Analysis of charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

Hardware/Software Design of Dynamic Real-Time Schedulers for Embedded Multiprocessor Systems

The new generation of multicore processors opens new perspectives for the design of embedded systems. Multiprocessing, however, poses new challenges to the scheduling of real-time applications, in which the ever-increasing computational demands are constantly flanked by the need of meeting critical time constraints. Many research works have contributed to this field introducing new advanced scheduling algorithms. However, despite many of these works have solidly demonstrated their effectiveness, the actual support for multiprocessor real-time scheduling offered by current operating systems is still very limited. This dissertation deals with implementative aspects of real-time schedulers in modern embedded multiprocessor systems. The first contribution is represented by an open-source scheduling framework, which is capable of realizing complex multiprocessor scheduling policies, such as G-EDF, on conventional operating systems exploiting only their native scheduler from user-space. A set of experimental evaluations compare the proposed solution to other research projects that pursue the same goals by means of kernel modifications, highlighting comparable scheduling performances. The principles that underpin the operation of the framework, originally designed for symmetric multiprocessors, have been further extended first to asymmetric ones, which are subjected to major restrictions such as the lack of support for task migrations, and later to re-programmable hardware architectures (FPGAs). In the latter case, this work introduces a scheduling accelerator, which offloads most of the scheduling operations to the hardware and exhibits extremely low scheduling jitter. The realization of a portable scheduling framework presented many interesting software challenges. One of these has been represented by timekeeping. In this regard, a further contribution is represented by a novel data structure, called addressable binary heap (ABH). Such ABH, which is conceptually a pointer-based implementation of a binary heap, shows very interesting average and worst-case performances when addressing the problem of tick-less timekeeping of high-resolution timers.

Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

Characterization of fold-related fractures in the carbonate rocks of the Cingoli anticline, northern Apennines, Italy

Thrust fault-related folds in carbonate rocks are characterized by deformation accommodated by different structures, such as joints, faults, pressure solution seams, and deformation bands. Defining the development of fracture systems related to the folding process is significant both for theoretical and practical purposes. Fracture systems are useful constrains in order to understand the kinematical evolution of the fold. Furthermore, understanding the relationships between folding and fracturing provides a noteworthy contribution for reconstructing the geodynamic and the structural evolution of the studied area. Moreover, as fold-related fractures influence fluid flow through rocks, fracture systems are relevant for energy production (geothermal studies, methane and CO2 , storage and hydrocarbon exploration), environmental and social issues (pollutant distribution, aquifer characterization). The PhD project shows results of a study carried out in a multilayer carbonate anticline characterized by different mechanical properties. The aim of this study is to understand the factors which influence the fracture formation and to define their temporal sequence during the folding process. The studied are is located in the Cingoli anticline (Northern Apennines), which is characterized by a pelagic multilayer characterized by sequences with different mechanical stratigraphies. A multi-scale analysis has been made in several outcrops located in different structural positions. This project shows that the conceptual sketches proposed in literature and the strain distribution models outline well the geometrical orientation of most of the set of fractures observed in the Cingoli anticline. On the other hand, the present work suggests the relevance of the mechanical stratigraphy in particular controlling the type of fractures formed (e.g. pressure solution seams, joints or shear fractures) and their subsequent evolution. Through a multi-scale analysis, and on the basis of the temporal relationship between fracture sets and their orientation respect layering, I also suggest a conceptual model for fracture systems formation.

Pervasive Sensing in Future Networks

Pervasive Sensing is a recent research trend that aims at providing widespread computing and sensing capabilities to enable the creation of smart environments that can sense, process, and act by considering input coming from both people and devices. The capabilities necessary for Pervasive Sensing are nowadays available on a plethora of devices, from embedded devices to PCs and smartphones. The wide availability of new devices and the large amount of data they can access enable a wide range of novel services in different areas, spanning from simple data collection systems to socially-aware collaborative filtering. However, the strong heterogeneity and unreliability of devices and sensors poses significant challenges. So far, existing works on Pervasive Sensing have focused only on limited portions of the whole stack of available devices and data that they can use, to propose and develop mainly vertical solutions. The push from academia and industry for this kind of services shows that time is mature for a more general support framework for Pervasive Sensing solutions able to enhance frail architectures, promote a well balanced usage of resources on different devices, and enable the widest possible access to sensed data, while ensuring a minimal energy consumption on battery-operated devices. This thesis focuses on pervasive sensing systems to extract design guidelines as foundation of a comprehensive reference model for multi-tier Pervasive Sensing applications. The validity of the proposed model is tested in five different scenarios that present peculiar and different requirements, and different hardware and sensors. The ease of mapping from the proposed logical model to the real implementations and the positive performance result campaigns prove the quality of the proposed approach and offer a reliable reference model, together with a direction for the design and deployment of future Pervasive Sensing applications.

