Deep Learning Architectures for time of arrival detection in Acoustic Emissions Monitoring

Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine its location in Structural Health Monitoring (SHM) applications. Information on the time difference of the signal generated by the damage event arriving at different sensors is essential in performing localization. This makes the time of arrival (ToA) an important piece of information to retrieve from the AE signal. Generally, this is determined using statistical methods such as the Akaike Information Criterion (AIC) which is particularly prone to errors in the presence of noise. And given that the structures of interest are surrounded with harsh environments, a way to accurately estimate the arrival time in such noisy scenarios is of particular interest. In this work, two new methods are presented to estimate the arrival times of AE signals which are based on Machine Learning. Inspired by great results in the field, two models are presented which are Deep Learning models - a subset of machine learning. They are based on Convolutional Neural Network (CNN) and Capsule Neural Network (CapsNet). The primary advantage of such models is that they do not require the user to pre-define selected features but only require raw data to be given and the models establish non-linear relationships between the inputs and outputs. The performance of the models is evaluated using AE signals generated by a custom ray-tracing algorithm by propagating them on an aluminium plate and compared to AIC. It was found that the relative error in estimation on the test set was < 5% for the models compared to around 45% of AIC. The testing process was further continued by preparing an experimental setup and acquiring real AE signals to test on. Similar performances were observed where the two models not only outperform AIC by more than a magnitude in their average errors but also they were shown to be a lot more robust as compared to AIC which fails in the presence of noise.

Enabling 5G and beyond: millimeter wave propagation and cloud RAN evolution

In the last few years, mobile wireless technology has gone through a revolutionary change. Web-enabled devices have evolved into essential tools for communication, information, and entertainment. The fifth generation (5G) of mobile communication networks is envisioned to be a key enabler of the next upcoming wireless revolution. Millimeter wave (mmWave) spectrum and the evolution of Cloud Radio Access Networks (C-RANs) are two of the main technological innovations of 5G wireless systems and beyond. Because of the current spectrum-shortage condition, mmWaves have been proposed for the next generation systems, providing larger bandwidths and higher data rates. Consequently, new radio channel models are being developed. Recently, deterministic ray-based models such as Ray-Tracing (RT) are getting more attractive thanks to their frequency-agility and reliable predictions. A modern RT software has been calibrated and used to analyze the mmWave channel. Knowledge of the electromagnetic properties of materials is therefore essential. Hence, an item-level electromagnetic characterization of common construction materials has been successfully achieved to obtain information about their complex relative permittivity. A complete tuning of the RT tool has been performed against indoor and outdoor measurement campaigns at 27 and 38 GHz, setting the basis for the future development of advanced beamforming techniques which rely on deterministic propagation models (as RT). C-RAN is a novel mobile network architecture which can address a number of challenges that network operators are facing in order to meet the continuous customers’ demands. C-RANs have already been adopted in advanced 4G deployments; however, there are still some issues to deal with, especially considering the bandwidth requirements set by the forthcoming 5G systems. Open RAN specifications have been proposed to overcome the new 5G challenges set on C-RAN architectures, including synchronization aspects. In this work it is described an FPGA implementation of the Synchronization Plane for an O-RAN-compliant radio system.

Propagation modelling and resource allocation in mobile radio communications

Over the past years, ray tracing (RT) models popularity has been increasing. From the nineties, RT has been used for field prediction in environment such as indoor and urban environments. Nevertheless, with the advent of new technologies, the channel model has become decidedly more dynamic and to perform RT simulations at each discrete time instant become computationally expensive. In this thesis, a new dynamic ray tracing (DRT) approach is presented in which from a single ray tracing simulation at an initial time t0, through analytical formulas we are able to track the motion of the interaction points. The benefits that this approach bring are that Doppler frequencies and channel prediction can be derived at every time instant, without recurring to multiple RT runs and therefore shortening the computation time. DRT performance was studied on two case studies and the results shows the accuracy and the computational gain that derives from this approach. Another issue that has been addressed in this thesis is the licensed band exhaustion of some frequency bands. To deal with this problem, a novel unselfish spectrum leasing scheme in cognitive radio networks (CRNs) is proposed that offers an energy-efficient solution minimizing the environmental impact of the network. In addition, a network management architecture is introduced and resource allocation is proposed as a constrained sum energy efficiency maximization problem. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms.

