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Cases are explored that describe non-market collective action strategies.
Alternate model cases are explored, each offering a unique treatment of extinction and reignition.
These cases are explored and the reasons underlying the inconsistent performance of automatic topic identification are investigated with statistical analysis and experimental design techniques.
Two experimental cases are explored here, one with 200 initial training ensemble members in the SVM training phase while the other with 1000 initial training ensemble members.
The Yin and Yang of TGF-β1 in both cases are explored below.
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Information of the global load displacement profile, traction stiffness, and cohesive zone length induced by the three zone cases was explored.
The use cases being explored by enterprises involve reducing reconciliation processes, improving network security, and automating workflows.
Two cases were explored within each scenario described above: an extreme case in which all seven passengers seated in a row were sick and a case in which only one seated passenger was sick.
Moreover, all discordant cases were explored by these additional techniques.
Patterns in the data were identified and deviant cases were explored.
Deviant cases were explored and an audit trail maintained to track development of ideas.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com