Sentence examples for to every edge from inspiring English sources
So we add a flag to every edge of G.
If we add a Randić weight to every edge and arc in M, then we can get a new weighted Hermitian-adjacency matrix.
How will you securely deploy an application image (e.g., a container) to every edge in your network and run them as needed?
From the above we can see that if we add a Randić weight to every edge in a simple graph G, then we can get a Randić matrix (R(G)).
For example, there is a path from the root node through the edges labeled End, Header, and TagAndLength ending in the leaf node with the value 0. For better readability and consistency with PDF, we prepend the forward slash symbol " /" to every edge label when printing a path; hence, the path in question prints as /End/Header/TagAndLength.
In addition we assign to every edge e = { x, y} the weight ω (e) := D x, y).
When the large tech companies compete from selling cloud storage to phone hardware to music sales to consumers, every edge is worth buying so that your competition can't do the same.
By giving real people (not opt-in test subjects) a chance to experience self-driving vehicles in a controlled setting, Olson believes May Mobility will be able to scale the technology more quickly than other companies trying to develop autonomous cars to handle every "edge case" scenario.
We describe here such an approach, bearing some similarity with the method of Muffato (2010) applied to teleost fishes: (i) construct a complete graph G= V, E) where the set of vertices corresponds to the columns of the matrix and (ii) assign to every edges an appropriate cost/weight [Hamming distance, Jaccard coefficient, see Garriga et al. (2008) for example].
President Bush's political guru, Karl Rove, has made no secret of his determination to squeeze every edge out of the statehouses held by the G.O.P., even to the point of reopening the redistricting issue beyond the usual 10-year census limit.
As there exists no standard way of generalizing the clustering coefficient to weighted graphs [see e.g. [40], [41]] and it is not obvious how to interpret edge weights when computing the average shortest path length, we have decided to treat every edge equally and apply the classic unweighted approach [39].
