Current Issue : April - June Volume : 2014 Issue Number : 2 Articles : 6 Articles
A new procedure for determining the acceptance or rejection of a system that undergoes a start-up demonstration set of tests is\r\npresented. It is a generalization of the recently introduced CSDF model (consecutive successes distant failures). According to the\r\nnew total successes consecutive successes total failures distant failures (TSCSTFDF) procedure, a unit is accepted when either a\r\ntotal number of successful tests or a specified number of consecutive successes are observed before a total number of failures or\r\nthe occurrence of near failures which are too close to each other.The practical advantage of this new procedure is the significant\r\nreduction in the expected number of required tests together with improved second-order statistics (standard deviation)....
The recent proliferation of Markov chain Monte Carlo (MCMC) approaches has led to the use of the Bayesian inference in a wide\r\nvariety of fields. To facilitateMCMC applications, this paper proposes an integrated procedure for Bayesian inference usingMCMC\r\nmethods, froma reliability perspective.Thegoal is to build a framework for related academic research and engineering applications\r\nto implementmodern computational-based Bayesian approaches, especially for reliability inferences.Theprocedure developed here\r\nis a continuous improvement process with four stages (Plan, Do, Study, and Action) and 11 steps, including: (1) data preparation; (2)\r\nprior inspection and integration; (3) prior selection; (4)model selection; (5) posterior sampling; (6)MCMCconvergence diagnostic;\r\n(7) Monte Carlo error diagnostic; (8) model improvement; (9) model comparison; (10) inference making; (11) data updating and\r\ninference improvement. The paper illustrates the proposed procedure using a case study....
The exact evaluation of the Poisson and Binomial cumulative distribution and inverse (quantile) functions may be too challenging\r\nor unnecessary for some applications, and simpler solutions (typically obtained by applying Normal approximations or exponential\r\ninequalities) may be desired in some situations. Although Normal distribution approximations are easy to apply and potentially\r\nvery accurate, error signs are typically unknown; error signs are typically known for exponential inequalities at the expense of some\r\npessimism. In this paper, recent work describing universal inequalities relating the Normal and Binomial distribution functions is\r\nextended to cover the Poisson distribution function; new quantile function inequalities are then obtained for both distributions.\r\nExponential boundsââ?¬â?which improve upon the Chernoff-Hoeffding inequalities by a factor of at least twoââ?¬â?are also obtained for\r\nboth distributions....
The microelectromechanical system (MEMS) is one of the most diversified fields of microelectronics; it is rated to be the\r\nmost promising technology of modern engineering. MEMS can sense, actuate, and integrate mechanical and electromechanical\r\ncomponents of micro- and nano sizes on a single silicon substrate using microfabrication techniques. MEMS industry is at the\r\nverge of transforming the semiconductor world into MEMS universe, apart from other hindrances; the reliability of these devices\r\nis the focal point of recent research. Commercialization is highly dependent on the reliability of these devices. MEMS requires a\r\nhigh level of reliability. Several technological factors, operating conditions, and environmental effects influencing the performances\r\nof MEMS devices must be completely understood.This study reviews some of the major reliability issues and failure mechanisms.\r\nSpecifically, the fatigue in MEMS is a major material reliability issue resulting in structural damage, crack growth, and lifetime\r\nmeasurements of MEMS devices in the light of statistical distribution and fatigue implementation of Paris� law for fatigue crack\r\naccumulation under the influence of undesirable operating and environmental conditions....
This paper derives closed-form solutions for the ??-and-h shape parameters associated with the Tukey family of distributions based\r\non the method of percentiles (MOP). A proposed MOP univariate procedure is described and compared with the method of\r\nmoments (MOM) in the context of distribution fitting and estimating skew and kurtosis functions. The MOP methodology is\r\nalso extended from univariate to multivariate data generation. A procedure is described for simulating nonnormal distributions\r\nwith specified Spearman correlations. TheMOP procedure has an advantage over theMOMbecause it does not require numerical\r\nintegration to compute intermediate correlations. Simulation results demonstrate that the proposedMOP procedure is superior to\r\nthe MOM in terms of distribution fitting, estimation, relative bias, and relative error....
The purpose of this paper is to give a detailed proof of Yamada-Watanabe theorem for stochastic evolution equation driven by pure\r\nPoisson random measure....
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