941 resultados para Semantic Errors


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Il progetto QRPlaces - Semantic Events, oggetto di questo lavoro, focalizza l’attenzione sull’analisi, la progettazione e l’implementazione di un sistema che sia in grado di modellare i dati, relativi a diversi eventi facenti parte del patrimonio turistico - culturale della Regione Emilia Romagna 1, rendendo evidenti i vantaggi associati ad una rappresentazione formale incentrata sulla Semantica. I dati turistico - culturali sono intesi in questo ambito sia come una rappresentazione di “qualcosa che accade in un certo punto ad un certo momento” (come ad esempio un concerto, una sagra, una raccolta fondi, una rappresentazione teatrale e quant’altro) sia come tradizioni e costumi che costituiscono il patrimonio turistico-culturale e a cui si fa spesso riferimento con il nome di “Cultural Heritage”. Essi hanno la caratteristica intrinseca di richiedere una conoscenza completa di diverse informa- zioni correlata, come informazioni di geo localizzazione relative al luogo fisico che ospita l’evento, dati biografici riferiti all’autore o al soggetto che è presente nell’evento piuttosto che riferirsi ad informazioni che descrivono nel dettaglio tutti gli oggetti, come teatri, cinema, compagnie teatrali che caratterizzano l’evento stesso. Una corretta rappresentazione della conoscenza ad essi legata richiede, pertanto, una modellazione in cui i dati possano essere interconnessi, rivelando un valore informativo che altrimenti resterebbe nascosto. Il lavoro svolto ha avuto lo scopo di realizzare un dataset rispondente alle caratteristiche tipiche del Semantic Web grazie al quale è stato possibile potenziare il circuito di comunicazione e informazione turistica QRPlaces 2. Nello specifico, attraverso la conversione ontologica di dati di vario genere relativi ad eventi dislocati nel territorio, e sfruttando i principi e le tecnologie del Linked Data, si è cercato di ottenere un modello informativo quanto più possibile correlato e arricchito da dati esterni. L’obiettivo finale è stato quello di ottenere una sorgente informativa di dati interconnessi non solo tra loro ma anche con quelli presenti in sorgenti esterne, dando vita ad un percorso di collegamenti in grado di evidenziare una ricchezza informativa utilizzabile per la creazione di valore aggiunto che altrimenti non sarebbe possibile ottenere. Questo aspetto è stato realizzato attraverso un’in- terfaccia di MashUp che utilizza come sorgente il dataset creato e tutti i collegamenti con la rete del Linked Data, in grado di reperire informazioni aggiuntive multi dominio.

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This work is concerned with the increasing relationships between two distinct multidisciplinary research fields, Semantic Web technologies and scholarly publishing, that in this context converge into one precise research topic: Semantic Publishing. In the spirit of the original aim of Semantic Publishing, i.e. the improvement of scientific communication by means of semantic technologies, this thesis proposes theories, formalisms and applications for opening up semantic publishing to an effective interaction between scholarly documents (e.g., journal articles) and their related semantic and formal descriptions. In fact, the main aim of this work is to increase the users' comprehension of documents and to allow document enrichment, discovery and linkage to document-related resources and contexts, such as other articles and raw scientific data. In order to achieve these goals, this thesis investigates and proposes solutions for three of the main issues that semantic publishing promises to address, namely: the need of tools for linking document text to a formal representation of its meaning, the lack of complete metadata schemas for describing documents according to the publishing vocabulary, and absence of effective user interfaces for easily acting on semantic publishing models and theories.

