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These two processes, made computationally operational through the development of self-transition and decision effect matrices, are then combined into a joint transition matrix, with which we can model the effects of maintenance actions on bridge performance and costs.
Specifically, the formulation of image primitives in terms of scale-space derivatives makes it possible to use tools from differential geometry for deriving relationships between image features and physical properties of objects in the environment, allowing for computationally operational and theoretically well-founded modelling of possibilities or constraints for visual perception.
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Mathematical programming models that seek optimal design and operational plans for distribution systems can be computationally intractable.
Traditional simulators have limited accuracy, can be computationally expensive and typically do not account for minor operational differences between physical robots.
The traditional simplex method is computationally intensive and may not be appropriate for many operational applications on a per-pixel basis for regional and global data.
Two wave separation algorithms are presented; the first is a known method that has been improved to provide simplified calibration and the second is a computationally inexpensive technique that has been adapted to improve its operational bandwidth.
Besides the operational cost associated with matrix assembly, FRS repeatedly solves huge and computationally expensive sparse, ill-conditioned and unsymmetrical linear system.
Compared to AIC and BIC, CV is computationally much more demanding, but also more reliable in principle: (1) this is an operational test, in which one measures the predictive power on data that have not been seen during the learning step, which guarantees the 'honesty' of the measure.
Accurate evaluation of a design or operational parameter choice for cooling is difficult as it requires several runs of computationally intensive computational fluid dynamics (CFD) based models.
Extensive investigations have shown that the LETKF is an accurate and computationally efficient data assimilation system for complex geophysical models, including the Global Forecast System, which is the U. S. Weather Service's operational model [ 22]; a coastal estuarine model of New York Harbor [ 25]; and a dynamical model of the Martian atmosphere [ 26], among others.
Considering that disparity map extraction of an image is a computationally demanding task, practical real-time FPGA based algorithms require increased device utilization resource usage, depending on the disparity levels operational range, which leads to significant power consumption.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com