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The variance of randomly generated points within a unit square can be reduced through a stratification process. In mathematics, more specifically in the theory of Monte Carlo methods, variance reduction is a procedure used to increase the precision of the estimates obtained for a given simulation or computational effort. [1]
This automation eliminates the decision-making a technician had to perform, and unlike a technician, the computer can perform these tasks tirelessly and with greater precision. All of these steps are performed in the same logical sequence as manual patch clamping, but don't require extensive training to perform, and are completely controlled by ...
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Precision engineering is a subdiscipline of electrical engineering, software engineering, electronics engineering, mechanical engineering, and optical engineering concerned with designing machines, fixtures, and other structures that have exceptionally low tolerances, are repeatable, and are stable over time.
Genetic engineering, also called genetic modification or genetic manipulation, is the modification and manipulation of an organism's genes using technology.It is a set of technologies used to change the genetic makeup of cells, including the transfer of genes within and across species boundaries to produce improved or novel organisms.
Once the message has been sent, becomes the process , while () becomes the process [/], which is with the place-holder substituted by , the data received on . The class of processes that P {\displaystyle {\mathit {P}}} is allowed to range over as the continuation of the output operation substantially influences the properties of the calculus.
The Su-34 ‘Fullback’ is a two-seat supersonic bomber that can carry a hulking 15.5 tons of weapons on 12 hardpoints, and has a sensor suite better adapted for using precision guided weapons ...
Strict reduction is the simplest type of approximation-preserving reduction. In a strict reduction, the approximation ratio of a solution y' to an instance x' of a problem B must be at most as good as the approximation ratio of the corresponding solution y to instance x of problem A. In other words: