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CORDIS - Risultati della ricerca dell’UE
CORDIS

Critical Action Planning over Extreme-Scale Data

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Initial Use Case Evaluation, Pilots, Demonstrators and Simulation Models and Tools (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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.

Pubblicazioni

Proactive Streaming Analytics at Scale: A Journey from the State-of-the-art to a Production Platform (si apre in una nuova finestra)

Autori: Giatrakos, Nikos; Alevizos, Elias; Deligiannakis, Antonios; Kinkenberg, Ralf; Artikis, Alexander
Pubblicato in: ACM CIKM, 2023
Editore: ACM
DOI: 10.1145/3583780.3615293

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

Autori: Pottebaum, Jens; Rechberger, Christina; Hieb, Michael; Gräßler, Iris; Resch, Christian
Pubblicato in: 2023, ISBN 978-3-900397-11-1
Editore: Disaster Competence Network Austria

The Flow of Trust: A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications (si apre in una nuova finestra)

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

On the number of stable solutions in the Kuramoto model (si apre in una nuova finestra)

Autori: Alex Arenas; Antonio Garijo; Sergio Gómez; Jordi Villadelprat
Pubblicato in: Chaos, 2023, ISSN 1089-7682
Editore: Chaos
DOI: 10.1063/5.0161977

Dual Control of Coupled Oscillator Networks (si apre in una nuova finestra)

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

Electricity Load Lost in the Largest Windstorms—Is the Fragility-Based Model up to the Task? (si apre in una nuova finestra)

Autori: Justinas Jasiūnas; Ilona Láng-Ritter; Tatu Heikkinen; Peter D. Lund
Pubblicato in: Energies, Vol 16, Iss 15, p 5678 (2023), 2023, ISSN 1996-1073
Editore: 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 (si apre in una nuova finestra)

Autori: Giulio Burgio; Sergio Gómez; Alex Arenas
Pubblicato in: Physical Review Letters, 2024, ISSN 1079-7114
Editore: 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 (si apre in una nuova finestra)

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

Re-interpreting rules interpretability (si apre in una nuova finestra)

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

Complex Event Recognition with Allen Relations (si apre in una nuova finestra)

Autori: Periklis Mantenoglou; Dimitrios Kelesis; Alexander Artikis
Pubblicato in: International Conference on Principles of Knowledge Representation and Reasoning, 2023, ISSN 2334-1033
Editore: IJCAI Organization
DOI: 10.5281/zenodo.8171625

EnvClus*: Extracting Common Pathways for Effective Vessel Trajectory Forecasting (si apre in una nuova finestra)

Autori: Zygouras, Nikolas; Troupiotis-Kapeliaris, Alexandros; Zissis, Dimitrios
Pubblicato in: IEEE Access, 2024, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.5281/zenodo.13376844

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