• Title/Summary/Keyword: Function Distribution

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Measurement of Electron Energy Distribution of the Radio-Frequency Inductively Coupled Plasma (고주파 유도결합 플라즈마의 전자에너지 분포 계측 (II))

  • Hwang, Dong-Won;Ha, Chang-Ho;Jeon, Yong-Woo;Choi, Sang-Tae;Park, Won-Zoo;Lee, Kwang-Sik;Lee, Dong-In
    • Proceedings of the KIEE Conference
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    • 1998.07e
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    • pp.1803-1805
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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 electron temperature and 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, then we found out the generation mechanism of Radio-Frequency Inductively Coupled Plasma.

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Validity of Ocean Wave Spectrum Using Rayleigh Probability Density Function

  • Choi, Young Myung;Yang, Young Jun;Kwon, Sun Hong
    • International Journal of Ocean System Engineering
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    • v.2 no.4
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    • pp.250-258
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    • 2012
  • The distribution of wave heights is assumed to be a Rayleigh distribution, based on the assumption of a narrow band and Gaussian distribution of wave elevation. The present study was started with doubts about the narrow band assumption. We selected the wave spectra widely used to simulate irregular random waves. The wave spectra used in this study included the Pierson-Moskowitz spectrum, Bretschneider-Mitsuyasu spectrum, and JONSWAP spectrum. The directionality of the waves was considered. The cosine 2-l type directional spreading function and mixed form of the half-cosine 2-s type with Mitsuyasu type directional spreading are considered here to investigate the effects of a directional spreading function on random waves. The simulated wave height distribution is compared with a Rayleigh distribution.

An Effective Algorithm for the Noncentral Chi-Squared Distribution Function (비중심카이제곱분포 함수에 대한 효율적인 알고리즘)

  • Gu, Son-Hee
    • The KIPS Transactions:PartA
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    • v.9A no.2
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    • pp.267-270
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    • 2002
  • The evaluation of the cumulative distribution function of the noncentral $\chi^2$ distribution is required in approximate determination of the power of the $\chi^2$ test. This article provides an algorithm for evaluating the noncentral $\chi^2$ distribution function in terms of a single "central" $\chi^2$ distribution function and compared various approximations.ximations.

Design Of Air-Distribution System in a Duct (취출구를 가진 덕트의 공기분배장치 설계)

  • Kang, Hyung-Seon;Cho, Byung-Ki;Koh, Young-Ha
    • Journal of Advanced Marine Engineering and Technology
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    • v.31 no.8
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    • pp.954-960
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    • 2007
  • The purpose of this paper is to obtain design method of air-distribution system. Air-distribution system is composed of blower, duct, diffusers and measuring equipment. The air-flow rate from each diffuser is not equal. The air-flow rate is calculated with the combined equations which are Bernoulli's equation, continuity equation and minor loss equations. Inlet condition and outlet condition are adapted in each duct system. Then square difference between function of maximum air-flow rate and minimum air-flow rate is used as an object function. Area of diffuser and velocity are established as constraints. To minimize the object function, the optimization method is used. After optimization the design variables are selected under satisfaction of constraints. The air-distribution system is calculated again with the result of optimized design variable. It is shown that the air-distribution system has the equal air-flow rate from diffusers.

A Study on Selection of Distribution Function for Reliability Prediction Using Accelerated Life Test Data (가속 수명시험 데이터를 기반으로 하는 신뢰성 예측에 적합한 분포 함수 선택에 관한 연구)

  • Kim Ji-Hun;Park Dong-Gue;Han Hyun-Kak
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.3
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    • pp.393-397
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    • 2006
  • The study about Accelerated Life Test and analysis of failed data is increased in order to predict and evaluate reliability of products, according as the development cycle of products is reduced. Therefore, the decision of optimal distribution function about failed data for accurate analysis of failed data and test condition for Accelerated Life Test is very important. This paper compares Anderson-Darling method with Likelihood Function method for the decision of optimal distribution function about failed data. Anderson-Darling considers only failed data and Likelihood Function considers both failed data and life-stress relationship in decision of distribution function. In the results of comparison about two methods, we found that the distribution function chosen by each method is different and the life time predicted by each decided distribution function is different.