First steps in underwater photogrammetry with the support of an unmanned underwater vehicle

The evolution of modern and increasingly sensitive image sensors, the increasingly compact design of the cameras, and the recent emergence of low-cost cameras allowed the Underwater Photogrammetry to become an infallible and irreplaceable technique used to estimate the structure of the seabed with high accuracy. Within this context, the main topic of this work is the Underwater Photogrammetry from a geomatic point of view and all the issues associated with its implementation, in particular with the support of Unmanned Underwater Vehicles. Questions such as: how does the technique work, what is needed to deal with a proper survey, what tools are available to apply this technique, and how to resolve uncertainties in measurement will be the subject of this thesis. The study conducted can be divided into two major parts: one devoted to several ad-hoc surveys and tests, thus a practical part, another supported by the bibliographical research. However the main contributions are related to the experimental section, in which two practical case studies are carried out in order to improve the quality of the underwater survey of some calibration platforms. The results obtained from these two experiments showed that, the refractive effects due to water and underwater housing can be compensated by the distortion coefficients in the camera model, but if the aim is to achieve high accuracy then a model that takes into account the configuration of the underwater housing, based on ray tracing, must also be coupled. The major contributions that this work brought are: an overview of the practical issues when performing surveys exploiting an UUV prototype, a method to reach a reliable accuracy in the 3D reconstructions without the use of an underwater local geodetic network, a guide for who addresses underwater photogrammetry topics for the first time, and the use of open-source environments.

Studio della propagazione radio MIMO in scenari street-intersection

L'elaborato si suddivide essenzialmente in due parti principali. Una prima parte descrittiva dove vengono presentati i concetti fondamentali per la corretta comprensione della seconda, nella quale viene descritto il progetto svolto. Esso mira a valutare l’effetto che oggetti in metallo presenti in prossimità di un incrocio stradale hanno sulla propagazione del segnale radio, e in particolare sulla generazione di cammini multipli. I cammini multipli vengono infatti sfruttati dalle tecnologie di trasmissione a multiple antenne (MIMO) per incrementare la capacità di trasmissione. Un parametro sintetico che permette di caratterizzare le prestazioni dei sistemi MIMO è il cosiddetto Condition Number, che si è utilizzato in questo elaborato. Per effettuare lo studio delle prestazioni MIMO si sono utilizzate simulazioni elettromagnetiche a raggi (ray-tracing) e misure sperimentali, che sono state effettuate in prossimità del campus dell’Università Jiaotong di Shanghai, in Cina. Inizialmente, utilizzando una mappa standard dell’ambiente di propagazione, contenente i soli edifici, i valori di Condition Number ottenuti dalle simulazioni ray-tracing differivano notevolmente dai valori sperimentali. Il mio compito è stato quello di modellare nuovi elementi di forma cilindrica che ben simulano le proprietà fisico-geometriche dei pali e di altri oggetti metallici presenti lungo il tragitto e nelle intersezioni stradali e di inserirli nella mappa nella corretta posizione. Le simulazioni poi sono servite per valutare l’efficacia in termini di miglioramento delle prestazioni, in particolare sulla generazione di nuovi cammini sfasati nel tempo e nello spazio, e il relativo effetto sui valori numerici del condition number. Successivamente, è stata fatta una valutazione sull’influenza della vegetazione presente in loco per vedere quanta influenza abbia sul collegamento radio.

