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In [56], the authors apply evolutionary-fuzzy strategy to predict the utilization level of links.
Line 3 gets the maximum cumulative interference level of links in ({textbf {H}_{0}^{t} cup left { {l_{pi}^{{x_{0}}}} right }}).
Similar(58)
Results show that the level of linking social capital is critical in determining post-disaster trajectories.
We define I i as the cumulative interference level of link l i.
Above this critical level of link error, the spatial structure of (V') no longer hints towards excellent seed placement in (G).
Even though Theorem 1 estimates only the degree of local interference at level of vertex, we can extend it to the level of link using Corollary 1.
This is because most off-the-shelf APs and wireless devices do not measure or report this level of link and channel-related performance information.
At the same level of link-prediction error, and despite a higher budget, (text {OAS}_{text {tg}}) barely outperforms random-seeding performance.
Effectively, for high thresholds, the cascade size caused by the planner's (text {OAS}_{text {mg}}) estimate of (V') appears to be very stable (despite substantial differences in (E(G)) and (E(G'))) up to a critical level of link-prediction error.
First is the open data community in general, following the 5 star open data approach defined by Berners-Lee [1], aiming to open data according to the fifth level of Linked Open Data specification.
Under modified greedy seeding, the transition from noisy (G') informing near-optimal seeding strategies in (G) to being almost useless in reasoning about (G) is sudden: (text {OAS}_{text {mg}}) declines steeply at a critical level of link-prediction error.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com