On the path of Exploratory Search Users - A Semantic Web tool

L’Exploratory Search, paradigma di ricerca basato sulle attività di scoperta e d’apprendimento, è stato per diverso tempo ignorato dai motori di ricerca tradizionali. Invece, è spesso dalle ricerche esplorative che nascono le idee più innovative. Le recenti tecnologie del Semantic Web forniscono le soluzioni che permettono d’implementare dei motori di ricerca capaci di accompagnare gli utenti impegnati in tale tipo di ricerca. Aemoo, motore di ricerca sul quale s’appoggia questa tesi ne è un esempio efficace. A partire da quest’ultimo e sempre con l’aiuto delle tecnologie del Web of Data, questo lavoro si propone di fornire una metodologia che permette di prendere in considerazione la singolarità del profilo di ciascun utente al fine di guidarlo nella sua ricerca esplorativa in modo personalizzato. Il criterio di personalizzazione che abbiamo scelto è comportamentale, ovvero basato sulle decisioni che l’utente prende ad ogni tappa che ritma il processo di ricerca. Implementando un prototipo, abbiamo potuto testare la validità di quest’approccio permettendo quindi all’utente di non essere più solo nel lungo e tortuoso cammino che porta alla conoscenza.

An optimal control tool for trajectory generation of autonomous drones

In the recent years, autonomous aerial vehicles gained large popularity in a variety of applications in the field of automation. To accomplish various and challenging tasks the capability of generating trajectories has assumed a key role. As higher performances are sought, traditional, flatness-based trajectory generation schemes present their limitations. In these approaches the highly nonlinear dynamics of the quadrotor is, indeed, neglected. Therefore, strategies based on optimal control principles turn out to be beneficial, since in the trajectory generation process they allow the control unit to best exploit the actual dynamics, and enable the drone to perform quite aggressive maneuvers. This dissertation is then concerned with the development of an optimal control technique to generate trajectories for autonomous drones. The algorithm adopted to this end is a second-order iterative method working directly in continuous-time, which, under proper initialization, guarantees quadratic convergence to a locally optimal trajectory. At each iteration a quadratic approximation of the cost functional is minimized and a decreasing direction is then obtained as a linear-affine control law, after solving a differential Riccati equation. The algorithm has been implemented and its effectiveness has been tested on the vectored-thrust dynamical model of a quadrotor in a realistic simulative setup.

Ray-tracing assessment of the robustness of Physical Layer Security key generation protocol

Nowadays, information security is a very important topic. In particular, wireless networks are experiencing an ongoing widespread diffusion, also thanks the increasing number of Internet Of Things devices, which generate and transmit a lot of data: protecting wireless communications is of fundamental importance, possibly through an easy but secure method. Physical Layer Security is an umbrella of techniques that leverages the characteristic of the wireless channel to generate security for the transmission. In particular, the Physical Layer based-Key generation aims at allowing two users to generate a random symmetric keys in an autonomous way, hence without the aid of a trusted third entity. Physical Layer based-Key generation relies on observations of the wireless channel, from which harvesting entropy: however, an attacker might possesses a channel simulator, for example a Ray Tracing simulator, to replicate the channel between the legitimate users, in order to guess the secret key and break the security of the communication. This thesis work is focused on the possibility to carry out a so called Ray Tracing attack: the method utilized for the assessment consist of a set of channel measurements, in different channel conditions, that are then compared with the simulated channel from the ray tracing, to compute the mutual information between the measurements and simulations. Furthermore, it is also presented the possibility of using the Ray Tracing as a tool to evaluate the impact of channel parameters (e.g. the bandwidth or the directivity of the antenna) on the Physical Layer based-Key generation. The measurements have been carried out at the Barkhausen Institut gGmbH in Dresden (GE), in the framework of the existing cooperation agreement between BI and the Dept. of Electrical, Electronics and Information Engineering "G. Marconi" (DEI) at the University of Bologna.

Heat kernel and worldline path integrals for the Proca theory

In this thesis we study the heat kernel, a useful tool to analyze various properties of different quantum field theories. In particular, we focus on the study of the one-loop effective action and the application of worldline path integrals to derive perturbatively the heat kernel coefficients for the Proca theory of massive vector fields. It turns out that the worldline path integral method encounters some difficulties if the differential operator of the heat kernel is of non-minimal kind. More precisely, a direct recasting of the differential operator in terms of worldline path integrals, produces in the classical action a non-perturbative vertex and the path integral cannot be solved. In this work we wish to find ways to circumvent this issue and to give a suggestion to solve similar problems in other contexts.

