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Therefore, the nodes with large carrying capacity may be small in influence.
By adding some fixed nodes with large storage space, the problem can be solve to some extent.
By ordering the individuals according to the rule that nodes with large similarity are close to each other, we plot the structural similarity in Figure 3(D).
Surprisingly, the classic Pagerank centrality metric failed to identify effective lawyers but a penalized variation compensate for nodes with large out strength proposed here showed better performance.
The reason BW is the most sensitive to topology update interval is that, within a topology update interval, nodes with large bandwidth were allocated upstream in this method.
In contrast, the proposed SI-LMS and SI-RLS algorithms will keep the nodes with lower MSE values and reduce the combining weight of the nodes with large MSE values as illustrated in Fig. 2 b.
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Figure 8 Box plots for three 2D conductance models at the 12 nodes with largest GIC.
Using the model to predict the probability of surrounding nodes reaching to the destination nodes, we can obtain the forwarding probability of the corresponding node and then choose the nodes with largest forwarding probability to relay messages.
This is due to nodes with larger transmission radius being able to inform more nodes in one transmission, and thus, fewer transmissions will be needed to inform its neighbors.
The 1D model has the largest influence on the generation of electric field values and hence GIC. Figure 7 Box plots for the seven 1D conductivity models at the 12 nodes with largest GIC.
Each time the system ran out of memory, 50% of the nodes with larger f(x) values were thrown away.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com