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To overcome these challenges, we propose a method for inferring user preferences and generating recommendations without relying on the availability or quality of text reviews.
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To overcome this challenge, we propose a method for solving it approximately, although we are unable to prove analytically the convergence of the modified algorithm.
To address this challenge, we propose a method where random variables comprising equivalence classes constrained by the available information are approximated using polynomial chaos expansions (PCEs).
To overcome these challenges we propose a semi-automated segmentation method that relies only on T2-weighted (T2W) and optionally post-contrast T1-weighted (T1W) images.
To address these challenges, we propose a robust visual object tracking method based on binocular vision in this paper.
To address the aforementioned challenges, we propose a new direct path detection scheme based on multipath interference cancelation and data-aided method in the following sections.
To address these corruption challenges, we propose a global health governance approach.
Results: To address these challenges, we propose an unsupervised Bayesian clustering method termed Clustering 16S rRNA for OTU Prediction (CROP).
To address these challenges, we propose an approach based on integrating automatic text mining and network analysis methods to extract known disease genes and to predict unknown disease genes, which can be good candidates for experimental study.
We propose a method to address these challenges of complex discovery: first, the PPI network is integrated with other heterogeneous data sources that specify relationships between proteins, such as functional association and co-occurrence in literature, to form an expanded, composite network.
In this paper, we propose a method for designing such a system and overcoming the aforementioned challenges.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com