• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.85.2-85.2
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• 2019

We developed a new grid-based Monte Carlo code to trace far UV He II line photons that are incident on a thick H I region and subsequently transferred through Rayleigh and Raman scattering with atomic hydrogen. In particular, we consider a neutral region that is moving away from the He II emission source which is either monochromatic or is described by a Gaussian profile. The resultant Raman scattered He II line profiles from a monochromatic source are characterized by a double peaked core part with an extended Raman red tail that is attributed to multiple re-entry events. Complicated behaviors are observed in the case of a Gaussian He II source including the formation of a secondary red peak near the Balmer center dependent on the H I column density. A preliminary application of our results to the CFHT data of the planetary nebula IC 5117 is presented.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.130-138
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• 1995

Machined graphite/epoxy surfaces were studied by using SEM (Scanning Electron Microscopy), surface profilometry and its analysis to determine suitable surface describing parameters for machined unidirectional and multidirectional laminate composite. The surface roughness and profile are found to be highly depdndent on the fiber layup direction and the measurement direction. It was possible to machine 90 .deg. and -45 .deg. plies due to the adjacent plies, which were holding those plies. It was found that the microgeometrical variations in terms of roughness parameters $R_{a}$ without $D_{y}$(Maximum Damage Depth) region and $D_{y}$are better descriptors of the machined laminate composite surface than commonly used roughness parameters $R_{a}$and $R_{max}$ The characteristics of surface profiles in laminate composite are well represented in CPD (Cumulative Probability Distribution) plot and PPD (Percentage Probability Density) plot. Edge-trimmed multidirectional laminate surfaces are Gaussian and random for profiles measured along the tool movement direction, they are periodic and non-Gaussian in the direction perpendicular to the tool movement.t.ent.t.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• Honam Mathematical Journal
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• v.41 no.4
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• pp.683-695
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• 2019

In the present paper, we study curves in 𝔼³ with density $e^{ax^2+by^2}$, where a, b ∈ ℝ not all zero constants and give the parametric expressions of the curves with vanishing weighted curvature. Also, we create ruled surfaces whose base curves are the curve with vanishing weighted curvature and the ruling curves are Smarandache curves of this curve. Then, we give some characterizations about these ruled surfaces by obtaining the mean curvatures, Gaussian curvatures, distribution parameters and striction curves of them.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5095-5111
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• 2016

The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.161-163
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• 2016

Organic semiconductors, in contrast with inorganic semiconductors, have DOS of the Gaussian distribution function which leads to difficulties to obtain the electron density with a closed equation. For this reason, the prediction of the device operation is extremely difficult in the development of OLED and the repetitive trial-and-error is required to find the appropriate electrical and optical properties of the devices. In this paper, the standard to analyze organic semiconductor is proposed by the optimization of the time and the accuracy which is necessary for the numerical calculation of the electron density in organic semiconductors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.721-727
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• 2016

In this paper, in order to resolve the problem of reduction for D2D (device to device) advertisement dissemination efficiency of conventional dissemination algorithms, we here propose several clustering algorithms (modified single linkage algorithm (MSL), K-means algorithm, and expectation maximization algorithm with Gaussian mixture model (EM)) based advertisement dissemination algorithms to improve advertisement dissemination efficiency in D2D communication networks. Target areas are clustered in several target groups by the proposed clustering algorithms. Then, D2D advertisements are consecutively distributed by using a routing algorithm based on the geographical distribution of the target areas and a relay selection algorithm based on the distance between D2D sender and D2D receiver. Via intensive MATLAB simulations, we analyze the performance excellency of the proposed algorithms with respect to maximum number of relay transmissions and D2D user density ratio in a target area and a non-target area.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.60.2-60.2
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• 2018

We present the near infrared JHK photometric properties and the spatial distribution of red supergiants(RSGs) of NGC 3623, NGC 3627 and NGC 3628 in the Leo Triplet system using the data obtained with 3.8m UKIRT(United Kingdom Infra-Red Telescope) at Hawaii. We checked interaction between the three galaxies by making a spatial density map of RSGs. From (J-K,K)0 Color-Magnitude Diagram which include resolved stars in three galaxy and control field with PARSEC isochrone, we figured out the RSG candidates of the Leo triplet are at 0.9<(J-K)0<1.2, mK<17.5 and separated them from background and foreground sources. Using gaussian kernel density estimation, we drew spatial density map of RSGs in the Leo triplet with an assumption that all RSGs are an identical population. The density map shows extended features of NGC 3628 to NGC 3627 along the declination direction. The asymmetries between NGC 3627 and NGC 3628 might be evidence for that the distribution of actual star components(RSGs) follows the neutral hydrogen distribution and also for interaction between two galaxies. And the extended features along the right ascension direction might be a supporting evidence for the existence of a TDG(Tidal Dwarf Galaxy). In case of NGC 3623, we could not see any sign of interaction in density map.