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Experiments show that both approaches remarkably outperform the existing methods on different sets of benchmarks.
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The proposed algorithm is evaluated on four different sets of benchmark instances and compared with other algorithms from the literature.
Extensive numerical experiments are presented on different sets of benchmark instances for the homogeneous and the heterogeneous single depot dial-a-ride problem.
The new algorithm is tested on two different sets of benchmark problems: a Boolean function set used in logic circuit design and a well studied set of real world problems.
The proposed method is simulated on two different sets of testbenches namely Benchmark suite I and III respectively.
We provide two simulated examples, a real social network and different sets of power law benchmark networks, to illustrate how our method can correctly detect communities in directed networks.
> -wrap-foot> Since OSLay and MCM can only run with one reference, we use Ragout and RACA to benchmark different sets of multiple references (see Table 3).
For large 454 sequencing projects, the software provider recommended a set of pre-assembly and assembly parameters; however, because they were optimized for shorter reads than those obtained in our study, we performed several benchmark assemblies under different sets of parameters (Supplementary Tables S1 and S2).
To benchmark time (and also memory) consumption, we use three different sets of sequences.
Two different sets of experiences and emotions.
Different sets of experiments were performed.
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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