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Properties of the Poisson-power Function Distribution

  • Kim, Joo-Hwan
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.166-175
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    • 1995
  • When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector without any errors, it obeys Poisson law. Under the two assumptions that neutral particle scattering distribution and aiming errors have a circular Gaussian distributions that neutral particle scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of neutral particles vecomes a Poisson-power function distribution. We study and prove some properties, such as limiting distribution, unimodality, stochastical ordering, computational recursion fornula, of this distribution. We also prove monotone likelihood ratio(MLR) property of this distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem.

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ESTIMATION OF THE DISTRIBUTION FUNCTION FOR STATIONARY RANDOM FIELDS OF ASSOCIATED PROCESSES

  • Kim, Tae-Sung;Ko, Mi-Hwa;Yoo, Yeon-Sun
    • Communications of the Korean Mathematical Society
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    • v.19 no.1
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    • pp.169-177
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    • 2004
  • For a stationary field $\{X_{\b{j}},\b{j}{\;}\in{\;}{\mathbb{Z}}^d_{+}\}$ of associated random variables with distribution function $F(x)\;=\;P(X_{\b{1}}\;{\leq}\;x)$ we study strong consistency and asymptotic normality of the empirical distribution function, which is proposed as an estimator for F(x). We also consider strong consistency and asymptotic normality of the empirical survival function by applying these results.

On the Estimation of the Empirical Distribution Function for Negatively Associated Processes

  • Kim, Tae-Sung;Lee, Seung-Woo;Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.229-235
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    • 2001
  • Let {X$\_$n/, n$\geq$1] be a stationary sequence of negatively associated random variables with distribution function F(x)=P(X$_1$$\leq$x). The empirical distribution function F$\_$n/(x) based on X$_1$, X$_2$,....., X$\_$n/ is proposed as an estimator for F$\_$n/(x). Strong consistency and asymptotic normality of F$\_$n/(x) are studied. We also apply these ideas to estimation of the survival function.

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Reliability estimation and ratio distribution in a general exponential distribution

  • Lee, Chang-Soo;Moon, Yeung-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.3
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    • pp.623-632
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    • 2014
  • We shall consider the estimation for the parameter and the right tail probability in a general exponential distribution. We also shall consider the estimation of the reliability P(X < Y ) and the skewness trends of the density function of the ratio X=(X+Y) for two independent general exponential variables each having different shape parameters and known scale parameter. We then shall consider the estimation of the failure rate average and the hazard function for a general exponential variable having the density function with the unknown shape and known scale parameters, and for a bivariate density induced by the general exponential density.

Prediction of Pollutant Emission Distribution for Quantitative Risk Assessment (정량적 위험성평가를 위한 배출 오염물질 분포 예측)

  • Lee, Eui Ju
    • Journal of the Korean Society of Safety
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    • v.31 no.4
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    • pp.48-54
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    • 2016
  • The prediction of various emissions from coal combustion is an important subject of researchers and engineers because of environmental consideration. Therefore, the development of the models for predicting pollutants very fast has received much attention from international research community, especially in the field of safety assessment. In this work, response surface method was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of a drop tube furnace (DTF) to predict the spatial distribution of pollutant concentrations as well as final ones. The distribution of carbon dioxide in DTF was assumed to have Boltzman function, and the resulted function with parameters of a high $R^2$ value facilitates predicting an accurate distribution of $CO_2$. However, CO distribution had a difference near peak concentration when Gaussian function was introduced to simulate the CO distribution. It might be mainly due to the anti-symmetry of the CO concentration in DTF, and hence Extreme function was used to permit the asymmetry. The application of Extreme function enhanced the regression accuracy of parameters and the prediction was in a fairly good agreement with the new experiments. These results promise the wide use of statistical models for the quantitative safety assessment.