Preserving data privacy in Machine Learning pipelines with Federated Learning
FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.
Leveraging Large Language Models for Financial Predictions
FAME project blog
In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.
FAME: Federated Decentralized Trusted Data Marketplace for Embedded Finance
IEEE
Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.
ZONESEC: built-in cyber-security for wide area surveillance system
ZONESEC: built-in cyber-security for wide area surveillance system. Aljosa Pasic, Jose-Ramon Martinez-Salio, Susana Gonzalez Zarzosa, Rodrigo Diaz. Reggio Calabria, Italy, August 29 – September 1, 2017 (ARES 2017)
ZONESEC: built-in cyber-security for wide area surveillance system
It describes how the multi-agent architecture originaly proposed in ZONeSEC project can be applied also to cyber-security components in order to address challenges such as cost, complexity or difficulty to coordinate activities in distributed settings, such as cross-border surveillance operations
Large Scale Surveillance, Detection and Alerts Information Management System for Critical Infrastructure
University of Southampton IT Innovation Centre prepared paper named “Large Scale Surveillance, Detection and Alerts Information Management System for Critical Infrastructure”.
A Fully Balanced Ultra-Wide Band Mixer MMIC with Multi-Tanh Triplet Input for High Dynamic Range Radar Receiver Systems
Technical university of Dresden published three papers: “A Fully Balanced Ultra-Wide Band Mixer MMIC with Multi-Tanh Triplet Input for High Dynamic Range Radar Receiver Systems” was accepted for ICNF conference in Vilnius, from June 20-23 (http://www.icnf2017.ff.vu.lt/) and another paper, named “
ZONESEC: built-in cyber-security for wide area surveillance system
Paper named “ZONESEC: built-in cyber-security for wide area surveillance system” has been accepted for publication in S-CI 2017 Workshop, which will take place in conjunction with ARES 2017 to be held 29 august-1 September in Reggio Calabria, Italy.