• Convergence Security Journal
• /
• v.6 no.3
• /
• pp.117-126
• /
• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Convergence Security Journal
• /
• v.6 no.3
• /
• pp.145-153
• /
• 2006

Infinite failure NHPP models for a record value satisfies mode proposed in the literature exhibit either monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, propose comparative study of software reliability model using Erlang distribution, Rayleigh and Gumbel distribution. Equations to estimate the parameters using maximum likelihood estimation of infinite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing distribution, we used to the special pattern. Analysis of failure data set using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

• Convergence Security Journal
• /
• v.7 no.1
• /
• pp.45-53
• /
• 2007

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 hyper-exponential distribution reliability model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares). The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution (shape 0.1 & scale 1) of Minitab (version 14) statistical package.

• Convergence Security Journal
• /
• v.7 no.2
• /
• pp.1-8
• /
• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault (intensity function). In this paper, intensity function of Goel-Okumoto model was reviewed, proposes Kappa (2) and the Burr distribution, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares) The methodology developed in this paper is exemplified with a software reliability real data set introduced by NTDS (Naval Tactical Data System)

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.7 no.2
• /
• pp.245-263
• /
• 1997

For twelve solvent thinners, evaporation rates of components were investigated and models to estimate the actual concentration have been evaluated. Also, the current ACGIH TLVs (Threshold Limit Values) for the concentration of organic mixtures have been adjusted. The results of this study are summarized as follows : 1. Airborne concentrations of solvent thinner components were related to their respective vapor pressure (r=0.96). On the other hand, there was no significant relation between the concentrations in the air of the thinner compounds and the original amount in liquid form. 2. Airborne concentrations of each chemical were estimated by temperature at $8.5{\pm}1$, $16.7{\pm}1$ and $31.5{\pm}2^{\circ}C$ with an air velocity of 1.5 m/s. The concentrations were increased by increasing temperature (p<0.05). The percentage of concentrations were proportionate to their respective percentage of vapor pressure. Among the chemicals studied, n-butyl acetate, n-butyl alcohol, m-xylene, p-xylene and o-xylene showed a clear relationship to temperature. 3. Airborne concentration of each chemical was estimated by air velocity at 0.05, 1.50 and 2.50 m/s, with a constant temperature at $17{\pm}2^{\circ}C$. The concentrations were increased by increasing air velocity (p<0.05). The percentage of concentrations were proportionate to their respective percentage of vapor pressure. Among the chemicals studied, n-butyl alcohol, m-xylene and p-xylene showed a clear relationship to velocity. 4. In estimating the concentrations of solvent thinners by temperature and air velocity, ACGIH TLVs for mixtures tended to be larger than the values obtained by ACGIH exposure index. It shows that ACGIH TLVs for mixtures are not adequate for evaluating the airborne concentration of thinners and other organic mixtures. 5. The evaporation rate of the thinners were compared to the theoretical equations of Hummel, Braun and Mackay. The Hummel and Braun methods were close to exposure index but Makay's showed an underestimated value. In order to see the accuracy of each three models, the SSE (Error Sum of Squares) calculated for Hummel's was 1.73, being the closest to the actual values. 6. Present ACGIH TLVs for mixtures are not appropriate evaluate industrial environments. In this study, a correction of TLVs using vapor pressure of respective components was suggested. In order to evaluate the corrected TLVs a paired t-test was performed. There was no significant difference between the exposure index and the concentration over suggested TLVs (p>0.05). Thus, this corrected TLVs seem appropriate in order to evaluate actual industrial workplaces organic chemical concentration in the air.