However, in order to exploit more information for improved estimation results, it is often advantageous to employ error concealment using reliability information on a bit level as in [19,26].
EXCELLENT improved considerably the selectiveness, with some overhead, and became clearly advantageous for large error rates and not too small threshold p. This happened in all datasets, with clearer effect on the MC58 and CFTR datasets.
The authors suggest that the rapidity of such a boundary extension error is advantageous rather than harmful; it shows how the visual system incorporates fleeting views of images with spurious boundaries into a coherent representation of the world around us.
Moreover, we also found that our second additional filtration condition considerably improves the selectiveness, with some time overhead, and becomes clearly advantageous mostly for large error rates.
It would be advantageous to estimate recall error in populations using these and similar methods, as this would improve the precision of model selection.
Results show that it may be advantageous to determine the extrapolated error to cell size/time step zero instead of assuming that it is zero, especially when it is hard to determine the asymptotic order of grid convergence.
This method is potentially advantageous because it provides Bayesian error bars for the estimates, and is based on integrating over the posterior distribution instead of maximizing it and has some advantages in terms of how much sparsity can be enforced.
Trial and error could be advantageous because professional advice can be tested and adapted to fit with parents' own understanding of their child's diabetes.
Paradoxically, such errors can generate advantageous phenotypic diversity in fungi and bacteria through poorly understood molecular processes.
These high error rates are also advantageous to the virus, as they drive rapid adaptation to changing environmental landscapes, such as transmission to a new host or an emerging immune escape variant [ 16, 17].
In advance of a computational model updating or an error localisation, it can be advantageous to make a preparatory error localisation using data from a nominal analytical model.
