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New business models from large and small firms alike that foster jobs, conserve resources and inspire innovation thrive within these neighbourhoods.
Machine learning is a sub-discipline of artificial intelligence that can be used to create predictive models from large and complex datasets.
Such architectures often emerge from legacy code, but, creating feature models from large, legacy systems is a long and arduous task.
These issues become crucial for modern techniques of building nonlinear dynamical models from large time series data sets (e.g., Smith 1992), for example the sunspot record or the daily closing value of a particular stock for some specific period of time.
Bioinformatics is one area with a high demand for generation of comprehensive models from large datasets.
Many methods have been proposed to estimate general amino acid substitution models from large and diverse databases [[ 1, 6], and references therein].
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We demonstrate that our approach provides an excellent trade-off between quality and compactness, and is eligible for fast production of polyhedral building models from large-scale urban height maps, as well as, for direct meshing of sparse street-side Structure-from-Motion (SfM) data.
In order to obtain a good B-spline curve model from large data, the knots are usually respected as variables.
We have previously developed a PKPD-based warfarin model from large adult patient populations using population modelling.
Reviewer: The authors, in their attempt to probe into the nature of genome reduction in obligate intracellular (OI) "specialists", lay out a stepwise model from large free-living organisms to somewhat reduced host-associated organisms finally to OI organisms with their small genomes.
Experimental models range from large animal models designed to mimic the human clinical situation, to gene modified mice, isolated hearts and cell cultures.
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