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Many industries and academic institutions share the vision that an appropriate use of information originated from the environment may add value to services in multiple domains and may help humans in dealing with the growing information overload which often seems to jeopardize our life. It is also clear that information sharing and mutual understanding between software agents may impact complex processes where many actors (humans and machines) are involved, leading to relevant socioeconomic benefits. Starting from these two input, architectural and technological solutions to enable “environment-related cooperative digital services” are here explored. The proposed analysis starts from the consideration that our environment is physical space and here diversity is a major value. On the other side diversity is detrimental to common technological solutions, and it is an obstacle to mutual understanding. An appropriate environment abstraction and a shared information model are needed to provide the required levels of interoperability in our heterogeneous habitat. This thesis reviews several approaches to support environment related applications and intends to demonstrate that smart-space-based, ontology-driven, information-sharing platforms may become a flexible and powerful solution to support interoperable services in virtually any domain and even in cross-domain scenarios. It also shows that semantic technologies can be fruitfully applied not only to represent application domain knowledge. For example semantic modeling of Human-Computer Interaction may support interaction interoperability and transformation of interaction primitives into actions, and the thesis shows how smart-space-based platforms driven by an interaction ontology may enable natural ad flexible ways of accessing resources and services, e.g, with gestures. An ontology for computational flow execution has also been built to represent abstract computation, with the goal of exploring new ways of scheduling computation flows with smart-space-based semantic platforms.

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The aim of the thesis is to investigate the topic of semantic under-determinacy, i.e. the failure of the semantic content of certain expressions to determine a truth-evaluable utterance content. In the first part of the thesis, I engage with the problem of setting apart semantic under-determinacy as opposed to other phenomena such as ambiguity, vagueness, indexicality. As I will argue, the feature that distinguishes semantic under-determinacy from these phenomena is its being explainable solely in terms of under-articulation. In the second part of the thesis, I discuss the topic of how communication is possible, despite the semantic under-determinacy of language. I discuss a number of answers that have been offered: (i) the Radical Contextualist explanation which emphasises the role of pragmatic processes in utterance comprehension; (ii) the Indexicalist explanation in terms of hidden syntactic positions; (iii) the Relativist account, which regards sentences as true or false relative to extra coordinates in the circumstances of evaluation (besides possible worlds). In the final chapter, I propose an account of the comprehension of utterances of semantically under-determined sentences in terms of conceptual constraints, i.e. ways of organising information which regulate thought and discourse on certain matters. Conceptual constraints help the hearer to work out the truth-conditions of an utterance of a semantically under-determined sentence. Their role is clearly semantic, in that they contribute to “what is said” (rather than to “what is implied”); however, they do not respond to any syntactic constraint. The view I propose therefore differs, on the one hand, from Radical Contextualism, because it stresses the role of semantic-governed processes as opposed to pragmatics-governed processes; on the other hand, it differs from Indexicalism in its not endorsing any commitment as to hidden syntactic positions; and it differs from Relativism in that it maintains a monadic notion if truth.

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L’Exploratory Search, paradigma di ricerca basato sulle attività di scoperta e d’apprendimento, è stato per diverso tempo ignorato dai motori di ricerca tradizionali. Invece, è spesso dalle ricerche esplorative che nascono le idee più innovative. Le recenti tecnologie del Semantic Web forniscono le soluzioni che permettono d’implementare dei motori di ricerca capaci di accompagnare gli utenti impegnati in tale tipo di ricerca. Aemoo, motore di ricerca sul quale s’appoggia questa tesi ne è un esempio efficace. A partire da quest’ultimo e sempre con l’aiuto delle tecnologie del Web of Data, questo lavoro si propone di fornire una metodologia che permette di prendere in considerazione la singolarità del profilo di ciascun utente al fine di guidarlo nella sua ricerca esplorativa in modo personalizzato. Il criterio di personalizzazione che abbiamo scelto è comportamentale, ovvero basato sulle decisioni che l’utente prende ad ogni tappa che ritma il processo di ricerca. Implementando un prototipo, abbiamo potuto testare la validità di quest’approccio permettendo quindi all’utente di non essere più solo nel lungo e tortuoso cammino che porta alla conoscenza.