WEC-Sim Application for the Assessment of Wave Energy Generation in the Tyrrhenian Sea and the North Sea Through the 2-Body Point Absorber (2BPA) and the Oscillating Surge Wave Energy Converter (OSWEC)

In recent years, developed countries have turned their attention to clean and renewable energy, such as wind energy and wave energy that can be converted to electrical power. Companies and academic groups worldwide are investigating several wave energy ideas today. Accordingly, this thesis studies the numerical simulation of the dynamic response of the wave energy converters (WECs) subjected to the ocean waves. This study considers a two-body point absorber (2BPA) and an oscillating surge wave energy converter (OSWEC). The first aim is to mesh the bodies of the earlier mentioned WECs to calculate their hydrostatic properties using axiMesh.m and Mesh.m functions provided by NEMOH. The second aim is to calculate the first-order hydrodynamic coefficients of the WECs using the NEMOH BEM solver and to study the ability of this method to eliminate irregular frequencies. The third is to generate a *.h5 file for 2BPA and OSWEC devices, in which all the hydrodynamic data are included. The BEMIO, a pre-and post-processing tool developed by WEC-Sim, is used in this study to create *.h5 files. The primary and final goal is to run the wave energy converter Simulator (WEC-Sim) to simulate the dynamic responses of WECs studied in this thesis and estimate their power performance at different sites located in the Mediterranean Sea and the North Sea. The hydrodynamic data obtained by the NEMOH BEM solver for the 2BPA and OSWEC devices studied in this thesis is imported to WEC-Sim using BEMIO. Lastly, the power matrices and annual energy production (AEP) of WECs are estimated for different sites located in the Sea of Sicily, Sea of Sardinia, Adriatic Sea, Tyrrhenian Sea, and the North Sea. To this end, the NEMOH and WEC-Sim are still the most practical tools to estimate the power generation of WECs numerically.

Synthetic data generation for the assessment of antimicrobial resistance through machine learning

As a consequence of the diffusion of next generation sequencing techniques, metagenomics databases have become one of the most promising repositories of information about features and behavior of microorganisms. One of the subjects that can be studied from those data are bacteria populations. Next generation sequencing techniques allow to study the bacteria population within an environment by sampling genetic material directly from it, without the needing of culturing a similar population in vitro and observing its behavior. As a drawback, it is quite complex to extract information from those data and usually there is more than one way to do that; AMR is no exception. In this study we will discuss how the quantified AMR, which regards the genotype of the bacteria, can be related to the bacteria phenotype and its actual level of resistance against the specific substance. In order to have a quantitative information about bacteria genotype, we will evaluate the resistome from the read libraries, aligning them against CARD database. With those data, we will test various machine learning algorithms for predicting the bacteria phenotype. The samples that we exploit should resemble those that could be obtained from a natural context, but are actually produced by a read libraries simulation tool. In this way we are able to design the populations with bacteria of known genotype, so that we can relay on a secure ground truth for training and testing our algorithms.

Procedure di Programmazione Dinamica per Determinare le K Migliori Soluzioni del Knapsack Problem 0-1 e dello Shortest Path Problem

In questa tesi viene trattata la problematica di determinare le migliori K soluzioni per due problemi di ottimizzazione, il Knapsack Problem 0-1 e lo Shortest Path Problem. Tali soluzioni possono essere impiegate all'interno di metodi di column generation per la risoluzione di problemi reali, ad esempio Bin Packing Problems e problemi di scheduling di veicoli ed equipaggi. Sono stati implementati, per verificarne sperimentalmente le prestazioni, nuovi algoritmi di programmazione dinamica, sviluppati nell’ambito di un programma di ricerca. Inizialmente, per entrambi i problemi, è stato descritto un algoritmo che determinasse le migliori K soluzioni per ogni possibile sottoproblema; partendo da uno zaino con capacità nulla, nel caso del Knapsack Problem 0-1, e dalla determinazione di un cammino dal vertice sorgente in se stesso per lo Shortest Path Problem, l’algoritmo determina le migliori soluzioni di sottoproblemi via via sempre più grandi, utilizzando le soluzioni costruite per gli stati precedenti, fino a ottenere le migliori soluzioni del problema globale. Successivamente, è stato definito un algoritmo basato su un approccio di ricorsione backward; in questo caso si utilizza una funzione ricorsiva che, chiamata a partire dallo stato corrispondente al problema globale, viene richiamata solo sugli stati intermedi strettamente necessari, e per ognuno di essi non vengono determinate soluzioni superflue.