Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Diogo R Ferreira"'
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 2, p 025048 (2024)
We explore the possibility of fully replacing a plasma physics kinetic simulator with a graph neural network-based simulator. We focus on this class of surrogate models given the similarity between their message-passing update mechanism and the tradi
Externí odkaz:
https://doaj.org/article/9971926299a647329025699421e80646
Publikováno v:
Fusion science and technology 76 (2020): 901–911. doi:10.1080/15361055.2020.1820749
info:cnr-pdr/source/autori:Ferreira, Diogo R.; Carvalho, Pedro J.; Sozzi, Carlo; Lomas, Peter J./titolo:Deep Learning for the Analysis of Disruption Precursors Based on Plasma Tomography/doi:10.1080%2F15361055.2020.1820749/rivista:Fusion science and technology/anno:2020/pagina_da:901/pagina_a:911/intervallo_pagine:901–911/volume:76
Fusion Science and Technology
info:cnr-pdr/source/autori:Ferreira, Diogo R.; Carvalho, Pedro J.; Sozzi, Carlo; Lomas, Peter J./titolo:Deep Learning for the Analysis of Disruption Precursors Based on Plasma Tomography/doi:10.1080%2F15361055.2020.1820749/rivista:Fusion science and technology/anno:2020/pagina_da:901/pagina_a:911/intervallo_pagine:901–911/volume:76
Fusion Science and Technology
The JET baseline scenario is being developed to achieve high fusion performance and sustained fusion power. However, with higher plasma current and higher input power, an increase in pulse disruptivity is being observed. Although there is a wide rang
Autor:
Diogo R. Ferreira, Elsa Reis, João Miguel Pereira, Lígia Castanheira, Magda Lemos, Elsa Fernandes, Rodrigo Santos
Publikováno v:
The Primary Care Companion For CNS Disorders. 23
Autor:
Cristina M. R. R. Oliveira, Ricardo J.N. Bettencourt da Silva, Miguel Barros, Diogo R. Ferreira
Publikováno v:
Microchemical Journal. 146:856-863
For most titrations based on the visual detection of the end-point this operation is an important uncertainty component. Well-known models are available to estimate the uncertainty of gravimetric and volumetric steps involved in these titrations, but
Autor:
Diogo R. Ferreira
In the fusion community, the use of high performance computing (HPC) has been mostly dominated by heavy-duty plasma simulations, such as those based on particle-in-cell and gyrokinetic codes. However, there has been a growing interest in applying mac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cadf601c9904b42b0958a665d9fec98e
http://arxiv.org/abs/2106.06101
http://arxiv.org/abs/2106.06101
Publikováno v:
Social Indicators Research
Hospitals consume most of the health systems' financial resources. In Portugal, for instance, public hospitals represent more than half of the National Health Service debt and are decisive in their financial insufficiency. Although profit is not the
Publikováno v:
Mining Data for Financial Applications ISBN: 9783030669805
MIDAS@PKDD/ECML
MIDAS@PKDD/ECML
Financial markets, such as the stock exchange, are known to be extremely volatile and sensitive to news published in the media. Using sentiment analysis, as opposed to using time series alone, should provide a better indication for the prospects of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5dfd6bdd63a9710b1463ddeee47b2904
https://doi.org/10.1007/978-3-030-66981-2_2
https://doi.org/10.1007/978-3-030-66981-2_2
Autor:
S. Nowak, Jet Contributors, F.G. Rimini, E. Alessi, D. Van Eester, L. Garzotti, Carlo Sozzi, M. Baruzzo, E. Lerche, D. Frigione, Fulvio Auriemma, D. Brunetti, E. Giovannozzi, P. Buratti, G. Pucella, E. Joffrin, L. Piron, Diogo R. Ferreira, P. J. Lomas
Publikováno v:
Nuclear Fusion
Nuclear fusion (Online) 61 (2021): 046020-1–046020-12. doi:10.1088/1741-4326/abe3c7
info:cnr-pdr/source/autori:Pucella G.; Buratti P.; Giovannozzi E.; Alessi E.; Auriemma F.; Brunetti D.; Ferreira D.R.; Baruzzo M.; Frigione D.; Garzotti L.; Joffrin E.; Lerche E.; Lomas P.J.; Nowak S.; Piron L.; Rimini F.; Sozzi C.; Van Eester D./titolo:Onset of tearing modes in plasma termination on JET: The role of temperature hollowing and edge cooling/doi:10.1088%2F1741-4326%2Fabe3c7/rivista:Nuclear fusion (Online)/anno:2021/pagina_da:046020-1/pagina_a:046020-12/intervallo_pagine:046020-1–046020-12/volume:61
Nuclear fusion (Online) 61 (2021): 046020-1–046020-12. doi:10.1088/1741-4326/abe3c7
info:cnr-pdr/source/autori:Pucella G.; Buratti P.; Giovannozzi E.; Alessi E.; Auriemma F.; Brunetti D.; Ferreira D.R.; Baruzzo M.; Frigione D.; Garzotti L.; Joffrin E.; Lerche E.; Lomas P.J.; Nowak S.; Piron L.; Rimini F.; Sozzi C.; Van Eester D./titolo:Onset of tearing modes in plasma termination on JET: The role of temperature hollowing and edge cooling/doi:10.1088%2F1741-4326%2Fabe3c7/rivista:Nuclear fusion (Online)/anno:2021/pagina_da:046020-1/pagina_a:046020-12/intervallo_pagine:046020-1–046020-12/volume:61
In this work the onset of tearing modes in the termination phase of plasma pulses on JET is investigated. It is shown that the broadening or the shrinking of the current density profile, as a consequence of a core hollowing or an edge cooling of the
Autor:
Diogo. R. Ferreira
Publikováno v:
A Primer on Process Mining ISBN: 9783030418182
A Primer on Process Mining ISBN: 9783319564265
A Primer on Process Mining ISBN: 9783319564265
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e342afbc9a7e94699609da62f94f5575
https://doi.org/10.1007/978-3-030-41819-9_3
https://doi.org/10.1007/978-3-030-41819-9_3
Autor:
Tobias Golling, Mikhail Hushchyn, Yuval Reina, Vincenzo Innocente, Isabelle Guyon, Andrey Ustyuzhanin, Cécile Germain, Heather Gray, Steven Farrell, Diogo R. Ferreira, Jean-Roch Vlimant, Yetkin Yilmaz, Sergey Gorbunov, Vladimir Gligorov, Paolo Calafiura, Nicole Finnie, Trian Xylouris, Edward Moyse, David Rousseau, Laurent Basara, Sabrina Amrouche, Moritz Kiehn, Andreas Salzburger, Johan Sokrates Wind, Victor Estrade, Liam James Finnie, Jean-Francois Puget
Publikováno v:
The NeurIPS '18 Competition
The NeurIPS '18 Competition, 8, Springer, pp.231-264, 2019, The Springer Series on Challenges in Machine Learning, 978-3-030-29134-1. ⟨10.1007/978-3-030-29135-8_9⟩
The NeurIPS '18 Competition ISBN: 9783030291341
The NeurIPS '18 Competition, 8, Springer, pp.231-264, 2019, The Springer Series on Challenges in Machine Learning, 978-3-030-29134-1. ⟨10.1007/978-3-030-29135-8_9⟩
The NeurIPS '18 Competition ISBN: 9783030291341
This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the trajectory of particles in the Large Hadron Collider (LHC). This experim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23990ca0b28c3e9ccfbece76ebfa23a7
http://cds.cern.ch/record/2672222
http://cds.cern.ch/record/2672222