Implicazioni teoriche e sperimentali della sincronizzazione assoluta nella teoria della relatività speciale

Sono indagate le implicazioni teoriche e sperimentali derivanti dall'assunzione, nella teoria della relatività speciale, di un criterio di sincronizzazione (detta assoluta) diverso da quello standard. La scelta della sincronizzazione assoluta è giustificata da alcune considerazioni di carattere epistemologico sullo status di fenomeni quali la contrazione delle lunghezze e la dilatazione del tempo. Oltre che a fornire una diversa interpretazione, la sincronizzazione assoluta rappresenta una estensione del campo di applicazione della relatività speciale in quanto può essere attuata anche in sistemi di riferimento accelerati. Questa estensione consente di trattare in maniera unitaria i fenomeni sia in sistemi di riferimento inerziali che accelerati. L'introduzione della sincronizzazione assoluta implica una modifica delle trasformazioni di Lorentz. Una caratteristica di queste nuove trasformazioni (dette inerziali) è che la trasformazione del tempo è indipendente dalle coordinate spaziali. Le trasformazioni inerziali sono ottenute nel caso generale tra due sistemi di riferimento aventi velocità (assolute) u1 e u2 comunque orientate. Viene mostrato che le trasformazioni inerziali possono formare un gruppo pur di prendere in considerazione anche riferimenti non fisicamente realizzabili perché superluminali. È analizzato il moto rigido secondo Born di un corpo esteso considerando la sincronizzazione assoluta. Sulla base delle trasformazioni inerziali si derivano le trasformazioni per i campi elettromagnetici e le equazioni di questi campi (che sostituiscono le equazioni di Maxwell). Si mostra che queste equazioni contengono soluzioni in assenza di cariche che si propagano nello spazio come onde generalmente anisotrope in accordo con quanto previsto dalle trasformazioni inerziali. L'applicazione di questa teoria elettromagnetica a sistemi accelerati mostra l'esistenza di fenomeni mai osservati che, pur non essendo in contraddizione con la relatività standard, ne forzano l'interpretazione. Viene proposto e descritto un esperimento in cui uno di questi fenomeni è misurabile.

Advanced Techniques for Face Recognition under Challenging Environments

Automatically recognizing faces captured under uncontrolled environments has always been a challenging topic in the past decades. In this work, we investigate cohort score normalization that has been widely used in biometric verification as means to improve the robustness of face recognition under challenging environments. In particular, we introduce cohort score normalization into undersampled face recognition problem. Further, we develop an effective cohort normalization method specifically for the unconstrained face pair matching problem. Extensive experiments conducted on several well known face databases demonstrate the effectiveness of cohort normalization on these challenging scenarios. In addition, to give a proper understanding of cohort behavior, we study the impact of the number and quality of cohort samples on the normalization performance. The experimental results show that bigger cohort set size gives more stable and often better results to a point before the performance saturates. And cohort samples with different quality indeed produce different cohort normalization performance. Recognizing faces gone after alterations is another challenging problem for current face recognition algorithms. Face image alterations can be roughly classified into two categories: unintentional (e.g., geometrics transformations introduced by the acquisition devide) and intentional alterations (e.g., plastic surgery). We study the impact of these alterations on face recognition accuracy. Our results show that state-of-the-art algorithms are able to overcome limited digital alterations but are sensitive to more relevant modifications. Further, we develop two useful descriptors for detecting those alterations which can significantly affect the recognition performance. In the end, we propose to use the Structural Similarity (SSIM) quality map to detect and model variations due to plastic surgeries. Extensive experiments conducted on a plastic surgery face database demonstrate the potential of SSIM map for matching face images after surgeries.

Quality of Service in Distributed Stream Processing for large scale Smart Pervasive Environments

The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.

Analysis and modelling of the performance of technologies for flue gas treatment in Waste-to-Energy processes

