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Periodic regular and random microstructure computer models with up to a hundred spheres were considered.
First, we employ standard mathematical test functions to demonstrate the method's ability to identify models with up to six interacting variables; these functions determine its performance and limitations.
Regular hexagonal and random Monte Carlo models with up to 800 fully aligned both identical and distributed diameter fibers are studied.
Using a much larger 2100-hour training corpus (combining Switchboard and Fisher) we examine the performance of very large DNN models – with up to ten times more parameters than those typically used in speech recognition systems.
For the regression analyses, we used a model selection and averaging approach that calculated all possible subset models with up to four predictors and chose from this set those subset models with the lowest values (ΔAICc ≤ 2) of the Akaike Information Criterion corrected for small sample size (AICc).
These fractional constitutive models quantitatively describe both the linear viscoelasticity of all of the liquid foods as well as the shear thinning of their steady shear viscosity (through application of the Cox-Merz rule), and outperform conventional multi-mode Maxwell models with up to 50 physical elements in terms of the goodness of fit to experimental data.
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Here, we investigate the host repopulation capacity of such dTEHVs in a non-human primate model with up to 8 weeks follow-up.
As for making money, RealPlayer Cloud will follow a freemium model, with up to two gigabytes of storage for free.
In a HMM speech recognition system using monophone models, 3 states per model with up to 20 mixtures per state for each of 39 phoneme models is typical.
Patient risk stratification was dependent on the segmentation method used to develop the prognostic model with up to 73 patients (17.1%) changing risk stratification group.
Therefore, we propose an optimized architecture for the simulation of Fermi-Hubbard model with up to next-nearest neighbours in 2D.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com