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To determine the specificity of the proposed method, a set of extract of blank milk samples (n = 20) were injected into the chromatographic system on the same day.
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The outcome was a set of extracted signal features correlated with the consumed tool life percentage.
In this context, we use the ELECTRE TRI method, considering a set of extracted rules as the alternatives and support, confidence and lift as the criteria.
We conclude that the application of multi-criteria decision analysis to a set of extracted rules can contribute to solving the problem that arises when using traditional algorithms, in terms of redundancy and a lack of interesting rules.
To solve such problem, we proposed an approach that use a set of extracted rules and quality measurement within the multi-criteria analysis process to make correspondent recommendations of relevant rules.
The result of the reasoning process is a set of extracted metadata used for learning services discovery and adaptation based on system-centric context (i.e. device and environment context) and learner-centric context (i.e. learner and activity context).
Besides those two trivial approaches, the challenge is to balance precision and recall keeping a set of extracted terms with most, ideally all, relevant terms and very few, or ideally none, irrelevant terms.
As shown in the experiment results, when applying Apriori algorithm or its derivatives on a dataset, we obtained 27 extracted rules, and when applying multi-criteria analysis approach on a set of extracted rules, we obtained only six significant and interesting rules.
The objective image quality metrics are classified in three groups: full reference (there exists an original image with which the distorted image is to be compared), no-reference or "blind" quality assessment and reduced-reference quality assessment (the reference image is only partially available, in the form of a set of extracted features).
In addition, by applying multi-criteria analysis approach combined with multi-agent system, we reduce a set of extracted rules, then we eliminate the redundant rules, and the most important is the automation of rules extraction process using multi-agent system.
This subseries contains a set of annual reports (1892-1962) bound into seven volumes, and a set of extracts from these reports (1893-1985) in five volumes.
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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