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The performance of many computational paradigms can be considerably improved by using appropriate quadrant-recursive spatial orders.
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Massively parallel computational paradigms can mitigate many issues associated with the analysis of large and complex remotely sensed data sets.
Cloud computing offers new computational paradigms to not only deal with data and analyses at scale but also reduce the building and operation costs.
However, many computational formalisms do not conform to the functional paradigm: Turing machines; imperative programming languages, such as C; logic programming languages, such as Prolog; and so on.
These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing.
Many computational methods to predict logP have been described.
Furthermore, many computational issues have to be addressed.
The method is used in many computational fluid dynamics packages.
Many computational methods for identifying phosphorylation sites have been developed.
Many computational methods predict variant effects.
Efficient and effective computational methods are essential for solving many computational biology and computational medicine challenges.
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