• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.12
• /
• pp.2311-2318
• /
• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of Korean Society for Quality Management
• /
• v.31 no.4
• /
• pp.164-175
• /
• 2003

This paper investigates bootstrap confidence intervals of the process capability index(PCI) based on the expected loss derived from the empirical distribution function(EDF). The PCI based on the expected loss is too complex to derive its confidence interval analytically, so the bootstrap method is a good alternative. We propose three types of the bootstrap confidence interval; the standard bootstrap(SB), the percentile bootstrap(PB), and the acceleration biased­corrected percentile bootstrap(ABC). We also perform a comprehensive simulation study under various process distributions, in order to compare the accuracy of the coverage probability of the bootstrap confidence intervals. In most cases, the coverage probabilities of the bootstrap confidence intervals from the EDF PCI turned out to be more accurate than those from the PCI based on the normal distribution. It is expected that the bootstrap confidence intervals from the EDF PCI can be utilized in real processes where the true distribution family may not be known.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.2 no.3
• /
• pp.83-92
• /
• 1999

To investigate the influence of forest road characteristics and site conditions on the stability of forest-road in granite area, four forest roads had been selected in Kyongbuk regions. The total of 13 road characteristic variables were evaluated by the discriminant analysis. The factors influencing the stability of forest road were bed rock, slope length, coverage, hardness, side-ditch erosion and road width. But aspect and soil texture were not significant for the stability in this area. In the correlation between forest environment and road structure, hardness and bed rock was highly significant in stability group, and coverage and side-ditch erosion was highly significant in instability group. 75 of 175 segments were instable whereas the others were stable. The centroids value by discriminant function in the stability and instability were estimated to 3.0585 and -1.9116, respectively. The stability criterion of forest road was discriminated from the centroids value of the each group. The main factors contributing the stability of forest road were significant in order of side-ditch erosion, coverage, soil texture, elevation, gradient, slope length and construction year. The prediction rate of discriminant function for stability evaluation of forest road was as high as 97.44%. In conclusion, the forest road structure factors such as length, coverage and slope gradient were controlled by construction techniques. If the factors like those should be considered in design, construction and forest road management, the stability of forest road may increase more. And also, it is necessary to take slope protection measures like small terraces and retaining walls for stability of cut slope.

• Communications for Statistical Applications and Methods
• /
• v.24 no.6
• /
• pp.641-649
• /
• 2017

Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1310-1311
• /
• 2003

Oil Field Geographical Information System (OFGIS) manages multiple spatial data, attribute data, and topographic data, which include almost every kind of ground info rmation and underground information. Subsystems managed by OFGIS include petroleum exploration subsystem (PESS), petroleum development and engineering subsystem (PDESS), petrochemical subsystem (PCSS), petroleum storage and transportation subsystem (PSTSS), petroleum sale subsystem (PSSS), etc. A basic OFGIS framework consists of oil field infrastructure coverage (OFIC), oil field specialized information coverage (OFSIC) and oil field synthesis and decision service coverage (OFSDSC). Basic function of OFGIS includes database management, geographic information management, spatial information processing and application.

• Communications for Statistical Applications and Methods
• /
• v.26 no.1
• /
• pp.35-46
• /
• 2019

Multivariate Confidence Region (MCR) cannot be used to obtain the confidence region of the mean vector of multivariate data when the normality assumption is not satisfied; however, the Quantile Confidence Region (QCR) could be used with a Multivariate Quantile Vector in these cases. The coverage rate of the QCR is better than MCR; however, it has a disadvantage because the QCR has a wide shape when the probability density function follows a bimodal form. In this study, we propose a Quantile Confidence Region using the Highest density (QCRHD) method with the Highest Density Region (HDR). The coverage rate of QCRHD was superior to MCR, but is found to be similar to QCR. The QCRHD is constructed as one region similar to QCR when the distance of the mean vector is close. When the distance of the mean vector is far, the QCR has one wide region, but the QCRHD has two smaller regions. Based on these features, it is found that the QCRHD can overcome the disadvantages of the QCR, which may have a wide shape.

• Communications for Statistical Applications and Methods
• /
• v.4 no.2
• /
• pp.523-532
• /
• 1997

We propose several estimators of the reliability function R of the two-parameter exponential distribution, and then compare those estimator in terms of the mean square error (MSE) through Monte Carlo method. We also consider the parametric bootstrap estimation. Using the parametric bootstrap estimator, we obtain the bootstrap confidence intervals for reliability function and compare the proposed bootstrap confidence intervals in terms of the length and the coverage probability through Monte Carlo method.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.2
• /
• pp.361-369
• /
• 2011

In this paper, we develop the reference and the matching priors for the reliability function of two-parameter exponential distribution. We derive the reference priors and the matching prior, and prove the propriety of joint posterior distribution under the general prior including the reference priors and the matching prior. Through the sim-ulation study, we show that the proposed reference priors match the target coverage probabilities in a frequentist sense.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.4
• /
• pp.359-366
• /
• 2009

MATLAB Autocode generation is a feature that converts a block diagram model in Simulink to a c program. Utilizing this function makes MATLAB/Simulink an integrated developing environment, from controller design to implementation. It can reduce development cost and time significantly. However, this automated process requires high reliability on the software, especially the original Simulink block diagram model. And thus, the verification of the codes becomes important. In this study, a UAV flight program which is generated with Simulink is validated and modified according to DO-178B. As a result of applying the procedures, the final program not only satisfied the functional requirement but is also verified with structural point of view with Decision Coverage 93%, Condition Coverage 95% and MC/DC 90%.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.89-96
• /
• 2007

Finite failure NHPP models presented in the literature exhibit either constant. monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times. and estimation of the reliability and availability of a software product require quality of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-type model was reviewed, proposes modified(the superosition and mixture) model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. model selection based on SSE statistics for the sake of efficient model, was employed.