December 2020

Erasmus+ SAFEYOU+

SAFEYOU

SAFE YOU aims to dynamically contribute to anti-doping in fitness and amateur sports. To do so effectively we should abide by the following principles: (i) Primary prevention, (ii) Empowerment through education, and (iii) Strategic partnership. Title: SAFEYOU Duration: – Funded under: Erasmus+ EU Programme Coordinator: Aristotle University of Thessaloniki, GR Tweetsafe app website Project website

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Fix the Fixing

Fix the Fixing

Fix the Fixing aims to develop a user-friendly educational tool will that will be used by stakeholders to increase people’s involved in sport awareness about corruption, fraud and match-fixing in different types and levels of sport; teach coping skills on resisting offers and temptations to engage in match-fixing; and indicate ways to properly report match-fixing

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KNOWeSCAPE: Analyzing the dynamics of information and knowledge landscapes

KNOWeSCAPE

There is no escape from the expansion of information, so that structuring and locating meaningful knowledge becomes ever more difficult. This project will tackle this urgent problem using the unique networking and capacity-building features provided by the COST framework. For the first time, a platform will be created where information professionals, sociologists, physicists, digital humanities

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EICOS: foundations for perSOnalized Cooperative Information Ecosystems

EICOS

The aim of EICOS is to provide the methodology, the theoretical and modeling foundations as well as the algorithmic techniques and the necessary software architecture that will facilitate the personalization, integration, and evolution management facilities for information ecosystems that operate over a decentralized infrastructure for a large variety of data types. The fundamental idea that

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TRACER: Identifying software vulnerabilities and securing legacy systems

TRACER

Legacy systems are likely to contain software vulnerabilities that can lead to various security breaches. On the other hand, these systems contain valuable information about the environment, the creation and the evolution of the organization they support. For this reason, redesigning large systems in order to be secure and compatible with new technologies is not

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REVITAL: Real and Virtual Social Interactions

REVITAL

Real and Virtual Social Interactions and Reciprocities via efficient sentiment and affective analysis methodologies for extracting or recording and analyzing emotional information in real and virtual life. Detect and characterize patterns of ‘online’ communication with patterns of ‘offline’ or face to face communication in real social networks and studying patterns of human emotions in real

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SEN2SOC: Sensors talk and humans sense

SmartSantander

Social and sensor data streams integration via data mining and statistical analysis methodologies and practices utilized to communicate sensor measurements to the public (citizens, authorities, etc), while at the same time human sensing is utilized in order to improve IoT infrastructures. Design and develop applications (Web and/or mobile) which will leverage evolving data streams occurring

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Cloud4Trends: Leveraging the cloud infrastructure for localized real-time trend detection in social media

VENUS-C

Cloud-based framework for social networks trends detection and analysis via real-time large-scale data clustering techniques, evolving social graph mining with tailored data preprocessing and cleaning. Emphasis placed on analyzing societal concerns and reaching consensus on collective decision-making via tailored web mining techniques which utilize the cloud infrastructure Venus-C to help address the challenges posed by

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ARCHIMEDIS: Enterprise Architecture for Digital Cities

ARCHIMEDIS

The purpose of this project concerns the investigation, determination and implementation of a common Enterprise Architecture, which can cover the particular needs of the most (if not of all) the different forms of digital cities. OSWINDS team has developed Social Data Observer as a platform which offers services to citizens and city visitors in terms

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MOVE: Knowledge Discovery from Moving Objects

MOVE

Develop improved methods for knowledge extraction from massive amounts of data regarding moving objects. This knowledge is essential to substantiate decision making in public and private sectors. Moving object data typically include trajectories of concrete objects (e.g. humans, vehicles, animals, and goods), as well as trajectories of abstract concepts (e.g. spreading diseases). While movement records

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