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Minimum mutual projection length: 3 m.
Figure 1b shows the angle α between the two edges, and their mutual projection.
The GM algorithm used by GIMME calculates distances between vertices, angles between edges, and the area of a mutual projection of edges.
Candidate edge x has a mutual projection length above the threshold of 3 m with source edge a (the remaining dissimilarity measures given in Section 3.3 do not exceed the respective maximum values, respectively), but not with source edge b.
In contrast, candidate edge y has a mutual projection length above the threshold with both source edges a and b (and also the remaining dissimilarity measures do not exceed the respective maximum values, respectively).
The length of the projection of the candidate to the source (i.e. reference) edge is called the reference length, shown in Fig. 1c together with the intersection of the areas confined to the edges and the perpendiculars of their mutual projection, respectively.
length of the mutual projection of the candidate and the source edge, Firstly, the candidate list is re-initialised with those outgoing edges of the current best edge, for which the dissimilarity measure is good (i.e. low) enough, and ordered with respect to the measure.
A geometry-based dissimilarity measure for pairs of source and candidate edges is given which is mainly based on three criteria: (i) average distance (ii) angular difference, and (iii) length of the mutual projection of the candidate and the source edge, respectively.
BestPlaces.net can give you a good idea just how self-serving the mutual fund projections can be.
This permissive role of the D1/D5 receptors in LC regulation of hippocampal plasticity is likely to relate to the role of the noradrenergic and dopaminergic systems in processing novelty and is probably mediated by mutual axonal projections and hippocampal neurotransmitter release.
Compressive sensing (CS) is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix.
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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