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Effect Modification of Rescue Stenting in ICAS-Related Middle Cerebral Artery Occlusion: The Role of Thrombectomy Failure, Stenosis Severity, and ASPECTS. [PDF]

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Alexandre AM   +42 more
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Procedure FAILURE — The computation of probability of failure

Advances in Engineering Software and Workstations, 1991
Summary: This article presents the description of the procedure FAILURE which may be used for the probability analysis of practically any reliability condition. The estimation of the probability of failures is based on the simulation method Monte Carlo.
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Execution Ordering in AND/OR Graphs with Failure Probabilities

Proceedings of the International Symposium on Combinatorial Search, 2021
In this paper we consider finding solutions for problems represented using AND/OR graphs, which contain tasks that can fail when executed. In our  setting each node represent an atomic task which is associated with a failure probability and a rollback penalty. This paper reports the following contributions - (a) an algorithm for finding
Priyankar Ghosh   +2 more
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Abstracting from failure probabilities

Proceedings Second International Conference on Application of Concurrency to System Design, 2002
In fault-tolerant computing, dependability of systems is usually demonstrated by abstracting from failure probabilities (under simplifying assumptions on failure occurrences). In the specification framework Focus, we show under which conditions and to which extent this is sound: We use a specification language that is interpreted in the usual abstract ...
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General Probability of System Failure

IEEE Transactions on Reliability, 1983
This paper presents a general method to determine probabilities of failure of any fixed subset of coherent system components under various conditions. The method uses a known reliability structure of the system and the known joint probability distribution of its components times-to- failure.
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Estimating the probability of failure when testing reveals no failures

IEEE Transactions on Software Engineering, 1992
Formulas for estimating the probability of failure when testing reveals no errors are introduced. These formulas incorporate random testing results, information about the input distribution; and prior assumptions about the probability of failure of the software.
Keith W. Miller 0001   +6 more
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