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In Fig. 3, these ideal benchmarks are compared to the NLMS algorithm using different constant values of the normalized step-size, α, and regularization parameter, δ; the input signal is a white Gaussian noise.
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However, when more specific benchmarks were compared statistically significant differences did appear in the health & safety and professional development areas.
Most of the widely used MSA benchmarks were compared in [21] and are also discussed in [31].
To assess which of these benchmarks shown the maximum information at the interactome level for breast cancer risk, we calculated the probability of showing similar proportions of annotations in the giant component and, to avoid functional bias, used as controls seed proteins with the same annotations at Level 3 as each of the benchmarks being compared.
Results from modelling using a priori parameter values from literature as a benchmark are compared.
Let (sigma) represent the score of the model being benchmarked and (sigma _r) the score of the reference model (to which the model being benchmarked is compared).
Benchmark solutions are compared with earlier computations using the finite element method, showing excellent agreement.
To validate gridless DSMC, results of several benchmark simulations are compared to results from a fixed-grid code.
The numerical results obtained using the Lagrangian approaches for the benchmark test are compared with existing experimental and numerical results.
The numerical results of the IA on two benchmark tests are compared with experimental and other numerical results.
These benchmark protocols are compared with the SIF and polynomial protocols, considering a vehicle spatial distribution characterized by a Poisson distribution with parameter ρ s z = 16veh.
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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