• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.102-105
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• 2002

In this paper, the electron transport characteristics in $CF_4$ has been analysed over the E/N range 1${\sim}$300 [Td] by a two-term approximation Boltzmann equation method and by a Monte Carlo simulation. The motion has been calculated to give swarm parameters for the electron drift velocity, longitudinal diffusion coefficient, the ratio of the diffusion coefficient to the mobility, electron ionization and attachment coefficients, effective ionization coefficient, mean energy, collision frequency and the electron energy distribution function. The swarm parameter from the swarm study are expected to serve as a critical test of current theories of low energy electron scattering by atoms and molecules, in particular, as well as crucial information for quantitative simulations of weakly ionized plasmas.

• Journal of the Korean institute of surface engineering
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• v.29 no.5
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• pp.532-539
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• 1996

Diamond-like carbon (DLC) films were deposited on silicon substrates by the plasma decomposition of hydrocarbons under various conditions, and studied by the spectroscopic ellipsometry (SE). We used the effective medium approximation with the dispersion model developed by Forouhi and Bloomer to determine simultaneously both the structure and the optical constants of the DLC films from their ellipsometric spectra. Especially, we investigated the variation of the multilayer structure including the interface layer, of the refractive indices, and of the extinction coefficients as the deposition conditions were varied; substrate pretreatment procedure, hydrocarbon precursors, and the substrate bias voltage were varied.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.412-415
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• 2003

It is important to classily fault types, discriminate fault section and calculate the fault location by any detecting technique for combined transmission lines. This paper proposes the technique to classily the fault types and fault section using neuro-fuzzy systems. Neuro-fuzzy systems are composed of three parts to perform different works. First, neuro-fuzzy system for fault type classification is performed with approximation coefficient of currents obtained by wavelet transform. The second neuro-fuzzy system discriminates the fault section between overhead and underground with detail coefficients of voltage and current. The last neuro-fuzzy system calculates the fault location with impedance in this paper, neuro-furry system shows the excellent results for classification of fault types and discrimination of fault section.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.468-469
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• 2007

In this paper, the electron transport characteristics in $CF_4$ has been analysed over the E/N range 1~300[Td] by a two-tenn approximation Boltzmann equation method and by a Monte Carlo simulation. The motion has been calculated to give swarm parameters for the electron drift velocity, longitudinal diffusion coefficient, the ratio of the diffusion coefficient to the mobility, electron ionization and attachment coefficients, effective ionization coefficient, mean energy, collision frequency and the electron energy distribution function. The swarm parameter from the swarm study are expected to serve as a critical test of current theories of low energy electron scattering by atoms and molecules, in particular, as well as crucial information for quantitative simulations of weakly ionized plasmas.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.8 s.185
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• pp.89-99
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• 2006

In this paper a new shape reconstruction method that allows us to construct surface models from very large sets of points is presented. In this method the global domain of interest is divided into smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together according to weighting coefficients to obtain a global solution using partition of unity function. The suggested approach gives us considerable flexibility in the choice of local shape functions which depend on the local shape complexity and desired accuracy. At each domain, a quadratic polynomial function is created that fits the points in the domain. If the approximation is not accurate enough, other higher order functions including cubic polynomial function and RBF(Radial Basis Function) are used. This adaptive selection of local shape functions offers robust and efficient solution to a great variety of shape reconstruction problems.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.679-695
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• 2014

A design method of second generation wavelet (SGW)-based multivariable finite elements is proposed for static and vibration beam analysis. An important property of SGWs is that they can be custom designed by selecting appropriate lifting coefficients depending on the application. The SGW-based multivariable finite element equations of static and vibration analysis of beam problems with two and three kinds of variables are derived based on the generalized variational principles. Compared to classical finite element method (FEM), the second generation wavelet-based multivariable finite element method (SGW-MFEM) combines the advantages of high approximation performance of the SGW method and independent solution of field functions of the MFEM. A multiscale algorithm for SGW-MFEM is presented to solve structural engineering problems. Numerical examples demonstrate the proposed method is a flexible and accurate method in static and vibration beam analysis.

• Journal of Power Electronics
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• v.19 no.2
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• pp.443-453
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• 2019

As the core component of transmission systems, converters are very prone to failure. To improve the accuracy of fault diagnosis for wind power converters, a fault feature extraction method combined with a wavelet transform and compressed sensing theory is proposed. In addition, an improved AdaBoost-SVM is used to diagnose wind power converters. The three-phase output current signal is selected as the research object and is processed by the wavelet transform to reduce the signal noise. The wavelet approximation coefficients are dimensionality reduced to obtain measurement signals based on the theory of compressive sensing. A sparse vector is obtained by the orthogonal matching pursuit algorithm, and then the fault feature vector is extracted. The fault feature vectors are input to the improved AdaBoost-SVM classifier to realize fault diagnosis. Simulation results show that this method can effectively realize the fault diagnosis of the power transistors in converters and improve the precision of fault diagnosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1241-1244
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• 2020

In this paper, we consider a downlink non-orthogonal multiple access system with a base station and N mobile stations, where we assume that instantaneous channel state information (CSI) is available at the base station. A power allocation scheme is proposed to achieve perfect fairness, which means equal data rates for all mobile stations. However, the power allocation scheme using full CSI requires high complexity. Hence, a simple power allocation scheme with low complexity is proposed by using high signal-to-noise power ratio (SNR) approximation. The simple power allocation scheme can achieve perfect fairness only for high SNR. However, it needs only the best CSI and the simple procedure to obtain power allocation coefficients. From simulation results, we show that the simple power allocation scheme provides remarkable fairness performance at high SNR.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.187-194
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• 2023

The remote sensing technique of measuring the magnetic field was applied first to sunspots by Hale (1908). Later Babcock (1961) showed that the solar surface magnetic field on a global scale is a dipole in first-order approximation and that this dipole field reverses once every solar cycle. The Wilcox Solar Observatory (WSO) supplies the spherical harmonics coefficients of the solar corona magnetic field of each Carrington Rotation, calculated based on the remotely-sensed photospheric magnetic field of the solar surface. To infer the internal current system producing the global solar coronal magnetic field structure and evolution of the Sun, we calculate the multipole components of the solar magnetic field using the WSO data from 1976 to 2019. The prominent cycle components over the last 4 solar activity cycles are axis-symmetric fields of the dipole and octupole. This implies that the current inversion driving the solar magnetic field reversal originates from the equatorial region and spreads to the whole globe. Thus, a more accurate solar dynamo model must include an explanation of the origin and evolution of such solar internal current dynamics.