Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Il Sistema IBE di Boneh e Franklin

Un sistema di cifratura IBE (Identity-Based Encription Scheme) si basa su un sistema crittografico a chiave pubblica, costituita però in questo caso da una stringa arbitraria. Invece di generare una coppia casuale di chiavi pubbliche e private e pubblicare la prima, l'utente utilizza come chiave pubblica la sua "identità", ovvero una combinazione di informazioni opportune (nome, indirizzo...) che lo identifichino in maniera univoca. In questo modo ad ogni coppia di utenti risulta possibile comunicare in sicurezza e verificare le reciproche firme digitali senza lo scambio di chiavi private o pubbliche, senza la necessità di mantenere una key directory e senza dover ricorrere ogni volta ai servizi di un ente esterno. Nel 2001 Boneh e Franklin proposero uno schema completamente funzionante con sicurezza IND-ID-CCA, basato su un analogo del problema computazionale di Diffie-Hellman e che da un punto di vista tecnico-matematico utilizza la crittografia su curve ellittiche e la mappa bilineare Weil Pairing.

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.

Ab-initio determination of x-ray absorption near edge structure (xanes) spectra in an ultrasoft and norm conserving pseudopotentials scheme

X-ray absorption spectroscopy (XAS) is a powerful means of investigation of structural and electronic properties in condensed -matter physics. Analysis of the near edge part of the XAS spectrum, the so – called X-ray Absorption Near Edge Structure (XANES), can typically provide the following information on the photoexcited atom: - Oxidation state and coordination environment. - Speciation of transition metal compounds. - Conduction band DOS projected on the excited atomic species (PDOS). Analysis of XANES spectra is greatly aided by simulations; in the most common scheme the multiple scattering framework is used with the muffin tin approximation for the scattering potential and the spectral simulation is based on a hypothetical, reference structure. This approach has the advantage of requiring relatively little computing power but in many cases the assumed structure is quite different from the actual system measured and the muffin tin approximation is not adequate for low symmetry structures or highly directional bonds. It is therefore very interesting and justified to develop alternative methods. In one approach, the spectral simulation is based on atomic coordinates obtained from a DFT (Density Functional Theory) optimized structure. In another approach, which is the object of this thesis, the XANES spectrum is calculated directly based on an ab – initio DFT calculation of the atomic and electronic structure. This method takes full advantage of the real many-electron final wavefunction that can be computed with DFT algorithms that include a core-hole in the absorbing atom to compute the final cross section. To calculate the many-electron final wavefunction the Projector Augmented Wave method (PAW) is used. In this scheme, the absorption cross section is written in function of several contributions as the many-electrons function of the finale state; it is calculated starting from pseudo-wavefunction and performing a reconstruction of the real-wavefunction by using a transform operator which contains some parameters, called partial waves and projector waves. The aim of my thesis is to apply and test the PAW methodology to the calculation of the XANES cross section. I have focused on iron and silicon structures and on some biological molecules target (myoglobin and cytochrome c). Finally other inorganic and biological systems could be taken into account for future applications of this methodology, which could become an important improvement with respect to the multiscattering approach.

Development of a biorefinery scheme for the valorization of olive mill wastewaters and grape pomaces

In the Mediterranean area, olive mill wastewater (OMW) and grape pomace (GP) are among the major agro-industrial wastes produced. These two wastes have a high organic load and high phytotoxicity. Thus, their disposal in the environment can lead to negative effects. Second-generation biorefineries are dedicated to the valorization of biowaste by the production of goods from such residual biomasses. This approach can combine bioremediation approaches to the generation of noble molecules, biomaterials and energy. The main aim of this thesis work was to study the anaerobic digestion of OMW and GP under different operational conditions to produce volatile fatti acids (VFAs) (first stage aim) and CH4 (second stage aim). To this end, a packed-bed biofilm reactor (PBBR) was set up to perform the anaerobic acidogenic digestion of the liquid dephenolized stream of OMW (OMWdeph). In parallel, the solid stream of OMW (OMWsolid), previously separated in order to allow the solid phase extraction of polyphenols, was addressed to anaerobic methanogenic digestion to obtain CH4. The latter experiment was performed in 100ml Pyrex bottles which were maintained at different temperatures (55-45-37°C). Together with previous experiments, the anaerobic acidogenic digestion of fermented GP (GPfreshacid) and dephenolized and fermented GP (GPdephacid) was performed in 100ml Pyrex bottles to estimate the concentration of VFAs achievable from each aforementioned GPs. Finally, the same matrices of GP and not pre-treated GP (GPfresh) were digested under anaerobic methanogenic condition to produce CH4. Anaerobic acidogenic and methanogenic digestion processes of GPs lasted about 33 days. Instead, the anaerobic acidogenic and methanogenic digestion process of OMWs lasted about 121 and 60 days, respectively. Each experiment was periodically monitored by analysing volume and composition of produced biogas and VFA concentration. Results showed that VFAs were produced in higher concentrations in GP compared to OMWdeph. The overall concentration of VFAs from GPfreshacid was approximately 39.5 gCOD L-1, 29 gCOD L-1 from GPdephacid, and 8.7 gCOD L-1 from OMWdeph. Concerning the CH4 production, the OMWsolid reached a high biochemical methane potential (BMP) at a thermophilic temperature (55°) than at mesophlic ones (37-45°C). The value reached was about 358.7 mlCH4 gSVsub-1. In contrast, GPfresh got a high BMP but at a mesophilic temperature. The BMP was about 207.3 mlCH4 gSVsub-1, followed by GPfreshacid with about 192.6 mlCH4 gSVsub-1 and lastly GPdephacid with about 102.2 mlCH4 gSVsub-1. In summary, based on the gathered results, GP seems to be a better carbon source for acidogenic and methanogenic microrganism compared to OMW, because higher amount of VFAs and CH4 were produced in AD of GP than OMW. In addition to these products, polyphenols were extracted by means of a solid phase extraction (SPE) procedure by another research group, and VFAs were utilised for biopolymers production, in particular polyhydroxyalkanoates (PHAs), by the same research group in which I was involved.

