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Another interesting approach is followed in [12] and [13], which combine SCA and ICA methods, proposing that ICA be performed in time-frequency regions in which the number of active sources do not exceed the number of sensors.
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The two decision-making methods propose that the best to worst prime movers are the internal combustion, sterling engine, conventional separate production and micro-gas turbine.
Simply put, all belief revision methods proposed that satisfy AGM-style axioms turn out to be intractable with the exception of the method that revises beliefs by changing the probabilities (minimally) in the KB.
In this article, two novel methods are proposed that are based on a hierarchical framework that models both pathway and SNP level effects.
A novel capacitance-based method is proposed that can estimate volume-mode bubble frequency changes due to bubble size, shape, and proximity to solid and air interfaces.
A hybrid analytical/numerical method is proposed that permits an efficient dynamic analysis of these structures.
To overcome this weakness, a model calibration method was proposed that is based on case-by-case parameter identification.
To inspect these special defects, a new and automated inspection method is proposed that employs structured-light illumination.
A hybrid analytical/numerical method is proposed that permits the efficient dynamic analysis of planar serial-frame structures.
A vibration reduction method is proposed that is effective for both constant- and variable-length deploying translating beams.
In the present study, a method is proposed that can be used to examine the temporal distribution of autobiographical memory (Janssen et al., 2005; Janssen & Murre, 2008).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com