• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.499-505
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• 1997

A non-invasive technique to measure absorption and scattering coefficients was investigated The reflected backscattered light from the surface of phantom and biological tissue was obtained by using a time-correlated single photon counting system in pico-second time domain. The absorption and scattering coefficients were acquired by the time of peak and asymptotic behavior of the time-resolved reflectance curve and agreed well the ones that is obtained with deconvolution method It was found that the approximation method was good for biological medium to calculate optical properties due to its convenience and accuracy.

• ETRI Journal
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• v.34 no.2
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• pp.190-198
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• 2012

An adaptive correlation noise model (CNM) construction algorithm is proposed in this paper to increase the efficiency of parity bits for correcting errors of the side information in transform domain Wyner-Ziv (WZ) video coding. The proposed algorithm introduces two techniques to improve the accuracy of the CNM. First, it calculates the mean of direct current (DC) coefficients of the original WZ frame at the encoder and uses it to assist the decoder to calculate the CNM parameters. Second, by considering the statistical property of the transform domain correlation noise and the motion characteristic of the frame, the algorithm adaptively models the DC coefficients of the correlation noise with the Gaussian distribution for the low motion frames and the Laplacian distribution for the high motion frames, respectively. With these techniques, the proposed algorithm is able to make a more accurate approximation to the real distribution of the correlation noise at the expense of a very slight increment to the coding complexity. The simulation results show that the proposed algorithm can improve the average peak signal-to-noise ratio of the decoded WZ frames by 0.5 dB to 1.5 dB.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.8
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• pp.104-108
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• 2008

Accurate sets of electron collision cross sections and the electron transport coefficients for atoms and molecules are necessary for quantitative understanding of plasma phenomena Kr and Xe atom are used in many industrial applications, such as in PDP and fluorescent induction lamps(FILs). Therefore, we analysed and calculated the electron transport coefficients, the electron drift velocity W, the longitudinal and transverse diffusion coefficient $ND_L$ and $ND_T$, and the ionization coefficient $\alpha$/N in pure Kr and Xe gases over the wide E/N range from 0.001 to 500[Td] at 1[Torr] by two-tenn approximation of the Boltzmann equation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.938-943
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• 2014

The scattered field by a gap/crack on the PEC surface of a large object having low-observable RCS cannot be negligible, but may not be analyzed by the known high-frequency technique. If the electrical width of the crack is very small, the crack can be modeled by an impedance strip, whose scattering formulation can be analytically obtained based on a low-frequency approximation. The scattering solution is formulated for the 2D strip and TE(Transverse Electric) or TM(Transverse Magnetic) wave incidence, from which a 3D ILDC(Incremental Length Diffraction Coefficients) can be extracted. Using the ILDC formulation, the scattering by any arbitrary shaped crack can be estimated. In this paper, an improved ILDC equations are proposed, which combine the known TE and TM solutions. The improved accuracy of the proposed solution is numerically verified.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.45-52
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• 2014

We cannot load the entire data for high-resolution terrain model to the GPU memory since its size is too big. Out-of-core approaches are commonly used to solve the problem. However, due to limited bandwidth of the secondary storage, it is difficult to render the terrain in real-time. A method that compresses the DEM data with wavelet transform on GPU, and renders the decoded data is suggested. However, it is inefficient since it has to sample the values from textures, convert them to vertices, and generate a mesh periodically. We propose a method to store the approximation coefficients of wavelet compression as vertex attributes and render the terrain by decoding the data on geometric shader. It can reduce the amount of transferring terrain texture since approximation coefficients are given as an attribute of the vertex. Also, it generate meshes without additional upload of terrain texture.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.116-123
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• 2013

