• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.219.2-219.2
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• 2014

Characteristics of Argon metastable density with electron density have been studied by using Laser induced fluorescence (LIF) in ICP. Two different evolutions of measured metastable densities with electron density depending on a measurement position are addressed. The experimental result is explained by using a zero dimensional global model and is due to electron kinetic properties in the positions that can be seen from electron energy probability functions measured by Langmuir probe. The underlying physics on metastable density with electron density and an experimental method of LIF are presented in detail.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.7
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• pp.822-830
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• 2012

Clutters are all unwanted radar returns to affect on detection of targets. Radar clutter is characterized by amplitude distributions, spectrum, etc. Clutter is modelled with considering these kinds of characteristics. In this paper, a Weibull distribution function approximated by uniform distribution function is suggested. Weibull distribution function is used to model the various clutters. This paper shows that the data generated by the approximated solution of Weibull distribution function satisfy the Weibull probability density function. This paper shows that the data generation time of approximated Weibull distribution function solution is reduced by 20 % compared with the generation time of original Weibull probability density function.

• ETRI Journal
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• v.32 no.3
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• pp.464-467
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• 2010

In this letter, we analyze the error performance of a mobile communication system with microdiversity and macrodiversity reception in gamma-shadowed Rician fading channels for a binary differential phase-shift keying modulation scheme. Analytical expressions for the probability density function (PDF) and moment-generating function (MGF) are derived. The average bit error probability can be calculated by averaging the conditional bit error probability over the PDF or using the MGF-based approach. Numerical results are graphically presented to show the effects of macrodiversity, correlation, number of diversity branches, and severity of both fading and shadowing.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.243-254
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• 2006

The relative frequency of order statistics is investigated for independent and identically distributed (i.i.d.) random variables. Specifically, it is shown that the probability $Pr\{X_{[s]}=x\}$ is no less than the probability $Pr\{X_{[r]}=x\}$ at any point $x{\geqq}x_0$ when r$X_{[r]}$ denotes the r-th order statistic of an i.i.d. discrete random vector and $x_0$ depends on the population probability distribution. A similar result for i.i.d. continuous random vectors is also presented.

• Smart Structures and Systems
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• v.25 no.5
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• pp.593-604
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• 2020

Temperature may have more significant influences on structural responses than operational loads or structural damage. Therefore, a comprehensive understanding of temperature distributions has great significance for proper design and maintenance of bridges. In this study, the temperature distribution of the steel box girder is systematically investigated based on the structural health monitoring system (SHMS) of the Sutong Cable-stayed Bridge. Specifically, the characteristics of the temperature and temperature difference between different measurement points are studied based on field temperature measurements. Accordingly, the probability density distributions of the temperature and temperature difference are calculated statistically, which are further described by the general formulas. The results indicate that: (1) the temperature and temperature difference exhibit distinct seasonal characteristics and strong periodicity, and the temperature and temperature difference among different measurement points are strongly correlated, respectively; (2) the probability density of the temperature difference distribution presents strong non-Gaussian characteristics; (3) the probability density function of temperature can be described by the weighted sum of four Normal distributions. Meanwhile, the temperature difference can be described by the weighted sum of Weibull distribution and Normal distribution.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.164-171
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• 2007

This research used GIS spatial analysis model and Huff probability model and achieved trade area analysis of area center. we constructed basic maps that were surveyed according to types of business, number of households etc. using a land registration map of LMIS(Land Management Information System) in Bokdae-dong, Cheongju-si. Kernel density function and NNI(Nearest Neighbor Index) was used to estimate store distribution center area in neighborhood life zones. The center point of area and scale were estimated by means of the center area. Huff probability model was used in abstracting trade areas according to estimated center areas, those was drew map. Therefore, this study describes method that can apply in Huff probability model through kernel density function and NNI of GIS spatial analysis techniques. A trade area was abstracted more exactly by taking advantage of this method, which will can aid merchant for the foundation of small sized enterprises.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.319-326
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• 2004

Uncertainty is inevitably involved in rock slope engineering since the rock masses are formed by natural process and subsequently the geotechnical characteristics of rock masses cannot be exactly obtained. Therefore the reliability analysis method has been suggested to deal properly with uncertainty. The reliability analysis method can be divided into level I, II and III on the basis of the approach for consideration of random variable and probability density function of reliability function. The level II approach, which is focused in this study, assumes the probability density function of random variables as normal distribution and evaluates the probability of failure with statistical moments such as mean and standard deviation. This method has the advantage that can be used the problem which the Monte Carlo simulation approach cannot be applied since the complete information on the random variables are not available. In this study, the analysis results of level II reliability approach compared with the analysis results of level III approach to verify the appropriateness of the level II approach. In addition, the results are compared with the results of the deterministic analysis.

• Journal of applied mathematics & informatics
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• v.35 no.3_4
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• pp.261-265
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• 2017

Let X and Y be independent identically distributed nondegenerate random variables with common absolutely continuous probability distribution function F(x) and the corresponding probability density function f(x) and $E(X^2)$<${\infty}$. Put Z = max(X, Y) and W = min(X, Y). In this paper, it is proved that Z - W and Z + W or$(X-Y)^2$ and X + Y are independent if and only if X and Y have normal distribution.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.