Sentence examples for we classify them from inspiring English sources

We classify them based on their computational capabilities.

We classify them differently if they are noise or ROIs.

We classify them into two categories: centralized approaches and decentralized approaches.

In Fig. 14, we classify them according to two categories: connected to the LCC and not connected to the LCC.

Once candidate queries are generated, we classify them to be recommended to the user by order of relevance.

We classify them into two categories whether there are Hispanic-dominated occupations or are not Hispanic-dominated occupations.

We classified them in order to provide them in a knowledge base, as they are used for scenario-based analyses that assess usability properties of mobile applications.

We classified them into four groups according to the nucleotide sequences of the Stx2 family; for example, group 1 (G1) contains VT2vha and group 2 (G2) contains VT2d-Ount.

Note that all test cases selected are quite complex and also perform read operations, but we classified them according to their main purpose.

We selected most relevant hashtags from this word frequency list, then, we classified them manually as following: Positive Trump: #MAGA, #makeamerikagreatagain and #voteTrump Negative Trump: #NeverTrump #dumptrump Positive Hillary: #imwithher, #strongertogether and #voteHillary Negative Hillary: #podestaemails, #NeverHillary and #crokeedHillary.

As long as they are not out of the labor force due to medical reasons or their mandatory military service, we classified them as "did not manage to find a job".