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Scholars discussed ICT-based application classification in road transport.
The off-line application classification in terms of Wi-Fi and CPU needs.
This classifier is applied to a challenging novel application: classification of archaeological ceramics.
User needs-based optimization component (UNOC): based on user actions and application classification.
But this two-state application classification (sensitive and non-sensitive) decreases the dynamicity and flexibility of bandwidth allocation.
This phase is composed of: The off-line application classification in terms of Wi-Fi and CPU needs.
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In this section, for each user, we present the prediction application scenario and the applications classification.
Sequences in green represent background processes, in colors, foreground process Table 5 Applications classification for CPU need Apps CPU application class Usr1 Usr2 Usr3 Usr4 Usr5 Usr6 Firefox M L Skype L Chrome L M Spotify L L VLC L L 2048 H M M Sudoku L L L Foxit L L OneNote L048 H M M Sudoku L L L Firefox M L Skype L Chrome L M Spotify L L VLC L L 2048 H M M Sudoku L L L Foxit L L OneNote L
With its several bioinformatics applications, classification based on radial basis function network has been extensively adopted to predict factors such as the cleavage sites in proteins [23], inter-residue contacts [24], protein disorder [25], discrimination of β-barrel proteins [15], and identification of O-linked glycosylation [26].
These applications' classifications and data requirements and sensitivities are discussed in this section.
Specifically, this paper reviews synchrophasor applications' classifications and data requirements, and points out that it is necessary to formalize a set of consistent and quantifiable data quality requirements for synchrophasor applications.
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