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The workflow engine technology implementation described above can be implemented at other institutions.
This code is inspired by the implementation described in.
n-ary relationships can be realized in a straightforward fashion mirroring the logical implementation described in the Section [5.5].
However, with the task parallel implementation described here we achieve 60 100% of theoretical speedup within a shared memory node, and 80 100% of linear speedup across nodes.
The adaptation layer implementation described here mainly consists in using triggers to emulate contact opportunities.
Also, messages are persistent to reuse their skeleton, as in the implementation described in Section 8.
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Our theory and implementation describe how humans use past behavior and untapped alternatives to build a model of characters' motives and constraints.
Our implementation describes the potential of failure already in the parser's return type.
CMIM was implemented as follows, with alternate implementations described by Fleuret [ 18].
Future refinement of the basic implementations described here can further increase the speedup obtained when using ESAC.
We therefore tested whether the implementations described in this paper improved this validation.
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