Sentence examples for models that handle from inspiring English sources

Each chip company makes some low-end models that handle certain tasks more slowly than their mainstream or top-of-line models.

An important prerequisite is the development of models that handle the fact that substitution properties change over time.

Some extensions of the classical approaches lead to models that handle genomes with unequal contents, but without duplicated markers, allowing rearrangements and indels.

Data centers are able to handle some of the heavy lifting when it comes to training the models that handle machine learning processes like image recognition as they don't necessarily have to worry about space (or partly heat, in the case of the TPU running with liquid cooling) constraints.

Toshiba also had two models that handle the conversion totally differently -- in fact, you can actually remove the screen from the laptop and have a separate, standalone tablet.

Models that handle heterotachy are thus of prime interest, particularly as larger and larger datasets are used [ 29].

Beyond these actions that can be automated, we have all the other actions of the FCAPS (Fault, Configuration, Accounting, Performance, Security) model that handle the overall management, for example, the configuration and activation actions of the QoS components, which generally are initialized by the architect according to SLA.

Instead, we must rely on a realistic battery model that handles at realtime simultaneous variable charge and discharge currents [48, 51].

In [27], Calafate et al. proposed a distributed admission control for MANET environments (DACME) model that handles multiconstrained real-time flows by periodically assessing end-to-end conditions on the path.

To cope with the complexity of the invasive species problem, we develop a mixed-integer programming (MIP) model that handles the problem as a full dynamic optimization model and solves it to optimality for the first time.

This research participates in solving the problem of assessing software quality by introducing a model that handles a fuzzy inference engine to mix both of the processes driven and application-driven quality assurance procedures.