• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.2
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• pp.123-133
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• 2010

A statistical evaluation methodology was developed to determine the compliance of candidate waste stream with clearance criteria based upon distribution of radionuclide in a waste stream at a certain confidence level. For the cases where any information on the radionuclide distribution is not available, the relation between arithmetic mean of radioactivity concentration and its acceptable maximum standard deviation was demonstrated by applying widely-known Markov Inequality and One-side Chebyshev Inequality. The relations between arithmetic mean and its acceptable maximum standard deviation were newly derived for normally or lognormally distributed radionuclide in a waste stream, using probability density function, cumulative density function, and other statistical relations. The evaluation methodology was tested for a representative case at 95% of confidence level and 100 Bq/g of clearance level of radioactivity concentration, and then the acceptable range of standard deviation at a given arithmetic mean was quantitatively shown and compared, by varying the type of radionuclide distribution. Furthermore, it was statistically demonstrated that the allowable range of clearance can be expanded, even at the same confidence level, if information on the radionuclide distribution is available.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2813-2827
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• 2018

Progressive censoring schemes have become quite popular in reliability study. Under progressive censored data, however, some units can be failed between two points of observation with exact times of failure of these units unobserved. For example, loss may arise in life-testing experiments when the failure times of some units were not observed due to mechanical or experimental difficulties. Therefore, multiply progressive censoring scheme was introduced. So, we derives a maximum likelihood estimator of the parameter of exponential distribution. And we introduced the goodness-of-fit test statistics using order statistic and Lorenz curve. We carried out Monte Carlo simulation to compare the proposed test statistics. In addition, real data set have been analysed. In Weibull and chi-squared distributions, the test statistics using Lorenz curve are more powerful than test statistics using order statistics.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.987-998
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• 2013

This paper considers the statistical characteristics on the air quality (PM10) of Korea collected hourly in 2011. PM10 in Korea exhibits very strong correlations even for higher lags, namely, long range dependence. It is power-law tailed in marginal distribution, and generalized Pareto distribution successfully captures the thicker tail than log-normal distribution. However, slowly decaying autocorrelations may confuse practitioners since a non-stationary model (such as changes in mean) can produce spurious long term correlations for finite samples. We conduct a statistical testing procedure to distinguish two models and argue that the high persistency can be explained by non-stationary changes in mean model rather than long range dependent time series models.

• Journal of the Korea Concrete Institute
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• v.23 no.4
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• pp.421-430
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• 2011

As a fundamental study to introduce the reliability-based design code, a statistical study is conducted for the material strength data collected from domestic construction sites. In order to develop a rational design code based on statistics and reliability theory, it is essential to obtain the statistical properties of material strength. Material strength data for concrete, reinforcing bars, and prestressing strands which are used in domestic construction sites are collected and statistically analyzed. Then, the statistical properties are compared with those used in the process of the reliability-based calibration of internationally leading design codes. The statistical properties of the domestic data are such that the bias factor is relatively uniform between 1.13 and 1.20 and the coefficient of variation is below 0.10. Reinforcing bar data show difference among different manufacturers but there is not much difference among re-bar diameters. In the case of tendons, which are high strength materials, both of the domestic and foreign data show smaller values of the bias factor and the coefficient of variation than those of concrete and re-bar. Statistical distribution of all the material strength can be properly assumed as normal, log-normal, or Gumbel distribution after analyzing the classified data by individual construction site and manufacturer rather than the mixed data obtained from different sources in order to express the individual distribution of each structure.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.104-110
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• 2003

As exhaust emission standards are more stringent, higher conversion efficiency of automotive catalytic converter is required. In addition, catalytic converter is deteriorated during mileage accumulation of vehicle. Therefore the specification of catalytic converter should be decided in consideration of emission standards and deterioration. Because the decision of the specification of catalytic converter is required at the beginning of vehicle development procedure, it is important and necessary to fix the target values of green vehicle exhaust emissions. To do this, a linear regression analysis was done with in-use exhaust emissions data of 5 different kinds of vehicle that received US94 emission standards certification, and data handling methods including some statistical estimation were proposed. As a result, the fixed target values of NMHC, CO, NOx of green vehicle against US94 emission standards were 0.079, 0.83, 0.116, respectively. And expected in-use deterioration factor of NMHC, CO, NOx were 1.75, 2.02, 1.38, respectively. And also it was blown that even if failure rate is 30% after 80,000km driven, it might be sufficiently safe from emission failure confirmatory test of Korea. It is hopeful to make a database of in-use emissions to increase the confidence in correctness of the calculated target values.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.2
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• pp.1-13
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• 2012

