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The posterior most possible values of modal parameters and their uncertainties were estimated through Bayesian inference.
Uncertainty in the parameters is containing all (or most) possible values that may be realized for the corresponding parameters.
In this way, once the user has defined such function expressing how a particular combination of system variables is "consistent" with its model, the basic idea on possibilistic calculus is, given a subset of the system variables (assumed as known or measured), estimate the "most possible" values of all the remaining variables via an optimization problem.
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They show that, for instance, the most possible value of v1 is 0.75 (possibility of 0.74), that v1 being 2.25 is quite possible, but that v1 bigger than 10 is almost impossible (possibility lower than 0.05).
The whole intent of Employees First is to do everything we can to enable those employees to create the most possible value.
For this reason, for each network examined, the network ran 15 times and then the most possible value one could take with only one "running" of the network was chosen.
The simplest point-wise estimate is the minimum-cost flux vector resulting from (7), which contains the most possible value for each flux.
So, precisely, the actual range of any given NP-TGT sensor represents a distribution with the most possible value of rupture force at 12, 16, 23, 33, 43, 50, 54, and 56 pN, respectively.
The obtained flux vector v mp contains the most possible flux values compatible (consistent) with the model and the measurements.
Current efforts in observational cosmology focus on measuring the most accurate possible values of Hubble's constant and of critical density.
Thus there are at most four possible values for the angle θ∈ [ 0,2π) in addition to θ=0,π for which the magnetic geodesic can approach the singular point p. □.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com