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Disassembly task times are assumed to be random variables with known probability distributions.
Task times are assumed to be random variables with known normal probability distributions.
In this paper, we propose a weighted multicast routing algorithm for MANET in which the mobility parameters are supposed to be random variables with unknown distribution.
This is achieved by considering the natural frequencies, the amplitudes and relative phases of the modes in a particular frequency band to be random variables with known probability density functions.
The target location coordinates and are assumed to be random variables with known statistics.
Let T, R and Y be random variables with CDF F T (x) = P (T ≤ x),F R (x) = P (R ≤ x) and F Y (x) = P (Y ≤ x).
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Let X be random variable with positive δ0and define a function g ≡ E exp {λ(X - EX)}.
The additive stochastic terms ξ(t), accounting for variability in gene expression or signaling noise, are random variables with a Gaussian white noise distribution N 0, η) with mean 0 and amplitude η.
We assume that the duration of surgeries are random variables with known probability distributions.
A basic problem is that the model parameters and the external loads are random variables with a certain probability distribution.
The problem stems from uncertainty quantification (UQ), where the independent variables of the functions are random variables with specified probability measure.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com