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Peng, C. (author), May, Ali (author), Abeel, T.E.P.M.F. (author)
BackgroundEnteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine...
journal article 2023
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O’Driscoll, Owen (author), Mouche, Alexis (author), Chapron, Bertrand (author), Kleinherenbrink, M. (author), López-Dekker, Paco (author)
Two air-sea interaction quantification methods are employed on synthetic aperture radar (SAR) scenes containing atmospheric-turbulence signatures. Quantification performance is assessed on Obukhov length L, an atmospheric surface-layer stability metric. The first method correlates spectral energy at specific turbulence-spectrum wavelengths...
journal article 2023
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Rozsas, Arpad (author), Slobbe, Arthur (author), Huizinga, Wyke (author), Kruithof, Maarten (author), Ajithkumar Pillai, Krishna (author), Kleijn, Kelvin (author), Giardina, Giorgia (author)
This paper proposes an automated approach to predict crack pattern similarities that correlate well with assessment by structural engineers. We use Siamese convolutional neural networks (SCNN) that take two crack pattern images as inputs and output scalar similarity measures. We focus on 2D masonry facades with and without openings. The image...
journal article 2022