Catalogo Ricerca UNISI

Catalogo Ricerca UNISI: [84343] Home page macrotipologia

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1 Contributo su Rivista 50610
- 1.1 Articolo in rivista 46481
- 1.2 Recensione in rivista 1609
- 1.3 Scheda bibliografica 55
- 1.4 Nota a sentenza 669
- 1.5 Abstract in rivista 1769
- 1.6 Traduzione in rivista 27

2 Contributo in Volume 15565
- 2.1 Contributo in volume (Capitolo o Saggio) 13686
- 2.2 Prefazione/Postfazione 545
- 2.3 Breve introduzione 212
- 2.4 Voce (in dizionario o enciclopedia) 723
- 2.5 Traduzione in volume 66
- 2.6 Recensione in volume 30
- 2.7 Schede di catalogo 303

3 Libro 2969
- 3.1 Monografia o trattato scientifico 2670
- 3.2 Concordanza 4
- 3.3 Indice 11
- 3.4 Bibliografia 9
- 3.5 Edizione critica 78
- 3.6 Pubblicazione di fonti inedite 24
- 3.7 Commento scientifico 81
- 3.8 Traduzione di libro 92

4 Contributo in Atti di Convegno (Proceeding) 11461
- 4.1 Contributo in Atti di convegno 7886
- 4.2 Abstract in Atti di convegno 3196
- 4.3 Poster 379

5 Altro 936
- 5.01 Composizione 2
- 5.02 Disegno 0
- 5.03 Design 0
- 5.04 Performance 0
- 5.05 Esposizione 3
- 5.06 Mostra 22
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 0
- 5.09 Cartografia 156
- 5.10 Banca dati 44
- 5.11 Software 13
- 5.12 Articolo sul sito web 137
- 5.13 Altro 559

6 Brevetti 234
- 6.1 Brevetto 234

7 Curatele 1626
- 7.1 Curatela 1626

8 Tesi di dottorato 944
- 8.1 Tesi Dottorato 944

Prodotti recenti

Giovanni Pisano: un'attestazione in meno e una sicura attestazione in più

The article examines two documentary attestations related to Giovanni Pisano. The first is purely speculative: it involves the proposal put forth in 1994 by Andrew Ladis to recognize the great sculptor among the affiliates of the Compagnia dei Raccomandati al Crocifisso, a fraternity of ‘disciplinati’ that represented the most significant lay devotees in Siena during the late Middle Ages. There was a belief that Giovanni Pisano could be identified as the confraternity member “Giovanni dell’Uo...

Bearing Failure Classification with Low Complexity Neural Network

In this work, an AI enabled fault classification system for roller bearings based on an approach tailored for embedded implementation is presented. The fault classification system is based on vibration signal analysis and exploits a low computational cost neural network (NN) along with a novel low-complexity preprocessing technique, which allows for minimizing the dependence of the classifier design on the bearing rotational speed and on the vibration signal sampling frequency. The proposed f...

Transglutaminases from plant sources

This chapter presents the specific characteristics of transglutaminases (TGases) in different plant species by comparing them with those of the best-known TGases of animal origin. It, therefore, explains the involvement of TGases in specific aspects of the physiology of plant organisms, highlighting, above all at the cellular level, similar roles, and differences concerning those performed by animal TGases. The features of the putative gene sequences encoding for plant TGases are illustrated ...

A Discrete Geometry Method for Atom Depth Computation in Complex Molecular Systems

The field of structural biology is rapidly advancing thanks to significant improvements in X-ray crystallography, nuclear magnetic resonance (NMR), cryo-electron microscopy, and bioinformatics. The identification of structural descriptors allows for the correlation of functional properties with characteristics such as accessible molecular surfaces, volumes, and binding sites. Atom depth has been recognized as an additional structural feature that links protein structures to their folding and ...

Extending Logic Explained Networks to Text Classification

Recently, Logic Explained Networks (LENs) have been proposed as explainable-by-design neural models providing logic explanations for their predictions. However, these models have only been applied to vision and tabular data, and they mostly favour the generation of global explanations, while local ones tend to be noisy and verbose. For these reasons, we propose LENp, improving local explanations by perturbing input words, and we test it on text classification. Our results show that (i) LENp p...

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