Sparse Signal Representation of Ultrasonic Signals for Structural Health Monitoring Applications

Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

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 fascicolo sanitario elettronico tra Semantic Web e diritto alla privacy

Principale obiettivo della ricerca è quello di ricostruire lo stato dell’arte in materia di sanità elettronica e Fascicolo Sanitario Elettronico, con una precipua attenzione ai temi della protezione dei dati personali e dell’interoperabilità. A tal fine sono stati esaminati i documenti, vincolanti e non, dell’Unione europea nonché selezionati progetti europei e nazionali (come “Smart Open Services for European Patients” (EU); “Elektronische Gesundheitsakte” (Austria); “MedCom” (Danimarca); “Infrastruttura tecnologica del Fascicolo Sanitario Elettronico”, “OpenInFSE: Realizzazione di un’infrastruttura operativa a supporto dell’interoperabilità delle soluzioni territoriali di fascicolo sanitario elettronico nel contesto del sistema pubblico di connettività”, “Evoluzione e interoperabilità tecnologica del Fascicolo Sanitario Elettronico”, “IPSE - Sperimentazione di un sistema per l’interoperabilità europea e nazionale delle soluzioni di Fascicolo Sanitario Elettronico: componenti Patient Summary e ePrescription” (Italia)). Le analisi giuridiche e tecniche mostrano il bisogno urgente di definire modelli che incoraggino l’utilizzo di dati sanitari ed implementino strategie effettive per l’utilizzo con finalità secondarie di dati sanitari digitali , come Open Data e Linked Open Data. L’armonizzazione giuridica e tecnologica è vista come aspetto strategico per ridurre i conflitti in materia di protezione di dati personali esistenti nei Paesi membri nonché la mancanza di interoperabilità tra i sistemi informativi europei sui Fascicoli Sanitari Elettronici. A questo scopo sono state individuate tre linee guida: (1) armonizzazione normativa, (2) armonizzazione delle regole, (3) armonizzazione del design dei sistemi informativi. I principi della Privacy by Design (“prottivi” e “win-win”), così come gli standard del Semantic Web, sono considerate chiavi risolutive per il suddetto cambiamento.

Generatore di entropia basato su dinamica caotica con interfaccia usb

È impossibile implementare sorgenti autenticamente casuali su hardware digitale. Quindi, storicamente, si è fatto ampio uso di generatori di numeri pseudo-casuali, evitando così i costi necessari per la progettazione di hardware analogico dedicato. Tuttavia, le sorgenti pseudo-casuali hanno proprietà (riproducibilità e periodicità) che si trasformano in vulnerabilità, nel caso in cui vengano adottate in sistemi di sicurezza informatica e all’interno di algoritmi crittografici. Oggi la richiesta di generatori di numeri autenticamente casuali è ai suoi massimi storici. Alcuni importanti attori dell’ICT sviluppato proprie soluzioni dedicate, ma queste sono disponibili solo sui sistemi moderni e di fascia elevata. È quindi di grande attualità rendere fruibili generatori autenticamente casuali per sistemi già esistenti o a basso costo. Per garantire sicurezza e al tempo stesso contenere i costi di progetto è opportuno pensare ad architetture che consentano di riusare parti analogiche già disponibili. Particolarmente interessanti risultano alcune architetture che, grazie all’utilizzo di dinamiche caotiche, consentono di basare buona parte della catena analogica di elaborazione su ADC. Infatti, tali blocchi sono ampiamente fruibili in forma integrata su architetture programmabili e microcontrollori. In questo lavoro, si propone un’implementazione a basso costo ed elevata flessibilità di un architettura basata su un ADC, inizialmente concepita all’Università di Bologna. La riduzione di costo viene ottenuta sfruttando il convertitore già presente all’interno di un microcontrollore. L’elevata flessibilità deriva dal fatto che il microcontrollore prescelto mette a disposizione una varietà di interfacce di comunicazione, tra cui quella USB, con la quale è possibile rendere facilmente fruibili i numeri casuali generati. Quindi, l’intero apparato comprende solo un microcontrollore e una minima catena analogica di elaborazione esterna e può essere interfacciato con estrema facilità ad elaboratori elettronici o sistemi embedded. La qualità della proposta, in termini di statistica delle sequenze casuali generate, è stata validata sfruttando i test standardizzati dall’U.S. NIST.

