898 resultados para Digital Object Identifier (DOI)


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Generic programming is likely to become a new challenge for a critical mass of developers. Therefore, it is crucial to refine the support for generic programming in mainstream Object-Oriented languages — both at the design and at the implementation level — as well as to suggest novel ways to exploit the additional degree of expressiveness made available by genericity. This study is meant to provide a contribution towards bringing Java genericity to a more mature stage with respect to mainstream programming practice, by increasing the effectiveness of its implementation, and by revealing its full expressive power in real world scenario. With respect to the current research setting, the main contribution of the thesis is twofold. First, we propose a revised implementation for Java generics that greatly increases the expressiveness of the Java platform by adding reification support for generic types. Secondly, we show how Java genericity can be leveraged in a real world case-study in the context of the multi-paradigm language integration. Several approaches have been proposed in order to overcome the lack of reification of generic types in the Java programming language. Existing approaches tackle the problem of reification of generic types by defining new translation techniques which would allow for a runtime representation of generics and wildcards. Unfortunately most approaches suffer from several problems: heterogeneous translations are known to be problematic when considering reification of generic methods and wildcards. On the other hand, more sophisticated techniques requiring changes in the Java runtime, supports reified generics through a true language extension (where clauses) so that backward compatibility is compromised. In this thesis we develop a sophisticated type-passing technique for addressing the problem of reification of generic types in the Java programming language; this approach — first pioneered by the so called EGO translator — is here turned into a full-blown solution which reifies generic types inside the Java Virtual Machine (JVM) itself, thus overcoming both performance penalties and compatibility issues of the original EGO translator. Java-Prolog integration Integrating Object-Oriented and declarative programming has been the subject of several researches and corresponding technologies. Such proposals come in two flavours, either attempting at joining the two paradigms, or simply providing an interface library for accessing Prolog declarative features from a mainstream Object-Oriented languages such as Java. Both solutions have however drawbacks: in the case of hybrid languages featuring both Object-Oriented and logic traits, such resulting language is typically too complex, thus making mainstream application development an harder task; in the case of library-based integration approaches there is no true language integration, and some “boilerplate code” has to be implemented to fix the paradigm mismatch. In this thesis we develop a framework called PatJ which promotes seamless exploitation of Prolog programming in Java. A sophisticated usage of generics/wildcards allows to define a precise mapping between Object-Oriented and declarative features. PatJ defines a hierarchy of classes where the bidirectional semantics of Prolog terms is modelled directly at the level of the Java generic type-system.

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This thesis presents the outcomes of a Ph.D. course in telecommunications engineering. It is focused on the optimization of the physical layer of digital communication systems and it provides innovations for both multi- and single-carrier systems. For the former type we have first addressed the problem of the capacity in presence of several nuisances. Moreover, we have extended the concept of Single Frequency Network to the satellite scenario, and then we have introduced a novel concept in subcarrier data mapping, resulting in a very low PAPR of the OFDM signal. For single carrier systems we have proposed a method to optimize constellation design in presence of a strong distortion, such as the non linear distortion provided by satellites' on board high power amplifier, then we developed a method to calculate the bit/symbol error rate related to a given constellation, achieving an improved accuracy with respect to the traditional Union Bound with no additional complexity. Finally we have designed a low complexity SNR estimator, which saves one-half of multiplication with respect to the ML estimator, and it has similar estimation accuracy.

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To date the hospital radiological workflow is completing a transition from analog to digital technology. Since the X-rays digital detection technologies have become mature, hospitals are trading on the natural devices turnover to replace the conventional screen film devices with digital ones. The transition process is complex and involves not just the equipment replacement but also new arrangements for image transmission, display (and reporting) and storage. This work is focused on 2D digital detector’s characterization with a concern to specific clinical application; the systems features linked to the image quality are analyzed to assess the clinical performances, the conversion efficiency, and the minimum dose necessary to get an acceptable image. The first section overviews the digital detector technologies focusing on the recent and promising technological developments. The second section contains a description of the characterization methods considered in this thesis categorized in physical, psychophysical and clinical; theory, models and procedures are described as well. The third section contains a set of characterizations performed on new equipments that appears to be some of the most advanced technologies available to date. The fourth section deals with some procedures and schemes employed for quality assurance programs.

