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The results obtained with several extensive benchmark experiments show that MedSim is able to specifically associate diseases with known proteins.
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The benchmark experiments showed that the WSE levels off when increasing from 60 to 80 vCPUs, and the running time allows for running the analysis over night.
Using a beam as a benchmark, both numerical simulations and experiments show that multiple resonances of the primary structure can be significantly reduced by the proposed ABH-RBD, and the same ABH-RBD is effective on different primary systems.
The experiments show that our technique works better on the benchmarks with more white space as it has more capability to distribute routing congestion evenly.
The reported experiments show that the algorithm is competitive to standard ILP approaches on benchmark examples.
Extensive experiments show that our method can achieve competitive performance on popular retrieval benchmarks.
Experiments show that both approaches remarkably outperform the existing methods on different sets of benchmarks.
Experiments show that the proposed algorithm outperforms all existing object proposal algorithms on the challenging KITTI benchmark in terms of both recall and localization.
The numerical experiments show that the proposed algorithm leads to a significantly more accurate final solution for a variety of benchmark test functions faster.
Experiments show that our approach provides consistent improvements over the state of the art results on multiple benchmarks.
Our experiments show that our approach results in quarter reduction (≈25%) in power, area, and delay, respectively, for FSM MCNC benchmarks.
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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