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Simulation results show that the proposed method generates more accurate HRF estimates compared to existing methods.

To compare 2 methods of calculating residual stromal bed (RSB) thickness after repeat LASIK, to determine which method generates more conservative RSB thickness estimates, and to determine any factors related to the discrepancy between these 2 calculation methods.

Our LPS9 method generates more accurate phylogenetic reconstructions than the previously proposed 5-tuples strategy.

However, we chose to perform multilevel linear regression analyses, because this method generates more easily interpretable data.

In the same time the method generates more stable ordered feature lists in comparison with existing methods.

For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated.

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The results also show that the series method generate more accurate hybrid models and has a higher improvement percentage than the parallel method.

As can be appreciated from the results, our method generated more visually coherent appearances than the state-of-the-art techniques.

Although the this method generate more samples, a question still not answered is whether these new samples actually imply in greater representativity.

We can see as the number of samples increasing, both of the Column-Sampling and the Nyström method generate more accurate eigenvectors, and the accuracies of them are very close.

We conducted investigations using a movie ratings/tags dataset with a taxonomy of SAs extracted from WordNet and a restaurant ratings/reviews dataset with an expert-created taxonomy of SAs, which demonstrated that our method generated more accurate recommendations than previous methods.

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