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"Who knows what's going to happen, but I'm hoping the one the House drew — the one that those who were elected drew — is the map we use".
For the revised slant edge saliency map, we use wavelet transform to find the slant edges and design to carve seams on the slant edges uniformly.
After obtaining the local quality map, we use texture component again as a weight function to derive a single quality score.
To build soil protection map, we use land use/land cover layer extracted from LANDSAT 7 ETM + images in addition to vegetation cover layer derived from MODIS NDVI product.
For example, in the 3D map we use for a simulation (Figure 10) the whole size of the textures is 461 MBytes in JPEG format, while the geometry information has only 15 MBytes in gzipped VRML.
Figure 7 illustrates the map we use that, we assume here, represents the current real state of the urban area, and the problem is then, given this state of the world, to find k = 5, 40, 100 or 3000 regions where there are crowds, using crowdsourcing.
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To ensure a robust initial map, we used a curve-matching algorithm.
Writing became a map we used to find our way and our dreams realized in the world.
To construct a protein interaction map, we used the STRING 8.2 software (http://string-db.org/) which predicts protein-protein interactions, including both physical and functional interactions [45].
According to the integrated map, we used interval mapping (Logarithm of odds, LOD > 3.0) to detect our quantitative trait.
To locate the address on the map we used the Italian road network (Tele Atlas, Italy).
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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