AmeriFlux BASE data pipeline to support network growth and data sharing

Autor: Housen Chu, Danielle S. Christianson, You-Wei Cheah, Gilberto Pastorello, Fianna O’Brien, Joshua Geden, Sy-Toan Ngo, Rachel Hollowgrass, Karla Leibowitz, Norman F. Beekwilder, Megha Sandesh, Sigrid Dengel, Stephen W. Chan, André Santos, Kyle Delwiche, Koong Yi, Christin Buechner, Dennis Baldocchi, Dario Papale, Trevor F. Keenan, Sébastien C. Biraud, Deborah A. Agarwal, Margaret S. Torn

Publikováno v: Scientific Data, Vol 10, Iss 1, Pp 1-13 (2023)

Abstract AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux’s diversity of ecosys

Externí odkaz: https://doaj.org/article/7c5aed423da24ec59696be87476dbfcf

Fostering collaboration through improved software development practices for the ONEFlux eddy covariance data processing pipeline

Autor: Gilberto Pastorello, Carlo Trotta, Alessio Ribeca, Keith Beattie, Sy-Toan Ngo, Housen Chu, You-Wei Cheah, Danielle Christianson, Giacomo Nicolini, Sigrid Dengel, Diego Polidori, Peter Isaac, Matthew Archer, Dominic Orchard, Deb Agarwal, Sebastien Biraud, Margaret Torn, Dario Papale

Standardized processing of eddy covariance data is important for studies combining data from multiple sites, for validating remote sensing measurements as well as runs of ecosystem and climate models, and for applications relying on these flux data t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7ad2895631fd8095b7a837ffe813c76e
https://doi.org/10.5194/egusphere-egu23-11187

Human locomotion with reinforcement learning using bioinspired reward reshaping strategies

Autor: Loick M'Pemba, Philippe Carvalho, Theo Marcille, Ismail Seghiri, Anh Tu Nguyen, Jean-Baptiste Six, Yann Maillet, Katharine Nowakowski, Sy Toan Ngo, Tien Tuan Dao

Publikováno v: Medical and Biological Engineering and Computing
Medical and Biological Engineering and Computing, 2021, 59 (1), pp.243-256. ⟨10.1007/s11517-020-02309-3⟩
Medical and Biological Engineering and Computing, Springer Verlag, 2021, 59 (1), pp.243-256. ⟨10.1007/s11517-020-02309-3⟩

Recent learning strategies such as reinforcement learning (RL) have favored the transition from applied artificial intelligence to general artificial intelligence. One of the current challenges of RL in healthcare relates to the development of a cont

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e924285d836266d1ac0e714524f01167
https://doi.org/10.1007/s11517-020-02309-3

Deep Reinforcement Learning for Mitigating Cyber-Physical DER Voltage Unbalance Attacks

Autor: Anna Scaglione, Sean Peisert, Sy-Toan Ngo, Daniel Arnold, Ciaran Roberts, Alexandre Milesi

Publikováno v: ACC

The deployment of DER with smart-inverter functionality is increasing the controllable assets on power distribution networks and, consequently, the cyber-physical attack surface. Within this work, we consider the use of reinforcement learning as an o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e8d6869f6d03341044ebf1bb3c698d1d
https://doi.org/10.23919/acc50511.2021.9482815

Human locomotion with reinforcement learning using bioinspired reward reshaping strategies

Autor: Katharine, Nowakowski, Philippe, Carvalho, Jean-Baptiste, Six, Yann, Maillet, Anh Tu, Nguyen, Ismail, Seghiri, Loick, M'Pemba, Theo, Marcille, Sy Toan, Ngo, Tien-Tuan, Dao

Publikováno v: Medicalbiological engineeringcomputing. 59(1)

Recent learning strategies such as reinforcement learning (RL) have favored the transition from applied artificial intelligence to general artificial intelligence. One of the current challenges of RL in healthcare relates to the development of a cont

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::c17ac3bd40d5d3bc1acb015d3e78c18f
https://pubmed.ncbi.nlm.nih.gov/33417125