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The startup is working with 20 law firms to simulate workflow examples and test results with human feedback.
Moreover, they are also available, along with several other ChEMBL-related workflow examples, in the KNIME EXAMPLES public server, which is accessible directly via the KNIME desktop.
In this paper, we demonstrated Python- and R-based workflow examples.
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Consider the valid mapping options shown in Figure7 for the running medical workflow example.
All possible valid workflow deployments – as defined by W – for the running medical workflow example are shown in Figure4.
Of course, there is a danger that all valid options depend on the availability of one particular cloud (as in the running medical workflow example).
The paper shows how a cost model can be introduced to rank the valid options; a model based on price is defined, and applied to the running medical workflow example.
For the running medical workflow example, adding the rule that d0 and d4 in Figure1 must be deployed on different clouds results in only allowing the single partitioning option shown in Figure10.
This has demonstrated that the need for inter-cloud data transfers raises interesting potential security violations that need to be addressed; in the running medical workflow example, this ruled out over half of the possible partitioning options.
Whilst this work is ongoing, even in its current form the method can illuminate dependability issues; for example, analysing the set of valid options can highlight the dependency of the workflow on a specific cloud (as in the running medical workflow example).
Workflow example using PFOA to identify candidates for follow-up.
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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