Catalogo Ricerca UNISI

Catalogo Ricerca UNISI: [96110] Home page macrotipologia

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1 Contributo su Rivista 58922
- 1.1 Articolo in rivista 54398
- 1.2 Recensione in rivista 1805
- 1.3 Scheda bibliografica 74
- 1.4 Nota a sentenza 750
- 1.5 Abstract in rivista 1866
- 1.6 Traduzione in rivista 29

2 Contributo in Volume 17185
- 2.1 Contributo in volume (Capitolo o Saggio) 15091
- 2.2 Prefazione/Postfazione 605
- 2.3 Breve introduzione 243
- 2.4 Voce (in dizionario o enciclopedia) 790
- 2.5 Traduzione in volume 72
- 2.6 Recensione in volume 31
- 2.7 Schede di catalogo 353

3 Libro 3190
- 3.1 Monografia o trattato scientifico 2872
- 3.2 Concordanza 4
- 3.3 Indice 11
- 3.4 Bibliografia 11
- 3.5 Edizione critica 91
- 3.6 Pubblicazione di fonti inedite 25
- 3.7 Commento scientifico 82
- 3.8 Traduzione di libro 94

4 Contributo in Atti di Convegno (Proceeding) 12331
- 4.1 Contributo in Atti di convegno 8543
- 4.2 Abstract in Atti di convegno 3368
- 4.3 Poster 420

5 Altro 1062
- 5.01 Composizione 2
- 5.02 Disegno 0
- 5.03 Design 0
- 5.04 Performance 0
- 5.05 Esposizione 3
- 5.06 Mostra 23
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 0
- 5.09 Cartografia 158
- 5.10 Banca dati 54
- 5.11 Software 19
- 5.12 Articolo sul sito web 210
- 5.13 Altro 593

6 Brevetti 242
- 6.1 Brevetto 242

7 Curatele 1798
- 7.1 Curatela 1798

8 Tesi di dottorato 1383
- 8.1 Tesi Dottorato 1383

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Keynote: Learning from World Wide Human-AI Social Interactions

The technologies most profoundly influencing contemporary society are based on the Web, on the social networks, and on Artificial Intelligence (AI). While these systems have considerably expanded human capacities for communication and knowledge exchange, they have simultaneously undermined privacy, concentrated control within a few dominant entities, and imposed substantial energy demands. The coexistence of humans and AI remains uncertain and largely unregulated, introducing risks that exten...

Machine learning for multiple sclerosis classification and disability prediction using clinical and MRI data

Introduction – Multiple sclerosis (MS) is a complex disease characterized by diverse clinical presentations and progression patterns. Accurate classification and prediction of disease severity are crucial for personalized treatment. We applied machine learning (ML) to demographic, clinical and MRI data to distinguish MS patients from healthy controls (HC), classify MS phenotypes and predict disability using the Expanded Disability Status Scale (EDSS) score. Methods – We included 1, 554 MS pat...

Neuro-Symbolic Learning from Temporal Sequences in Safety-Critical Systems

Safety-critical systems have seldom been used as an application domain for neuro-symbolic AI, despite their inherent characteristics that combine generation and processing of raw data, coming from heterogeneous devices, with enforcement or discovery of properties, usually encoded as rules or constraints. In this paper, we consider the task of classifying sequences of perceptual stimuli collected from a safety-critical system, where safety-related properties are represented in the form of line...

A Peer-to-Peer Platform for Lifelong Learning in Dynamic Human-AI Agent Communities

The lifelong learning research community often relies on simulated data streams derived from static, offline datasets without directly experiencing real-world environments where learning machines continuously develop and interact with others. In order to bridge this gap, this paper introduces UNaIVERSE (https://unaiverse.io), an open-source, decentralized peer-to-peer platform designed for agents (whether human or artificial) that adapt over time. UNaIVERSE enables authentic lifelong learning...

Habitat-specific and pressure-driven differences in community composition and conservation status in Mediterranean coastal habitats

Mediterranean dunes and salt marshes are home to a wide range of organisms and unique and fragile plant species assemblages. To correctly assess dunes and salt marshes conservation status a thorough knowledge of community properties and how these respond to anthropic pressure is needed. Here we analyse data from 647 vegetation plots located along the coast of Tuscany. To first assess the variability among habitats and the most informative metrics and functional traits we calculated taxonomic,...

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