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L’elaborato ha lo scopo di presentare le nuove opportunità di business offerte dal Web. Il rivoluzionario cambiamento che la pervasività della Rete e tutte le attività correlate stanno portando, ha posto le aziende davanti ad un diverso modo di relazionarsi con i propri consumatori, che sono sempre più informati, consapevoli ed esigenti, e con la concorrenza. La sfida da accettare per rimanere competitivi sul mercato è significativa e il mutamento in rapido sviluppo: gli aspetti che contraddistinguono questo nuovo paradigma digitale sono, infatti, velocità, mutevolezza, ma al tempo stesso misurabilità, ponderabilità, previsione. Grazie agli strumenti tecnologici a disposizione e alle dinamiche proprie dei diversi spazi web (siti, social network, blog, forum) è possibile tracciare più facilmente, rispetto al passato, l’impatto di iniziative, lanci di prodotto, promozioni e pubblicità, misurandone il ritorno sull’investimento, oltre che la percezione dell’utente finale. Un approccio datacentrico al marketing, attraverso analisi di monitoraggio della rete, permette quindi al brand investimenti più mirati e ponderati sulla base di stime e previsioni. Tra le più significative strategie di marketing digitale sono citate: social advertising, keyword advertising, digital PR, social media, email marketing e molte altre. Sono riportate anche due case history: una come ottimo esempio di co-creation in cui il brand ha coinvolto direttamente il pubblico nel processo di produzione del prodotto, affidando ai fan della Pagina Facebook ufficiale la scelta dei gusti degli yogurt da mettere in vendita. La seconda, caso internazionale di lead generation, ha permesso al brand di misurare la conversione dei visitatori del sito (previa compilazione di popin) in reali acquirenti, collegando i dati di traffico del sito a quelli delle vendite. Esempio di come online e offline comunichino strettamente.

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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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This PhD thesis discusses the impact of Cloud Computing infrastructures on Digital Forensics in the twofold role of target of investigations and as a helping hand to investigators. The Cloud offers a cheap and almost limitless computing power and storage space for data which can be leveraged to commit either new or old crimes and host related traces. Conversely, the Cloud can help forensic examiners to find clues better and earlier than traditional analysis applications, thanks to its dramatically improved evidence processing capabilities. In both cases, a new arsenal of software tools needs to be made available. The development of this novel weaponry and its technical and legal implications from the point of view of repeatability of technical assessments is discussed throughout the following pages and constitutes the unprecedented contribution of this work

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This study concerns teachers’ use of digital technologies in student assessment, and how the learning that is developed through the use of technology in mathematics can be evaluated. Nowadays math teachers use digital technologies in their teaching, but not in student assessment. The activities carried out with technology are seen as ‘extra-curricular’ (by both teachers and students), thus students do not learn what they can do in mathematics with digital technologies. I was interested in knowing the reasons teachers do not use digital technology to assess students’ competencies, and what they would need to be able to design innovative and appropriate tasks to assess students’ learning through digital technology. This dissertation is built on two main components: teachers and task design. I analyze teachers’ practices involving digital technologies with Ruthven’s Structuring Features of Classroom Practice, and what relation these practices have to the types of assessment they use. I study the kinds of assessment tasks teachers design with a DGE (Dynamic Geometry Environment), using Laborde’s categorization of DGE tasks. I consider the competencies teachers aim to assess with these tasks, and how their goals relate to the learning outcomes of the curriculum. This study also develops new directions in finding how to design suitable tasks for student mathematical assessment in a DGE, and it is driven by the desire to know what kinds of questions teachers might be more interested in using. I investigate the kinds of technology-based assessment tasks teachers value, and the type of feedback they give to students. Finally, I point out that the curriculum should include a range of mathematical and technological competencies that involve the use of digital technologies in mathematics, and I evaluate the possibility to take advantage of technology feedback to allow students to continue learning while they are taking a test.

