Example collocations logo

Simulations in sentence

70 examples of Simulations in a sentence

Extremely high-speed computer simulations of turbulent flows could help us identify patterns that could lead to a theory that organizes and unifies predictions across different situations.
The best we could do were simulations like this in supercomputers, but even here you see this ring of light, which is the orbit of photons.
Practicing simulations is a sort of safe testing ground for improving adaptability.
I'm talking about not individual little simulations but a massive possibility of huge networks of interaction.
So what I do is I use computer simulations in order to analyze but also to predict the behavior of these storms when they're just born at the Sun.
We've done massive suites of computer simulations, massive months of analytic calculations and here's what I can tell you so far.
We can run these simulations.
That means that as astrophysicists, we have to rely on sophisticated computer simulations in order to understand these complex phenomena.
These simulations can be used to really understand how gas behaves under such extreme conditions.
I'm about to show you one of those simulations.
And we're showing that we can actually turn this data into working models and simulations of brain regions.
We use CAT scans, we use isotopes, we use genomes, we use robots, we use mathematical simulations and all kinds of analytics.
And I worked with Mehta Vihar who creates virtual simulations for the army for tactical practice.
We make assumptions, translate them into equations, run simulations, all to answer the question: In a world where my assumptions are true, what do I expect to see? It's a pretty simple conceptual framework.
Though this could have be interesting without the heavy religious browbeating, as a whole the plodding movie makes one gag, the acting is horrible and the obviously computer-generated simulations are very fake looking.
In these simulations, there are tons of robots with whom you can interact.
Given that realistic neurosurgical simulations, which must account for a large number of variables and potential outcomes, are particularly difficult to develop, virtual reality is not yet being used widely in the field.
As these simulations become more realistic, their training value will increase.
One can imagine, for example, the Fed adopting an “optimal control” method, whereby monetary-policy settings are established by running multiple simulations of a macroeconomic model using different combinations of interest rates and balance-sheet tools to project future inflation and unemployment.
Comparing the outcomes of these two simulations suggests that large export flows of Palestinian labor to Israel reduce the capacity of the Palestinian economy to export goods by putting upward pressure on wages, undermining competitiveness.
These simulations also suggested that continued reliance on the export of labor results in a lower growth potential for the Palestinian economy than does a development strategy based on exporting goods.
Our simulations indicate that a non-discriminatory trade regime would magnify the potential positive impact of depreciation in the real exchange rate (as a result of the reduction in wages) on Palestinian GDP.
The paradigm has become so universally accepted – and the model simulations underpinning central banks’ decisions have become so complex – that few are willing to question it.
While the voluntary obligations contained in the Paris agreement are important, what is really needed is legally binding commitments (based, of course, on scientific calculations, modeling, and simulations).
Manufacturing is already an intensive user of “big data” – the use of massive data sets to discover new patterns, perform simulations, and manage complex systems in real-time.
By enabling more sophisticated simulations that discover glitches at an early stage, big data has helped Toyota, Fiat, and Nissan cut the time needed to develop new models by 30-50%.
Emergency shelters and evacuation routes must be planned and established using risk assessments and actual simulations.
One of us (Lo) has carried out simulations of diversified funds for early- and mid-stage cancer drugs, which show that a so-called megafund of $5-30 billion, comprising 100-200 compounds, could sufficiently de-risk the investment while generating returns of between 9-11%.
Further simulations suggest that funds specializing in some drug classes, such as therapies for orphan diseases, could achieve double-digit rates of return with just $250-500 million dollars and fewer compounds in the portfolio.
Simulations show that megafunds will not work for all classes of drugs in all therapeutic areas.
Back