The phrase "adaptive support" is correct and usable in written English.
It can be used in contexts where assistance or resources are tailored to meet the specific needs of an individual or situation.
Example: "The software provides adaptive support to users, adjusting its features based on their preferences and skill levels."
Alternatives: "customized assistance" or "tailored support".
Hwang (2014) specified the potential criteria for a smart learning environment as being context-aware, able to offer learners instant and adaptive support and adapt the learner interface and subject contents.
Hwang (2014) specified that the potential criteria of a smart learning environment include context-aware, able to offer instant and adaptive support to learners, and able to adapt the learner interface and subject contents.
The proposed method is based on the herein named Adaptive Census Transform that exploits adaptive support weights during the image transformation; the adaptively weighted sum of SADs is then used as the dissimilarity metric.
With adaptive support ventilation (ASV), a microprocessor-controlled mode of mechanical ventilation, the ventilator adapts tidal volume (VT) size based on the Otis least work of breathing formula.
This work develops an efficient reliability method which takes advantage of the Adaptive Support Vector Machine (ASVM) and the Monte Carlo Simulation (MCS).
Some ventilation techniques such as Adaptive Support Ventilation (ASV), Proportional Assist Ventilation (PAV), and Neurally Adjusted Ventilatory Assist (NAVA) are designed to address this problem.
The data mining approach uses an adaptive support vector regression (ASVR) technique; the benchmark model used is the MLR technique currently being used in the industry.
To evaluate adaptive support ventilation (ASV), an automatic microprocessor-controlled mode of mechanical ventilation, for the initial ventilatory management in consecutive patients eligible for early extubation after cardiac surgery.
In the second pass, the matching costs for different pixels are aggregated along the estimated disparity plane orientations using adaptive support weights, where the support weights of neighboring pixels are calculated using a combination of four terms: a spatial proximity term, a color similarity term, a disparity similarity term, and an occlusion handling term.
Our system exploits a novel cost aggregation approach called adaptive support weights method.
For this purpose, adaptive support weight (AW) algorithm was proposed to perform aggregation on the appropriate support.
