OGRE: analisi di un motore grafico 3D

In questa tesi descriveremo e analizzeremo il motore grafico OGRE, acronimo di Object-Oriented Graphics Rendering Engine. La scelta di analizzare proprio questo motore grafico è legata a diverse considerazioni. Innanzitutto, OGRE è rilasciato con licenza open source e quindi rende disponibile il suo codice sorgente. Questo è molto importante, in un contesto di studio e sperimentazione come quello universitario, perché permette di comprendere e analizzare anche il funzionamento interno del motore grafico. Inoltre, OGRE è un progetto maturo e stabile con una vasta comunità di sviluppatori e utilizzatori alle spalle. Esiste molta documentazione a riguardo, tra wiki, libri e manuali, e un forum molto attivo per la richiesta di aiuto e consigli. A conferma, sia della bontà del progetto che delle ottime prestazioni del motore grafico, basta dire che OGRE è utilizzato anche da applicazioni commerciali, come videogame, editor 3D e simulatori. Infine, la caratteristica che contraddistingue OGRE da tutti gli altri motori grafici è il fatto di essere "solamente" un motore di rendering puro. Ciò significa che qualsiasi funzionalità non direttamente legata al rendering, come ad esempio la gestione degli input dell'utente, non è supportata da OGRE. Anche se questo può sembrare un difetto, in realtà ciò permetterà di concentrarci solamente sugli aspetti legati al rendering che, in un motore grafico, costituiscono la parte fondamentale.

Surface-enhanced vibrational techniques for the detection of synthetic organic colorants

The research project object of this thesis is focused on the development of an advanced analytical system based on the combination of an improved thin layer chromatography (TLC) plate coupled with infrared (FTIR) and Raman microscopies for the detection of synthetic dyes. Indeed, the characterization of organic colorants, which are commonly present in mixtures with other components and in a very limited amount, still represents a challenging task in scientific analyses of cultural heritage materials. The approach provides selective spectral fingerprints for each compound, foreseeing the complementary information obtained by micro ATR-RAIRS-FTIR and SERS-Raman analyses, which can be performed on the same separated spot. In particular, silver iodide (AgI) applied on a gold coated slide is proposed as an efficient stationary phase for the discrimination of complex analyte mixtures, such as dyes present in samples of art-historical interest. The gold-AgI-TLC plate shows high performances related both to the chromatographic separation of analytes and to the spectroscopic detection of components. The use of a mid-IR transparent inorganic salt as the stationary phase avoids interferences of the background absorption in FTIR investigations. Moreover, by ATR microscopy measurements performed on the gold-AgI surface, a considerable enhancement in the intensity of spectra is observed. Complementary information can be obtained by Raman analyses, foreseeing a SERS activity of the AgI substrate. The method has been tested for the characterization of a mixture of three synthetic organic colorants widely used in dyeing processes: Brilliant Green (BG1), Rhodamine B (BV10) and Methylene Blue (BB9).

A deep learning-based approach for 3D people tracking

Questa tesi si occupa dell’estensione di un framework software finalizzato all'individuazione e al tracciamento di persone in una scena ripresa da telecamera stereoscopica. In primo luogo è rimossa la necessità di una calibrazione manuale offline del sistema sfruttando algoritmi che consentono di individuare, a partire da un fotogramma acquisito dalla camera, il piano su cui i soggetti tracciati si muovono. Inoltre, è introdotto un modulo software basato su deep learning con lo scopo di migliorare la precisione del tracciamento. Questo componente, che è in grado di individuare le teste presenti in un fotogramma, consente ridurre i dati analizzati al solo intorno della posizione effettiva di una persona, escludendo oggetti che l’algoritmo di tracciamento sarebbe portato a individuare come persone.

