Sentence examples for accommodate settings from inspiring English sources

The phrase "accommodate settings" is correct and usable in written English.
It can be used when referring to the ability to adjust or modify settings to meet specific needs or preferences.
Example: "The software is designed to accommodate settings for various user preferences, ensuring a personalized experience."
Alternatives: "adjust settings" or "modify configurations".

Exact(2)

Small tables cannot comfortably accommodate settings for parties of four.

Model (1) can be modified to accommodate settings with error-prone covariates as well.

Similar(58)

And bars, from front to back, are wider, to accommodate table settings.

The array is multiplexed into eight parallel outputs and features eight selectable gain settings to accommodate various background levels, auto-zero for better input uniformity, and sample-and-hold circuitry.

The latter could observe how different groups of staff interact with patients in various settings across the organisation to help identify how to introduce or modify the 5 moments in hand hygiene to accommodate the different settings and interactions: We need a solution as to how we might come up with hand hygiene model that keeps the patients safe and that suits these situations.

Best of all, a wide variety of realism settings accommodate everyone from lifelong New Yorkers who don't drive in real life to aspiring Andrettis.

As it points out in the blurb, most dishwasher baskets are still designed to accommodate 1970s place settings, which is why they can seem irritatingly inflexible today.

Four different arm press settings accommodate variations in range of motion and exercise preferences, approximating the specificity of a free-weight workout while providing protection from injury.

To accommodate the different settings (THR versus TKR) and perspectives (SHI versus hospital), four modifications of the model were run.

Their main advantage over alternative methods is that they provide estimates of predictive uncertainty and can accommodate unbalanced diagnostic settings or variations in disease prevalence, which are crucial for clinical applications [Hahn et al., 2012].

Our goal was to examine the selected decision trees for predicting insulin resistance to accommodate different clinical/research settings where values for all variables would not necessarily be available.

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