Sentence examples for prescribed error from inspiring English sources
Under a prescribed error bound, the design problem of the coupling strength, pinned nodes and impulse intervals is solved.
The method distinguishes itself by its size robustness, i.e., to achieve a prescribed error its computational effort does not depend on the number of periods.
Our approach reduces the size of the original problem being analysed; by solving this reduced problem, with a given confidence probability, we obtain assignments that satisfy the chance constraints in the original model within prescribed error tolerance thresholds.
If the error is larger than a prescribed error bound ε, we subdivide the segment at the point of maximum error, and apply the G2 interpolation process to the two new segments.
Some fundamental and yet challenging problems are addressed : (1) How to obtain a tight quasi-synchronization error bound; (2) How many and which nodes should be controlled; (3) How to design the coupling strength, to select the pinned nodes and to determine the impulse intervals to optimize the error bound or to achieve quasi-synchronization within a prescribed error bound.
In this paper, we design an O(nl/ε -time O(l2/ε+nl/ε -timelgO l2/ε+n -spacestCut, and O l2/ε+n -space-time O(l2/ε+n)-spalgorithmithms for the other two probleMaxMstCuttCut and MaxLstCut, where n is the number Of vertices inlthe tree, l the number of leaves, and ε>0 the prescribed error bound.
Pharmacist detected 117 new prescribing errors (i.e. prescribing error detecting for the first time) and these new prescribing errors concerned 77 stays (36% of the stays).
Nine demonstrated a significant reduction in prescribing error rates for all or some drug types.
They intended to study how various workplace stresses affected prescribing error rates.
The initial classification of the prescribing error type (grouping into a NCC-MERP category) was performed by the ICU hospital pharmacist who detected the prescribing error.
In this study, our objective was to describe and evaluate tools used to assess prescribing error severity in studies reporting prescribing error rates in the hospital setting.