A Reliable Downscaling of ECG Signals for the Detection of T wave Heterogeneity Features

In cardiovascular disease the definition and the detection of the ECG parameters related to repolarization dynamics in post MI patients is still a crucial unmet need. In addition, the use of a 3D sensor in the implantable medical devices would be a crucial mean in the assessment or prediction of Heart Failure status, but the inclusion of such feature is limited by hardware and firmware constraints. The aim of this thesis is the definition of a reliable surrogate of the 500 Hz ECG signal to reach the aforementioned objective. To evaluate the worsening of reliability due to sampling frequency reduction on delineation performance, the signals have been consecutively down sampled by a factor 2, 4, 8 thus obtaining the ECG signals sampled at 250, 125 and 62.5 Hz, respectively. The final goal is the feasibility assessment of the detection of the fiducial points in order to translate those parameters into meaningful clinical parameter for Heart Failure prediction, such as T waves intervals heterogeneity and variability of areas under T waves. An experimental setting for data collection on healthy volunteers has been set up at the Bakken Research Center in Maastricht. A 16 – channel ambulatory system, provided by TMSI, has recorded the standard 12 – Leads ECG, two 3D accelerometers and a respiration sensor. The collection platform has been set up by the TMSI property software Polybench, the data analysis of such signals has been performed with Matlab. The main results of this study show that the 125 Hz sampling rate has demonstrated to be a good candidate for a reliable detection of fiducial points. T wave intervals proved to be consistently stable, even at 62.5 Hz. Further studies would be needed to provide a better comparison between sampling at 250 Hz and 125 Hz for areas under the T waves.

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.

AGV Safety Areas Obstacle Detection and Interaction with Point Cloud Derived Map

This thesis project aims to the development of an algorithm for the obstacle detection and the interaction between the safety areas of an Automated Guided Vehicles (AGV) and a Point Cloud derived map inside the context of a CAD software. The first part of the project focuses on the implementation of an algorithm for the clipping of general polygons, with which has been possible to: construct the safety areas polygon, derive the sweep of this areas along the navigation path performing a union and detect the intersections with line or polygon representing the obstacles. The second part is about the construction of a map in terms of geometric entities (lines and polygons) starting from a point cloud given by the 3D scan of the environment. The point cloud is processed using: filters, clustering algorithms and concave/convex hull derived algorithms in order to extract line and polygon entities representing obstacles. Finally, the last part aims to use the a priori knowledge of possible obstacle detections on a given segment, to predict the behavior of the AGV and use this prediction to optimize the choice of the vehicle's assigned velocity in that segment, minimizing the travel time.

Fabrication of 2D and 3D microelectrode arrays for amperometric dopamine sensing: towards a metal free approach to bioelectronics

Dopamine is a neurotransmitter which has a role in several psychiatric and neurological disorders. In-vivo detection of its concentration at the microscopic scale would benefit the study of these conditions and help in the development of therapies. The ideal sensor would be biocompatible, able to probe concentrations in microscopic volumes and sensitive to the small physiological concentrations of this molecule (10 nM - 1 μM). The ease of oxidation of dopamine makes it possible to detect it by electrochemical methods. An additional requirement in this kind of experiments when run in water, though, is to have a large potential window inside which no redox reactions with water take place. A promising class of materials which are being explored is the one of pyrolyzed photoresists. Photoresists can be lithographically patterned with micrometric resolution and after pyrolysis leave a glassy carbon material which is conductive, biocompatible and has a large electrochemical water window. In this work I developed a fabrication procedure for microelectrode arrays with three dimensional electrodes, making the whole device using just a negative photoresist called SU8. Making 3D electrodes could be a way to enhance the sensitivity of the electrodes without occupying a bigger footprint on the device. I characterized the electrical, morphological, and electrochemical properties of these electrodes, in particular their sensitivity to dopamine. I also fabricated and tested a two dimensional device for comparison. The three dimensional devices fabricated showed inferior properties to their two dimensional counter parts. I found a possible explanation and suggested some ways in which the fabrication could be improved.

