Sentence examples for highlight the capabilities of from inspiring English sources

Three different cases of smart beam geometries are discussed to highlight the capabilities of this method.

After outlining the adopted solution method some optimized results are shown to highlight the capabilities of the proposed approach.

These findings highlight the capabilities of this reactor configuration to enhance the productivity and yield of biohydrogen.

The results highlight the capabilities of the KTRM and its implementation, and indicate that kinetic solvers may be needed for models characterized by Knudsen numbers on the order of unity.

To highlight the capabilities of the modeling approach, a series of parametric studies are conducted, which illustrate the influence of mortar-interface strength ratio and the spatial variation of material properties on the force-deformation response and the failure mechanism.

A numerical example and a parametric study, which highlight the capabilities of the proposed theoretical model and which provide some insight into the long-term and thermal behaviour of shallow concrete domes, are presented.

These imaging results further highlight the capability of high resolution X-ray tomography to investigate the role of electrode microstructure in battery degradation and failure.

We highlight the capability of our approach through a case study in formal modular specification and tool-assisted verification of a timestamp-based checkpointing protocol.

The numerical applications highlight the capability of the proposed procedure to solve three dimensional problems with taut and slack cables, out of plane distributed forces (modeling wind loads), point loads along the cables.

This paper highlight the capability of harmonic filters to give a stationary and dynamic behavior that can be employed for compensating resonances of electrical systems in order to avoid unwanted transient phenomena like overvoltages.

The results obtained highlight the capability of POPFNN-TVR in fuzzy knowledge extraction for modelling inter-lane relationships in a highway traffic stream, as well as in generalizing from sample data, as compared to traditional feed-forward neural networks using back-propagation learning.