• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.571-576
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• 2004

In this study, we selected the most effective interpolation method using both the data of sounding the depth of submarine topography and volume-production computer program. After processing the data by volume-production program, and then we selected the most effective interpolation method which nearest actual value of dredged soil quantity. Thus, these interpolation could be used for describing the optimal submarine topography.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1066-1073
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• 2014

This paper presents a new design method of optimal control of system which are changed the system parameters. The method used for this purpose are the Lagrange interpolation method and Pole's Moving range method. We selects a system within the scope of the changing the system parameters. Using pole's moving range we calculated the state weighting matrix of optimal control. The optimal controller is designed by Lagrange interpolation method of the state weighting matrix. We are compared with a traditional optimal controller and proposed method by simulation. The simulation showed that the proposed method is better control performance than traditional method of optimal controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.188-194
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• 2015

This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1492-1498
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• 2000

Pilot symbol aided modulation (PSAM) using the conventional sinc interpolation (CSI) achieves nearly the same BER performance as Caver' optimal Wiener interpolation but with much less complexity. The CSI, however, has to use a non-rectangular window function that is applied to the sinc function to smooth out the abrupt truncation of rectangular window. In this paper, we propose the modified sinc interpolation (MSI). With the weighting factor the MSI scheme with no window has almost the same BER performance as the CSI scheme using window, In addition, if we use the MSI with a window its BER performance gets close to that of the theoretical one. We assume the multicarrier QAM system and an optimal frame structure for performance evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3286-3301
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• 2014

Jung and Yoo proposed the first image interpolation-based reversible data hiding algorithm. Although their algorithm achieved superior interpolation results, the embedding capacity was insufficient. Lee and Huang proposed an improved algorithm to enhance the embedding capacity and the interpolation results. However, these algorithms present limitations to magnify the original image to any resolution and pixels in the boundary region of the magnified image are poorly manipulated. Furthermore, the capacity and the image quality can be improved further. This study modifies the pixel mapping scheme and adopts a bilinear interpolation to solve boundary artifacts. The modified reference pixel determination and an optimal pixel adjustment process can effectively enhance the embedding capacity and the image quality. The experimental results show our proposed algorithm achieves a higher embedding capacity under acceptable visual distortions, and can be applied to a magnified image at any resolution. Our proposed technique is feasible in reversible data hiding.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.3003-3009
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• 2000

In this paper, we propose a new efficient hybrid-mixed C(sup)0 curved beam element with the optimal interpolation functions determined from numerical tests, which gives very accurate locking-free two-node curved beam element. In the element level, the stress parameters are eliminated from the stationary condition and the nodeless degrees of freedom are also removed by static condensation so that a standard six-by-six stiffness matrix is finally obtained. The numeri cal benchmark problems show that the element with cubic displacement functions and quadratic stress functions is the most efficient.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.7
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• pp.826-835
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• 1988

In this paper, we analyze the generation of an image pyramid as a 2-dimensional decimation-interpolation process, and suggest a performance index of FIR filter for decimation and interpolation filter. Until now, most deciamtion and interpolation filters are designed via the approximation of the impulse response of an ideal filter. In this paper, however, we propose a new performance index that minimizes the maximum frequency-weighted mean square error between the desired and the generated interpolated signal, and propose an optimal half-band filter based on the proposed performance index as an example. Some simulation results with real images show that the proposed optimal half-band filter yields a higher PSNR as well as the more preferable image quality, in comparison with other currently used filters with the same computational complexity.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.363-370
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• 2017

Data assimilation is an initializing method for air quality forecasting such as PM10. It is very important to enhance the forecasting accuracy. Optimal interpolation is one of the data assimilation techniques. It is very effective and widely used in air quality forecasting fields. The technique, however, requires too much memory space and long execution time. It makes the PM10 air quality forecasting difficult in real time. We propose a fast optimal interpolation data assimilation method for PM10 air quality forecasting using a new kernel tridiagonal sparse matrix and CUDA massively parallel processing architecture. Experimental results show the proposed method is 5~56 times faster than conventional ones.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.439-459
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• 2023

Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.64-79
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• 1994

In this study, terrain classification, which was done by using the quantitative classification parameters and suitable interpolation method was applied to improve the accuracy of digital elevation models, and to increase its practical use of aerial photogrammetry. A terrain area was classified into three groups using the quantitative classification parameters to the ratio of horizontal, inclined area, magnitude of harmonic vectors, deviation of vector, the number of breakline and proposed the suitable interpolation. Also, the accuracy of digital elevation models was improved in case of large grid intervals by applying combined interpolation suitable for each terrain group. As a result of this study, I have an algorithm to perform the classification of the topography in the area of interest objectively and decided optimal data interpolation scheme for given topography.