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Table 1 summarizes the system resource utilization for each workload.
For each workload, the ratio is constant and is less than 1.5.
For each workload pattern, incing requests are calculated with 100 s interval.
This allows to determine if the factor is the same for each workload.
To improve accuracy of the results, the experiment is repeated 10 times for each workload pattern.
Meanwhile, the training time of our approach achieves 7.6 11.8× speedup over previous approaches for each workload.
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In all of 30 simulation for each BitTorrent workload, no more than 43 % of the requests in the trace was spent in the warm-up phase with cache size of 50%% of the the ideal cache size.
This results in 10 workload trace files, for each of the workload patterns.
Between Days 9 and 15, the number of medical activities performed changed by 0.02 per day for each level of workload (p = 0.84) Summarizing our findings, a relevant influence of the day-to-day variability of residents' workload on the number of medical activities performed by students was not found.
We generate 100 VSB queries for each type of workload, and evaluate the batch one by one.
For each session, the workload contains: a user identifier, start time, end time, number of bytes requested, and the size of the file accessed.
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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