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The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists.In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models.
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Compared to other TEG models, the tuning and validation process of the proposed model is more complete.
For position tuning (Figure 3, bottom four rows), the more expressive quadratic model captures the tuning patterns better than the linear model.
For CFD applications it is unclear how detailed the clinical data needs to be in terms of geometry (segmented from medical images) and parameterisation (variability described by the model and the tuning of patient-specific boundary conditions).
More recently, WAM has been tuned to model the ionospheric scintillations also over the equatorial latitudes.
The large difference in accuracy (around 2.3 dB) showed the benefit of modeling tuning relationships across multiple time offsets, though much of this improvement is also captured by data-fitted movement models.
We then constructed mixed effect models on the tune proportion for each sentence/question type.
Same as [ 4], in each round, 4 folds are used for training the model and tuning the parameters according to AUC.
Since the importance weights are updated by the discrepancy between the neural firings and the tuning model, a well-defined tuning model is necessary to an accurate estimation of posterior density.
The last one was used as the model tuning parameter and the others were predicted applying existing experimental correlations.
Changing these parameters might probably improve the prediction accuracy in the model tuning phase, but it is more likely that the resulting model would be too specific for a specific building (type), something we try to avoid in this research.
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