Sentence examples for knowledge about the expected from inspiring English sources

Exact(18)

As can be seen, in general, defining an adequate set of rules is non-trivial and presumes prior knowledge about the expected architecture.

Reasonable diligence would furthermore include the duty to consider information in the press, data published by consumer organizations, news about article recalls due to SVHCs, or knowledge about the expected presence of SVHCs in a certain article group or material.

Afterwards, based on knowledge about the expected uptime of the available link or the buffer status of the next hop, the fragmentation module determines which bundles will be entirely transferred and which bundles may be fragmented.

A different approach is taken in discrete tomography, in which objects that consist of a limited number of materials can be accurately reconstructed by exploiting prior knowledge about the expected materials [13].

They take into account the available prior knowledge about the expected characteristics of the pansharpened image, modeled in the so-called prior distribution p z), to determine the posterior probability distribution p z|y, x) by using Bayes law, p ( z | y, x ) = p ( y, x | z ) p ( z ) p ( y, x ), (8).

Prior distributions represent the prior knowledge about the expected number of genes that may be implicated with the trait and therefore correct for multiple comparisons.

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Similar(42)

In other words, we don't gain knowledge about the weather as expected.

In this step, awareness is developed and shared and implicit knowledge (about expectations, values, expected developments over time) is made explicit.

At this point, and due to the vague information about the expected performance (usually described qualitatively), customers need to have more knowledge about these performances.

The reader has at least knowledge about independence, expected values and variances and also basic definitions of stochastic, that is necessary to read articles in this field [16].

Second, it is a seedless and non-supervised method which does not require prior knowledge about expected number of clusters.

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