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An important problem that commonly arises in areas such as internet traffic-flow analysis, phylogenetics and electrical circuit design, is to find a representation of any given metric D on a finite set by an edge-weighted graph, such that the total edge length of the graph is minimum over all such graphs.
We wanted to determine an optimal neighborhood in which the total edge length of the graph was minimized according to some metric on the lattice.
Analyzing centrality as judged by the z-score of the change of the characteristic length of the graph after removal of a particular node identified enzymes with the most influence on the cohesion of the interactome.
The amount of horizontal deformation was then taken as the difference between the total length of the graph (numerically calculated to be 24.11 μm) and the horizontal distance (20.0 μm) of Fig. 7a), that is, 4.11 μm.
Ten most central proteins in the fPIN as judged by the z-score of the change of the characteristic length of the graph after removal of a particular protein, robustness centrality (RB).
In a graph consisting of N nodes, there are N 2 = N (N - 1 ) / 2 distinct node pairs, and the average path length of the graph is defined as the average distance between all possible node pairs.
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By [23], it is well known that M k ( G ) is equal to the number of closed walks of length k of the graph G.
The main objective is to minimize the scheduling length of the task graph and maximize the lifetime of the sensor nodes.
The solution objectives are to minimize the scheduling length of the task graph and maximize the fairness in energy-driven task mapping, while satisfying energy harvesting causality constraints and the task precedence constraints.
The exponential growth rate of the number of paths of length in the graph is, where is the largest eigenvalue of A. In the C-LPCD case, the practical values of are not very large, for instance, for a 512 512 image, with, we have, then we can easily compute the matrix and derive the exact size of the C-LPCD class of attacks.
(S(G)) is the graph obtained by inserting an additional vertex in each edge of G, i.e., replacing each edge of G by a path of length 2. The graph (S(G)) is also known as a subdivision graph of G. (R(G)) is the graph obtained by adding a new vertex corresponding to each edge of G, then joining each new vertex to the end vertices of the corresponding edge.
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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