• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Construction Engineering and Project Management
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• v.8 no.2
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• pp.17-33
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• 2018

This study investigates the stability of professionals' cost variability factor-rankings across different levels of cost-variability and response scenarios. Descriptive statistics are used to examine the stability of factor-ranking for 20 cost variability factors and a Multinomial Logistic (MNL) regression model was implemented to examine the stability of cost variability factors across three cost variability levels. The finding on the descriptive statistics indicated that professionals' factors-rankings are stable only for external factors. The MNL regression results on factor-stability suggested that 8 out of the 20 evaluated factors were unstable determinant of lower cost variability levels. These factors are "risk associated with the project", "personal bias and poor professionalism of the estimators", "limited time available to complete the project", "lack of skills and experience by estimator" "geographical location of projects", "incomplete & rush designs for estimate", "unforeseen or unexpected site constraints", "high class bidders for the contractors". Similarly lack of experience and large size projects were observed to be unstable as well. These observations suggest that professionals' view on pre-tender cost variability factor-ranking yields unstable factor rankings hence should not be relied upon as the only mechanisms to mitigate cost related risks in construction projects.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.175-177
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• 1995

The sensor signal validation and failure detection system must be able to detect, isolate, and identify sensor degradation as well as provide a reconstruction of the measurements. In this study, this is accomplished by combining the neural network, the Generalized Consistency Checking(GCC), and the Sequential Probability Ratio Test(SPRT) method in a decision estimator module. The GCC method is a computationally efficient system for redundant sensors, while the SPRT provides the ability to make decisions based on the degradation history of a sensor. The methodology is also extended to the detection of noise degradation. The acceptability of the proposed method is demonstration by using the simulation data in safety injection accident of nuclear power plants. The results show that the signal validation and sensor failure detection system is able to detect and isolate a bias failure and noise type failures under transient conditions. And also, the system is able to provide the validated signal by reconstructing the measurement signals in the failure conditions considered.

• Journal of Power Electronics
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• v.16 no.2
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• pp.643-653
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• 2016

The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO₄ battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.

• Journal of Korean Society for Quality Management
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• v.9 no.1
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• pp.3-11
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• 1981

A stress-strength model is formulated for s of k systems consisting of identical components. We consider minimum variance unbiased (MVU) estimation of system reliability for data consisting of a random sample from the stress distribution and one from the strength distribution when the two distirubtions are Weibull with unknown scale parameters and same known shape parameter. The asymptotic distribution of MVU estimate of system reliability in the model is obtained by using the standard asymptotic properties of the maximum likelihood estimate of system reliability and establishing their equivalence. Uniformly most accurate unbiased confidence intervals are also obtained for system reliability. Empirical comparison of the two estimates for small samples is studies by Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.315-325
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• 2016

Thanks to the advantages of low cost and quick results, public opinion polls on election in Korea have been generally conducted by telephone survey, even though it has critical disadvantage of low response rate. In public opinion polls on election in Korea, the general method to handle nonresponses is adjusting the survey weight to estimate parameters. This study first drives mathematical expression of estimator and its bias with variance estimators with/without nonresponses in election polls in Korea. We also investigates the nonresponse rate of telephone survey on 2012 Korea presidential election. The average response rate was barely about 14.4%. In addition, we conducted a survey in April 2014 on the respondents's attitude toward telephone surveys. In the survey, the first reason for which respondents do not answer on public opinion polls on election was "feel bothered". And the aged 20s group, the most low response group, also gave the same answer. We here suggest that survey researchers motivate survey respondents, specially younger group, to participate surveys and find methods boosting response rate such as giving incentive.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.7011-7016
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• 2013

Background: The liver fluke, Opisthorchis viverrini, and the associated incidence of subsequent cholangiocarcinoma (CCA) are still a public health problem in Thailand, and praziquantel (PZQ) remains the antihelminthic drug of choice for treatment. Evidence in hamsters shows that repeated infection and PZQ treatments could increase the risk of CCA. However, the existing evidence in humans is inconclusive regarding increased risk of CCA with frequency of PZQ intake. Objectives: To investigate the relationship between number of repeated PZQ treatments and CCA in patients with O viverrini infection. Materials and Methods: The reviewed studies were searched in EMBASE, MEDLINE, ProQuest, PubMed and SCOPUS from inception to October, 2012 using prespecified keywords. The risk of bias (ROB) of included studies was independently assessed by two reviewers using a quality scale from the Newcastle-Ottawa Scale (NOS). Risk effect of PZQ was estimated as a pooled odds ratio (OR) with its 95% confidence interval (95%CI) in the random-effects model using DerSimonian and Laird's estimator. Results: Three studies involving 637 patients were included. Based on the random effects model performed in two included studies of 237 patients, the association between PZQ treatments and CCA was not statistical significant with a pooled OR of 1.8 (95%CI; 0.81 to 4.16). Conclusions: The present systematic review and meta-analysis provides inconclusive evidence of risk effect of PZQ on increasing the risk of CCA and significant methodological limitations. Further research is urgently needed to address the shortcomings found in this review, especially the requirement for histological confirmation.