Anisotropic seismic tomography with the reversible jump Markov chain Monte Carlo

The established isotropic tomographic models show the features of subduction zones in terms of seismic velocity anomalies, but they are generally subjected to the generation of artifacts due to the lack of anisotropy in forward modelling. There is evidence for the significant influence of seismic anisotropy in the mid-upper mantle, especially for boundary layers like subducting slabs. As consequence, in isotropic models artifacts may be misinterpreted as compositional or thermal heterogeneities. In this thesis project the application of a trans-dimensional Metropolis-Hastings method is investigated in the context of anisotropic seismic tomography. This choice arises as a response to the important limitations introduced by traditional inversion methods which use iterative procedures of optimization of a function object of the inversion. On the basis of a first implementation of the Bayesian sampling algorithm, the code is tested with some cartesian two-dimensional models, and then extended to polar coordinates and dimensions typical of subduction zones, the main focus proposed for this method. Synthetic experiments with increasing complexity are realized to test the performance of the method and the precautions for multiple contexts, taking into account also the possibility to apply seismic ray-tracing iteratively. The code developed is tested mainly for 2D inversions, future extensions will allow the anisotropic inversion of seismological data to provide more realistic imaging of real subduction zones, less subjected to generation of artifacts.

Studio di modelli a raggi per Superfici Intelligenti Riconfigurabili

In questa trattazione viene presentato lo studio di un modello a raggi che permette di simulare il comportamento macroscopico delle Superfici Intelligenti. L’ottimizzazione del canale radio, in particolare dell’ambiente di propagazione, si rivela fondamentale per la futura introduzione del 6G. Per la pianificazione della propagazione in ambienti ampi, risulta necessario implementare modelli di simulazione. I modelli a raggi possono essere integrati più facilmente all’interno di algoritmi per le previsioni di campo computazionalmente efficienti, come gli algoritmi di Ray Tracing. Nell’elaborato si è analizzato il comportamento del modello, con riferimento a tre funzioni tipiche realizzate da una Superficie Intelligente: il riflettore anomalo, la lente focalizzante e la lente defocalizzante. Attraverso una griglia di ricevitori è stato calcolato il campo dell’onda nelle varie configurazioni. Infine, si sono confrontati i risultati ottenuti con quelli del modello elettromagnetico.

Soluzioni per coperture wireless in ambiente indoor con l'ausilio di superfici intelligenti riconfigurabili

I sistemi di comunicazione 6G si prevede che soddisfino requisiti più stringenti rispetto alle reti 5G in termini di capacità di trasmissione, affidabilità, latenza, copertura, consumo energetico e densità di connessione. I miglioramenti che si possono ottenere agendo solo sugli end-points dell'ambiente wireless potrebbero non essere sufficienti per adempiere a tali obiettivi. Performance migliori potrebbero invece essere raggiunte liberandosi del postulato che fissa l'ambiente di propagazione come elemento incontrollabile. In questo panorama spicca una tecnologia recente che prende il nome di Reconfigurable Intelligent Surface (RIS) e che si pone l'obiettivo di rendere personalizzabile l'ambiente di propagazione wireless attraverso elaborazioni quasi passive di segnale. Una RIS è una superficie sottile ingegnerizzata al fine di possedere proprietà che le permettono di controllare dinamicamente le onde elettromagnetiche attraverso, ad esempio, la riflessione, rifrazione e focalizzazione del segnale. Questo può portare alla realizzazione del cosiddetto Smart Radio Environment (SRE), ovvero un ambiente di propagazione che non è visto come entità aleatoria incontrollabile, ma come parametro di design che svolge un ruolo fondamentale nel processo di ottimizzazione della rete. Nel presente elaborato, partendo da un modello macroscopico del comportamento di una RIS sviluppato dal gruppo di ricerca di propagazione e integrato all'interno di un simulatore di ray tracing, si effettua uno studio di coperture wireless con l'ausilio di RIS in semplici scenari indoor di riferimento.

Development and applications of three-dimensional gamma ray tomography system using ray casting volume rendering techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modellazione e rendering del lungomare di Riccione mediante Blender

Lo scopo di questa tesi è quello di realizzare un modello tridimensionale del lungomare di Riccione, mediante l'uso di programmi di modellazione, grafica e CAD (computer aided design). Lo scopo è di riprodurre un intero ambiente virtuale che l'utente sia libero di esplorare e in cui possa muoversi in totale libertà. Il possibile utilizzo di un tale progetto è quindi essenzialmente divulgativo o a fini turistici, poiché permette di far conoscere il lungomare di Riccione e di farlo esplorare attivamente dall'utente attraverso il computer comodamente da casa. Questo potrebbe successivamente invogliare gli utenti a visitare dal vivo la città, destando curiosità in merito agli arredi turistici precedentemente osservati in maniera virtuale.

