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While ETX is a single-path metric, using this directly to find weights of the nodes will not reflect the improvements due to multiple next hop forwarders.
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We then calculated this weighted metric using the same process used for the unweighted metric, but with the difference in each cell weighted by the weather frequency weights for the table.
We computed this metric using equation 3 (Table S1), for cattle only.
We derive this new metric using linear regression on a number of OSS java projects.
We minimize this nonlinear metric using a novel coarse-to-fine hierarchical solver, further accelerated with a fine-to-coarse propagation of the integrated metric tensor.
The metric uses this distance measure of randomness of features as a measure of biometric quality of an iris sample.
In terms of an approximate metric used in this paper, citation threshold for engineering academics who work in related fields of mechanics and finite elements, and who are included in HiglyCited.com list, is about 6000 total citations.
Details of the metric used in this paper can be seen from (Table 1).
The evaluation metric used for this part is the average prediction error.
The performance metric used in this research for comparison of the studied algorithms is mean noise reduction.
The metric used in this contention is a utility U, corresponding to the received SNR in the dB scale, i.e., (U equiv log {SNR_{{{rcvd}}}}).
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