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Although, both the approaches provided good outcome that certainly useful for traffic accident prediction, [9, 11, 12] reveals that heterogeneity in road accident data exists and should be removed prior to the analysis of road accident data.
These approaches provided good estimates of macroscopic moment curvature diagrams for both textures, by reproducing the orthotropy of flexural peak strength in relation with the texture geometry, the different shape of the post-peak response and the residual strength due to the orthotropic influence of the average vertical compression stress.
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The results show that these approaches provide good alternative approaches for the calculation of ground-state energy for a strongly confined helium atom.
When we compare the feature selection methods (CFS, IGRF and our three local search methods), we can see that our approaches provide good results compared to both CFS and IGRF ranking methods.
By comparing the results, we note that all the approaches provide good performance in the case of high SNR (15 and 10 dB) and the images are formed in a clean and dense way.
While those approaches provide good accuracy, they are also relatively bulky and expensive.
While gel-based approaches provide good separation and direct visualization of individual proteins, highly accurate LC-MS/MS analysis on protein digests extracted from gel spots leads to high-confidence identification of these proteins.
A numerical example demonstrates that this approach provides good performance.
As a result, such a contour-based approach provides good (i.e., reasonable) reconstruction quality at low cost.
This approach provides good estimations for large noise cases, but it can overestimate the noise in small noise cases.
This approach provides good results but is not useful for a low-complexity and low-cost realization since it requires an extra analog feedback network.
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