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In this work, a comprehensive study is done on a large set of FDSOI devices.
All considered measures are tested and compared on a large set of random and structured populations.
Object Kinetic Monte Carlo relies on a large set of parameters and reactions.
Several variants of the algorithm are tested and compared on a large set of benchmark problems.
We present computational results on a large set of randomly generated instances.
Our implementation is tested on a large set of benchmark instances.
We thus use term association discovering algorithm to expand terms based on a large set of scientific article abstracts.
The algorithm has been tested on a large set of benchmark instances and compared with other existing algorithms.
Results obtained on a large set of randomly generated problem instances are also shown, aimed at comparing the two policies.
Experimental results conducted on a large set of broadcast soccer videos demonstrate the effectiveness of the proposed approach.
A systematic study was carried out on a large set of ternary systems taken from DECHEMA and NIST.
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