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Accident analysis is used in a data model to represent uncertain knowledge and to perform reasoning.
Bayesian Networks are models which capture uncertainties in terms of probabilities that can be used to perform reasoning under uncertainty.
In many cases, the fact that an intelligent system needs to perform reasoning on-line contributes to the difficulty of this reasoning.
As Semantic Web technologies are mainly based on Description Logics, their application to data stream processing also offers new opportunities to perform reasoning tasks over continuously and rapidly changing flows of information.
Create computational models of contexts pertaining to the citizen and urban system (energy, traffic, transport, building, mobility, healthcare, utility, etc). in a way that allows software agents/systems to perform reasoning and manipulation.
The whole process involves the following steps: 1. Create computational models of contexts pertaining to the citizen and urban system (energy, traffic, transport, building, mobility, healthcare, utility, etc). in a way that allows software agents/systems to perform reasoning and manipulation 2.
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The system performs reasoning under uncertainty and presents to users corrective actions, with explanations of the root causes.
With regards to the effect of L1 on learners' reasoning, analyzing data showed that the learners employed the L2 mainly while reading and for repetitions of parts of the questions, proper names, etc., while they were performing reasoning tasks.
OWL ontologies may also act as a vocabulary of terms for defining RDF triples; SPARQL-based continuous query languages, as a way of querying RDF streams and performing reasoning tasks by combining them with the static background knowledge.
We describe a semantic data validation tool that is capable of observing incoming real-time sensor data and performing reasoning against a set of rules specific to the scientific domain to which the data belongs.
This way the whole cache will eventually be updated, either by performing reasoning or because flagged entries are replaced by new entries.
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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