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In the third phase, we need to select supporters (added into S2) from red sensors to dominate all yellow sensors.
It sounds too good to be true, but the thermometer uses 16 infra red sensors to take 4,000 measurements and make an accurate measurement.
We need n steps to pick out red sensors (added into RD) and yellow sensors (added into YL) from V. Algorithm 3 executes at most |YL| iterations.
If more than one red sensors have the same number of the yellow neighbors, then the algorithm selects the red sensor with the highest ID.
Last, each blue sensor u deletes red sensors from the set N2 u) and deletes yellow sensors from the set N u).
Researchers are currently studying a group of patients with knee injuries who are each fitted with infra red sensors - similar to ones used to create special effects - before taking to the treadmill.
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In each iteration, we select a red sensor s∈RD with the maximum number of yellow sensors in N s).
The algorithm repeats the following steps, until the condition YL=∅ is satisfied: Select a red sensor s∈V with the maximum number of yellow neighbors Sensor s is marked green and its yellow neighbors in N s)∩YL are marked red Delete sensors of N s)∩YL from YL. Select a red sensor s∈V with the maximum number of yellow neighbors.
According to Algorithm 3, when a red sensor v is marked green, all yellow neighbors of v are dominated by v.
We obtain an independent set S1 that is composed of black sensors and any red sensor is definitely dominated by a black sensor and any yellow sensor has two hops distance from a black sensor.
We demonstrate that the transcriptional output is proportional to the intensity of green light applied and that the green sensor is orthogonal to the red sensor at intensities of 532-nm light less than 0.01 W/m2.
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