• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.89-97
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• 2011

The aims of this study were to propose a method of estimation for mean residual life function (MRLF) from conditional survival function using the Buckley and James's (1979) pseudo random variables, and then to assess the performance of the proposed method through the simulation studies. The mean squared error (MSE) of proposed method were less than those of the Cox's proportional hazard model (PHM) and Beran's nonparametric method for non-PHM case. Futhermore in the case of PHM, the MSE's of proposed method were similar to those of Cox's PHM. Finally, to evaluate the appropriateness of practical use, we applied the proposed method to the gastric cancer data. The data set consist of the 1, 192 patients with gastric cancer underwent surgery at the Department of Surgery, K-University Hospital.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.61-72
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• 2011

In the benefits of ITS, there are intangible gains from real-time traffic information as well as classical gains such as travel time saving. These intangible gains are difficult to be estimated by existing transportation investment appraisal commonly used in SOC investment. The major reason is not because of the absence of methodology but because of the absence of generalized values of particular benefits from real time traffic information. This research explores the value of real-time traffic information on VMS that is the most representative of ITS services, by using CVM with Double Bounded Dichotomous Choice Question. Willingness-To-Pay (WTP) functions of drivers are built with survival functions using various types of probability distribution functions such as Exponential, Log-logistic, and Weibull functions. The results reveal that Log-logistic distribution is the most appropriate distribution model to estimate WTP, and the estimated coefficients are stable through LR (Likelihood Ratio) test. For the further study, it is recommended to perform statistical tests of temporal and spatial transferability that is not examined in this research due to the lack of data.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.152-161
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• 2008

We investigate that when we restrict the encoding modes on the enhancement layer based on that of the base layer exploiting the high correlation between the best modes at base and enhancement layers, we should determine the set of surviving search modes to yield the minimum excessive RD-cost caused by the restriction. Based on these sets, we implement a fast mode decision algorithm for H.264 Scalable Extension (SE). Simulation results show that the proposed algorithm is superior in the sense of the RD-performance to the conventional mode restriction method which is based on the conditional probabilities of the best modes.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.711-724
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• 2016

Under variable complex operating environment, various factors can affect the lifetimes of systems. In this research, we study bivariate reliability models having multiple dynamic competing risks. As competing risks, in addition to the natural failure, we consider the increased stress caused by the failure of one component, external shocks, and the level of stress of the working environment at the same time. Considering two reliability models which take into account all of these competing risks, we derive bivariate life distributions. Furthermore, we compare these two models and also compare the distributions of maximum and minimum statistics in the two models.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.135-147
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• 2012

The benefit of traffic information on variable message sign can be divided into two. At the public level, the benefit of ATIS is the travel time saving, which is not only induced from ATIS, but also mixed with that of ATMS. In the economic appraisal of ITS, the benefit of ATIS has so far been regarded as the derived benefit from ATMS. At the user level, the benefit of ATIS is reduced driver uncertainty through the forward traffic status information. User can benefit from the information on VMS and therefore may have the willingness to pay for it. Recently attempt to qualify the value of information on VMS was increased, but there was a danger of distorting or over-estimates of the ATIS benefit because the related studies didn't consider the time-dependent attributes of traffic information and provided the single value. Estimates of the time-varying value should be needed for a rigorous economic appraisal of ATIS. In this study, we varied the value of information on VMS according to peak and non peak trip and verified the hypothesis that time-varying of value was statistically significant.