This paper represents generation of time-varying underwater acoustic channels by performing scattering simulation with time-varying ocean surface and Kirchhoff approximation. In order to estimate the time-varying ocean surface, 1D Pierson-Moskowitz ocean power spectrum and Gaussian correlation function were used. The computed scattering coefficients are applied to the amplitudes of each impulse of BELLHOP simulation result. The scattering coefficients are then compared with measured doppler spectral density of signal components which were scattered from ocean surface and the correlation time used in the Gaussian correlation function was estimated by the comparison. Finally, bit-error-rate and channel correlation simulations were performed with the generated time-varying channel based on passive time-reversal communication scenario.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.453-460
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• 2019

The SR-DCSK(Short Reference Differential Chaos Shift Keying) is a variant of DCSK that improves data transmission speed and energy efficiency without additional complexity. However, even when the reference signal of the optimum length is applied, the BER performance of the SR-DCSK is not better than that of the conventional DCSK. In this paper, we propose a scheme to improve the performance of SR-DCSK by applying two scale factors (scale coefficients) to the reference signal and the information signal, respectively. And the performance of the proposed method is analyzed by BER using Gaussian Approximation. Based on the derived BER expressions, we minimize the BER for a given system parameter to optimize the ratio of the two coefficients. Simulation results confirm that the BER of the proposed method is much improved over the SR-DCSK when we apply the optimal ratio of the two scale factors.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.101-110
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• 2003

This paper introduces an identification method for nonlinear models in the form of rule-based Fuzzy-Neural Networks (FNN). In this study, the development of the rule-based fuzzy neural networks focuses on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The FNN modeling and identification environment realizes parameter identification through synergistic usage of clustering techniques, genetic optimization and a complex search method. We use a HCM (Hard C-Means) clustering algorithm to determine initial apexes of the membership functions of the information granules used in this fuzzy model. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are then adjusted using the identification algorithm of a GA hybrid scheme. The proposed GA hybrid scheme effectively combines the GA with the improved com-plex method to guarantee both global optimization and local convergence. An aggregate objective function (performance index) with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. According to the selection and adjustment of the weighting factor of this objective function, we reveal how to design a model having sound approximation and generalization abilities. The proposed model is experimented with using several time series data (gas furnace, sewage treatment process, and NOx emission process data from gas turbine power plants).

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.727-731
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• 2000

This paper presents a new practical autopilot design approach to acceleration control for tail-controlled STT(Skid-to-Turn) missiles. The approach is novel in that the proposed parametric affine missile model adopts acceleration as th controlled output and considers the couplings between the forces as well as the moments and control fin deflections. The aerodynamic coefficients in the proposed model are expressed in a closed form with fittable parameters over the whole operating range. The parameters are fitted from aerodynamic coefficient look-up tables by the function approximation technique which is based on the combination of local parametric models through curve fitting using the corresponding influence functions. In this paper in order to employ the results of parametric affine modeling in the autopilot controller design we derived a parametric affine missile model and designed a feedback linearizing controller for the obtained model. Stability analysis for the overall closed loop sys-tem is provided considering the uncertainties arising from approximation errors. the validity of the proposed modeling and control approach is demonstrated through simulations for an STT missile.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.1-8
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• 2016

It is well known that the behavior of PV curves is similar to a quadratic function. This is used in some papers to approximate PV curves and calculate the maximum-loading point by minimum number of power flow runs. This paper also based on quadratic approximation of the PV curves is aimed at completing previous works so that the computational efforts are reduced and the accuracy is maintained. To do this, an iterative method based on a quadratic function with two constant coefficients, instead of the three ones, is used. This simplifies the calculation of the quadratic function. In each iteration, to prevent the calculations from diverging, the equations are solved on the assumption that voltage magnitude at a selected load bus is known and the loading factor is unknown instead. The voltage magnitude except in the first iteration is selected equal to the one at the nose point of the latest approximated PV curve. A method is presented to put the mentioned voltage in the first iteration as close as possible to the collapse point voltage. This reduces the number of iterations needed to determine the maximum-loading point. This method is tested on four IEEE test systems.