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The TrUST Project: Improving the Fruition of Historical Centres through Smart Objects.

, , and . EUSPN/ICTH, volume 63 of Procedia Computer Science, page 159-164. Elsevier, (2015)

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stellar formation rates in galaxies using machine learning models., , , , and . ESANN, (2018)Integrated data access, visualization and analysis for Galactic Plane surveys: the VIALACTEA case., , , , , , , , , and 1 other author(s). Astroinformatics, volume 12 of Proceedings of the International Astronomical Union, page 291-298. Cambridge University Press, (2016)C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data., , , , , and . Astroinformatics, volume 12 of Proceedings of the International Astronomical Union, page 327-332. Cambridge University Press, (2016)Milky Way Analysis through a Science Gateway: Workflows and Resource Monitoring., , , , , , , , , and 4 other author(s). IWSG, volume 1871 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)VIALACTEA science gateway for Milky Way analysis., , , , , , , , , and 6 other author(s). Future Gener. Comput. Syst., (2019)Healthcare Data Summarization via Medical Entity Recognition and Generative AI., , , , , , , , and . itaDATA, volume 3606 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)Machine Learning Based Data Mining for Milky Way Filamentary Structures Reconstruction., , , , , , , , , and . Advances in Neural Networks, volume 54 of Smart Innovation, Systems and Technologies, Springer, (2016)SMuNe: A Smart Multisensor Network Based on Embedded Systems in IoT Environment., , and . SITIS, page 841-848. IEEE Computer Society, (2015)Milky way analysis through a Science Gateway: workflows and resource monitoring., , , , , , , , , and 4 other author(s). PeerJ PrePrints, (2017)Astrophysical Data Analytics based on Neural Gas Models, using the Classification of Globular Clusters as Playground., , , , , and . DAMDID/RCDL, volume 2022 of CEUR Workshop Proceedings, page 381-388. CEUR-WS.org, (2017)