Sentence examples for tolerance to data from inspiring English sources

If we do this, then we find 16 edges connecting 13 vertices, as shown in Figure 4. We can use this approach more generally to construct networks that have a required level of tolerance to data uncertainty, omitting any edges that do not appear in at least q% of the bootstrap samples.

Yet again, these values are low, indicating that the topology of relevance networks is sensitive to uncertainty in the data (note that r and τ are not directly comparable, so it is difficult to compare the relative tolerance to data uncertainty of relevance networks and GGMs).

In addition to predictive capacity, other key characteristics for the clinical success of a predictive model, are simplicity and effectiveness of application, which include easy customization to local conditions and/or institutions, easy updating with new data, computational facility, tolerance to missing data and ability to provide supplementary clinical information.

However, SMT over-production does not increase tolerance to selenate (data not shown).

Tests on rhesus monkeys to evaluate the feasibility of the approach for an IPG used for brain stimulation evaluation show that the software upgrade can be implemented stably with good tolerance to the wireless data transmissions.

Our study provides additional evidence that mutation of MC1R contributes to an increased tolerance to thermal stimuli, similar to data presented by Mogil and colleagues [20].

To do so they will utilize organs-on-chips technology to compare how the microbiomes in human versus mouse guts influence tolerance to infection, and collect data using a pig infection model to identify and study tolerant individuals.

The remainder of this paper is organized as follows: Section Motivation and background presents the motivations related to the use of audio signals as carriers as well selecting some performance criteria used to assess hidden data tolerance to common signal manipulations.

The predominance of the M form over the S form in the study area is most likely associated with its higher tolerance to salinity (Costantini, unpublished data).

Its main advantage is that knowledge of the problem can be used to resolve the confusion caused by structural complexity, provide tolerance to noisy or missing data, and provide a means of labeling the recovered structures.

Many other bi-clustering algorithms, including Bimax and the recently described BiBiT (Rodriguez-Baena et al., 2011), discover only homogenous bi-clusters and have low tolerance to noise and missing data.