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This paper describes a particle filter-based (PF-based) prognostic approach based on both Sequential Monte Carlo (SMC) and Bayesian techniques to predict the lumen maintenance life of LED light sources.
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Very few studies, in either hospitalized patients or critically ill subjects, have attempted to individualize a therapeutic intervention based on both initial values and their sequential evaluation over time.
We addressed the phylogeography, evolutionary history and genetic structure of populations of Z. quitzeoensis through a sequential approach, based on both microsatellite and mitochondrial cytochrome b sequences.
Our implementation operates in up- and down-swing phases which are based on Sequential Forward Selection (SFS) and Sequential Backward Selection (SBS).
Based on the sequential offloading requests, our action model is designed as the one-to-many auction structure.
Reduced models are formulated based on the sequential identification of controlling resistances in the complete model.
Based on the sequential Monte Carlo simulation method, these technologies are integrated into the reliability evaluation process.
The research approach employed in this paper is based on a sequential exploratory mixed method strategy.
This technique has been developed based on the sequential estimation of three quantities, viz.
The methodology is based on coupling sequential chemical extractions with 3D fluorescence spectroscopy.
The method is based on the sequential multilateration technique, using a TL.
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