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After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions.
Several elements have been brought to the bulk of knowledge that supports the design and implementation of public-private partnership in the transport sector.
Using a case from the publishing industry, we illustrate how contextualized decision paths/traces provide a rich base of formal and informal knowledge that supports IPD teams.
This awareness provides key knowledge that supports space missions and includes the detection of conjunction events, the detection and characterisation of in-orbit fragmentations and the re-entry of risk objects.
ZOOMA classifies matches as 'Automatic' or 'Curation required' based on whether or not there is manually curated knowledge that supports the suggested matches.
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The CBR system presents a knowledge base that supports the cost estimation at the early stage of a construction project.
There are a limited number of CAD investigations on the nature of knowledge processing that supports the cognitive activities of universal design process.
Within this context, they are capable of acquiring a rich knowledge base that supports the acquisition of vocabulary and the use of higher order cognitive skills such as planning, predicting, and drawing inferences.
One of the seminal works addressing this concern was IBM's autonomic computing initiative [2], which introduced a layer implementing what is known as the MAPE-K control loop to monitor, analyze, plan, and execute adaptation (with a knowledge base that supports the different activities in the control loop) for the purpose of managing a target system.
We describe our 'conceptual categories', which are a method of knowledge representation that supports these flexibilities, and some new results on symbol systems, which leads to some new mathematical questions about what can be represented in formal systems and how they can be extended automatically.
The evaluation of data-use interventions and the communication of successful interventions build the knowledge base that supports future investments in interventions to strengthen data use.
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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