• Structural Engineering and Mechanics
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• 제28권4호
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• pp.373-386
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• 2008

In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

• 한국멀티미디어학회논문지
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• 제19권3호
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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.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.

• Structural Engineering and Mechanics
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• 제13권2호
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• pp.231-239
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• 2002

The problem of dynamic analysis of truss structures based on probability is studied in this paper. Considering the randomness of both physical parameters (elastic module and mass density) of structural materials and geometric dimension of bars respectively or simultaneously, the stiffness and mass matrixes of the elements and structure have been built. The structure dynamic characteristic based on probability is analyzed, and the expressions of numeral characteristics of inherence frequency random variable are derived from the Rayleigh's quotient. The method of structural dynamic analysis based on probability is developed. Finally, two examples are given.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1987년도 춘계학술발표회 논문집
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• pp.191-195
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• 1987

When a 160QAM receiver in the band of spread spectrum system is interfered with a pseudo-random frequency-hopp-ing signal the interference signal has the form of the pulse amplitude probability density function. Each interfrering pulse amplitude probability density function Each interfering pulse amplitude is dependent upon theprobability density function of hopping frequency and the selectivity characteristic of 16QAM system in this paper the error rate equation of a system performance has been derived in the above condition which are interfrerence form and impulsive noise environmensts. The results of system analysis show us that the system performance is de-graded by impulsive noise and interference power, which improved as the frequency hopping bandsidth increases whit respect to receiver bandwidth

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.183-191
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• 2014

We define a multivariate Cauchy distribution using a probability density function; subsequently, a Ferguson's definition of a multivariate Cauchy distribution can be viewed as a characterization theorem using the characteristic function approach. To clarify this characterization theorem, we construct two dependent Cauchy random variables, but their sum is not Cauchy distributed. In doing so the proofs depend on the characteristic function, but we use the cumulative distribution function to obtain the exact density of their sum. The derivation methods are relatively straightforward and appropriate for graduate level statistics theory courses.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1691-1694
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• 2005

The fatigue characteristic of a material or a structure is derived from fatigue tests of standard specimens. However test results of standard specimens are very different from those of real structures or components. Therefore, to calculate more accurate fatigue life, the geometrical effect and surface condition must be considered by comparing test results of standard specimens with those of real structures or components. Thus the object of this paper is to evaluate the fatigue characteristic of a real waterwork pipe by conducting fatigue tests with standard specimens and non-standard(plate-shaped) specimens of base metal and weld metal. Also, to evaluate fatigue characteristic based on life distribution, statistical fatigue characteristic was analyzed by the normal distribution and related data of P-S-N curve.

• 한국연소학회지
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• 제7권2호
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• pp.7-14
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• 2002

The probability density functions (PDF) of temperature were measured by coherent anti-Stokes Raman Spectroscopy (CARS) in flames of gas turbine combustor sector rig of an aero-engine. The combustor was operated at simulated ground idle conditions with standard kerosene fuel. Temperature PDFs had been measured near fuel nozzle with change of rotation of a swirler and existence of a prefilmer. The characteristic features of temperature PDFs showed the variation of combustion configurations at four experimental conditions. Without a prefilmer, large recirculation of high temperature gas was expected in the co-flow condition and un vaporized fuel fragments were detected in the counter-flow condition. With a prefilmer, the enhanced mixing increased combustion intensity near fuel nozzle in the counter-flow condition and the flame was attached far from the fuel nozzle in the co-flow condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.847-850
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• 1987

In this paper a new method to correct the differential non-linearity(D NL) error for a successive approximation is proposed. The DNL of ADC is very important characteristic in the field of radiation pulse height analysis or measurement of probability density function. The results of computer simulations are shown to demonstrate the feasibility of the proposed correction method.

• International Journal of Reliability and Applications
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• 제4권3호
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• pp.97-111
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• 2003

By applying Theorem 2.6.4 (Fang and Zhang, 1990, p.66) the dispersion matrix of a multivariate power exponential (MPE) distribution is derived. It is shown that the MPE and the gamma distributions are related and thus the MPE and chi-square distributions are related. By extending Fang and Xu's Theorem (1987) from the normal distribution to the Univariate Power Exponential (UPE) distribution an explicit expression is derived for calculating the probability of an UPE random variable over an interval. A representation of the characteristic function (c.f.) for an UPE distribution is given. Based on the MPE distribution the probability density functions of the generalized non-central chi-square, the generalized non-central t, and the generalized non-central F distributions are derived.