Study of charge, spin, and structural orderings in quantum materials using nuclei and muons as local probes

Quantum Materials are many body systems displaying emergent phenomena caused by quantum collective behaviour, such as superconductivity, charge density wave, fractional hall effect, and exotic magnetism. Among quantum materials, two families have recently attracted attention: kagome metals and Kitaev materials. Kagome metals have a unique crystal structure made up of triangular lattice layers that are used to form the kagome layer. Due to superconductivity, magnetism, and charge ordering states such as the Charge Density Wave (CDW), unexpected physical phenomena such as the massive Anomalous Hall Effect (AHE) and possible Majorana fermions develop in these materials. Kitaev materials are a type of quantum material with a unique spin model named after Alexei Kitaev. They include fractional fluctuations of Majorana fermions and non-topological abelian anyons, both of which might be used in quantum computing. Furthermore, they provide a realistic framework for the development of quantum spin liquid (QSL), in which quantum fluctuations produce long-range entanglements between electronic states despite the lack of classical magnetic ordering. In my research, I performed several nuclear magnetic resonance (NMR), nuclear quadrupole resonance (NQR), and muon spin spectroscopy (µSR) experiments to explain and unravel novel phases of matter within these unusual families of materials. NMR has been found to be an excellent tool for studying these materials’ local electronic structures and magnetic properties. I could use NMR to determine, for the first time, the structure of a novel kagome superconductor, RbV3Sb5, below the CDW transition, and to highlight the role of chemical doping in the CDW phase of AV3Sb5 superconductors. µSR has been used to investigate the effect of doping on kagome material samples in order to study the presence and behaviour of an anomalous phase developing at low temperatures and possibly related to time-reversal symmetry breaking.

Tecniche di ottimizzazione del software per sistemi su singolo chip per applicazioni di Nomadic Computing

I moderni sistemi embedded sono equipaggiati con risorse hardware che consentono l’esecuzione di applicazioni molto complesse come il decoding audio e video. La progettazione di simili sistemi deve soddisfare due esigenze opposte. Da un lato è necessario fornire un elevato potenziale computazionale, dall’altro bisogna rispettare dei vincoli stringenti riguardo il consumo di energia. Uno dei trend più diffusi per rispondere a queste esigenze opposte è quello di integrare su uno stesso chip un numero elevato di processori caratterizzati da un design semplificato e da bassi consumi. Tuttavia, per sfruttare effettivamente il potenziale computazionale offerto da una batteria di processoriè necessario rivisitare pesantemente le metodologie di sviluppo delle applicazioni. Con l’avvento dei sistemi multi-processore su singolo chip (MPSoC) il parallel programming si è diffuso largamente anche in ambito embedded. Tuttavia, i progressi nel campo della programmazione parallela non hanno mantenuto il passo con la capacità di integrare hardware parallelo su un singolo chip. Oltre all’introduzione di multipli processori, la necessità di ridurre i consumi degli MPSoC comporta altre soluzioni architetturali che hanno l’effetto diretto di complicare lo sviluppo delle applicazioni. Il design del sottosistema di memoria, in particolare, è un problema critico. Integrare sul chip dei banchi di memoria consente dei tempi d’accesso molto brevi e dei consumi molto contenuti. Sfortunatamente, la quantità di memoria on-chip che può essere integrata in un MPSoC è molto limitata. Per questo motivo è necessario aggiungere dei banchi di memoria off-chip, che hanno una capacità molto maggiore, come maggiori sono i consumi e i tempi d’accesso. La maggior parte degli MPSoC attualmente in commercio destina una parte del budget di area all’implementazione di memorie cache e/o scratchpad. Le scratchpad (SPM) sono spesso preferite alle cache nei sistemi MPSoC embedded, per motivi di maggiore predicibilità, minore occupazione d’area e – soprattutto – minori consumi. Per contro, mentre l’uso delle cache è completamente trasparente al programmatore, le SPM devono essere esplicitamente gestite dall’applicazione. Esporre l’organizzazione della gerarchia di memoria ll’applicazione consente di sfruttarne in maniera efficiente i vantaggi (ridotti tempi d’accesso e consumi). Per contro, per ottenere questi benefici è necessario scrivere le applicazioni in maniera tale che i dati vengano partizionati e allocati sulle varie memorie in maniera opportuna. L’onere di questo compito complesso ricade ovviamente sul programmatore. Questo scenario descrive bene l’esigenza di modelli di programmazione e strumenti di supporto che semplifichino lo sviluppo di applicazioni parallele. In questa tesi viene presentato un framework per lo sviluppo di software per MPSoC embedded basato su OpenMP. OpenMP è uno standard di fatto per la programmazione di multiprocessori con memoria shared, caratterizzato da un semplice approccio alla parallelizzazione tramite annotazioni (direttive per il compilatore). La sua interfaccia di programmazione consente di esprimere in maniera naturale e molto efficiente il parallelismo a livello di loop, molto diffuso tra le applicazioni embedded di tipo signal processing e multimedia. OpenMP costituisce un ottimo punto di partenza per la definizione di un modello di programmazione per MPSoC, soprattutto per la sua semplicità d’uso. D’altra parte, per sfruttare in maniera efficiente il potenziale computazionale di un MPSoC è necessario rivisitare profondamente l’implementazione del supporto OpenMP sia nel compilatore che nell’ambiente di supporto a runtime. Tutti i costrutti per gestire il parallelismo, la suddivisione del lavoro e la sincronizzazione inter-processore comportano un costo in termini di overhead che deve essere minimizzato per non comprometterre i vantaggi della parallelizzazione. Questo può essere ottenuto soltanto tramite una accurata analisi delle caratteristiche hardware e l’individuazione dei potenziali colli di bottiglia nell’architettura. Una implementazione del task management, della sincronizzazione a barriera e della condivisione dei dati che sfrutti efficientemente le risorse hardware consente di ottenere elevate performance e scalabilità. La condivisione dei dati, nel modello OpenMP, merita particolare attenzione. In un modello a memoria condivisa le strutture dati (array, matrici) accedute dal programma sono fisicamente allocate su una unica risorsa di memoria raggiungibile da tutti i processori. Al crescere del numero di processori in un sistema, l’accesso concorrente ad una singola risorsa di memoria costituisce un evidente collo di bottiglia. Per alleviare la pressione sulle memorie e sul sistema di connessione vengono da noi studiate e proposte delle tecniche di partizionamento delle strutture dati. Queste tecniche richiedono che una singola entità di tipo array venga trattata nel programma come l’insieme di tanti sotto-array, ciascuno dei quali può essere fisicamente allocato su una risorsa di memoria differente. Dal punto di vista del programma, indirizzare un array partizionato richiede che ad ogni accesso vengano eseguite delle istruzioni per ri-calcolare l’indirizzo fisico di destinazione. Questo è chiaramente un compito lungo, complesso e soggetto ad errori. Per questo motivo, le nostre tecniche di partizionamento sono state integrate nella l’interfaccia di programmazione di OpenMP, che è stata significativamente estesa. Specificamente, delle nuove direttive e clausole consentono al programmatore di annotare i dati di tipo array che si vuole partizionare e allocare in maniera distribuita sulla gerarchia di memoria. Sono stati inoltre sviluppati degli strumenti di supporto che consentono di raccogliere informazioni di profiling sul pattern di accesso agli array. Queste informazioni vengono sfruttate dal nostro compilatore per allocare le partizioni sulle varie risorse di memoria rispettando una relazione di affinità tra il task e i dati. Più precisamente, i passi di allocazione nel nostro compilatore assegnano una determinata partizione alla memoria scratchpad locale al processore che ospita il task che effettua il numero maggiore di accessi alla stessa.

Formalizing languages for service oriented computing

Service Oriented Computing is a new programming paradigm for addressing distributed system design issues. Services are autonomous computational entities which can be dynamically discovered and composed in order to form more complex systems able to achieve different kinds of task. E-government, e-business and e-science are some examples of the IT areas where Service Oriented Computing will be exploited in the next years. At present, the most credited Service Oriented Computing technology is that of Web Services, whose specifications are enriched day by day by industrial consortia without following a precise and rigorous approach. This PhD thesis aims, on the one hand, at modelling Service Oriented Computing in a formal way in order to precisely define the main concepts it is based upon and, on the other hand, at defining a new approach, called bipolar approach, for addressing system design issues by synergically exploiting choreography and orchestration languages related by means of a mathematical relation called conformance. Choreography allows us to describe systems of services from a global view point whereas orchestration supplies a means for addressing such an issue from a local perspective. In this work we present SOCK, a process algebra based language inspired by the Web Service orchestration language WS-BPEL which catches the essentials of Service Oriented Computing. From the definition of SOCK we will able to define a general model for dealing with Service Oriented Computing where services and systems of services are related to the design of finite state automata and process algebra concurrent systems, respectively. Furthermore, we introduce a formal language for dealing with choreography. Such a language is equipped with a formal semantics and it forms, together with a subset of the SOCK calculus, the bipolar framework. Finally, we present JOLIE which is a Java implentation of a subset of the SOCK calculus and it is part of the bipolar framework we intend to promote.

Analisi degli aspetti di qualità nella gestione dei sistemi di drenaggio urbano attraverso modellazione numerica e indagini di campo

In order to protect river water quality, highly affected in urban areas by continuos as intermittent immissions, it is necessary to adopt measures to intercept and treat these polluted flows. In particular during rain events, river water quality is affected by CSOs activation. Built in order to protect the sewer system and the WWTP by increased flows due to heavy rains, CSOs divert excess flows to the receiving water body. On the basis of several scientific papers, and of direct evidences as well, that demonstrate the detrimental effect of CSOs discharges, also the legislative framework moved towards a stream standard point of view. The WFD (EU/69/2000) sets new goals for receiving water quality, and groundwater as well, through an integrated immission/emissions phylosophy, in which emission limits are associated with effluent standards, based on the receiving water characteristics and their specific use. For surface waters the objective is that of a “good” ecological and chemical quality status. A surface water is defined as of good ecological quality if there is only slight departure from the biological community that would be expected in conditions of minimal anthropogenic impact. Each Member State authority is responsible for preparing and implementing a River Basin Management Plan to achieve the good ecological quality, and comply with WFD requirements. In order to cope with WFD targets, and thus to improve urban receiving water quality, a CSOs control strategy need to be implemented. Temporarily storing the overflow (or at least part of it) into tanks and treating it in the WWTP, after the end of the storm, showed good results in reducing total pollutant mass spilled into the receiving river. Italian State Authority, in order to comply with WFD statements, sets general framework, and each Region has to adopt a Water Remediation Plan (PTA, Piano Tutela Acque), setting goals, methods, and terms, to improve river water quality. Emilia Romagna PTA sets 25% reduction up to 2008, and 50% reduction up to 2015 fo total pollutants masses delivered by CSOs spills. In order to plan remediation actions, a deep insight into spills dynamics is thus of great importance. The present thesis tries to understand spills dynamics through a numerical and an experimental approach. A four months monitoring and sampling campaign was set on the Bologna sewer network, and on the Navile Channel, that is the WWTP receiving water , and that receives flows from up to 28 CSOs during rain events. On the other hand, the full model of the sewer network, was build with the commercial software InfoWorks CS. The model was either calibrated with the data from the monitoring and sampling campaign. Through further model simulations interdependencies among masses spilled, rain characteristics and basin characteristics are looked for. The thesis can be seen as a basis for further insighs and for planning remediation actions.

Enabling computationally intensive bioinformatics applications on the Grid platform

Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.

Formazione, apprendimento e nuove prospettive e-learning. Lo sviluppo delle nuove tecnologie didattiche e la creazione di sistemi di apprendimento lungo l’intero arco della vita

The thesis of this paper is based on the assumption that the socio-economic system in which we are living is characterised by three great trends: growing attention to the promotion of human capital; extremely rapid technological progress, based above all on the information and communication technologies (ICT); the establishment of new production and organizational set-ups. These transformation processes pose a concrete challenge to the training sector, which is called to satisfy the demand for new skills that need to be developed and disseminated. Hence the growing interest that the various training sub-systems devote to the issues of lifelong learning and distance learning. In such a context, the so-called e-learning acquires a central role. The first chapter proposes a reference theoretical framework for the transformations that are shaping post-industrial society. It analyzes some key issues such as: how work is changing, the evolution of organizational set-ups and the introduction of learning organization, the advent of the knowledge society and of knowledge companies, the innovation of training processes, and the key role of ICT in the new training and learning systems. The second chapter focuses on the topic of e-learning as an effective training model in response to the need for constant learning that is emerging in the knowledge society. This chapter starts with a reflection on the importance of lifelong learning and introduces the key arguments of this thesis, i.e. distance learning (DL) and the didactic methodology called e-learning. It goes on with an analysis of the various theoretic and technical aspects of e-learning. In particular, it delves into the theme of e-learning as an integrated and constant training environment, characterized by customized programmes and collaborative learning, didactic assistance and constant monitoring of the results. Thus, all the aspects of e-learning are taken into exam: the actors and the new professionals, the virtual communities as learning subjects, the organization of contents in learning objects, the conformity to international standards, the integrated platforms and so on. The third chapter, which concludes the theoretic-interpretative part, starts with a short presentation of the state-of-the-art e-learning international market that aims to understand its peculiarities and its current trends. Finally, we focus on some important regulation aspects related to the strong impulse given by the European Commission first, and by the Italian governments secondly, to the development and diffusion of e-learning. The second part of the thesis (chapters 4, 5 and 6) focus on field research, which aims to define the Italian scenario for e-learning. In particular, we have examined some key topics such as: the challenges of training and the instruments to face such challenges; the new didactic methods and technologies for lifelong learning; the level of diffusion of e-learning in Italy; the relation between classroom training and online training; the main factors of success as well as the most critical aspects of the introduction of e-learning in the various learning environments. As far as the methodological aspects are concerned, we have favoured a qualitative and quantitative analysis. A background analysis has been done to collect the statistical data available on this topic, as well as the research previously carried out in this area. The main source of data is constituted by the results of the Observatory on e-learning of Aitech-Assinform, which covers the 2000s and four areas of implementation (firms, public administration, universities, school): the thesis has reviewed the results of the last three available surveys, offering a comparative interpretation of them. We have then carried out an in-depth empirical examination of two case studies, which have been selected by virtue of the excellence they have achieved and can therefore be considered advanced and emblematic experiences (a large firm and a Graduate School).

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Specification and Verification of Declarative Open Interaction Models - A Logic-based framework

The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

Self-organising coordination systems

Many research fields are pushing the engineering of large-scale, mobile, and open systems towards the adoption of techniques inspired by self-organisation: pervasive computing, but also distributed artificial intelligence, multi-agent systems, social networks, peer-topeer and grid architectures exploit adaptive techniques to make global system properties emerge in spite of the unpredictability of interactions and behaviour. Such a trend is visible also in coordination models and languages, whenever a coordination infrastructure needs to cope with managing interactions in highly dynamic and unpredictable environments. As a consequence, self-organisation can be regarded as a feasible metaphor to define a radically new conceptual coordination framework. The resulting framework defines a novel coordination paradigm, called self-organising coordination, based on the idea of spreading coordination media over the network, and charge them with services to manage interactions based on local criteria, resulting in the emergence of desired and fruitful global coordination properties of the system. Features like topology, locality, time-reactiveness, and stochastic behaviour play a key role in both the definition of such a conceptual framework and the consequent development of self-organising coordination services. According to this framework, the thesis presents several self-organising coordination techniques developed during the PhD course, mainly concerning data distribution in tuplespace-based coordination systems. Some of these techniques have been also implemented in ReSpecT, a coordination language for tuple spaces, based on logic tuples and reactions to events occurring in a tuple space. In addition, the key role played by simulation and formal verification has been investigated, leading to analysing how automatic verification techniques like probabilistic model checking can be exploited in order to formally prove the emergence of desired behaviours when dealing with coordination approaches based on self-organisation. To this end, a concrete case study is presented and discussed.

Architectures for Context Aware Services in Smart Environments

This thesis deals with Context Aware Services, Smart Environments, Context Management and solutions for Devices and Service Interoperability. Multi-vendor devices offer an increasing number of services and end-user applications that base their value on the ability to exploit the information originating from the surrounding environment by means of an increasing number of embedded sensors, e.g. GPS, compass, RFID readers, cameras and so on. However, usually such devices are not able to exchange information because of the lack of a shared data storage and common information exchange methods. A large number of standards and domain specific building blocks are available and are heavily used in today's products. However, the use of these solutions based on ready-to-use modules is not without problems. The integration and cooperation of different kinds of modules can be daunting because of growing complexity and dependency. In this scenarios it might be interesting to have an infrastructure that makes the coexistence of multi-vendor devices easy, while enabling low cost development and smooth access to services. This sort of technologies glue should reduce both software and hardware integration costs by removing the trouble of interoperability. The result should also lead to faster and simplified design, development and, deployment of cross-domain applications. This thesis is mainly focused on SW architectures supporting context aware service providers especially on the following subjects: - user preferences service adaptation - context management - content management - information interoperability - multivendor device interoperability - communication and connectivity interoperability Experimental activities were carried out in several domains including Cultural Heritage, indoor and personal smart spaces – all of which are considered significant test-beds in Context Aware Computing. The work evolved within european and national projects: on the europen side, I carried out my research activity within EPOCH, the FP6 Network of Excellence on “Processing Open Cultural Heritage” and within SOFIA, a project of the ARTEMIS JU on embedded systems. I worked in cooperation with several international establishments, including the University of Kent, VTT (the Technical Reserarch Center of Finland) and Eurotech. On the national side I contributed to a one-to-one research contract between ARCES and Telecom Italia. The first part of the thesis is focused on problem statement and related work and addresses interoperability issues and related architecture components. The second part is focused on specific architectures and frameworks: - MobiComp: a context management framework that I used in cultural heritage applications - CAB: a context, preference and profile based application broker which I designed within EPOCH Network of Excellence - M3: "Semantic Web based" information sharing infrastructure for smart spaces designed by Nokia within the European project SOFIA - NoTa: a service and transport independent connectivity framework - OSGi: the well known Java based service support framework The final section is dedicated to the middleware, the tools and, the SW agents developed during my Doctorate time to support context-aware services in smart environments.

A model for diffusive and displacive phase transitions in steels

Heat treatment of steels is a process of fundamental importance in tailoring the properties of a material to the desired application; developing a model able to describe such process would allow to predict the microstructure obtained from the treatment and the consequent mechanical properties of the material. A steel, during a heat treatment, can undergo two different kinds of phase transitions [p.t.]: diffusive (second order p.t.) and displacive (first order p.t.); in this thesis, an attempt to describe both in a thermodynamically consistent framework is made; a phase field, diffuse interface model accounting for the coupling between thermal, chemical and mechanical effects is developed, and a way to overcome the difficulties arising from the treatment of the non-local effects (gradient terms) is proposed. The governing equations are the balance of linear momentum equation, the Cahn-Hilliard equation and the balance of internal energy equation. The model is completed with a suitable description of the free energy, from which constitutive relations are drawn. The equations are then cast in a variational form and different numerical techniques are used to deal with the principal features of the model: time-dependency, non-linearity and presence of high order spatial derivatives. Simulations are performed using DOLFIN, a C++ library for the automated solution of partial differential equations by means of the finite element method; results are shown for different test-cases. The analysis is reduced to a two dimensional setting, which is simpler than a three dimensional one, but still meaningful.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.