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Secondly, we integrate advisory agents as in the example of sections "Competency referencing of learning scenario components" and "Recommendations based on competency comparison" to recommend adapted activities and resources to individual learners, whatever their subgroup.
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An illustration of this property is given in the example of Section 7.2.
(The role of these matrices is illustrated in the numerical example of Section 4).
However, Theorems A.1 and A.2 cannot be applied to the example of Section 3.
Some important aspects of the meaning of the SR-5 rule are discussed in the second example of Section 2.3.
In the next example, we have two inputs and two outputs, as in the first example of Section 7.1.
The next two functions on Figure 10 represent the two methods of adaptation employed in the example of section "Personalization of massive open online courses".
In the example of section "Personalization of massive open online courses", we presented three main options that we generalize in the design sub-process of Figure 11.
The important differentiating feature from the previous example of Section 7.1 is that the singular term for the transfer function of this network is nontrivial.
Going back to the cyclone example of Section 6.2, it might be interesting to link a particular portion of the report to only a portion of a related document where the latter might contain more than required.
Under this scenario, the channel realization is immaterial and the minimum expected time to empty the queues is 3 sec (slots), i.e., equal to the result of the static network example of Section III.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com