Assimilation of data from conventional and non conventional networks through a LETKF scheme in the COSMO model

The present work studies a km-scale data assimilation scheme based on a LETKF developed for the COSMO model. The aim is to evaluate the impact of the assimilation of two different types of data: temperature, humidity, pressure and wind data from conventional networks (SYNOP, TEMP, AIREP reports) and 3d reflectivity from radar volume. A 3-hourly continuous assimilation cycle has been implemented over an Italian domain, based on a 20 member ensemble, with boundary conditions provided from ECMWF ENS. Three different experiments have been run for evaluating the performance of the assimilation on one week in October 2014 during which Genova flood and Parma flood took place: a control run of the data assimilation cycle with assimilation of data from conventional networks only, a second run in which the SPPT scheme is activated into the COSMO model, a third run in which also reflectivity volumes from meteorological radar are assimilated. Objective evaluation of the experiments has been carried out both on case studies and on the entire week: check of the analysis increments, computing the Desroziers statistics for SYNOP, TEMP, AIREP and RADAR, over the Italian domain, verification of the analyses against data not assimilated (temperature at the lowest model level objectively verified against SYNOP data), and objective verification of the deterministic forecasts initialised with the KENDA analyses for each of the three experiments.

I) Improving low photocurrent of pseudorotaxane based solar cell II) Synthesis and characterization of new Fe(0) cyclopentadienone complexes

Next to conventional solar panels that harvest direct sunlight, p-type dye-sensitized solar cells (DSSCs) have been developed, which are able to harvest diffuse sunlight. Due to unwanted charge recombination events p-type DSSCs exhibit low power conversion efficiencies (PCEs). Previous research has shown that dye-redox mediator (RM) interactions can prevent these recombination events, resulting in higher PCEs. It is unknown how the nature of dye-RM interactions affects the PCEs of pseudorotaxane-based solar cells. In this research this correlation is investigated by comparing one macrocycle, the 3-NDI, in combination with the three dyes that contains a recognition sites. 2D-DOSY-NMR experiments have been conducted to evaluate the diffusion constants (LogD) of the three couple. The research project has been stopped due to the coronavirus pandemic. The continuation of this thesis would have been to synthesize a dye on the basis of the data obtained from the diffusion tests and attempt the construction of a solar cell to then evaluate its effectiveness. During my training period I synthetized new Fe(0) cyclopentadienone compounds bearing a N-Heterocyclic Carbene ligand. The aim of the thesis was to achieve water solubility by modifications of the cyclopentadienone ligand. These new complexes have been modified using a sulfonation reaction, replacing an hydroxyl with a sulfate group, on the alkyl backbone of the cyclopentadienone ligand. All the complexes were characterized with IR, ESI-MS and NMR spectroscopy, and a new Fe(0) cyclopentadienone complex, involved as an intermediate, was obtained as a single crystal and was characterized also with X-Ray spectroscopy.

Neural Network based Non Orthogonal Random Access for 6G NTN-IoT

Pervasive and distributed Internet of Things (IoT) devices demand ubiquitous coverage beyond No-man’s land. To satisfy plethora of IoT devices with resilient connectivity, Non-Terrestrial Networks (NTN) will be pivotal to assist and complement terrestrial systems. In a massiveMTC scenario over NTN, characterized by sporadic uplink data reports, all the terminals within a satellite beam shall be served during the short visibility window of the flying platform, thus generating congestion due to simultaneous access attempts of IoT devices on the same radio resource. The more terminals collide, the more average-time it takes to complete an access which is due to the decreased number of successful attempts caused by Back-off commands of legacy methods. A possible countermeasure is represented by Non-Orthogonal Multiple Access scheme, which requires the knowledge of the number of superimposed NPRACH preambles. This work addresses this problem by proposing a Neural Network (NN) algorithm to cope with the uncoordinated random access performed by a prodigious number of Narrowband-IoT devices. Our proposed method classifies the number of colliding users, and for each estimates the Time of Arrival (ToA). The performance assessment, under Line of Sight (LoS) and Non-LoS conditions in sub-urban environments with two different satellite configurations, shows significant benefits of the proposed NN algorithm with respect to traditional methods for the ToA estimation.