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CORDIS - Résultats de la recherche de l’UE
CORDIS

Critical Action Planning over Extreme-Scale Data

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Initial Use Case Evaluation, Pilots, Demonstrators and Simulation Models and Tools (s’ouvre dans une nouvelle fenêtre)

This deliverable will present the interim evaluation of the CREXDATA use cases, the simulation models and tools developed at CREXDATA, as well as the developed pilots. It also includes the final scenario definitions for the use cases and initial conclusions from evaluation results across use cases.

Ethics Manual (s’ouvre dans une nouvelle fenêtre)

A report that will: 1) explain how all data intended to be used for training and/or validating the CREXDATA practices and models are relevant, high quality, and limited to the purposes at hand; 2) assess whether the AI, ML and CEF models and their use in the context of the use cases have any detrimental impact on humans in terms of social behavior engineering, privacy violation, surveillance and free will; 3) provide adequate information in regard to the prototype's quality following a risk-based approach.

Initial Report on Complex Event Forecasting, Learning and Analytics (s’ouvre dans une nouvelle fenêtre)

This deliverable will present the initial set of developed algorithms for (i) multi-resolution complex event forecasting, (ii) reinforced learning, (iii) federated machine learning, and (iv) data analytics as a service.

Initial Report on System Architecture, Integration and Released Software Stacks (s’ouvre dans une nouvelle fenêtre)

This deliverable will present the initial system architecture, the system integration and the initial version of the released software stacks.

Initial Report on Explainable AI, Visual Analytics and Augmented Reality (s’ouvre dans une nouvelle fenêtre)

This deliverable will present the initial set of developed algorithms for (i) explainable AI, (ii) visual analytics for supporting XAI and for data analytics under uncertainty, and (iii) Augmented Reality.

Data handling, Joint Scheme for Pilot and Demonstrator Research Design, Requirements Analysis and Initial Scenario Definition (s’ouvre dans une nouvelle fenêtre)

This deliverable will present the data handling process in accordance with D1.2, joint scheme for pilot and demonstrator research design across use cases, as well as requirements analysis and initial scenario definitions per use cases. D2.1 sets up structure and procedures for research data acquisition, analysis and evaluation, which will be reflected in the structure of deliverables D2.2/D2.3.

Plan for Dissemination and Exploitation, Project Presentation and Website (s’ouvre dans une nouvelle fenêtre)

This deliverable will detail the plan for the project dissemination, communication and exploitation strategy to be adopted throughout the project lifetime, as well as will initiate a list of related projects, potential adopters and actions that CREXDATAwill use to approach stakeholders. This deliverable also contains a fact sheet providing an overview of the project, following the EU standards, the project presentation and the project website, as key dissemination and exploitationchannels for promoting and communicating the project achievements.

Initial Report on the Dissemination, Exploitation and Business Plan (s’ouvre dans une nouvelle fenêtre)

This deliverable includes the initial report on the dissemination and exploitation activities undertaken throughout the project, as well as the initial version of the business plan that incorporates CREXDATA’s achievements.

Quality Assurance Plan (s’ouvre dans une nouvelle fenêtre)

The quality assurance plan will highlight potential risks and associated contingency plans. This plan will deal with quality assurance regarding the information flow, communication channels and reporting procedures within the consortium and to others; also quality assurance of technical and scientific results and of the project documentation.

Data Management Plan (s’ouvre dans une nouvelle fenêtre)

A report that will a) provide an overview of the datasets generated and usedin the context of the project and the use cases thereof, b) outline how data will be generated and/or collected and processed, c) assess on top of the methodology and standards to be introduced, whether and how this data will be shared and/or made open in cases this is possible, always pursuing to adhere to the FAIR principles, and how it will be curated and preserved, in direct alignment with the ethics requirements. The Data Management Plan will evolve during the lifetime of CREXDATA, to present the status of the project's reflections on data management.