Image Space Adaptive Rendering

In this thesis, we develop an adaptive framework for Monte Carlo rendering, and more specifically for Monte Carlo Path Tracing (MCPT) and its derivatives. MCPT is attractive because it can handle a wide variety of light transport effects, such as depth of field, motion blur, indirect illumination, participating media, and others, in an elegant and unified framework. However, MCPT is a sampling-based approach, and is only guaranteed to converge in the limit, as the sampling rate grows to infinity. At finite sampling rates, MCPT renderings are often plagued by noise artifacts that can be visually distracting. The adaptive framework developed in this thesis leverages two core strategies to address noise artifacts in renderings: adaptive sampling and adaptive reconstruction. Adaptive sampling consists in increasing the sampling rate on a per pixel basis, to ensure that each pixel value is below a predefined error threshold. Adaptive reconstruction leverages the available samples on a per pixel basis, in an attempt to have an optimal trade-off between minimizing the residual noise artifacts and preserving the edges in the image. In our framework, we greedily minimize the relative Mean Squared Error (rMSE) of the rendering by iterating over sampling and reconstruction steps. Given an initial set of samples, the reconstruction step aims at producing the rendering with the lowest rMSE on a per pixel basis, and the next sampling step then further reduces the rMSE by distributing additional samples according to the magnitude of the residual rMSE of the reconstruction. This iterative approach tightly couples the adaptive sampling and adaptive reconstruction strategies, by ensuring that we only sample densely regions of the image where adaptive reconstruction cannot properly resolve the noise. In a first implementation of our framework, we demonstrate the usefulness of our greedy error minimization using a simple reconstruction scheme leveraging a filterbank of isotropic Gaussian filters. In a second implementation, we integrate a powerful edge aware filter that can adapt to the anisotropy of the image. Finally, in a third implementation, we leverage auxiliary feature buffers that encode scene information (such as surface normals, position, or texture), to improve the robustness of the reconstruction in the presence of strong noise.

Superior color rendering with a phosphor-converted blue-cyan monolithic light-emitting diode

The future generation of modern illumination should not only be cheap and highly efficient, but also demonstrate high quality of light, light which allows better color differentiation and fidelity. Here we are presenting a novel approach to create a white solid-state light source providing ultimate color rendition necessary for a number of applications. The proposed semi-hybrid device combines a monolithic blue-cyan light emitting diode (MBC LED) with a green-red phosphor mixture. It has shown a superior color rendering index (CRI), 98.6, at correlated color temperature of around 3400 K. The MBC LED epi-structure did not suffer from the efficiency reduction typical for monolithic multi-color emitters and was implemented in the two most popular chip designs: “epi-up” and “flip-chip”. Redistribution of the blue and cyan band amplitudes in the white-light emission spectrum, using the operating current, is found to be an effective tool for fine tuning the color characteristics. (Figure presented.).

A survey of techniques and technologies for web-based real-time interactive rendering

When exploring a virtual environment, realism depends mainly on two factors: realistic images and real-time feedback (motions, behaviour etc.). In this context, photo realism and physical validity of computer generated images required by emerging applications, such as advanced e-commerce, still impose major challenges in the area of rendering research whereas the complexity of lighting phenomena further requires powerful and predictable computing if time constraints must be attained. In this technical report we address the state-of-the-art on rendering, trying to put the focus on approaches, techniques and technologies that might enable real-time interactive web-based clientserver rendering systems. The focus is on the end-systems and not the networking technologies used to interconnect client(s) and server(s).

Synthesis, characterization and thermal behaviour on solid pyruvates of light trivalent lanthanides

Solid State Ln-L compounds, where Ln stands for light trivalent lanthanides (La - Gd) and L is pyruvate, have been synthesized. Thermogravimetry and derivative thermogravimetry (TG/DTG), differential scanning calorimetry (DSC), X-Ray powder diffractometry, infrared spectroscopy, elemental analysis, and complexometry were used to characterize and to study the thermal behaviour of these compounds. The results led to information about the composition, dehydration, ligand denticity, thermal behaviour and thermal decomposition of the isolated compounds.