Predictive computer simulations of highly resolved large-scale 3D deflagrations and detonations are dependent on a robust reaction model embedded in a computational framework capable of running on massively parallel computer architectures.
Classical mechanics in a computational framework, Lagrangian formulation, action, variational principles, and Hamilton's principle.
There are many different ways to represent knowledge in a computational framework, and the differences occur along a number of different dimensions.
Inspired from such cognitive concepts, the contribution consists in a computational framework that enables a virtual entity to possess an autonomous world of simulation within the simulation.
Both formulations, with and without the improvements, are tested in a computational framework in order to discriminate the most promising solution methods.
Determining the actual properties of the chemical world that are detected by ORs may thus provide an efficient way to represent molecules in a computational framework in general.
Yildirim, I. et al. Efficient and robust analysis-by-synthesis in vision: a computational framework, behavioral tests, and modeling neuronal representations. in Annual Conference of the Cognitive Science Society (eds. Noelle, D. C. et al.) (Cognitive Science Society, Austin, TX, USA, 2015).
I. Yildirim, Kulkarni, T., Freiwald, W. A., and Tenenbaum, J. B., "Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations", in Annual Conference of the Cognitive Science Society, 2015.
Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations.
In this work, a computational framework is presented to compute the time evolution of force constants for a coarse grained (CG) elastic network model along an all-atom molecular dynamics trajectory of a protein system.
In this study, a computational framework using a network of distributed computers, each equipped with graphics processing units (GPUs), is proposed.
