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Quantitative results show that utilizing spectral similarity helps binary decision making in overlapped time-frequency regions and significantly improves separation performance.
There is a certain amount of binary decision making by the human - BPM, rhythm, key, mood, instrumentation - and then the AI generates possibilities.
From a statistical viewpoint the binary decision making process has a lot of appeal.
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The binary decisions made by all sensing nodes are reported to an AP in the local area network (LAN) or networks.
The optimal trajectory design problem is formulated as a multiphase mixed integer optimal control problem, which is converted into a mixed integer non-linear program by first making the unknown switching times part of the state, then applying a Hermite Simpson direct collocation method, and finally introducing binary variables to model the decision making.
Further support for NFATc2 dephosphorylation as the decision making step for binary IL-2 expression is coming from the hypotheses from Okamura et al. [24].
With segmentation, a binary decision is made as to whether a voxel or a part of it belongs to a certain structure.
A class of binary decision-making tasks called the two-alternative forced-choice task has been used extensively in psychology and behavioral economics experiments to investigate human decision making.
Binaries are the enemy of clear understanding and sound decision making.
This represents more effective and appropriate patient selection in comparison to target driven or binary decision-making based on licensing criteria alone.
Clinical applicability of a continuous variable has limitations in a binary decision-making process like acceptance or rejection of a kidney (if there is not a cutoff).
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