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The best results have been obtained when combining the information from all the sensors.
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Better results were obtained when combining gene lists from two datasets (RNAi screen plus microarray) prior to analysis.
Moreover, free-flowing compositions with a suitable working time were obtained when combining H3PO4+MAP solutions as main binders.
However, promising results are obtained when combining SVM with the VNS-based feature selection method.
By this, our best results were obtained when combining the proposed front-end technologies with the DNN-HMM.
By contrast, the ensembles exhibiting the highest predictive power on the test set were obtained when combining models with high and low predictive ability.
Good results were obtained when combining the SE algorithm with auditory modulation features and BN processing for SGMM-HMM, as well as the modified auditory modulation features for DNN-HMM.
At f d =50 Hz, the best performance is obtained when combining APCDQ with QBC for M u,i =2, and with dominant subspace QBC and k=3 for M u,i =4.
For the combination of speech enhancement with deep learning (either in the hybrid model or when using BN features as an intermediate representation), the baseline was not improved on average, and no significant improvements were obtained when combining the speech enhancement with auditory features for SimData of the REVERB challenge.
Similar results were obtained when combining mericitabine 35 with entry inhibitors (CIs of 0.18 0.68 at IC90; figure 1C and online supplementary table S1).
Synergistic effects were obtained when combining mild heat (55°C) with one or both essential oil compounds, leading to inactivation kinetics values three to four times lower than when using heat alone.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com