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This paper addresses the influence of the cM uncertainty on the predicted land settlement using a stochastic simulation approach where cM is regarded as a random variable and a large number of equally likely cM realizations are generated and implemented into a poroelastic finite element model.
We studied this by a simulation approach, where haplotypes from randomly drawn pairs of one male and one female from the population were combined into 100,000 offspring genotypes.
Instead, we employ a large-scale Monte-Carlo simulation approach where a model of the system is assessed thousands of times with parameter values that are randomly chosen from a large parameter space.
To more directly investigate the relationship between sequencing depth and transcriptome coverage, we performed a simulation approach where mRNA-Seq was the most cost effective strategy to equal a microarray in terms of total genes detected with a minimum of ~13.5 million reads needed.
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Then, the sensitivity of the inductor characterization to the model parameter variations is obtained through a simulation-based approach, where the Richardson extrapolation technique is used for the calculation of the partial derivatives.
The design process can benefit from a model-based and simulation-driven approach, where one starts from an abstract top-level model that is extended via stepwise refinements and design space exploration into a detailed and integrated systems model that can be physically realized.
Therefore, we design the simulation-based optimization approach where a simulator is combined with chaotic DE.
Virtual clinical simulation is an online educational approach where students use avatars to practice various skills.
The real propagation scenario shown in Figures 4 and 5 is translated into that shown in Figure 18 where the simulation approach followed is depicted.
Thus, whereas a deterministic simulation will not identify this rare event potassium outside the cell ends because it captures only average behaviors, the stochastic simulation approach may not capture traces where it happens, depending on the simulation time and on the number of simulated traces.
This paper presents a co-design approach where the co-simulation between hardware and software takes place early enough in the design cycle.
Write better and faster with AI suggestions while staying true to your unique style.
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