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Alarm identification refers to selecting a set of measurements to be configured to the alarm system.
In an earlier paper, we described an approach for selecting a set of focal species.
Further close investigation and comparisons are made by selecting a set of hotspots.
The next step is selecting a set of high-risk zones (i.e., the hotspots).
However, selecting a set of appropriate values of those parameters is generally problem dependent.
Build a cluster (mathfrak{C}) by selecting a set of nearby nodes (clinics) at random.
We propose a novel method to facilitate biologists in selecting a set of suitable housekeeping genes for inter-sample normalization.
Criteria in selecting a set of hotspots may vary across studies, as there is no any universal rule of selection.
It requires selecting a set of states, associating a motion command with every state, and synthesizing functions to recognize state achievement.
The developed damage model was combined with a 'cycle jump' technique to reduce the computational time based on selecting a set of loading cycles.
The iterative procedure consists of selecting a set of models based on the history matching quality (normalized misfit) to generate histograms.
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