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An important task of uncertainty quantification is to identify the probability of undesired events, in particular, system failures, caused by various sources of uncertainties.
In the following part, different porosity crossplots and overlays have been used to identify the probability of fractured zones in the limestone Matulla Formation.
Therefore, the SSA helped to identify the probability of the malicious mobile device, whereas the contending approaches either deploy no proper secure authentication or apply fragile authentication mechanisms that can only secure the traditional networks but are not appropriate for mobile cloud computing [37, 38].
Alternatively, the DSI is a continuous variable, we can identify the probability of FHF prognosis (survival or death) based on the magnitude and dynamic change of the DSI.
We apply an EM-like algorithm, presented as Algorithm 1, to identify the probability of each possible SD, CD and GD event.
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To identify the probabilities of sites under positive selection in each gene, site models were implemented where ω could vary among sites [ 58, 59], which facilitated the analysis of datasets including all mammals or cetaceans only.
It identifies the probability of making a wrong estimation (in reception) of the information bit that is being transmitted. .
A fragility analysis is conducted, which identifies the probability of exceeding a structural damage level depending on ground motion intensity, along with a limit state probability analysis to quantify the annual exceedance probability of a specified damage level.
Whilst the former identifies the probability of an outcome with the frequency of occurrence of that outcome in a sufficiently large number of samples, the latter reflects the degree of belief in a given outcome, quantified from an a-priori estimate which is progressively adjusted as long as new information is added.
For a given gene set, PIPA identifies the probability of seeing an observed number of protein interactions between siRNA hits by chance.
In multiple-choice format, 38%% of patients/HCPs (n = 12/32), 38%% of physicians (n = 12/32), and 28%% of nurses (n = 9/32) identified the probability of requiring lifelong dialysis if discharged consistently with published literature (less than 25%%).
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