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Institution

University of Trento

EducationTrento, Italy
About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.


Papers
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Journal ArticleDOI
TL;DR: Extensions to the Tropos methodology are introduced to enable it to model security concerns throughout the whole development process to help towards the development of more secure multiagent systems.
Abstract: Although security plays an important role in the development of multiagent systems, a careful analysis of software development processes shows that the definition of security requirements is, usually, considered after the design of the system. One of the reasons is the fact that agent oriented software engineering methodologies have not integrated security concerns throughout their developing stages. The integration of security concerns during the whole range of the development stages can help towards the development of more secure multiagent systems. In this paper we introduce extensions to the Tropos methodology to enable it to model security concerns throughout the whole development process. A description of the new concepts and modelling activities is given along with a discussion on how these concepts and modelling activities are integrated to the current stages of Tropos. A real life case study from the health and social care sector is used to illustrate the approach.

397 citations

Journal ArticleDOI
TL;DR: In this article, the Maud Rietveld texture analysis from diffraction images collected with CCDs or image plates is described and the results obtained using a custom laboratory image plate camera developed for texture analysis.
Abstract: The procedure to perform Rietveld texture analysis from diffraction images collected with CCDs or image plates is shown. In some cases only one transmission image may be sufficient to obtain an Orientation Distribution Function (ODF) if a sufficient number of peaks are included. The images are transformed in spectra and analyzed using the Maud Rietveld program containing some recently developed texture model well suited for this kind of analysis. In this work we will present the results obtained using a custom laboratory image plate camera developed for texture analysis. The instrument may work with a curve image plate detector in reflection condition or with a flat detector in transmission. The reflection condition is used mainly for ceramics and metal-alloys and the transmission mode for polymers and fibres. We will show how with the combination of such camera and the Rietveld Texture Analysis method we were able to analyze the ODF of the martensitic phase of Shape Memory Alloy (monoclinic NiTi SMA) as well as to obtain the quantitative texture of low symmetry polymers in fibre form.

397 citations

Proceedings Article
08 Jul 2012
TL;DR: While visual models with state-of-the-art computer vision techniques perform worse than textual models in general tasks, they are as good or better models of the meaning of words with visual correlates such as color terms, even in a nontrivial task that involves nonliteral uses of such words.
Abstract: Our research aims at building computational models of word meaning that are perceptually grounded. Using computer vision techniques, we build visual and multimodal distributional models and compare them to standard textual models. Our results show that, while visual models with state-of-the-art computer vision techniques perform worse than textual models in general tasks (accounting for semantic relatedness), they are as good or better models of the meaning of words with visual correlates such as color terms, even in a nontrivial task that involves nonliteral uses of such words. Moreover, we show that visual and textual information are tapping on different aspects of meaning, and indeed combining them in multimodal models often improves performance.

397 citations

Journal ArticleDOI
TL;DR: In this article, the authors exploit a unique data set created in 1999 on a sample of 228 public, nonprofit, and for-profit organizations operating in the social service sector, and on 2,066 workers.
Abstract: Exploiting a unique data set created in 1999 on a sample of 228 public, nonprofit, and for-profit organizations operating in the social service sector, and on 2,066 workers, the article tests wheth...

394 citations

Book ChapterDOI
20 Oct 2003
TL;DR: This paper shows how ontologies can be contextualized, thus acquiring certain useful properties that a pure shared approach cannot provide, and develops Context OWL (C-OWL), a language whose syntax and semantics have been obtained by extending the OWLntax and semantics to allow for the representation of contextual ontologies.
Abstract: Ontologies are shared models of a domain that encode a view which is common to a set of different parties. Contexts are local models that encode a party's subjective view of a domain. In this paper we show how ontologies can be contextualized, thus acquiring certain useful properties that a pure shared approach cannot provide. We say that an ontology is contextualized or, also, that it is a contextual ontology, when its contents are kept local, and therefore not shared with other ontologies, and mapped with the contents of other ontologies via explicit (context) mappings. The result is Context OWL (C-OWL), a language whose syntax and semantics have been obtained by extending the OWL syntax and semantics to allow for the representation of contextual ontologies.

390 citations


Authors

Showing all 10758 results

NameH-indexPapersCitations
Yi Chen2174342293080
Jie Zhang1784857221720
Richard B. Lipton1762110140776
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
Andrea Bocci1722402176461
P. Chang1702154151783
Bradley Cox1692150156200
Marc Weber1672716153502
Guenakh Mitselmakher1651951164435
Brian L Winer1621832128850
J. S. Lange1602083145919
Ralph A. DeFronzo160759132993
Darien Wood1602174136596
Robert Stone1601756167901
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023158
2022340
20212,399
20202,286
20192,129
20181,943