Many-Core Architectures: Hardware-Software Optimization and Modeling Techniques

During the last few decades an unprecedented technological growth has been at the center of the embedded systems design paramount, with Moore’s Law being the leading factor of this trend. Today in fact an ever increasing number of cores can be integrated on the same die, marking the transition from state-of-the-art multi-core chips to the new many-core design paradigm. Despite the extraordinarily high computing power, the complexity of many-core chips opens the door to several challenges. As a result of the increased silicon density of modern Systems-on-a-Chip (SoC), the design space exploration needed to find the best design has exploded and hardware designers are in fact facing the problem of a huge design space. Virtual Platforms have always been used to enable hardware-software co-design, but today they are facing with the huge complexity of both hardware and software systems. In this thesis two different research works on Virtual Platforms are presented: the first one is intended for the hardware developer, to easily allow complex cycle accurate simulations of many-core SoCs. The second work exploits the parallel computing power of off-the-shelf General Purpose Graphics Processing Units (GPGPUs), with the goal of an increased simulation speed. The term Virtualization can be used in the context of many-core systems not only to refer to the aforementioned hardware emulation tools (Virtual Platforms), but also for two other main purposes: 1) to help the programmer to achieve the maximum possible performance of an application, by hiding the complexity of the underlying hardware. 2) to efficiently exploit the high parallel hardware of many-core chips in environments with multiple active Virtual Machines. This thesis is focused on virtualization techniques with the goal to mitigate, and overtake when possible, some of the challenges introduced by the many-core design paradigm.

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Advanced data deduplication techniques and their application

Data deduplication describes a class of approaches that reduce the storage capacity needed to store data or the amount of data that has to be transferred over a network. These approaches detect coarse-grained redundancies within a data set, e.g. a file system, and remove them.rnrnOne of the most important applications of data deduplication are backup storage systems where these approaches are able to reduce the storage requirements to a small fraction of the logical backup data size.rnThis thesis introduces multiple new extensions of so-called fingerprinting-based data deduplication. It starts with the presentation of a novel system design, which allows using a cluster of servers to perform exact data deduplication with small chunks in a scalable way.rnrnAfterwards, a combination of compression approaches for an important, but often over- looked, data structure in data deduplication systems, so called block and file recipes, is introduced. Using these compression approaches that exploit unique properties of data deduplication systems, the size of these recipes can be reduced by more than 92% in all investigated data sets. As file recipes can occupy a significant fraction of the overall storage capacity of data deduplication systems, the compression enables significant savings.rnrnA technique to increase the write throughput of data deduplication systems, based on the aforementioned block and file recipes, is introduced next. The novel Block Locality Caching (BLC) uses properties of block and file recipes to overcome the chunk lookup disk bottleneck of data deduplication systems. This chunk lookup disk bottleneck either limits the scalability or the throughput of data deduplication systems. The presented BLC overcomes the disk bottleneck more efficiently than existing approaches. Furthermore, it is shown that it is less prone to aging effects.rnrnFinally, it is investigated if large HPC storage systems inhibit redundancies that can be found by fingerprinting-based data deduplication. Over 3 PB of HPC storage data from different data sets have been analyzed. In most data sets, between 20 and 30% of the data can be classified as redundant. According to these results, future work in HPC storage systems should further investigate how data deduplication can be integrated into future HPC storage systems.rnrnThis thesis presents important novel work in different area of data deduplication re- search.

