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The method we propose utilizes a combination of asymptotic and numerical techniques.
The method we propose may be of great interest in many types of bioanalytical studies.
Several stiff numerical tests, including phase separation, are displayed in order to highlight the efficiency of the method we propose.
In order to improve the performance of the method, we propose a self-adaptive rule which updates the penalty parameter automatically.
To this end, the method we propose utilises representative points to both incrementally cluster new data and to selectively retain important cluster information within a knowledge repository.
The method we propose includes using percolation theory to estimate the connectivity of the faults, and generating fuzzy rules from discrete fracture network simulations to estimate leakage probability.
The method we propose combines quantitative (objectively measured) and qualitative (expert opinion based) evaluations performed on alternatives in search of a best choice.
The method we propose is advanced switching algorithms that select a subset of the battery's cells for each current demand and control the discharge current from each, based on the electrochemical properties of the individual cells.
According to the validation of the method, we propose here, to our knowledge, the first application of solid-phase microextraction for the direct analysis of chlorophenols in red wine samples.
The method we propose represents a first insight into the numerical solution of more complicated problems and consists of a discretization of the differential and integral terms and of an iteration process to solve the resulting non-linear system.
We report on our computational experience on these test instances, showing that the method we propose is capable of finding tight lower bounds and approximate solutions for real-world instances, within acceptable computing time.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com