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As the simulation moves forward, LFU's performance steadily increases.
In this paper, we illustrate a Mobile Wireless Vehicular Environment Simulation (MoVES) framework for the parallel and distributed simulation of vehicular wireless ad hoc networks (VANETs).
The simulation moves incrementally towards the new location whilst seeking targets within detection radius, r.
The MCMC simulation moves forward in time through the determination of transition probabilities which, in turn, determine the amount of time that elapses between events.
From a common starting point, each simulation moves fairly rapidly to a different region of the plane, where it largely remains.
Time in the simulation moves forward by retrieving the next simulation event from the priority queue each time the previous event – a cell division and ensuing displacement events or a cell leaving the cycle – has been processed.
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Sensitivity analyses were conducted to determine how the life expectancy, QALYs, employment rates, working hours missed plus turnover costs and medical care costs change when the distribution of stage at diagnosis in the simulation model moves from the most "pessimistic" one (i.e., least benefit due to mammography) to the most "optimistic" one (i.e., greatest effect of mammography on stage).
First, the orangutans in this simulation moved randomly, which wild orangutans are unlikely to do.
At the highest error rate and under the parameters of this simulation, moving from a per-allele depth of 10× to 20× gains 14,000 additional loci, whereas moving from 20× to 40×, which also doubles sequencing cost, nets only an additional 2400 loci.
Each node in the network simulation represents one vehicle of the mobility simulations, moving according to the represented vehicles movement history in the trace file.
Using this framework, one then establishes the connection with experiments and detailed all-atom simulations, moving toward a fully quantitative theory for protein folding.
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