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As displayed from Tables 2 and 3 that the proposed approach produced very good experimental results for predicting SIPs, owing to the correct choice of classifiers and feature extraction methods.
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Experiment shows that our approach produces very robust results for the estimated 3D pose, and maintain very low false positive rate.
The approach produces very high quality surfaces with predictable, intuitive behavior, while generating, where possible, simple shapes, such as cylinders, spheres, or tori which are commonly used in geometric modeling.
Compared with other methods that have been developed for classification of arrhythmias with this same database, the proposed approach produces very good results, because the entire database was used.
Although this approach produces very high force sensitivity in directions that are perpendicular to the tool shaft (lateral directions), the axial rigidity of both the tool and fibers makes achieving high axial force sensitivity with FBG sensors a challenging problem.
Nevertheless, it is clear that the two approaches produced very similar results.
These two approaches produced very different results, Thiede notes, when the researchers applied them to the census data.
All approaches produced very similar results.
Both approaches produced very similar activation barriers (Fig. 10).
Some of the differences observed may reflect differences in experimental conditions; however, overall the two approaches produced very similar results.
For these reasons, although these approaches produced very interesting results for specific tasks, they are not easily applicable to the task of generating general global classifications of reactions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com