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eScience Research Group - Fluminense Federal University's Projects

criminal icon criminal

CRiMINaL is a framework to uncover crimes patterns using logic-based relational machine learning techniques develop by UFF eScience group

df-aset icon df-aset

Um dataset de traces de proveniência em dataflows

flower-prov icon flower-prov

Provenance-based Dynamic Fine-Tuning of Federated Machine Learning Framework

instructor icon instructor

IdeNtification of anomalous veSsel TRajectory Using ClusTers Of tRajectories

newscollab icon newscollab

NewsCollab: a crowdsourcing system to support data-driven journalism

nmfst.p icon nmfst.p

The NMFSt.P Notebook is introduced as a tool in bioinformatics for conducting exploratory analysis on phylogenetic trees. It simplifies the comparison of multiple trees to identify frequent subtrees, addressing the computational intensity and laboriousness associated with this task, particularly in scenarios involving large input tree sets.

optic icon optic

OPTImization Confidentially of workflow results

pandora icon pandora

A Collaborative Platform for Semiautomatic Transcription of Handwritten Crime Reports

pargres icon pargres

ParGRES Database Cluster Middleware

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