The availability of software systems can be increased by preventive measures which are triggered by failure prediction mechanisms. In this paper we present and evaluate two non-parametric techniques which model and predict the occurrence of failures as a function of discrete and continuous measurements of system variables. We employ two modelling approaches: an extended Markov chain model and a...

in this paper, using numerical methods and test results, the behavior of reinforced concrete beams strengthened with fiber-reinforced polymers (frp) is investigated. in the numerical analysis, the concrete damaged plasticity model is used for considering the nonlinear behavior and strain softening of concrete. the abaqus finite element program is utilized for the analysis of 12 flexural beams s...

Background—Despite the rising heart failure (HF) incidence and aging United States population, there are no validated prediction models for incident HF in the elderly. We sought to develop a new prediction model for 5-year risk of incident HF among older persons. Methods and Results—Proportional hazards models were used to assess independent predictors of incident HF, defined as hospitalization...

Due to the dynamics of the environment and the variability on the product usage, product units in the field are usually exposed to varying failure-causing stresses. Some products are equipped with sensors and smart chips that measure and record usage/ environmental information over the life of the product. For some products, it is possible to track environmental variables dynamically, even in r...

The ever-growing demand and heterogeneity of Cloud Computing is garnering popularity with scientific communities to utilize the services of Cloud for executing large scale scientific applications in the form of set of tasks known as Workflows. As scientific workflows stipulate a process or computation to be executed in the form of data flow and task dependencies that allow users to simply artic...

Error logs are a fruitful source of information both for diagnosis as well as for proactive fault handling – however elaborate data preparation is necessary to filter out valuable pieces of information. In addition to the usage of well-known techniques, we propose three algorithms: (a) assignment of error IDs to error messages based on Levenshtein’s edit distance, (b) a clustering approach to g...

I compared 101 wolf (Canis lupus) pack territories formed in Wisconsin during 1993–2004 to the logistic regression predictive model of Mladenoff et al. (1995, 1997, 1999). Of these, 60% were located in putative habitat suitabilities ,50%, including 22% in suitabilities of 0–9%. About a third of the area with putative suitabilities .50% remained unoccupied by known packs after 24 years of recolo...

Traditional bankruptcy prediction models, designed using classification or regression techniques, achieve short-term performances (1 year) that are fairly good, but that often worsen when the prediction horizon exceeds 1 year. We show how to improve the performance of such models beyond one year using models that take into account the evolution of firm financial health over a short period of ti...

In this thesis we present two prediction techniques for estimating the error coverage of target programs stimulated with different inputs. Preliminarily, we investigate the effects of the inputs on the failure distribution of the target programs using fault injection experiments. From this study, we could find a linear correlation between the length of the input and the error coverage. This res...