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In this work we study a model for the breast image reconstruction in Digital Tomosynthesis, that is a non-invasive and non-destructive method for the three-dimensional visualization of the inner structures of an object, in which the data acquisition includes measuring a limited number of low-dose two-dimensional projections of an object by moving a detector and an X-ray tube around the object within a limited angular range. The problem of reconstructing 3D images from the projections provided in the Digital Tomosynthesis is an ill-posed inverse problem, that leads to a minimization problem with an object function that contains a data fitting term and a regularization term. The contribution of this thesis is to use the techniques of the compressed sensing, in particular replacing the standard least squares problem of data fitting with the problem of minimizing the 1-norm of the residuals, and using as regularization term the Total Variation (TV). We tested two different algorithms: a new alternating minimization algorithm (ADM), and a version of the more standard scaled projected gradient algorithm (SGP) that involves the 1-norm. We perform some experiments and analyse the performance of the two methods comparing relative errors, iterations number, times and the qualities of the reconstructed images. In conclusion we noticed that the use of the 1-norm and the Total Variation are valid tools in the formulation of the minimization problem for the image reconstruction resulting from Digital Tomosynthesis and the new algorithm ADM has reached a relative error comparable to a version of the classic algorithm SGP and proved best in speed and in the early appearance of the structures representing the masses.

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The objective of our study was to compare the performance of low-dose linear slit digital radiography (DR) with computed radiography (CR) for the detection of trauma sequelae in the chest including rib fractures, pneumothorax, and lung contusion.

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The effect of copper (Cu) filtration on image quality and dose in different digital X-ray systems was investigated. Two computed radiography systems and one digital radiography detector were used. Three different polymethylmethacrylate blocks simulated the pediatric body. The effect of Cu filters of 0.1, 0.2, and 0.3 mm thickness on the entrance surface dose (ESD) and the corresponding effective doses (EDs) were measured at tube voltages of 60, 66, and 73 kV. Image quality was evaluated in a contrast-detail phantom with an automated analyzer software. Cu filters of 0.1, 0.2, and 0.3 mm thickness decreased the ESD by 25-32%, 32-39%, and 40-44%, respectively, the ranges depending on the respective tube voltages. There was no consistent decline in image quality due to increasing Cu filtration. The estimated ED of anterior-posterior (AP) chest projections was reduced by up to 23%. No relevant reduction in the ED was noted in AP radiographs of the abdomen and pelvis or in posterior-anterior radiographs of the chest. Cu filtration reduces the ESD, but generally does not reduce the effective dose. Cu filters can help protect radiosensitive superficial organs, such as the mammary glands in AP chest projections.

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To investigate the aetiology and long-term clinical outcomes of patients diagnosed with digital ischemia.

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Visual imagery – similar to visual perception – activates feature-specific and category-specific visual areas. This is frequently observed in experiments where the instruction is to imagine stimuli that have been shown immediately before the imagery task. Hence, feature-specific activation could be related to the short-term memory retrieval of previously presented sensory information. Here, we investigated mental imagery of stimuli that subjects had not seen before, eliminating the effects of short-term memory. We recorded brain activation using fMRI while subjects performed a behaviourally controlled guided imagery task in predefined retinotopic coordinates to optimize sensitivity in early visual areas. Whole brain analyses revealed activation in a parieto-frontal network and lateral–occipital cortex. Region of interest (ROI) based analyses showed activation in left hMT/V5+. Granger causality mapping taking left hMT/V5+ as source revealed an imagery-specific directed influence from the left inferior parietal lobule (IPL). Interestingly, we observed a negative BOLD response in V1–3 during imagery, modulated by the retinotopic location of the imagined motion trace. Our results indicate that rule-based motion imagery can activate higher-order visual areas involved in motion perception, with a role for top-down directed influences originating in IPL. Lower-order visual areas (V1, V2 and V3) were down-regulated during this type of imagery, possibly reflecting inhibition to avoid visual input from interfering with the imagery construction. This suggests that the activation in early visual areas observed in previous studies might be related to short- or long-term memory retrieval of specific sensory experiences.

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Somatosensory object discrimination has been shown to involve widespread cortical and subcortical structures in both cerebral hemispheres. In this study we aimed to identify the networks involved in tactile object manipulation by principal component analysis (PCA) of individual subjects. We expected to find more than one network.