Seismic fragility functions are derived for probabilistic evaluation of seismic control performance of energy dissipation devices installed in reinforced concrete structures. Displacement-dependent dampers are added to the nonlinear single-degree-of-freedom systems with different natural periods and hysteretic characteristics of which stiffness and strength has uncertainty. Nonlinear time history analysis is conducted for those SDOF systems and the result is processed statistically to obtain seismic fragility functions in the form of log normal distribution. Variation of seismic fragility functions for different parameters of SDOF systems and dampers are investigated and the seismic control performance is assessed probabilistically.

• Journal of Ocean Engineering and Technology
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• v.30 no.6
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• pp.440-450
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• 2016

The capsizing and consequent sinking of a coastal car ferry was recently reported, with numerous human casualties. The primary cause was determined to be a sudden turn with improperly stowed and secured cargo. Part I of this study introduces how long term acceleration components are determined from seakeeping analyses. A carferry with a displacement of 1,633 tonf was selected as the target vessel. Sea data that included the significant wave heights and periods were collected at four observation buoys, some of which were far away from two main voyage routes: Incheon-Jeju and Pusan-Jeju. Frequency response analyses were performed to obtain the linearized radiation force coefficients, hydrostatic stiffnesses, and wave excitation forces. Time response analyses were sequentially performed to produce the motion-induced acceleration processes. The probabilistic distributions of the acceleration components were determined using a peak and valley counting method. Long term extreme acceleration components were proposed as a final result.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.83-92
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• 2020

Recently, many companies and organizations are interested in predictive process monitoring for the efficient operation of business process models. Traditional process monitoring focused on the elapsed execution state of a particular process instance. On the other hand, predictive process monitoring focuses on predicting the future execution status of a particular process instance. In this paper, we implement the function of the business process remaining time prediction, which is one of the predictive process monitoring functions. In order to effectively model the remaining time, normalization by activity is proposed and applied to the predictive model by taking into account the difference in the distribution of time feature values according to the properties of each activity. In order to demonstrate the superiority of the predictive performance of the proposed model in this paper, it is compared with previous studies through event log data of actual companies provided by 4TU.Centre for Research Data.

• Journal of the Korean Geotechnical Society
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• v.35 no.6
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• pp.17-26
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• 2019

In this study, the statistical characteristics of the resistance bias factors were analyzed using a high-quality field load test database, and the total resistance bias factors were estimated considering the soil uncertainty and construction errors for the application of the limit state design of aggregate pier foundation. The MLR model by Bong and Kim (2017), which has a higher prediction performance than the previous models was used for estimating the resistance bias factors, and its suitability was evaluated. The chi-square goodness of fit test was performed to estimate the probability distribution of the resistance bias factors, and the normal distribution was found to be most suitable. The total variability in the nominal resistance was estimated including the uncertainty of undrained shear strength and construction errors that can occur during the aggregate pier construction. Finally, the probability distribution of the total resistance bias factors is shown to follow a log-normal distribution. The parameters of the probability distribution according to the coefficient of variation of total resistance bias factors were estimated by Monte Carlo simulation, and their regression equations were proposed for simple application.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.409-420
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• 2020

In business survey, modified cut-off sampling is commonly used to greatly increase the accuracy of the estimation while reducing the number of samples. However, non-response rate of take-all stratum has increased significantly and the sample substitution is not possible because the non-response in the take-all stratum affects the accuracy of the estimation. It is important to adjust the bias appropriately if non-response is affected by the variable of interest. In this study, a bias adjusted estimation is proposed as an appropriate method to deal with a non-response in the take-all stratum. In particular, the estimator proposed by Chung and Shin (2020) was applied to the bias adjustment for the take-all stratum; therefore, we suggest a new method to adjust properly for the take-all stratum. The superiority of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.