Sentence examples for incrementally adapting from inspiring English sources

Exact(1)

Just as Carl Sandburg's fog came in on little cat feet, we should worry that because we are incrementally adapting to the effects of climate change, we are failing fully to recognize what a monumental crisis this portends for younger generations and how it affects children now.

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In the MLLR-based model adaptation, we adopted the unsupervised adaptation method where the acoustic mean models were incrementally adapted with each test utterance.

It incrementally adapts, merges and splits segments along a sequence based on the coherence of motion information within each segment.

Major new complexities present interesting and challenging project management issues and many agencies have incrementally adapted the project development process to improve efficiencies.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to employ a density‐based clustering approach that can incrementally adapts the number of clusters (i.e., the number of unique physical locations) in our system.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to use a density-based clustering approach that can incrementally adapts the number of clusters (i.e., the number of distinct physical locations).

They rely on fuzzy systems model architecture and are able to incrementally adapt themselves during the on-line process, resolving dynamic process changes which may appear on-line over time due to long-term fluctuations (e.g., caused by dirt) and changes in the composition of the educt, often leading to severe error drifts of static models.

Training duration and intensity were incrementally adapted to the individual anaerobic threshold (IAT) (between 70 and 100%) as monitored by heart rate.

Rather, we suspect evidence from a previous study about how remote health services incrementally adapt over time, in relation to their context, might be relevant [ 42].

The proposed method utilizes global information about each class of training sample space and can generate RBF hidden neurons incrementally to adapt the sample space.

As ILRBF-BP utilizes global information about each class of training sample space, it can generate RBF hidden neurons incrementally to adapt the sample space, and the hybrid RBF-BP network architecture improves the network performance further.

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