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The optimization step aims to identify an optimal setup of sample assignments from multiple candidates.
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On this basis feasible utilisation strategies are identified for particular types of biomass within the region of interest, as well as their relative contributions, in an optimal setup for biomass use in the region.
However, for other instances where the collection of samples is unbalanced and/or incomplete, an optimization step is needed to create a more optimal setup of sample assignment.
Specifically, OSTA is developed to address one practical issue in genomics studies – when the available experimental samples ready to be profiled in the genomics instruments are collected, how should one allocate these samples to different batches in a proper way to achieve an optimal setup minimizing the impact of batch effects at the genomic profiling stage?
Results for the number of required observations compared to an optimal setup with 100 observations are shown for several variations of the true parameters b and e in Table 2.
An optimal setup for testing the performance of Snort has been suggested in a number of references [34, 35].
The optimal setup of this FIB created SIL is demonstrated and provides an improvement in resolution by a factor of 1.8.
Therefore, it is necessary to find the optimal setup of measurement to minimize the number of unobservable paths.
However, the interaction and optimal setup of UEP FEC codes at the AL and the PL have not been previously investigated.
When the L-method is used, the optimal setup only consists of 23 stations.
Briefly, using the double-loop cross-validation setup described before, we used the inner cross-validation loop to determine an optimal set of features.
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