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We proposed a fast ME method which reduced the block searching strategy and range to increase the calculation speed greatly.
Construction of the second tube utilized the New Austrian Tunnelling method, which reduced the cost of the tunnel by $5 to $6 million.
The sensitivity of data was analyzed by using the method which reduced the biggest weight of literature.
Work-related costs were based on a small sample of patients that resulted partly from our use of the friction-cost method, which reduced the number of employed patients in the cost estimations.
Volunteers were randomly assigned into the 3 intervention groups by using a minimization method, which reduced the baseline differences between the treatments, and each new volunteer was sequentially assigned to a group after the assignment of previous volunteers was taken into account.
Similar(54)
Furthermore, we propose a differential training method which reduces the sensitivity to approximation errors.
It is a simplistic method which reduces the shape matching problem to sampling, normalizations, and comparison of probability distributions.
We obtain this result by the variational reduction method which reduces the infinite dimensional problem to the finite dimensional one.
The BER performance is improved due to the self-SIC method, which reduces the interference at the receiver.
The coupled model is solved based on a nonoverlapping domain decomposition method, which reduces the problem to the coupling interface.
The second one is a Kalman filter with a particular tuning method, which reduces the effects of some parameter uncertainties.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com