• Title/Summary/Keyword: Probability density estimation

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Statistical and Probabilistic Assessment for the Misorientation Angle of a Grain Boundary for the Precipitation of in a Austenitic Stainless Steel (II) (질화물 우선석출이 발생하는 결정립계 어긋남 각도의 통계 및 확률적 평가 (II))

  • Lee, Sang-Ho;Choe, Byung-Hak;Lee, Tae-Ho;Kim, Sung-Joon;Yoon, Kee-Bong;Kim, Seon-Hwa
    • Korean Journal of Metals and Materials
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    • v.46 no.9
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    • pp.554-562
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    • 2008
  • The distribution and prediction interval for the misorientation angle of grain boundary at which $Cr_2N$ was precipitated during heating at $900^{\circ}C$ for $10^4$ sec were newly estimated, and followed by the estimation of mathematical and median rank methods. The probability density function of the misorientation angle can be estimated by a statistical analysis. And then the ($1-{\alpha}$)100% prediction interval of misorientation angle obtained by the estimated probability density function. If the estimated probability density function was symmetric then a prediction interval for the misorientation angle could be derived by the estimated probability density function. In the case of non-symmetric probability density function, the prediction interval could be obtained from the cumulative distribution function of the estimated probability density function. In this paper, 95, 99 and 99.73% prediction interval obtained by probability density function method and cumulative distribution function method and compared with the former results by median rank regression or mathematical method.

Model based Fault Detection and Diagnosis of Induction Motors using Probability Density Estimation (확률분포추정기법을 이용한 유도전동기의 모델기반 고장진단 알고리즘 개발)

  • Kim, Kwang-Su;Lee, Young-Jin;Song, Xian-Hui;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • 2008.04b
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    • pp.171-173
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    • 2008
  • This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

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Model based Fault Detection and Diagnosis of Induction Motors using Online Probability Density Estimation (온라인 확률추정기법을 이용한 모델기반 유도전동기의 고장진단 알고리즘 연구)

  • Kim, Kwang-Su;Lee, Young-Jin;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.1503-1504
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    • 2008
  • This paper presents stochastic methodology based fault diction and diagnosis algorithm for induction motor systems. First, we construct probability distribution model from healthy motors and then probability distribution for faulty motors is recursively calculated by means of the proposed probability estimation. We measure motor current with hall sensors as system state. The estimated probability is compared to the model to generate a residue signal which is utilized for fault detection and diagnosis, that is, where a fault is occurred. We carry out real-time induction motor experiment to evaluate efficiency and reliability of the proposed approach.

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Strategy of the Fracture Network Characterization for Groundwater Modeling

  • Ji, Sung-Hoon;Park, Young-Jin;Lee, Kang-Kun;Kim, Kyoung-Su
    • Proceedings of the Korean Radioactive Waste Society Conference
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    • 2009.06a
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    • pp.186-186
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    • 2009
  • The characterization strategy of fracture networks are classified into a deterministic or statistical characterization according to the type of required information. A deterministic characterization is most efficient for a sparsely fractured system, while the statistics are sufficient for densely fractured rock. In this study, the ensemble mean and variability of the effective connectivity is systematically analyzed with various density values for different network structures of a power law size distribution. The results of high resolution Monte Carlo analyses show that statistical characteristics can be a necessary information to determine the transport properties of a fracture system when fracture density is greater than a percolation threshold. When the percolation probability (II) approaches unity with increasing fracture density, the effective connectivity of the network can be safely estimated using statistics only (sufficient condition). It is inferred from conditional simulations that deterministic information for main pathways can reduce the uncertainty in estimation of system properties when the network becomes denser. Overall results imply that most pathways need to be identified when II < 0.5 statistics are sufficient when II $\rightarrow$ 1 and statistics are necessary and the identification of main pathways can significantly reduce the uncertainty in estimation of transport properties when 0.5$\ll$1. It is suggested that the proper estimation of the percolation probability of a fracture network is a prerequisite for an appropriate conceptualization and further characterization.

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Estimation of Geometric Mean for k Exponential Parameters Using a Probability Matching Prior

  • Kim, Hea-Jung;Kim, Dae Hwang
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.1-9
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    • 2003
  • In this article, we consider a Bayesian estimation method for the geometric mean of $textsc{k}$ exponential parameters, Using the Tibshirani's orthogonal parameterization, we suggest an invariant prior distribution of the $textsc{k}$ parameters. It is seen that the prior, probability matching prior, is better than the uniform prior in the sense of correct frequentist coverage probability of the posterior quantile. Then a weighted Monte Carlo method is developed to approximate the posterior distribution of the mean. The method is easily implemented and provides posterior mean and HPD(Highest Posterior Density) interval for the geometric mean. A simulation study is given to illustrates the efficiency of the method.

Defect Detection algorithm of TFT-LCD Polarizing Film using the Probability Density Function based on Cluster Characteristic (TFT-LCD 영상에서 결함 군집도 특성 기반의 확률밀도함수를 이용한 결함 검출 알고리즘)

  • Gu, Eunhye;Park, Kil-Houm
    • 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.

Power Estimation by Using Testability (테스트 용이도를 이용한 전력소모 예측)

  • Lee, Jae-Hun;Min, Hyeong-Bok
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.3
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    • pp.766-772
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    • 1999
  • With the increase of portable system and high-density IC, power consumption of VLSI circuits is very important factor in design process. Power estimation is required in order to estimate the power consumption. A simple and correct solution of power estimation is to use circuit simulation. But it is very time consuming and inefficient way. Probabilistic method has been proposed to overcome this problem. Transition density using probability was an efficient method to estimate power consumption using BDD and Boolean difference. But it is difficult to build the BDD and compute complex Boolean difference. In this paper, we proposed Propowest. Propowest is building a digraph of circuit, and easy and fast in computing transition density by using modified COP algorithm. Propowest provides an efficient way for power estimation.

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Approximated Outage Probability for ADF Relay Systems with Burst MPSK and MQAM Symbol Transmission

  • Ko, Kyunbyoung;Lim, Sungmook
    • International Journal of Contents
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    • v.11 no.1
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    • pp.7-14
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    • 2015
  • In this paper, we derive the outage probability for M-ary phase shifting keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) burst transmission (BT) of adaptive decode-and-forward (ADF) cooperative relay systems over quasi-static Rayleigh fading channels. Within a burst, there are pilot symbols and data symbols. Pilot symbols are used for channel estimation schemes and each relay node's transmission mode selection schemes. At first, we focus on ADF relay systems in which the probability density function (PDF) is derived on the basis of error events at relay nodes corresponding to channel estimation errors. Next, the average outage probability is derived as an approximate expression for an arbitrary link signal-to-noise ratio (SNR) for different modulation orders. Its accuracy is demonstrated by comparison with simulation results. Further, it is confirmed that BT-ADF relay systems with pilot symbol based channel estimation schemes enables to select correctly decoded relay nodes without additional signaling between relay nodes and the destination node, and it is verified that the ideal performance is achieved with small SNR loss.

Estimation of ecological flow rate for Zacco platypus based on habitat suitability index considering probability density function (확률밀도함수를 고려한 서식처 적합도 지수에 의한 피라미 생태유량 산정)

  • Jang, Kyeung Ho;Park, Young Ki;Kang, Jae Il;Kim, Min Hwan
    • Journal of Korea Water Resources Association
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    • v.51 no.3
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    • pp.207-219
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    • 2018
  • In this study, the ecological flow rate of the Zacco playtypus habitat was simulated based on the Instream Flow Incremental Methodology (IFIM) in reachs of urban and natural stream using the habitat suitability index (HSI) of the probability density function (PDF). To apply this method, PHABSIM model was used in this study. However, in this study, the HSI of the probability density function was developed by adjusting the parameters of the PDF based on Kang (2010) HSI. As a result, the normal distribution is closest to the ecological flow rate of the Kang (2010) in the urban stream. However, the two-parameter log-pearson distribution tended to be the closest in the natural stream. The ecological flow rate was simulated by the HSI and the reach of stream with the PDF. Based on the comparison of simulation results, we propose an ecological flow rate estimation method using probabilistic method.

Probability density evolution analysis on dynamic response and reliability estimation of wind-excited transmission towers

  • Zhang, Lin-Lin;Li, Jie
    • Wind and Structures
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    • v.10 no.1
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    • pp.45-60
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    • 2007
  • Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.