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Then add t to the trajectory of mobile sensor s.
For any two POIs p i, p j, there is an edge between p i and p j (i.e., (p i,p j ) ∈ Estart), and w((p i, p j )) = d(p i, p j ); for any start position of mobile sensor s i and any POI p j, there must be an edge (s i, p j ) between s i and p j (i.e., (s i, p j ) ∈ Estart), and w((s i, p j )) = d(s i, p j ).
Fcover, Fdegree, and Fobstacle are used to calculate the total virtual force F that mobile sensor S i takes during the unit time, which is expressed in Equation (4).
Similar(57)
We denote the set of mobile sensors as S = { s 1, …, s k } and the set of POIs as P = { p 1, …, p m }.
(2) Select the shortest edge e t s in G where s is the start position of a mobile sensor and t is a POI.
We then consider the next sensor, s 7. Suppose the mobile charger has no enough energy to recharge s 7. We use Eq. (5) to select a sensor to ignore in this cycle.
C = { c 1, c 2, …, c k }, c i is the i th mobile sensor's trajectory.
For each mobile sensor's determined start position, we always choose the POI that can minimize the length difference between the maximal and minimal trajectories of mobile sensors.
Since the mobile sensor's mission within the pipeline does not last for a long time, the power limitation does not affect such achievement.
The use of mobile sensor platforms to monitor an athlete's performance is well reported.
From a user, MSNS receives the information on the number of mobile sensor nodes, connectivity degree, sensor node's sensing range, communication range, and supersonic wave range.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com