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The parameters needed by our framework are managed via a web-based interface, which configures each EE.
In others words, achieving the maximum throughput in the HetNet is possible as long as the deployment guidelines provided by our framework are applied.
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Applications in our framework are described by documents called application manifests, which define: The services involved in the composition (which can be specific or generic) and their description.
In other words, return migration in our framework is driven by the comparison between savings and remittances and by the feedback effect.
In addition, our framework is initialized by setting,, and.
Our framework is informed by perspectives that seek to understand collective activity from a sense-making perspective.
The versatility of our framework is demonstrated by devising improved approximation algorithms also for other related problems.
Our framework is implemented by extending the Java RMI stub to allow custom designs for streaming buffers and controls, and by providing a continuous buffer for raw data in the transport layer socket.
Our framework is illustrated by a model of the T1D risks associated with polymorphic markers located in the HLA region of chromosome 6 in the Finnish population.
Our framework is supported by a similar strategies used to enhance participation of Maori people in a cardiovascular-based RCT in New Zealand.
Our framework was motivated by the idea that larger reference datasets should make imputation faster and simpler, rather than slower and more complicated.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com