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Figure 9 shows two illustrations of a matching surface.
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Since the outcome plays an important role in this paper we introduced a special term, the matching surface.
Especially, in VS-SAIM the dynamic "featureless" map, the matching surface, is an integral part of interactions between the selection process and the identification process. 1 Intuitively, this seems to be a more biologically plausible approach to modelling processes during visual search tasks.
The graphs at the top show a one-dimensional illustration of the matching surface as found in real simulations (e.g. Fig. 9).
Moreover this leads to a smaller decrease in contrast in the matching surface for the vertical line as distractor compared to the diagonal line as distractor.
This, in turn, led to better matching values at the target location in the matching surface.
The phosphating film can also change the wear mechanism of the matching surface, particularly, in some bad conditions.
Moreover, the custom-fit structure ensures the matching surface geometry between the cast and arm and thus disperses pressure.
In VS-SAIM the selection network and its input, the matching surface, are "featureless" maps.
In order to explain this result, it is necessary to examine the matching surface closer.
Matching surface features are evident when comparing the AFM and AFMIR scans.
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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