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Nel presente lavoro si introduce un nuovo indice per la valutazione dei prodotti della ricerca: l'indice di multidisciplinarieta`. Questa nuova metrica puo` essere un interessante parametro di valutazione: il panorama degli studi multidisciplinari e` vasto ed eterogeneo, ed all'interno di questo sono richieste necessarie competenze trasversali. Le attuali metriche adottate nella valutazione di un accademico, di un journal, o di una conferenza non tengono conto di queste situazioni intermedie, e limitano la loro valutazione dell'impatto al semplice conteggio delle citazioni ricevute. Il risultato di tale valutazione consiste in un valore dell'impatto della ricerca senza una connotazione della direzione e della rilevanza di questa nel contesto delle altre discipline. L'indice di multidisciplinarieta` proposto si integrerebbe allora all'interno dell'attuale panorama delle metriche di valutazione della ricerca, offrendo -accanto ad una quantificazione dell'impatto- una quantificazione della varieta` dei contesti disciplinari nei quali si inserisce.

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The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.

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Das aSPECT Spektrometer wurde entworfen, um das Spektrum der Protonen beimrnZerfall freier Neutronen mit hoher Präzision zu messen. Aus diesem Spektrum kann dann der Elektron-Antineutrino Winkelkorrelationskoeffizient "a" mit hoher Genauigkeit bestimmt werden. Das Ziel dieses Experiments ist es, diesen Koeffizienten mit einem absoluten relativen Fehler von weniger als 0.3% zu ermitteln, d.h. deutlich unter dem aktuellen Literaturwert von 5%.rnrnErste Messungen mit dem aSPECT Spektrometer wurden an der Forschungsneutronenquelle Heinz Maier-Leibnitz in München durchgeführt. Jedoch verhinderten zeitabhängige Instabilitäten des Meßhintergrunds eine neue Bestimmung von "a".rnrnDie vorliegende Arbeit basiert hingegen auf den letzten Messungen mit dem aSPECTrnSpektrometer am Institut Laue-Langevin (ILL) in Grenoble, Frankreich. Bei diesen Messungen konnten die Instabilitäten des Meßhintergrunds bereits deutlich reduziert werden. Weiterhin wurden verschiedene Veränderungen vorgenommen, um systematische Fehler zu minimieren und um einen zuverlässigeren Betrieb des Experiments sicherzustellen. Leider konnte aber wegen zu hohen Sättigungseffekten der Empfängerelektronik kein brauchbares Ergebnis gemessen werden. Trotzdem konnten diese und weitere systematische Fehler identifiziert und verringert, bzw. sogar teilweise eliminiert werden, wovon zukünftigernStrahlzeiten an aSPECT profitieren werden.rnrnDer wesentliche Teil der vorliegenden Arbeit befasst sich mit der Analyse und Verbesserung der systematischen Fehler, die durch das elektromagnetische Feld aSPECTs hervorgerufen werden. Hieraus ergaben sich vielerlei Verbesserungen, insbesondere konnten die systematischen Fehler durch das elektrische Feld verringert werden. Die durch das Magnetfeld verursachten Fehler konnten sogar soweit minimiert werden, dass nun eine Verbesserung des aktuellen Literaturwerts von "a" möglich ist. Darüber hinaus wurde in dieser Arbeit ein für den Versuch maßgeschneidertes NMR-Magnetometer entwickelt und soweit verbessert, dass nun Unsicherheiten bei der Charakterisierung des Magnetfeldes soweit reduziert wurden, dass sie für die Bestimmung von "a" mit einer Genauigkeit von mindestens 0.3% vernachlässigbar sind.

