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

Campionamento e ricostruzione di immagini full wavefield per il monitoraggio strutturale

L'elaborato affronta la definizione di differenti strategie per il campionamento e la ricostruzione di segnali wavefield per applicazioni di monitoraggio strutturale. In accordo con quanto indicato dalla teoria del Compressive Sensing, obiettivo della tesi è la minimizzazione del numero di punti di acquisizione al fine di ridurre lo sforzo energetico del campionamento. I risultati sono validati in ambiente Matlab utilizzando come riferimento segnali acquisiti su setup sperimentali in alluminio o materiale composito in presenza di diverse tipologie di difetto.

Neutrino interactions in the SAND LAr volume at the DUNE Near Detector site

The neutrino mass ordering and the leptonic CP violation phase are key parameters of the three-neutrino flavour mixing still to be determined. Measuring these parameters is the main goal of DUNE, a next generation Long Baseline neutrino experiment under construction in the United States. DUNE will feature a Near and a Far Detector site. An important component of the Near detector complex is the SAND apparatus, which will include GRAIN, a novel liquid Argon detector that aims at imaging neutrino interactions using scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is under study. This thesis work is aimed at a first quantitative assessment of a 3D neutrino event reconstruction algorithm for GRAIN. The processing procedure is optimized and the reconstruction performance is evaluated. Promising results are obtained.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Approccio combinato geo-location database e sensing per individuare i livelli di potenza trasmissibili da white space device

La Cognitive Radio è un dispositivo in grado di reagire ai cambiamenti dell’ambiente radio in cui opera, modificando autonomamente e dinamicamente i propri parametri funzionali tra cui la frequenza, la potenza di trasmissione e la modulazione. Il principio di base di questi dispositivi è l’accesso dinamico alle risorse radio potenzialmente non utilizzate, con cui utenti non in possesso di licenze possono sfruttare le frequenze che in un determinato spazio temporale non vengono usate, preoccupandosi di non interferire con gli utenti che hanno privilegi su quella parte di spettro. Devono quindi essere individuati i cosiddetti “spectrum holes” o “white spaces”, parti di spettro assegnate ma non utilizzate, dai quali prendono il nome i dispositivi.Uno dei modi per individuare gli “Spectrum holes” per una Cognitive Radio consiste nel cercare di captare il segnale destinato agli utenti primari; questa tecnica è nota con il nome di Spectrum Sensing e consente di ottenere essenzialmente una misura all’interno del canale considerato al fine di determinare la presenza o meno di un servizio protetto. La tecnica di sensing impiegata da un WSD che opera autonomamente non è però molto efficiente in quanto non garantisce una buona protezione ai ricevitori DTT che usano lo stesso canale sul quale il WSD intende trasmettere.A livello europeo la soluzione che è stata ritenuta più affidabile per evitare le interferenze sui ricevitori DTT è rappresentata dall’uso di un geo-location database che opera in collaborazione con il dispositivo cognitivo.Lo scopo di questa tesi è quello di presentare un algoritmo che permette di combinare i due approcci di geo-location database e Sensing per definire i livelli di potenza trasmissibile da un WSD.

Una piattaforma collaborativa di urban-sensing basata su dispositivi android

Tesi di laurea volta a descrivere la realizzazione di un sistema che permette la condivisione dei dati dai sensori dei dispositivi android su un server centrale

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Multiple pathogen detection using nanoplasmonic sensing

Opportunistic diseases caused by Human Immunodeficiency Virus (HIV) and Hepatitis B Virus (HBV) is an omnipresent global challenge. In order to manage these epidemics, we need to have low cost and easily deployable platforms at the point-of-care in high congestions regions like airports and public transit systems. In this dissertation we present our findings in using Localized Surface Plasmon Resonance (LSPR)-based detection of pathogens and other clinically relevant applications using microfluidic platforms at the point-of-care setting in resource constrained environment. The work presented here adopts the novel technique of LSPR to multiplex a lab-on-a-chip device capable of quantitatively detecting various types of intact viruses and its various subtypes, based on the principle of a change in wavelength occurring when metal nano-particle surface is modified with a specific surface chemistry allowing the binding of a desired pathogen to a specific antibody. We demonstrate the ability to detect and quantify subtype A, B, C, D, E, G and panel HIV with a specificity of down to 100 copies/mL using both whole blood sample and HIV-patient blood sample discarded from clinics. These results were compared against the gold standard Reverse Transcriptase Polymerase Chain Reaction (RT-qPCR). This microfluidic device has a total evaluation time for the assays of about 70 minutes, where 60 minutes is needed for the capture and 10 minutes for data acquisition and processing. This LOC platform eliminates the need for any sample preparation before processing. This platform is highly multiplexable as the same surface chemistry can be adapted to capture and detect several other pathogens like dengue virus, E. coli, M. Tuberculosis, etc.