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This work presents an approach for modelling a class of contemporary, non-resonant translatory piezoelectric actuators.
This will enable modelling a class of tasks from sets of repeated demonstrations of the same task, so that a generalised probabilistic representation is derived to be used for task planning in artificial systems.
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A discrete linear model is used for modeling a class of MIMO nonlinear systems.
A new numerical approach for modeling a class of flow structure interaction problems typically encountered in biological systems is presented.
RONs are introduced to model a class of sector-like nonlinearities that occur in a probabilistic way according to a two-dimensional discrete random variables joint distribution.
The problem of modeling a class of two-phase moving-bed tubular gasification reactors by means of a lumped (finite-dimensional) representation is addressed in this paper.
This type of approach is particularly relevant when the number of training samples available to model a class of objects is very limited.
According to the ABCDE model, A-class function in Arabidopsis is required for perianth identity and, AP2, in particular, leads to repression of C-class function [ 48].
Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems5,6,7.
Each device is modelled by a class specialization that defines the device behaviours in terms of power consumption.
Specifically, we model a class of IaaS Clouds that offer tiered services by configuring physical machines into three pools with different provisioning delay and power consumption characteristics.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com