• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.3
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• pp.147-160
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• 2020

A stochastic probabilistic model for harbor structures such as rubble-mound breakwater has been formulated by using the generalized Wiener process considering the nonlinearity of damage drift and its nonlinear uncertainty, by which the damage path with real-time can be tracked, the residual useful lifetime at some age can also be analyzed properly. The formulated stochastic model can easily calculate the probability of failure with the passage of time through the probability density function of cumulative damage. In particular, the probability density functions of residual useful lifetime of the existing harbor structures can be derived, which can take into account the current age, its present damage state and the future damage process to be occurred. By using the maximum likelihood method and the least square method together, the involved parameters in the stochastic model can be estimated. In the calibration of the stochastic model presented in this paper, the present results are very well similar with the results of MCS about tracking of the damage paths as well as evaluating of the density functions of the cumulative damage and the residual useful lifetime. MTTF and MRL are also evaluated exactly. Meanwhile, the stochastic probabilistic model has been applied to the rubble-mound breakwater. The related parameters can be estimated by using the experimental data of the cumulative damages of armor units measured as a function of time. The theoretical results about the probability density function of cumulative damage and the probability of failure are very well agreed with MCS results such that the density functions of the cumulative damage tend to move to rightward and the amounts of its uncertainty are increased as the elapsed time goes on. Thus, the probabilities of failure with the elapsed time are also increased sharply. Finally, the behaviors of residual useful lifetime have been investigated with the elapsed age. It is concluded for rubble-mound breakwaters that the probability density functions of residual useful lifetime tends to have a longer tail in the right side rather than the left side because of the gradual increases of cumulative damage of armor units. Therefore, its MRLs are sharply decreased after some age. In this paper, the special attentions are paid to the relationship of MTTF and MRL and the elapsed age of the existing structure. In spite of that the sum of the elapsed age and MRL must be equal to MTTF deterministically, the large difference has been shown as the elapsed age is increased which is due to the uncertainty of cumulative damage to be occurred in the future.

• IE interfaces
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• v.15 no.2
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• pp.209-217
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• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.382-384
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• 2004

In this parer, we propose a clustering that perform algorithm using new convergence properties. For detection and optimization of cluster, we use to similarity measure with cumulative probability and to inference the its parameters with MLE. A merits of using the cumulative probability in our method is very effectiveness that robust to noise or unnecessary data for inference the parameters. And we adopt similarity threshold to converge the number of cluster that is enable to past convergence and delete the other influence for this learning algorithm. In the simulation, we show effectiveness of our algorithm for convergence and optimization of cluster in riven data set.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.177-183
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• 1999

This paper presents how to evaluate the transformer damage caused by reclosing scheme at the distribution substation. We describe a quantitative relationship between the reclosing scheme and the number of fault current flowing through transformer wsing the probability of a reclosing success/failure. The transformer damage from reclosing scheme is presented using a weight function and a damage function. A weight function is associated with the number of reclosing attempts and the reclosing deadtime to consider cumulative stress caused by reclosing scheme. A damage function is associated with a transformer impact ratio and a transformer functional life. In the case study, the transformer damage is simulated for the probability of a reclosing success. And the evaluation of transformer damage using KEPCO's operation data is performed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.5
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• pp.48-57
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• 2012

This paper analyzes the characteristic of gird connected photovoltaic power generation system which is available to connect the utility. Renewable energy photovoltaic power system has been linked to the system to analyze the impact of photovoltaic system. It is measured that power data for the Grid connected photovoltaic power plant with instantaneous measuring and 3-sec measuring for 7 days. Harmonic field measurements have shown that the harmonic contents of a waveform varies with time. A cumulative probability approach is the most commonly used method to solve time varying harmonics. So, it is used 50[%] cumulative probability approach. This paper provides an in depth analysis on power quality field measurement of the Grid connected photovoltaic power plant.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.89-102
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• 1994

A new method for approximating the average run length (ARL) of cumulative sum (CUSUM) chart is proposed. This method uses the conditional expectation for the test statistic before the stopping time and its asymptotic conditional density function. The values obtained by this method are compared with some other methods in normal and exponential case.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.4
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• pp.1-9
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• 2002

The distribution characteristics of data retention time for DRAM was studied in connection with the probability distribution of the cell parameters. Using the cell parameters and the transient characteristics of cell node voltage, data retention time was investigated. The activation energy for dielectric layer growth on cell capacitance, the recombination trap energy for leakage current in the junction depletion region, and the sensitivity characteristics of sense amplifier were used as the random variables to perform the Monte Carlo simulation, and the probability distributions of cell parameters and distribution characteristics of cumulative failure bit on data retention time in DRAM cells were calculated. we found that the sensitivity characteristics of sense amplifier strongly affected on the tail bit distribution of data retention time.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4307-4309
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• 2014

Purpose: To calculate the probability of one person's life-time death caused by a malignant tumor and provide theoretical basis for cancer prevention. Materials and Methods: The probability of one person's death caused by a tumor was calculated by a probability additive formula and based on an abridged life table. All data for age-specific mortality were from the third retrospective investigation of death cause in China. Results: The probability of one person's death caused by malignant tumor was 18.7% calculated by the probability additive formula. On the same way, the life-time death probability caused by lung cancer, gastric cancer, liver cancer, esophageal cancer, colorectal and anal cancer were 4.47%, 3.62%, 3.25%, 2.25%, 1.11%, respectively. Conclusions: Malignant tumor is still the main cause of death in one's life time and the most common causes of cancer death were lung, gastric, liver, esophageal, colorectal and anal cancers. Targeted forms of cancer prevention and treatment strategies should be worked out to improve people's health and prolong life in China. The probability additive formula is a more scientific and objective method to calculate the probability of one person's life-time death than cumulative death probability.

• International Journal of Reliability and Applications
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• v.14 no.2
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• pp.107-114
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• 2013

Modelling of failures is an important element of reliability modelling. Empirical modelling approach suitable for complex item is explored in this paper. First step of the empirical modelling approach is to plot hazard function, density function, Weibull probability plot as well as cumulative intensity function to see which model fits best for the given data. Next step of the empirical modelling approach is select appropriate model for the data and fit the parametric model accordingly and estimate the parameters.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.