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Adsorption equilibrium data are formulated into an isotherm model.
The register data are formulated as probabilities of low, medium, and high exposure.
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As shown in Fig. 2, the first phase (Data Formulation) includes activities through which the required data were formulated.
LS-BICSA, generally applicable to a set of irregular data, is formulated by the pure bi-cubic spline functions.
To test whether adequate kinetic estimation could be obtained using IF corrected by fewer blood samples, three reduced sets of discrete blood sample data were formulated.
An initial programming problem with uncertain data is formulated as follows: mathop {hbox{min} }limits_{x},varvec{c}^{T} varvec{x} (23) {text{s}}.
An empirical model integrating the fluid-phase permeabilities for a given set of bottom-hole fluid density data is formulated to estimate the average reservoir permeability.
A recursive stochastic matrix equation that characterizes the damage development using the true probability distributions and correlation properties of test data, is formulated.
This inverse mapping problem for estimating force-applied location by a few known strain data is formulated and analyzed for a square plate structure.
Then a block sparse model of the extended data is formulated without the influence of the unknown noncircularity phase, and a novel signal reconstruction algorithm based on nuclear norm minimization is proposed to recover the block-sparse matrix.
A model (or, source receptor relationship) that relates the source distribution to the concentration data is formulated, and Bayesian probability theory is used to derive the posterior probability density function of the source parameters.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com