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Methods are needed to improve accuracy and completeness of the problem list.
These results are discussed within a systems approach framework to help us assess the completeness of the problem representations of the subjects, their awareness of critical events, and how these events would collectively contribute to the occurrence of error.
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Let us recall that this confirms the NP-completeness of the problem.
Because of the NP-completeness of the problem, we present two corresponding 2-approximation algorithms for the two problems.
This algorithm is still exponential due to the NP-completeness of the problem but is faster than the Ullman one in practice.
The reductions required to show the completeness of these problems typically require the construction of what has come to be known as a gadget – i.e. a constituent of an instance of one problem which can be used to simulate a constituent of an instance of a different problem.
A major result is the NP-completeness of this problem, to be contrasted with the minimization of the number of servers, which has polynomial complexity.
However, due to the NP-completeness of this problem, it requires a considerable amount of time to obtain the solution, making it practically intractable for large-scale networks.
To prove the NP-completeness of the CORP problem, it suffices to prove that the decision problem CORP-D is NP-complete.
First the #P-completeness of this problem was proven.
We show the NP-completeness of this problem for planar graphs.
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CEO of Professional Science Editing for Scientists @ prosciediting.com