• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.13-19
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• 2004

This study shows the possible use of the Poisson process for the characterization of dry year return period and duration. For the analysis we used an annual precipitation data, which has been collected since 1911 in Seoul. The highest threshold for the application of the Poisson process was determined to be the mean-0.5standard deviation, and then the results from the Poisson process are compared with the observed. Especially, the Poisson process was found to reproduce the mean duration and return interval quite well and show the possibility of using the Poisson process for the drought analysis.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.813-822
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• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.747-759
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• 2008

This study, a point rainfall process model, which could represent appropriately observed rainfall data, was to select. The point process models-rectangular pulses Poisson process model(RPPM), Neyman-Scott rectangular pulses Poisson process model(NS-RPPM), and modified Neyman-Scott rectangular pulses Poisson process model(modified NS-RPPM)-all based on Poisson process were considered as possible rainfall models, whose statistical analyses were performed with their simulation rainfall data. As results, simulated rainfall data using the NS-RPPM and the modified NS-RPPM represent appropriately statistics of observed data for several aggregation levels. Also, simulated rainfall data using the modified NS-RPPM shows similar characteristics of rainfall occurrence to the observed rainfall data. Especially, the modified NS-RPPM reproduces high-intensity rainfall events that contribute largely to occurrence of natural harzard such as flood and landslides most similarly. Also, the modified NS-RPPM shows the best results with respect to the total rainfall amount, duration, and inter-event time. In conclusions, the modified NS-RPPM was found to be the most appropriate model for the long-term simulation of rainfall.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.51-59
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• 2006

The purpose of this paper is to present reliability analysis procedures for repairable systems and apply the procedures for assessing the reliabilities of two subsystems of a specific group of military equipment based on field failure data. The mean cumulative function, M(t), the average repair rate, ARR(t), and analytic test methods are used to determine whether a failure process follows a renewal or non-renewal process. For subsystem A, the failure process turns out to follow a homogeneous Poisson process, and subsequently, its mean time between failures, availability, and the necessary number of spares are estimated. For subsystem B, the corresponding M(t) plot shows an increasing trend, indicating that its failure process follows a non-renewal process. Therefore, its M(t) is modeled as a power function of t, and a preventive maintenance policy is proposed based on the annual mean repair cost.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.109-124
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• 2002

This study is an effort to develop a stochastic model of precipitation series that preserves the pattern of occurrence of precipitation events throughout the year as well as several characteristics of the duration, amount, and intensity of precipitation events. In this study an event cluster model is used to describe the occurrence of precipitation events. A logarithmic negative mixture distribution is used to describe event duration and separation. The number of events within each cluster is also described by the Poisson cluster process. The duration of each event within a cluster and the separation of events within a single cluster are described by a logarithmic negative mixture distribution. The stochastic model for hourly precipitation occurrence process is fitted to historical precipitation data by estimating the model parameters. To allow for seasonal variations in the precipitation process, the model parameters are estimated separately for each month. an analysis of thirty-four years of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many features of historical precipitation. The seasonal variations in number of precipitation events in each month for the historical and simulated data are also approximately identical. The marginal distributions for event characteristics for the historical and simulated data were similar. The conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.787-796
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• 2014

Situations where sample size is not constant are common when monitoring a process with Poisson count data. In this paper, we propose a generalized likelihood ratio(GLR) control chart to detect shifts in the Poisson rate when the sample size varies. The performance of the proposed GLR chart is compared with the performance of several cumulative sum(CUSUM) type charts. It is shown that the overall performance of the GLR chart is comparable with CUSUM type charts and is significantly better in cases where the actual value of the shift is different from the pre-specified value in CUSUM type charts.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.805-812
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• 2003

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.319-327
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• 1999

Zero-Inflated Poisson distributions have been widely used for defect-free products in manufacturing processes. It is very interesting to check the shift after the unknown changepoint. If the detectives are caused by the two different types of factor, we should use bivariate zero-inflated model. In this paper, likelihood ratio tests were used to detect the shift of changes after the changepoint. Some inferences for the parameters in this model were made.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.617-623
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• 2018

In this paper, we propose a novel seamless video composition method based on shape matching and Poisson equation. Video composition method consists of video segmentation process and video blending process. In the video segmentation process, the user first sets a trimap for the first frame, and then performs a grab-cut algorithm. Next, considering that the performance of video segmentation may be reduced if the color, brightness and texture of the object and the background are similar, the object region segmented in the current frame is corrected through shape matching between the objects of the current frame and the previous frame. In the video blending process, the object of source video and the background of target video are blended seamlessly using Poisson equation, and the object is located according to the movement path set by the user. Simulation results show that the proposed method has better performance not only in the naturalness of the composite video but also in computational time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.17
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• pp.67-80
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• 1988

This study is concerned with the comparison of two time homogeneous Poisson processes. Traditionally, the methods of testing equality of Poisson processes were based on the binomial distribution or its normal approximations. The sampling plans used in these methods are to observe the processes concurrently over a predetermined time interval, possibly different for each process. However, when the values of the intensities of the processes are small, inverse type sampling plans are more appropriate since there may be cases where only a few or even no events are observed in the predetermined time interval. This study considers 9 inverse type sampling plans for the comparison of two Poisson processes. For each sampling plans considered, critical regions and the design parameters of the sampling plan are determined to guarantee the significance level and the power at some values of the alternative hypothesis. The Problem of comparing of two Weibull processes are also considered.