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The definitions of edge weight and vertex strength take sensor energy, transmission distance, and flow into consideration.
Thus, the in vertex strength is a candidate metric for ranking the lawyers.
Figure 4 b shows the vertex strength distribution also indicating to be heavy-tailed.
In a weighted network, this centrality can be generalized to account for edge weights, giving rise to vertex strength [13].
Moreover, in a directed network this metric can be extended to in and out vertex strength, as with vertex degree.
Metrics such as vertex strength, Pagerank, and closeness were used to rank vertices, identifying the most effective lawyers in the network.
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The vertex strengths drive the growth of topology; meanwhile, the edge weights change correspondingly.
LFPy, therefore, remains the superior tool for modelling extracellular potentials around single neurons, while VERTEX's strength lies in simulating LFPs in large-scale networks.
Experimental data demonstrate that the WSN topology we obtain has the property of weighted networks of the IOT: the edge weight, vertex degree, and strength follow a power-law distribution.
The k-core of a graph is a maximal subgraph in which each vertex has at least strength k.
Note that a large degree vertex does not necessarily have a large strength, both for in and out.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com