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For the proof of concept, a case study implements and evaluates the methodologies considering a tunnel lining model from a project in the field of mechanized tunneling.
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We derive an efficient variational Bayesian inference algorithm for the proposed model, and we experimentally investigate its efficacy as a robot learning by demonstration methodology, considering a number of demanding robot learning by demonstration scenarios.
This paper presents a compliance optimization methodology considering an initial stress field.
It is important to note that this methodology considers a worst case scenario in which all VM allocations consume full resources at all times.
Thus, the methodology considers a parametric study for optimal designs of buttressed earth-retaining walls, where one of the parameters is the wall height.
Based on the skeletal model target, the methodology considers a combustion mechanism as two parts: a comprehensive part describing reaction processes involving small radicals and molecules as the 'core', and a skeletal one which, in coupling with the 'core', controls the ignition characteristics.
In order to design superior integrated systems, [18] reviewed the existing design options for heating systems incorporating fuel cell micro-CHP in dwellings, motivating a new methodology considering all possible interconnections of plant.
We illustrate application of the methodology by considering a navigation example based on integration of inertial and satellite measurements.
Most of the power saving methodologies consider single AP in a vicinity.
Often, these methodologies consider 3D patterns as: (a) those described by the residues surrounding co-crystallized ligands/ions available from X-ray crystal structures, and b) those identified by sequence-based methods (e.g. PROSITE consensus patterns; [35]).
We illustrate the general methodology by considering an important emerging disease - Leishmaniasis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com