Experimental characterization of backscattering properties of UWB antennas in the presence of close objects

RTLS and RFID systems are becoming more and more important in several fields. When these systems meet the UWB technology, they can take advantage of each other strengths. Since nowadays a strong importance is given to the "green" technology, we chose to adopt a passive solution. In this case the backscattering modulation can be used to carry data. Therefore it is necessary to analyze the behavior of the antennas used as tags, when they are closed to dierent material objects. In particular, the antenna mode part has been deeply observed, as it is the crucial part of the signal regarding the backscatter modulation.

A study of two Languages for Active Objects with Futures

In computer systems, specifically in multithread, parallel and distributed systems, a deadlock is both a very subtle problem - because difficult to pre- vent during the system coding - and a very dangerous one: a deadlocked system is easily completely stuck, with consequences ranging from simple annoyances to life-threatening circumstances, being also in between the not negligible scenario of economical losses. Then, how to avoid this problem? A lot of possible solutions has been studied, proposed and implemented. In this thesis we focus on detection of deadlocks with a static program analysis technique, i.e. an analysis per- formed without actually executing the program. To begin, we briefly present the static Deadlock Analysis Model devel- oped for coreABS−− in chapter 1, then we proceed by detailing the Class- based coreABS−− language in chapter 2. Then, in Chapter 3 we lay the foundation for further discussions by ana- lyzing the differences between coreABS−− and ASP, an untyped Object-based calculi, so as to show how it can be possible to extend the Deadlock Analysis to Object-based languages in general. In this regard, we explicit some hypotheses in chapter 4 first by present- ing a possible, unproven type system for ASP, modeled after the Deadlock Analysis Model developed for coreABS−−. Then, we conclude our discussion by presenting a simpler hypothesis, which may allow to circumvent the difficulties that arises from the definition of the ”ad-hoc” type system discussed in the aforegoing chapter.

Il Compressed Sensing

Introduzione al metodo del Compressed Sensing per il campionamento di segnali sparsi.

Tecniche per l'acquisizione a basso consumo di segnali sparsi tramite compressed sensing

Tecniche per l'acquisizione a basso consumo di segnali sparsi tramite compressed sensing

Ultra low power analog-to-information conversion by short-time compressed sensing

Il compressed sensing è un’innovativa tecnica per l’acquisizione dei dati, che mira all'estrazione del solo contenuto informativo intrinseco di un segnale. Ciò si traduce nella possibilità di acquisire informazione direttamente in forma compressa, riducendo la quantità di risorse richieste per tale operazione. In questa tesi è sviluppata un'architettura hardware per l'acquisizione di segnali analogici basata sul compressed sensing, specializzata al campionamento con consumo di potenza ridotto di segnali biomedicali a basse frequenze. Lo studio è svolto a livello di sistema mediante l'integrazione della modulazione richiesta dal compressed sensing in un convertitore analogico-digitale ad approssimazioni successive, modificandone la logica di controllo. Le prestazioni risultanti sono misurate tramite simulazioni numeriche e circuitali. Queste confermano la possibilità di ridurre la complessità hardware del sistema di acquisizione rispetto allo stato dell'arte, senza alterarne le prestazioni.

Multifrequency VLBA observations of two compact symmetric objects

In this thesis the results of the multifrequency VLBA observations of the GPS 1944+5448 and the HFP J0111+3906 are presented. They are compact objects smaller than about 100 pc, completely embedded in the host galaxy. The availability of multi-epoch VLBI observations spanning more than 10 years, allowed us to compute the hot spot advance speed in order to obtain the kinematic age of both sources. Both radio sources are young, in agreement with the idea that they are in an early evolutionary stage. The spectral analysis of each source component, such as the lobes, the hot spots, the core and the jets, making a comparison with the theoretical ones is described. In addition the physical parameters derived from VLBA images as the magnetic field, the luminosity, the energy and the ambient medium density of both sources are discussed.

Compressed sensing in digital tomosynthesis reconstruction

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.