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ALAMO is a computational methodology for learning algebraic functions from data.
We present a computational methodology for modeling cellular-scale blood flow in arbitrary and highly complex geometry.
In the present paper a computational methodology for assessing and improving the microclimate in the urban environment is developed.
A computational methodology for instantiating models of particular kinds of language in terms of extracted word frequencies and variational analysis using singular value decomposition.
In this work, we present a computational methodology for convection and advection that handles discontinuities with second order accuracy and maintains conservation to machine precision.
A computational methodology for analysis of space robot manipulator systems, considering the effects of the clearances in the joint, is presented.
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A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights.
Thus, synergy networks provide a computational methodology helpful for deriving "disease interactomes" from biological data.
The (N3 -Fe(III)CDO aN3 -Fe/Cys)-Fe(III CDO species investigandd iN3 /Cys -Fe have provided us with a valuable opportuN3 /Cys -Feluate further a computatIII CDOethodology speciese for modelinvestigatedtine (superoxo/Cys)-Fe(III)CDO inthisediate, and thus to distinguish betwork thavehree provided spin states for this species.
A computational methodology is proposed for aerodynamic noise prediction of long-span bodies at low Mach numbers.
A computational methodology is proposed for CFD-based aerodynamic design to exploit a reduced order model as surrogate evaluator.
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