Publications

Proactive Streaming Analytics at Scale: A Journey from the State-of-the-art to a Production Platform (s’ouvre dans une nouvelle fenêtre)

Auteurs: Giatrakos, Nikos; Alevizos, Elias; Deligiannakis, Antonios; Kinkenberg, Ralf; Artikis, Alexander
Publié dans: ACM CIKM, 2023
Éditeur: ACM
DOI: 10.1145/3583780.3615293

Extremwettersituationen in alpinen Gebieten: Management kritischer Situationen in Echtzeit bei extremen und komplexen Daten

Auteurs: Pottebaum, Jens; Rechberger, Christina; Hieb, Michael; Gräßler, Iris; Resch, Christian
Publié dans: 2023, ISBN 978-3-900397-11-1
Éditeur: Disaster Competence Network Austria

The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications (s’ouvre dans une nouvelle fenêtre)

Auteurs: Stef van den, Elzen; Gennady, Andrienko; Natalia, Andrienko; Brian D, Fisher; Rafael M, Martins; Jaakko, Peltonen; Alexandru C, Telea; Michel, Verleysen; Theresa-Marie, Rhyne
Publié dans: IEEE Computer Graphics and Applications, Vol. 43, no.2, p. 78-88 (2023), 2023, ISSN 1558-1756
Éditeur: IEEE
DOI: 10.1109/MCG.2023.3237286

On the number of stable solutions in the Kuramoto model (s’ouvre dans une nouvelle fenêtre)

Auteurs: Alex Arenas; Antonio Garijo; Sergio Gómez; Jordi Villadelprat
Publié dans: Chaos, 2023, ISSN 1089-7682
Éditeur: Chaos
DOI: 10.1063/5.0161977

Dual Control of Coupled Oscillator Networks (s’ouvre dans une nouvelle fenêtre)

Auteurs: Per Sebastian Skardal; Alex Arenas
Publié dans: IEEE Open Journal of Control Systems, Vol 2, Pp 146-154 (2023), 2023, ISSN 2694-085X
Éditeur: IEEE
DOI: 10.48550/arxiv.2210.01103

Electricity Load Lost in the Largest Windstorms—Is the Fragility-Based Model up to the Task? (s’ouvre dans une nouvelle fenêtre)

Auteurs: Justinas Jasiūnas; Ilona Láng-Ritter; Tatu Heikkinen; Peter D. Lund
Publié dans: Energies, Vol 16, Iss 15, p 5678 (2023), 2023, ISSN 1996-1073
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/en16155678

Triadic Approximation Reveals the Role of Interaction Overlap on the Spread of Complex Contagions on Higher-Order Networks (s’ouvre dans une nouvelle fenêtre)

Auteurs: Giulio Burgio; Sergio Gómez; Alex Arenas
Publié dans: Physical Review Letters, 2024, ISSN 1079-7114
Éditeur: American Physical Society
DOI: 10.48550/arxiv.2306.11441

Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study (s’ouvre dans une nouvelle fenêtre)

Auteurs: Benjamin Steinegger; Clara Granell; Giacomo Rapisardi; Sergio Gómez; Joan Matamalas; David Soriano-Paños; Jesús Gómez-Gardeñes; Alex Arenas
Publié dans: JMIR Public Health and Surveillance, Vol 9, p e40514 (2023), 2023, ISSN 2369-2960
Éditeur: JMIR Public Health and Surveillance
DOI: 10.2196/40514

Re-interpreting rules interpretability (s’ouvre dans une nouvelle fenêtre)

Auteurs: Linara Adilova; Michael Kamp; Gennady Andrienko; Natalia Andrienko
Publié dans: International Journal of Data Science and Analytics, 2022, ISSN 2364-4168
Éditeur: Springer Nature
DOI: 10.21203/rs.3.rs-1525944/v1

Complex Event Recognition with Allen Relations (s’ouvre dans une nouvelle fenêtre)

Auteurs: Periklis Mantenoglou; Dimitrios Kelesis; Alexander Artikis
Publié dans: International Conference on Principles of Knowledge Representation and Reasoning, 2023, ISSN 2334-1033
Éditeur: IJCAI Organization
DOI: 10.5281/zenodo.8171625

EnvClus*: Extracting Common Pathways for Effective Vessel Trajectory Forecasting (s’ouvre dans une nouvelle fenêtre)

Auteurs: Zygouras, Nikolas; Troupiotis-Kapeliaris, Alexandros; Zissis, Dimitrios
Publié dans: IEEE Access, 2024, ISSN 2169-3536
Éditeur: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.5281/zenodo.13376844

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