. In this paper, we propose an algorithm of finding a spline surface which interpolates the given data and an appropriate method to calculate the earthwork. We present some computational results showing that our proposed method provides better accuracy than Chen and Lin's method.