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In the section "Related work", we compare offline violent extremist recruitment with the recent increase in cyber-recruitment efforts.
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Providers' movements, as recorded by the IMUs, were then compared offline between experienced and novice providers.
Notably, we compare online and offline heuristics in terms of energy savings and LSP acceptance rates.
Critically, we compare online against offline approaches and evaluate them using a novel metric that succinctly quantifies the advantage of an LSP establishment method in terms of energy saved and acceptance rate.
We compare tracer distributions predicted by the offline FFSL transport scheme with those predicted by the original hydrodynamic model, assess the conservation of mass in all cases and contrast the computational efficiency of the schemes.
In this section, we compare the Twitter prediction performance to an offline-only model, and we extend the time series model to incorporate both data sources.
We compare the optimal solutions with different degrees of future information to the offline optimal algorithm.
Finally, we compare the estimation performance of the proposed online power scheduling scheme with some typical offline power scheduling schemes.
We compare the runs where a particular user was online, with the runs where this user was offline.
Lastly, we compared the performance of our offline and online solutions with an upper bound and the throughput achieved by the hasty policy and also demonstrated how the buffers at the relay help achieve higher throughput.
In our first study, we compared intravascular microdialysis lactate values offline with arterial blood lactate concentration [ 17], but we did not study the online continuous monitoring of lactate.
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