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When researchers plot on a graph how many patients remain alive over time, the curves tend to drop to near zero for metastatic cancer.
Fig. 6 Number of nodes alive over time.
Fig. 11 Number of nodes alive over time [d = 100 m].
The biggest challenge in maintaining your network is not meeting people but keeping contacts alive over time.
To that end, the performance evaluation metrics include the number of transmissions, energy consumption, and the number of nodes alive over time.
In this subsection, we set the number of sensor nodes to 200, and the initial of each node is 0.5 J. Figure 6 shows the number of nodes alive over time for all compared algorithms.
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"The evidence really tends to exclude the idea that they entered the chamber one at a time, alive, over some time, because we have infants, small children, and very old adults who would almost certainly not have managed to get into this chamber without being deposited there".
"People change over time.
We compare our algorithms with HEED algorithm from four respects: the number of rounds until the first node dies, the number of alive sensor nodes over time, the evolution of the remaining energy in the network, and the impact of the initial energy quantity on the performance.
It was designed as a population-based individual patient-level simulation model with annual time cycles simulating transitions between two Markov states (alive and dead) over time (see Figure 1).
For the first scenario, when the sensor field size is 100 × 100 m2 with d = 100 m and containing 50 randomly deployed sensor nodes, Fig. 11 plots the number of nodes remaining alive over the simulation time.
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CEO of Professional Science Editing for Scientists @ prosciediting.com