Characterization of in-gap electronic states in two-dimensional single crystal PEA2PbBr4 perovskite for X-ray detection

Hybrid Organic-Inorganic Halide Perovskites (HOIPs) include a large class of materials described with the general formula ABX3, where A is an organic cation, B an inorganic cation and X an halide anion. HOIPs show excellent optoelectronic characteristics such as tunable band gap, high adsorption coefficient and great mobility life-time. A subclass of these materials, the so-called two- dimensional (2D) layered HOIPs, have emerged as potential alternatives to traditional 3D analogs to enhance the stability and increase performance of perovskite devices, with particular regard in the area of ionizing radiation detectors, where these materials have reached truly remarkable milestones. One of the key challenges for future development of efficient and stable 2D perovskite X-ray detector is a complete understanding of the nature of defects that lead to the formation of deep states. Deep states act as non-radiative recombination centers for charge carriers and are one of the factors that most hinder the development of efficient 2D HOIPs-based X-ray detectors. In this work, deep states in PEA2PbBr4 were studied through Photo-Induced Current Transient Spectroscopy (PICTS), a highly sensitive spectroscopic technique capable of detecting the presence of deep states in highly resistive ohmic materials, and characterizing their activation energy, capture cross section and, under stringent conditions, the concentration of these states. The evolution of deep states in PEA 2 PbBr 4 was evaluated after exposure of the material to high doses of ionizing radiation and during aging (one year). The data obtained allowed us to evaluate the contribution of ion migration in PEA2PbBr4. This work represents an important starting point for a better understanding of transport and recombination phenomena in 2D perovskites. To date, the PICTS technique applied to 2D perovskites has not yet been reported in the scientific literature.

Virtualization of Wiring Harness Manipulation Tasks through the PyChrono Simulation Engine

The purpose of this thesis work is the study and creation of a harness modelling system. The model needs to simulate faithfully the physical behaviour of the harness, without any instability or incorrect movements. Since there are various simulation engines that try to model wiring's systems, this thesis work focused on the creation and test of a 3D environment with wiring and other objects through the PyChrono Simulation Engine. Fine-tuning of the simulation parameters were done during the test to achieve the most stable and correct simulation possible, but tests showed the intrinsic limits of the Engine regarding the collisions' detection between the various part of the cables, while collisions between cables and other physical objects such as pavement, walls and others are well managed by the simulator. Finally, the main purpose of the model is to be used to train Artificial Intelligence through Reinforcement Learnings techniques, so we designed, using OpenAI Gym APIs, the general structure of the learning environment, defining its basic functions and an initial framework.

Sviluppo di Algoritmi di Localizzazione 3D Passiva per UAVs

Gli UAV, o meglio conosciuti come ‘droni’, sono aeromobili a pilotaggio remoto il cui utilizzo si estende dal settore militare a quello civile. Quest’ultimi, possono essere attrezzati con numerosi dispositivi accessori, come ad esempio disturbatori di frequenze. La simbiosi UAV-jammer attacca le comunicazioni wireless tramite interferenze a radiofrequenza, per degradare o interrompere il servizio offerto dalle reti. Questo elaborato, si concentra sull’analisi di algoritmi di localizzazione passiva, per stimare la posizione dell’UAV e interrompere l’interferenza. Inizialmente, viene descritto il segnale emesso dall’UAV, che utilizza lo standard di comunicazione 802.11a. A seguire, dato che la localizzazione passiva si basa sulle misure TDOA rilevate da una stazione di monitoraggio a terra, vengono presentati tre algoritmi di stima TDOA, tra i quali fast TDOA, adaptive threshold-based first tap detection e un algoritmo sviluppato per i nuovi sistemi GNSS. Successivamente, vengono esaminati tre algoritmi di localizzazione passiva, che sfruttano il principio dei minimi quadrati (LS), ovvero il CTLS, LCLS e CWLS. Infine, le prestazioni degli algoritmi di localizzazione vengono valutate in un ambiente di simulazione realistico, con canale AWGN o con canale ITU Extended pedestrian A.