Simulation of visible light communications in vehicular networks

The rapid development in the field of lighting and illumination allows low energy consumption and a rapid growth in the use, and development of solid-state sources. As the efficiency of these devices increases and their cost decreases there are predictions that they will become the dominant source for general illumination in the short term. The objective of this thesis is to study, through extensive simulations in realistic scenarios, the feasibility and exploitation of visible light communication (VLC) for vehicular ad hoc networks (VANETs) applications. A brief introduction will introduce the new scenario of smart cities in which visible light communication will become a fundamental enabling technology for the future communication systems. Specifically, this thesis focus on the acquisition of several, frequent, and small data packets from vehicles, exploited as sensors of the environment. The use of vehicles as sensors is a new paradigm to enable an efficient environment monitoring and an improved traffic management. In most cases, the sensed information must be collected at a remote control centre and one of the most challenging aspects is the uplink acquisition of data from vehicles. My thesis discusses the opportunity to take advantage of short range vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications to offload the cellular networks. More specifically, it discusses the system design and assesses the obtainable cellular resource saving, by considering the impact of the percentage of vehicles equipped with short range communication devices, of the number of deployed road side units, and of the adopted routing protocol. When short range communications are concerned, WAVE/IEEE 802.11p is considered as standard for VANETs. Its use together with VLC will be considered in urban vehicular scenarios to let vehicles communicate without involving the cellular network. The study is conducted by simulation, considering both a simulation platform (SHINE, simulation platform for heterogeneous interworking networks) developed within the Wireless communication Laboratory (Wilab) of the University of Bologna and CNR, and network simulator (NS3). trying to realistically represent all the wireless network communication aspects. Specifically, simulation of vehicular system was performed and introduced in ns-3, creating a new module for the simulator. This module will help to study VLC applications in VANETs. Final observations would enhance and encourage potential research in the area and optimize performance of VLC systems applications in the future.

Progettazione ed implementazione di un dispositivo portabile per l'acquisizione ed il filtraggio di segnali biomedici

The use of wearable devices for the monitoring of biological potentials is an ever-growing area of research. Wearable devices for the monitoring of vital signs such as heart-rate, respiratory rate, cardiac output and blood oxygenation are necessary in determining the overall health of a patient and allowing earlier detection of adverse events such as heart attacks and strokes and earlier diagnosis of disease. This thesis describes a bio-potential acquisition embedded system designed with an innovative analog front-end, showing the performance in EMG and ECG applications and the comparison between different noise reduction algorithms. We demonstrate that the proposed system is able to acquire bio-potentials with a signal quality equivalent to state of the art bench-top biomedical devices and can be therefore used for monitoring purpose, with the advantages of a low-cost low-power wearable device.

FEM and experimental analysis of a wind turbine blade

This paperwork compares the a numerical validation of the finite element model (FEM) with respect the experimental tests of a new generation wind turbine blade designed by TPI Composites Inc. called BSDS (Blade System Design Study). The research is focused on the analysis by finite element (FE) of the BSDS blade and its comparison with respect the experimental data from static and dynamic investigations. The goal of the research is to create a general procedure which is based on a finite element model and will be used to create an accurate digital copy for any kind of blade. The blade prototype was created in SolidWorks and the blade of Sandia National Laboratories Blade System Design Study was accurately reproduced. At a later stage the SolidWorks model was imported in Ansys Mechanical APDL where the shell geometry was created and modal, static and fatigue analysis were carried out. The outcomes of the FEM analysis were compared with the real test on the BSDS blade at Clarkson University laboratory carried out by a new procedures called Blade Test Facility that includes different methods for both the static and dynamic test of the wind turbine blade. The outcomes from the FEM analysis reproduce the real behavior of the blade subjected to static loads in a very satisfying way. A most detailed study about the material properties could improve the accuracy of the analysis.

"Pillowe": progettazione e sviluppo di un cuscino intelligente

Progettazione di un cuscino che si occupa di noi e ci aiuta nell'addormentarci attraverso la musica. Il tutto grazie all'aiuto di sensori e dell'Arduino che comunicheranno con lo smartphone per dare un'esperienza flessibile e personalizzabile.

Performance Modeling Of Reconfigurable Distributed Systems Based On The Opensparc Fpga Board And The Sirc Communication Framewor

This thesis explores system performance for reconfigurable distributed systems and provides an analytical model for determining throughput of theoretical systems based on the OpenSPARC FPGA Board and the SIRC Communication Framework. This model was developed by studying a small set of variables that together determine a system¿s throughput. The importance of this model is in assisting system designers to make decisions as to whether or not to commit to designing a reconfigurable distributed system based on the estimated performance and hardware costs. Because custom hardware design and distributed system design are both time consuming and costly, it is important for designers to make decisions regarding system feasibility early in the development cycle. Based on experimental data the model presented in this paper shows a close fit with less than 10% experimental error on average. The model is limited to a certain range of problems, but it can still be used given those limitations and also provides a foundation for further development of modeling reconfigurable distributed systems.

