Exact(3)
A differentially private distributed model predictive controller (MPC) is proposed by extending a framework recently proposed in the literature for this application.
By extending a framework of the International Nuclear Event Scales (INES) widely used throughout the world, the author proposes a new concept of reactor safety goals that facilitates engineering applications, while removing some of the uncertainties often encountered in implementing safety goals.
Recognizing these, the author proposes a new concept of safety goals1 to facilitate engineering application, while removing some of the uncertainties often encountered in implementing the safety goals, by extending a framework of the International Nuclear Event Scales (INES) being widely used in the world.
Similar(57)
By using and extending a framework of so-called non-local currents that has been established recently, we show that one can gain knowledge about the structure of eigenstates in locally symmetric setups through a Kirchhoff-type law for the non-local currents.
We describe a technique that uses tractography to visualize neural pathways in human brains by extending an existing framework that uses overlapping Gaussian tensors to model the signal.
In the paper entitled "A Full Bi-tensor Neural Tractography Algorithm Using the Unscented Kalman Filter," coauthored by Stefan Lienhard, James Malcolm, Carl Frederik Westin, and Yogesh Rathi, a technique for visualizing neural pathways in human brains by extending an existing framework which uses overlapping Gaussian tensors to model that the signal is described.
We simultaneously account for these effects by extending a zero-inflated Binomial (ZIB) framework to allow the inclusion of semiparametric, smooth spatial terms into both the occupancy and detection component of the model, in a maximum likelihood framework easily implemented in common software.
The BioDEAL framework lets users expose any ontology by extending a Java class or implementing specific web services.
We achieve this insight by extending a univariate approach, linking trait variation to individual contributions to population growth [13] into a multivariate framework.
By extending an existing unsupervised knowledge-driven framework to the supervised classification domain, we were able to investigate the effects of including knowledge from previous gene expression studies (through compendia) as well as known cellular processes (through gene sets) on the accuracy of outcome prediction in breast cancer.
Finally, by extending Arrow's framework we can admit information about the strengths of individual preferences that was ruled out of consideration by Arrow.
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