Explore the words cloud of the AIDA project. It provides you a very rough idea of what is the project "AIDA" about.
The following table provides information about the project.
KATHOLIEKE UNIVERSITEIT LEUVEN
|Coordinator Country||Belgium [BE]|
|Total cost||1˙499˙690 €|
|EC max contribution||1˙499˙690 € (100%)|
1. H2020-EU.184.108.40.206. (Enabling exploitation of space data)
|Duration (year-month-day)||from 2018-09-01 to 2021-08-31|
Take a look of project's partnership.
|1||KATHOLIEKE UNIVERSITEIT LEUVEN||BE (LEUVEN)||coordinator||432˙500.00|
|2||SYSTHMATA YPOLOGISTIKIS ORASHS IRIDA LABS AE||EL (RIO)||participant||250˙000.00|
|3||STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN||NL (UTRECHT)||participant||219˙190.00|
|4||CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS||FR (PARIS)||participant||158˙250.00|
|5||UNIVERSITA DELLA CALABRIA||IT (ARCAVACATA DI RENDE)||participant||150˙000.00|
|6||CINECA CONSORZIO INTERUNIVERSITARIO||IT (CASALECCHIO DI RENO BO)||participant||128˙750.00|
|7||UNIVERSITA DI PISA||IT (PISA)||participant||121˙000.00|
|8||SPACE CONSULTING INTERNATIONAL LLC||US (DURHAM NH)||participant||40˙000.00|
AIDA brings a transformational innovation to the analysis of heliophysics data in four steps.
First, AIDA will develop a new open source software called AIDApp written in Python (a free language) and capable of collecting, combining and correlating data from different space missions. AIDApp wants to replace mission-specific tools written for costly languages (such as IDL) that exclude many scientists, students and amateur space enthusiasts from exploring the data, with a much-needed single platform where methods are shared and continuously improved by the whole community.
Second, AIDA will introduce modern data assimilation, statistical methods and machine learning (ML) to heliophysics data processing. Unlike traditional methods based on human expertise, these methods rely on statistics and information theory to extract features that are hidden in the data.
Third, AIDA will combine real data from space missions with synthetic data from simulations developing a virtual satellite component for AIDApp. This feature will be demonstrated in the comparison with existing mission data and in the planning of new missions (e.g. ESA’s THOR).
Fourth, AIDA will deploy in AIDApp methods of Artificial Intelligence (AI) to analyse data flows from heliophysics missions. This task requires bridging together competences in computer science and in heliophysics and pushes well beyond the current state of the art in space data analysis, connecting space researchers with AI, one of the fastest growing trends in modern science and industrial development.
AIDA will use the new AIDApp in selecting key heliophysics problems to produce a database (AIDAdb) of new high-level data products that include catalogs of features and events detected by ML and AI algorithms. Moreover, many of the AI methods developed in AIDA will themselves represent higher-level data products, for instance in the form of trained neural networks that can be stored and reused as a database of coefficients.
|Report on the identification of numerical simulations to analyze and on the collection of data by virtual spacecraft||Documents, reports||2020-03-11 14:41:23|
|Graphic image, dissemination and outreach plan||Websites, patent fillings, videos etc.||2020-03-11 14:41:24|
|Minutes of the 1st Advisory Board meeting||Documents, reports||2020-03-11 14:41:28|
|Data Management Plan version 1.0||Open Research Data Pilot||2020-03-11 14:41:27|
|Report on application of DA techniques to OpenGGCM||Documents, reports||2020-03-11 14:41:24|
Take a look to the deliverables list in detail: detailed list of AIDA deliverables.
|year||authors and title||journal||last update|
JÃ©rÃ©my Dargent, Federico Lavorenti, Francesco Califano, Pierre Henri, Francesco Pucci, Silvio S. Cerri
Interplay between Kelvinâ€“Helmholtz and lower-hybrid drift instabilities
published pages: 1/19, ISSN: 0022-3778, DOI: 10.1017/s0022377819000758
|Journal of Plasma Physics 85/6||2020-02-19|
Romain Dupuis, Martin V. Goldman, David L. Newman, Jorge Amaya, Giovanni Lapenta
Characterizing Magnetic Reconnection Regions Using Gaussian Mixture Models on Particle Velocity Distributions
published pages: 22, ISSN: 1538-4357, DOI: 10.3847/1538-4357/ab5524
|The Astrophysical Journal 889/1||2020-02-19|
Oreste Pezzi, Giulia Cozzani, Francesco Califano, Francesco Valentini, Massimiliano Guarrasi, Enrico Camporeale, Gianfranco Brunetti, Alessandro RetinÃ², Pierluigi Veltri
ViDA: a Vlasovâ€“DArwin solver for plasma physics at electron scales
published pages: 1/25, ISSN: 0022-3778, DOI: 10.1017/s0022377819000631
|Journal of Plasma Physics 85/5||2020-02-19|
Francesco Pecora, Francesco Pucci, Giovanni Lapenta, David Burgess, Sergio Servidio
Statistical Analysis of Ions in Two-Dimensional Plasma Turbulence
published pages: , ISSN: 0038-0938, DOI: 10.1007/s11207-019-1507-6
|Solar Physics 294/9||2019-09-16|
Olga Malandraki, Olga Khabarova, Roberto Bruno, Gary P. Zank, Gang Li, Bernard Jackson, Mario M. Bisi, Antonella Greco, Oreste Pezzi, William Matthaeus, Alexandros Chasapis Giannakopoulos, Sergio Servidio, Helmi Malova, Roman Kislov, Frederic Effenberger, Jakobus le Roux, Yu Chen, Qiang Hu, N. Eugene Engelbrecht
Current Sheets, Magnetic Islands, and Associated Particle Acceleration in the Solar Wind as Observed by Ulysses near the Ecliptic Plane
published pages: 116, ISSN: 0004-637X, DOI: 10.3847/1538-4357/ab289a
|The Astrophysical Journal 881/2||2019-09-16|
The Challenge of Machine Learning in Space Weather: Nowcasting and Forecasting
published pages: , ISSN: 1542-7390, DOI: 10.1029/2018sw002061
Leonardo Primavera, Francesco Malara, Sergio Servidio, Giuseppina Nigro, Pierluigi Veltri
Parametric Instability in Two-dimensional AlfvÃ©nic Turbulence
published pages: 156, ISSN: 0004-637X, DOI: 10.3847/1538-4357/ab29f5
|The Astrophysical Journal 880/2||2019-09-16|
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