HIGH PERFORMANCE, LOW COST SUBSPACE DECOMPOSITION AND POLYNOMIAL ROOTING FOR REAL TIME DIRECTION OF ARRIVAL ESTIMATION: ANALYSIS AND IMPLEMENTATION

This thesis develops high performance real-time signal processing modules for direction of arrival (DOA) estimation for localization systems. It proposes highly parallel algorithms for performing subspace decomposition and polynomial rooting, which are otherwise traditionally implemented using sequential algorithms. The proposed algorithms address the emerging need for real-time localization for a wide range of applications. As the antenna array size increases, the complexity of signal processing algorithms increases, making it increasingly difficult to satisfy the real-time constraints. This thesis addresses real-time implementation by proposing parallel algorithms, that maintain considerable improvement over traditional algorithms, especially for systems with larger number of antenna array elements. Singular value decomposition (SVD) and polynomial rooting are two computationally complex steps and act as the bottleneck to achieving real-time performance. The proposed algorithms are suitable for implementation on field programmable gated arrays (FPGAs), single instruction multiple data (SIMD) hardware or application specific integrated chips (ASICs), which offer large number of processing elements that can be exploited for parallel processing. The designs proposed in this thesis are modular, easily expandable and easy to implement. Firstly, this thesis proposes a fast converging SVD algorithm. The proposed method reduces the number of iterations it takes to converge to correct singular values, thus achieving closer to real-time performance. A general algorithm and a modular system design are provided making it easy for designers to replicate and extend the design to larger matrix sizes. Moreover, the method is highly parallel, which can be exploited in various hardware platforms mentioned earlier. A fixed point implementation of proposed SVD algorithm is presented. The FPGA design is pipelined to the maximum extent to increase the maximum achievable frequency of operation. The system was developed with the objective of achieving high throughput. Various modern cores available in FPGAs were used to maximize the performance and details of these modules are presented in detail. Finally, a parallel polynomial rooting technique based on Newton’s method applicable exclusively to root-MUSIC polynomials is proposed. Unique characteristics of root-MUSIC polynomial’s complex dynamics were exploited to derive this polynomial rooting method. The technique exhibits parallelism and converges to the desired root within fixed number of iterations, making this suitable for polynomial rooting of large degree polynomials. We believe this is the first time that complex dynamics of root-MUSIC polynomial were analyzed to propose an algorithm. In all, the thesis addresses two major bottlenecks in a direction of arrival estimation system, by providing simple, high throughput, parallel algorithms.

Management Challenges in Nurturing a Safe Work Environment

As engineers, we are trained to use logical, rational problem solving to insure our mines operate at maximum efficiency. We tend to use the same technical approach to design safety into all mining systems. This works well for machines, but not so much for the human component. Recent insights in the field of behavioral economics provide useful ideas for addressing the fact that we are driven by emotions more often than by rational thought. Understanding the nonrational aspect of human behavior is an important piece of any safety system design.

Early Versus Late Effort in Dynamic Agencies with Unverifiable Information

In this paper we analyze a dynamic agency problem where contracting parties do not know the agent's future productivity at the beginning of the relationship. We consider a two-period model where both the agent and the principal observe the agent's second-period productivity at the end of the first period. This observation is assumed to be non-verifiable information. We compare long-term contracts with short-term contracts with respect to their suitability to motivate effort in both periods. On the one hand, short-term contracts allow for a better fine-tuning of second-period incentives as they can be aligned with the agent's second-period productivity. On the other hand, in short-term contracts first-period effort incentives might be distorted as contracts have to be sequentially optimal. Hence, the difference between long-term and short-term contracts is characterized by a trade-off between inducing effort in the first and in the second period. We analyze the determinants of this trade-off and demonstrate its implications for performance measurement and information system design.