Machine Learning Prediction of TiO2-Coating Wettability Tuned via UV Exposure

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Mohamad Jafari Gukeh ◽  
Shashwata Moitra ◽  
Ali Noaman Ibrahim ◽  
Sybil Derrible ◽  
Constantine M. Megaridis

Nanoscale ◽  
2021 ◽  
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Susana I. L. Gomes ◽  
Mónica J. B. Amorim ◽  
Suman Pokhrel ◽  
Lutz Mädler ◽  
Matteo Fasano ◽  
...  

Based on a highly detailed materials characterisation database (including atomistic and multiscale modelling), single and univariate statistical methods, combined with machine learning techniques, revealed key descriptors of biological functions.



2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.



2009 ◽  
Vol 40 (10) ◽  
pp. 6
Author(s):  
JEFF EVANS
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2007 ◽  
Vol 38 (10) ◽  
pp. 1-8
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BRUCE JANCIN
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2020 ◽  
Author(s):  
Man-Wai Mak ◽  
Jen-Tzung Chien


2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
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2020 ◽  
Author(s):  
Marc Peter Deisenroth ◽  
A. Aldo Faisal ◽  
Cheng Soon Ong
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Lorenza Saitta ◽  
Attilio Giordana ◽  
Antoine Cornuejols


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Shai Ben-David
Keyword(s):  


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