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de Araujo Alves Lima, Rosemere (author), Tao, R. (author), Bernasconi, A. (author), Carboni, Michele (author), Carrere, Nicolas (author), Teixeira De Freitas, S. (author)
Understanding the relationship between the sensors’ outputs and the damage evolution within the joints is becoming increasingly crucial to improving structural health monitoring systems and collecting data to improve the joint’s design. Therefore, a study of the acoustic emission method associated with visual fracture evaluation was proposed to...
poster 2023
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Ottati, F. (author), Gao, Chang (author), Chen, Qinyu (author), Brignone, Giovanni (author), Casu, Mario R. (author), Eshraghian, Jason K. (author), Lavagno, Luciano (author)
As deep learning models scale, they become increasingly competitive from domains spanning from computer vision to natural language processing; however, this happens at the expense of efficiency since they require increasingly more memory and computing power. The power efficiency of the biological brain outperforms any large-scale deep...
journal article 2023
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Janssens, M. (author), Hulshoff, S.J. (author)
Data-driven parameterizations offer considerable potential for improving the fidelity of General Circulation Models. However, ensuring that these remain consistent with the governing equations while still producing stable simulations remains a challenge. In this paper, we propose a combined Variational-Multiscale (VMS) Artificial Neural...
journal article 2022
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Alwosheel, A.S.A. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Artificial Neural Networks (ANNs) are rapidly gaining popularity in transportation research in general and travel demand analysis in particular. While ANNs typically outperform conventional methods in terms of predictive performance, they suffer from limited explainability. That is, it is very difficult to assess whether or not particular...
journal article 2021
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Sewdien, V. N. (author), Preece, R. (author), Rueda, José L. (author), van der Meijden, M.A.M.M. (author)
The participation of volatile wind energy resources in the generation mix of power systems is increasing. It is therefore becoming more and more crucial for system operators to accurately predict the wind power generation across different short term horizons (5 to 60 minutes ahead) in order to adequately balance the system and maintain system...
conference paper 2018
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Campoli, G. (author)
doctoral thesis 2014
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