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In the last years, the popularity of spiking neural networks (SNN) and spiking models has increased.
As the role of computational models has increased, the accuracy of computational results has been of great concern to engineering decision-makers.
We simulated these strains in six historical genome-scale models of E. coli, and we report that the predictive power of the models has increased as they have expanded in size and scope.
The size and sophistication of models has increased significantly since that paper and a range of techniques are available from predicting the initial mechanical environment through to advanced adaptive simulations including bone adaptation, tissue differentiation, damage accumulation and wear.
Use of these models has increased over the last several decades, especially in conjunction with emerging alternative methods to animal testing, such as in vitro studies and data-driven in silico quantitative-structure-activity-relationship (QSAR) predictions.
While the complexity of ecological simulation models has increased along with advances in computer hardware, recent reviews have concluded that such complex models have generally not fulfilled their potential for advancing ecological understanding.
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Emilie Crown, who runs the Montgomery County program, said the addition of anchors and top fasteners in various models had increased the complexity of installing a car seat.
Through observation of the HW performance and HW feedback, these simulation models have increased the understanding of trauma management.
In parallel, improvements in temporal river temperature models have increased the accuracy of temperature predictions at individual sites.
However, as models have increased in complexity to include multi-segmental dynamics, discrepancy has arisen amongst researchers regarding the accuracy and limitations of identifying neural control parameters using a single stimulus.
Results using live data show the fuzzy models have increased the predictive accuracy of OSCAR-CITS across four learning style dimensions and facilitated the discovery of some interesting relationships amongst behaviour variables.
More suggestions(15)
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models has enhanced
specimen has increased
kinds has increased
specimens has increased
systems has increased
models has grown
methodologies has increased
modelling has increased
sample has increased
models has introduced
models shows increased
models has failed
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models has evolved
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