Detecting social patterns within 20th century documentary photos: a deep learning based approach

The job of a historian is to understand what happened in the past, resorting in many cases to written documents as a firsthand source of information. Text, however, does not amount to the only source of knowledge. Pictorial representations, in fact, have also accompanied the main events of the historical timeline. In particular, the opportunity of visually representing circumstances has bloomed since the invention of photography, with the possibility of capturing in real-time the occurrence of a specific events. Thanks to the widespread use of digital technologies (e.g. smartphones and digital cameras), networking capabilities and consequent availability of multimedia content, the academic and industrial research communities have developed artificial intelligence (AI) paradigms with the aim of inferring, transferring and creating new layers of information from images, videos, etc. Now, while AI communities are devoting much of their attention to analyze digital images, from an historical research standpoint more interesting results may be obtained analyzing analog images representing the pre-digital era. Within the aforementioned scenario, the aim of this work is to analyze a collection of analog documentary photographs, building upon state-of-the-art deep learning techniques. In particular, the analysis carried out in this thesis aims at producing two following results: (a) produce the date of an image, and, (b) recognizing its background socio-cultural context,as defined by a group of historical-sociological researchers. Given these premises, the contribution of this work amounts to: (i) the introduction of an historical dataset including images of “Family Album” among all the twentieth century, (ii) the introduction of a new classification task regarding the identification of the socio-cultural context of an image, (iii) the exploitation of different deep learning architectures to perform the image dating and the image socio-cultural context classification.

Design and implementation of a synchronous interleaved boost converter for fuel cell-powered catamaran

The present work describes the different stages of design, implementation, and validation procedures for an interleaved DC-DC boost converter intended for the 2022 Futura, a fuel cell-powered racing catamaran developed by the UniBoAT team. The main goal of the entire design has been the significant reduction of the weight of the converter by removing heat sinks and reducing component size while increasing its efficiency by adopting high-end power switches and the interleaved architecture operated with a synchronous control strategy. The obtained converter has been integrated into the structure containing the fuel cell stack obtaining a fully integrated system. The realized device has been based on an interleaved architecture with six phases controlled digitally through the average current mode control. The design has been validated through simulations carried out using the software LT-Spice, whereas experimental validations have been performed by means of laboratory bench tests and on-field tests. Detailed thermal and efficiency analyses are provided with the bench tests under the two synchronous and non-synchronous operating modes and with the adoption of the phase shedding technique. The prototype implementation and its performance in real operating conditions are also discussed. Eventually, it is underlined as the designed converter can be used in other applications requiring a voltage-controlled boost converter.

Time to digital converter

In questa tesi è analizzato il caso di sensori con uscita in frequenza e periodo, si traduce in ultima analisi nella capacità di misurare con precisione un intervallo temporale. La rivelazione del tempo risulta essere lo stadio fondamentale da cui deriva la risoluzione dell'intero sistema di misura. Nella realtà, la questione della simultaneità cioè individuare con assoluta precisione due eventi che si verificano contemporaneamente, in un determinato istante t, è un problema piuttosto complesso: le difficoltà sono correlate soprattutto alle limitazioni fisiche intrinseche degli strumenti di misura. E' utile allora fornire un'analisi sui principi e le tecniche alla base della misura di intervalli temporali, detta Time Interval Measurement (TIM). Lo scopo della tesi è studiare i vari metodi per realizzare TDC lineari digitali, facendo un'analisi critica e ed evidenziando pro e contro che i vari approcci presentano, attingendo e analizzando criticamente informazioni dalle varie fonti riportate in bibliografia.

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.

Optimized methods to digital survey and 3D modelling of cultural heritage assets

Currently making digital 3D models and replicas of the cultural heritage assets play an important role in the preservation and having a high detail source for future research and intervention. In this dissertation, it is tried to assess different methods for digital surveying and making 3D replicas of cultural heritage assets in different scales of size. The methodologies vary in devices, software, workflow, and the amount of skill that is required. The three phases of the 3D modelling process are data acquisition, modelling, and model presentation. Each of these sections is divided into sub-sections and there are several approaches, methods, devices, and software that may be employed, furthermore, the selection process should be based on the operation's goal, available facilities, the scale and properties of the object or structure to be modeled, as well as the operators' expertise and experience. The most key point to remember is that the 3D modelling operation should be properly accurate, precise, and reliable; therefore, there are so many instructions and pieces of advice on how to perform 3D modelling effectively. It is an attempt to compare and evaluate the various ways of each phase in order to explain and demonstrate their differences, benefits, and drawbacks in order to serve as a simple guide for new and/or inexperienced users.