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The analysis starts in automatically transforming the behaviour of an architecture into a Labelled Transition System.
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Our work is similar to this kind of simulator because our objective is to evaluate the power-performance behaviour of a micro-architecture level design abstraction.
The validity of this approach is verified by computer simulation of the behaviour of the architecture which derived the correct critical exponents for the percolation model.
The "safe" behaviour of the architecture is guaranteed by enforcing some place invariants on the marking of the net.
Owing to the heterogeneous behaviour of the architecture, the system can automatically reconfigure its actions to adapt to unpredicted events (such as actuator failure).
This study aimed to determine the characteristics of the in vivo behaviour of human muscle architecture during a pre-motion silent period (PMSP) using ultrasonography.
An architecture is represented by means of an architecture description.
In the present paper we compare nonlinear regression analysis with the behaviour of different architectures of multilayer feed forward neural networks trained by error back propagation.
This is because (i) the static architecture alone does not determine the dynamical behaviour of a network and (ii) the abundances are obtained from heterogeneous populations of cells.
Of particular note is the behaviour of several monitoring architectures at the 1000 VM point.
A satisfactorily agreement between the experimental data and predicted results has been found for the bending behaviour of the different architectures.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com