• Journal of the Korean Electrochemical Society
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• v.14 no.3
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• pp.145-151
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• 2011

ZnSe, as a II-VI compound semiconductor which has a wide band gap in the visible region is applicable to the various fields such as laser diode, display and solar cell. By using the electrochemical deposition method, ZnSe thin film was synthesized on the ITO glass substrate. The synthesis of ZnSe grains and their structure having zinc blende shape were verified through the analysis of XRD and SEM. UV spectrophotometric method determined the band gap as the value of 2.76 eV. Applying the DFT (Density Functional Theory) in the molecular dynamics, the band structure of ZnSe grains was analyzed. For ZnSe grains with zinc blende structure, the band structure and its density of state were simulated using LDA (Local Density Approximation), PBE (Perdew Burke Ernzerhof), and B3LYP (Becke, 3-parameter, Lee-Yang-Parr) functionals. Among the calculations of energy band gap upon each functional, the simulated one of 2.65 eV based on the B3LYP functional was mostly near by the experimental measurement.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.179-187
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• 2019

Vehicular density is usually low in a highway environment. Consequently, connectivity of the vehicular ad hoc networks (VANETs) might be poor. We are investigating the problem of deploying the approximation optimal roadside units (RSUs) on the highway covered by VANETs, which employs VANETs to provide excellent connectivity. The goal is to estimate the minimal number of deployed RSUs to guarantee the connectivity probability of the VANET within a given threshold considering that RSUs are to be allocated equidistantly. We apply an approximation algorithm to distribute RSUs locations in the VANETs. Thereafter, performance of the proposed scheme is evaluated by calculating the connectivity probability of the VANET. The simulation results show that there is the threshold value M of implemented RSUs corresponding to each vehicular network with N vehicles. The connectivity probability increases slowly with the number of RSUs getting larger.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.241-247
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• 2013

The doctor blade is equipped in a toner cartridge and is a device to maintain the uniform thickness of a toner by controlling the pressure on the developing roller. The contact pressure between the developing roller and the doctor blade is one of the significant factors for image quality and durability of toner cartridge. The purpose of this study is to develop approximation model in order to minimize the time and cost which are needed much required in making optimal design of the doctor blade. Central composite design was used for the design of experiment and response surface design was used for approximation. The data for contact pressure were acquired through finite element analysis and data of image density and toner weight were acquired through experiment. The approximation model developed in this study has presented very high fitness.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.569-572
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• 2015

We first deduce a uniform formula forthe Fermi energy of degenerate and relativistic electrons in the weak-magnetic field approximation. Then we obtain an expression of the special solution for the electron Fermi energy through this formula, and express the electron Fermi energy as a function of electron fraction and matter density. Our method is universally suitable for relativistic electron- matter regions in neutron stars in the weak-magnetic field approximation.

• Kyungpook Mathematical Journal
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• v.58 no.4
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• pp.733-746
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• 2018

The concept of f-statistical convergence which is, in fact, a generalization of statistical convergence, has been introduced recently by Aizpuru et al. (Quaest. Math. 37: 525-530, 2014). The main object of this paper is to prove an f-statistical analog of the classical Korovkin type approximation theorem of Boyanov and Veselinov. It is shown that the f-statistical analog is intermediate between the classical theorem and its statistical analog. As an application, we estimate the rate of f-statistical convergence of the sequence of positive linear operators defined from $C^*[0,{\infty})$ into itself.

• Journal of Applied and Pure Mathematics
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• v.5 no.1_2
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• pp.69-93
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• 2023

Here we give multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or ℝ^N, N ∈ ℕ, by the multivariate normalized, quasi-interpolation, Kantorovich type and quadrature type neural network operators. We treat also the case of approximation by iterated operators of the last four types. These approximations are derived by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high order Fréchet derivatives. Our multivariate operators are defined by using a multidimensional density function induced by a parametrized Gudermannian sigmoid function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.337-347
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• 2024

Kernel density estimation is a prevalent technique employed for nonparametric density estimation, enabling direct estimation from the data itself. This estimation involves two crucial elements: selection of the kernel function and the determination of the appropriate bandwidth. The selection of the bandwidth plays an important role in kernel density estimation, which has been developed over the past decade. A range of methods is available for selecting the bandwidth, including the plug-in bandwidth. In this article, the proposed plug-in bandwidth is introduced, which leverages shifted Chebyshev series-based approximation to determine the optimal bandwidth. Through a simulation study, the performance of the suggested bandwidth is analyzed to reveal its favorable performance across a wide range of distributions and sample sizes compared to alternative bandwidths. The proposed bandwidth is also applied for kernel density estimation on real dataset. The outcomes obtained from the proposed bandwidth indicate a favorable selection. Hence, this article serves as motivation to explore additional plug-in bandwidths that rely on function approximations utilizing alternative series expansions.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.397-406
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• 2014

The minimum density power divergence estimation has been a popular topic in the field of robust estimation for since Basu et al. (1988). The minimum density power divergence estimator has strong robustness properties with the little loss in asymptotic efficiency relative to the maximum likelihood estimator under model conditions. However, a limitation in applying this estimation method is the algebraic difficulty on an integral involved in an estimation function. This paper considers a minimum density power divergence estimation method with approximated divergence avoiding such difficulty. As an example, we consider the normal-exponential convolution model introduced by Bolstad (2004). The estimated divergence in this case is too complicated; consequently, a Laplace approximation is employed to obtain a manageable form. Simulations and an empirical study show that the minimum density power divergence estimators based on an approximated estimated divergence for the normal-exponential model perform adequately in terms of bias and efficiency.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.151-160
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• 2012

Most of the distributed high-dimensional indexing structures provide a reasonable search performance especially when the dataset is uniformly distributed. However, in case when the dataset is clustered or skewed, the search performances gradually degrade as compared with the uniformly distributed dataset. We propose a method of improving the k-nearest neighbor search performance for the distributed vector approximation-tree based on the strongly clustered or skewed dataset. The basic idea is to compute volumes of the leaf nodes on the top-tree of a distributed vector approximation-tree and to assign different number of bits to them in order to assure an identification performance of vector approximation. In other words, it can be done by assigning more bits to the high-density clusters. We conducted experiments to compare the search performance with the distributed hybrid spill-tree and distributed vector approximation-tree by using the synthetic and real data sets. The experimental results show that our proposed scheme provides consistent results with significant performance improvements of the distributed vector approximation-tree for strongly clustered or skewed datasets.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.181-182
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• 2003

A preconditioned numerical method for gas-liquid to-phase flow is applied to solve cavitating flow. The present method employs a density based finite-difference method of dual time-stepping integration procedure and Roe's flux difference splitting approximation with MUSCL-TVD scheme. A homogeneous equilibrium cavitation model is used. The method permits simple treatment of the whole gas-liquid two-phase flow field including wave propagation, large density changes and incompressible flow characteristics at low Mach number. By this method, two-dimensional internal flows through a venturi tuve and decelerating cascades are computed and discussed.