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To create benchmarks, we can investigate what something should cost, and we can look at historical averages among employees.
For DSP benchmarks, we can produce arrangements that, on average, consume 20% less energy than an all shared memory arrangement and 27% less energy than an all private memory arrangement.
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Through competitive benchmarking, we can also get a big-picture understanding of industry-wide trends.
To perform this benchmarking we can create a meta-workflow (Geo_Opt M-WF) with different types of optimization runs.
With game developers constantly pushing up the industry benchmark, we can only watch with awe as newer games surprise us with their stunning graphics and engaging game play.
Furthermore, as a benchmark, we can determine the performance of S when MU does not interfere at all on the femtocell due to its positioning.
Now that the hype machine has spun down, winners have been declared, and there have been a few valuations and acquisitions to benchmark, we can clearly see that the results have been nothing short of disappointing.
As a benchmark, we can collect the ensemble of pseudomeasurements given by ray tracing (using WiSE or other tools) and do the same estimation for modeling parameters as above.
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Using the California Flats installation as a benchmark, we can estimate that provisioning all 30,000 of these solar installations worldwide would require 150 billion modules, an unfathomably large quantity that, stacked, would weigh nearly 5 trillion pounds2.5.5 billion tons) and stretch 30 million miles into space, or almost one-third of the way toward its power source, the sun.
Since we have chosen TW as the benchmark, we can say that the extended CW standard commits type I errors: it rejects mergers that would increase TW.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com