Sentence examples for leverage the detection from inspiring English sources

They represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.

The maps represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.

The CNVR-maps represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.

Our approach is to leverage the botnet detection work carried out by some organizations to easily locate collaborating bots elsewhere.

Second, our LSPR device is capable of leveraging the LSPR detection for rapid quantification of small-sized, physiologically relevant cytokines.

Taking advantage of this powerful new capability, we and others have developed novel strategies to leverage RNA-Seq for the detection of sample-specific protein variations [ 4– 11].

Thus, if a heteroscedastic time series with leverage effect is contaminated by a large single outlier, the detection of genuine leverage effect will be difficult, as it was the detection of genuine heteroscedasticity; see Carnero et al.

Emergence: stresses the detection and leveraging of the collective wisdom of the community (Frappaolo et al. [2008]).

9 Social: dimension emphasizes the importance of incorporation of the transparency (to access), diversity (in content and community members), and openness (to structure) as the core cultural values in the Enterprise 2.0 environment (Frappaolo et al. [2008]).   10 Emergence: stresses the detection and leveraging of the collective wisdom of the community (Frappaolo et al. [2008]).  .

We show that k large consecutive outliers bias such correlations towards zero for (hge k), rendering the detection of genuine leverage effect difficult.

In order to show how the potential outliers can mislead the detection of the leverage effect, as measured by the cross-correlations between past and squared returns, we use a rolling window scheme, where the sample size used to compute the cross-correlations is (T=1000).