• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.901-909
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• 2013

A skewed double power function distribution is defined by a double power function distribution. We shall evaluate the coefficient of the skewness of a skewed double power function distribution. We shall obtain an approximate maximum likelihood estimator (MLE) and a moment estimator (MME) of the skew parameter in the skewed double power function distribution, and compare simulated mean squared errors for those estimators. And we shall compare simulated MSEs of two proposed reliability estimators in two independent skewed double power function distributions with different skew parameters.

• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.955-960
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• 2009

As we shall dene an exponentiated complementary power function distribution, we shall consider moments, hazard rate, and inference for parameter in the distribution. And we shall consider an inference of the reliability and distributions for the quotient and the ratio in two independent exponentiated complementary power function random variables.

• Communications for Statistical Applications and Methods
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• 제15권3호
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• pp.325-332
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• 2008

We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.243-255
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• 1996

The number of neutron signals from a neutral particle beam(NPB) at the detector, without any errors, obeys Poisson distribution, Under two assumptions that NPB scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of signals becomes a Poisson-power function distribution. In this paper, we show that the error rate in simple hypothesis testing for the limiting Poisson-power function distribution is not zero. That is, the limit of ${\alpha}+{\beta}$ is zero when Poisson parameter$\kappa\rightarro\infty$, but this limit is not zero (i.e., $\rho\ell$>0)for the Poisson-power function distribution. We also give optimal decision algorithms for a specified error rate.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.229-241
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• 1997

We consider discrimination curve and minimum dwell time for Poisson distribution and Poisson-power function distribution. Let the random variable X has Poisson distribution with mean .lambda.. For the hypothesis testing H$\_$0/:.lambda. = t vs. H$\_$1/:.lambda. = d (d$\_$0/ if X.leq.c. Since a critical value c can not be determined to satisfy both types of errors .alpha. and .beta., we considered discrimination curve that gives the maximum d such that it can be discriminated from t for a given .alpha. and .beta.. We also considered an algorithm to compute the minimum dwell time which is needed to discriminate at the given .alpha. and .beta. for the Poisson counts and proved its convergence property. For the Poisson-power function distribution, we reject H$\_$0/ if X.leq..'{c}.. Since a critical value .'{c}. can not be determined to satisfy both .alpha. and .beta., similar to the Poisson case we considered discrimination curve and computation algorithm to find the minimum dwell time for the Poisson-power function distribution. We prosent this algorithm and an example of computation. It is found that the minimum dwell time algorithm fails for the Poisson-power function distribution if the aiming error variance .sigma.$\^$2/$\_$2/ is too large relative to the variance .sigma.$\^$2/$\_$1/ of the Gaussian distribution of intensity. In other words, if .ell. is too small, we can not find the minimum dwell time for a given .alpha. and .beta..

• Kyungpook Mathematical Journal
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• 제55권2호
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• pp.335-344
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• 2015

In the paper we discuss the value distribution of the product of the derivative of a transcendental meromorphic function and a power of the function.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.975-980
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• 1993

In accordance with increase, if electronic power demanded, more efficient supervisory control of distribution system will be required. This study contains development of MMI(man-machine-interface) system with GUI(graphic-user-interface), for the automatic power distribution system. The main function of MMI system is to edit network of power distribution and to management of data base for network. The GUI function of MMI system enables more efficient management of power distribution system.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1998년도 학술발표회논문집
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• pp.131-133
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• 1998

Electron temperature, electron density and electron energy distribution function were measured in Radio-Frequency Inductively Coupled Plasma(RFICP) using a probe method. Measurements were conducted in argon discharge for pressure from 10 mTorr to 40 mTorr and input rF power from 100W to 600W and flow rate from 3 sccm to 12 sccm. Spatial distribution of electron temperature, electron density and electron energy distribution function were measured for discharge with same aspect ratio (R/L=2). Electron temperature was found to depend on pressure, but only weakly on power. Electron density and electron energy distribution function strongly depended on both pressure and power. Electron density and electron energy distribution function increased with increasing flow rate. Radial distribution of the electron density and electron energy distribution function were peaked in the plasma center. Normal distribution of the electron density, electron energy distribution function were peaked in the center between quartz plate and substrate. These results were compared to a simple model of ICP, finally, we found out the generation mechanism of Radio-Frequency Inductively Coupled Plasma.

• 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.

• 충청수학회지
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• 제26권2호
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• pp.269-273
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• 2013

We prove a characterization of the power function distribution by lower record values. We prove that $F(x)=(\frac{x}{a})^{\alpha}$ for all $x$, 0 < $x$ < $a$, ${\alpha}$ > 0 and $a$ > 0 if and only if $\frac{X_{L(n)}}{X_{L(m)}}$ and $X_{L(m)}$ are independent for $1{\leq}m$ < $n$.