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Principale obiettivo della ricerca è quello di ricostruire lo stato dell’arte in materia di sanità elettronica e Fascicolo Sanitario Elettronico, con una precipua attenzione ai temi della protezione dei dati personali e dell’interoperabilità. A tal fine sono stati esaminati i documenti, vincolanti e non, dell’Unione europea nonché selezionati progetti europei e nazionali (come “Smart Open Services for European Patients” (EU); “Elektronische Gesundheitsakte” (Austria); “MedCom” (Danimarca); “Infrastruttura tecnologica del Fascicolo Sanitario Elettronico”, “OpenInFSE: Realizzazione di un’infrastruttura operativa a supporto dell’interoperabilità delle soluzioni territoriali di fascicolo sanitario elettronico nel contesto del sistema pubblico di connettività”, “Evoluzione e interoperabilità tecnologica del Fascicolo Sanitario Elettronico”, “IPSE - Sperimentazione di un sistema per l’interoperabilità europea e nazionale delle soluzioni di Fascicolo Sanitario Elettronico: componenti Patient Summary e ePrescription” (Italia)). Le analisi giuridiche e tecniche mostrano il bisogno urgente di definire modelli che incoraggino l’utilizzo di dati sanitari ed implementino strategie effettive per l’utilizzo con finalità secondarie di dati sanitari digitali , come Open Data e Linked Open Data. L’armonizzazione giuridica e tecnologica è vista come aspetto strategico per ridurre i conflitti in materia di protezione di dati personali esistenti nei Paesi membri nonché la mancanza di interoperabilità tra i sistemi informativi europei sui Fascicoli Sanitari Elettronici. A questo scopo sono state individuate tre linee guida: (1) armonizzazione normativa, (2) armonizzazione delle regole, (3) armonizzazione del design dei sistemi informativi. I principi della Privacy by Design (“prottivi” e “win-win”), così come gli standard del Semantic Web, sono considerate chiavi risolutive per il suddetto cambiamento.

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The aim of this dissertation is to show the power of contrastive analysis in successfully predicting the errors a language learner will make by means of a concrete case study. First, there is a description of what language transfer is and why it is important in the matter of second language acquisition. Second, a brief explanation of the history and development of contrastive analysis will be offered. Third, the focus of the thesis will move to an analysis of errors usually made by language learners. To conclude, the dissertation will focus on the concrete case study of a Russian learner of English: after an analysis of the errors the student is likely to make, a recorded conversation will be examined.

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La ricerca nel campo del cultural heritage management ha adottato negli ultimi decenni le tecnologie web quali strumenti privilegiati per stabilire i nuovi approcci e indirizzi nella valorizzazione della conoscenza. Questa tesi si colloca nell'ambito interdisciplinare tra le scienze umanistiche e informatiche e si fonda sulla consapevolezza del reciproco arricchimento che può derivare dal continuo confronto, le une disponendo di mezzi più espressivi e popolari per divulgare il proprio patrimonio e le altre usufruendo di “materia prima” autorevole (ossia dati strutturati di qualità e alto livello di fiducia) in fase di sperimentazione. Lo studio dei punti di tangenza tra le discipline muove da due ambiti precisi, ovvero le applicazioni informatiche nel campo dell'archivistica e gli sviluppi del semantic web nel settore delle digital humanities.

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This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

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Il presente lavoro si occupa di fare una rassegna esaustiva di alcuni Linked Open Dataset nel contesto delle pubblicazioni scientifiche, cercando di inquadrare la loro eterogeneità ed identificando i principali pregi e difetti di ciascuno. Inoltre, descriviamo il nostro prototipo GReAT (Giorgi's Redundant Authors Tool), creato per il corretto riconoscimento e disambiguazione degli autori.

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Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

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The aim of this dissertation is to provide a translation from English into Italian of an extract from the research report “The Nature of Errors Made by Drivers”. The research was conducted by the MUARC (the Monash University Accident Research Centre) and published in June 2011 by Austroads, the association of Australasian road transport and traffic agencies. The excerpt chosen for translation is the third chapter, which provides an overview of the on-road pilot study conducted to analyse why drivers make mistakes during their everyday drive, including the methodology employed and the results obtained. This work is divided into six sections. It opens with an introduction on the topic and the formal structure of the report, followed by the first chapter, which provides an overview of the main features of the languages for special purposes and the specialised texts, an analysis of the text type and a presentation of the extract chosen for translation. In the second chapter the linguistic and extralinguistic resources available to specialised translators are presented, focussing on the ones used to translate the text. The third chapter is dedicated to the source text and its translation, while the fourth one provides an analysis of the strategies chosen to translate the text and a comment on the solutions to problematic passages. Finally, the last section – the conclusion – provides a comment on the entire work and on the professional activity of translators. The work closes with an appendix, which contains a glossary of the terms extracted from the translated text.