Waste management represents an important issue in our society and Waste-to-Energy incineration plants have been playing a significant role in the last decades, showing an increased importance in Europe. One of the main issues posed by waste combustion is the generation of air contaminants. Particular concern is present about acid gases, mainly hydrogen chloride and sulfur oxides, due to their potential impact on the environment and on human health. Therefore, in the present study the main available technological options for flue gas treatment were analyzed, focusing on dry treatment systems, which are increasingly applied in Municipal Solid Wastes (MSW) incinerators. An operational model was proposed to describe and optimize acid gas removal process. It was applied to an existing MSW incineration plant, where acid gases are neutralized in a two-stage dry treatment system. This process is based on the injection of powdered calcium hydroxide and sodium bicarbonate in reactors followed by fabric filters. HCl and SO2 conversions were expressed as a function of reactants flow rates, calculating model parameters from literature and plant data. The implementation in a software for process simulation allowed the identification of optimal operating conditions, taking into account the reactant feed rates, the amount of solid products and the recycle of the sorbent. Alternative configurations of the reference plant were also assessed. The applicability of the operational model was extended developing also a fundamental approach to the issue. A predictive model was developed, describing mass transfer and kinetic phenomena governing the acid gas neutralization with solid sorbents. The rate controlling steps were identified through the reproduction of literature data, allowing the description of acid gas removal in the case study analyzed. A laboratory device was also designed and started up to assess the required model parameters.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.

Engineering Complex Computational Ecosystems

Self-organising pervasive ecosystems of devices are set to become a major vehicle for delivering infrastructure and end-user services. The inherent complexity of such systems poses new challenges to those who want to dominate it by applying the principles of engineering. The recent growth in number and distribution of devices with decent computational and communicational abilities, that suddenly accelerated with the massive diffusion of smartphones and tablets, is delivering a world with a much higher density of devices in space. Also, communication technologies seem to be focussing on short-range device-to-device (P2P) interactions, with technologies such as Bluetooth and Near-Field Communication gaining greater adoption. Locality and situatedness become key to providing the best possible experience to users, and the classic model of a centralised, enormously powerful server gathering and processing data becomes less and less efficient with device density. Accomplishing complex global tasks without a centralised controller responsible of aggregating data, however, is a challenging task. In particular, there is a local-to-global issue that makes the application of engineering principles challenging at least: designing device-local programs that, through interaction, guarantee a certain global service level. In this thesis, we first analyse the state of the art in coordination systems, then motivate the work by describing the main issues of pre-existing tools and practices and identifying the improvements that would benefit the design of such complex software ecosystems. The contribution can be divided in three main branches. First, we introduce a novel simulation toolchain for pervasive ecosystems, designed for allowing good expressiveness still retaining high performance. Second, we leverage existing coordination models and patterns in order to create new spatial structures. Third, we introduce a novel language, based on the existing ``Field Calculus'' and integrated with the aforementioned toolchain, designed to be usable for practical aggregate programming.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

La ricerca traslazionale in farmacologia gastroenterologica

Il presente studio si concentra sull’analisi degli aspetti traslazionali nella ricerca farmacologica applicata alla Gastroenterologia. La trattazione si articola in due parti: una prima elaborazione teorica, che permette di inquadrare nel contesto della ricerca traslazionale il razionale scientifico ed etico alla base delle attività sperimentali eseguite durante il triennio; una seconda parte, nella quale si riportano i metodi, i risultati e le osservazioni conclusive derivanti dallo studio sperimentale. Nella prima parte vengono analizzate alcune caratteristiche delle procedure, adottate nella ricerca in ambito farmacologico gastrointestinale, che permettono di ottenere un dato verosimile derivabile da modelli diversi rispetto all’organismo umano. Sono inclusi nella trattazione gli aspetti etici dell’utilizzo di alcuni modelli animali di patologie intestinali organiche e funzionali in relazione al loro grado di predittività rispetto alla realtà sperimentale clinica. Nella seconda parte della trattazione, viene presentato uno studio esplorativo tissutale multicentrico sul ruolo del sistema oppioide e cannabinoide nella sindrome dell’intestino irritabile (IBS). Obiettivo dello studio è la valutazione dell’espressione e la localizzazione del recettore oppioide µ (µOR), del suo ligando β endorfina (β-END) e del recettore cannabinoide 2 (CB2) nei pazienti con IBS ad alvo costipato (IBS-C) e diarroico (IBS-D), ed in soggetti sani (HC). I dati ottenuti indicano un’implicazione del sistema oppioide e cannabinoide nella risposta immune alterata riscontrata nei pazienti con IBS ed in particolare nel sottogruppo IBS-C. La presente trattazione suggerisce come la creazione di nuovi sistemi di indagine sempre più validi da un punto di vista traslazionale possa dipendere, almeno in parte, dalla capacità di integrare realtà disciplinari, tecnologie ed esperienze metodologiche diverse nel contesto della ricerca in campo biomedico e farmacologico ed in particolare tramite un mutuo scambio di informazioni tra realtà clinica e ricerca di base

Meccanizzazione dei vigneti allevati a doppia cortina e a cordone libero

La ricerca svolta ha voluto approfondire le possibilità offerte dai sistemi di allevamento dei vigneti a Doppia Cortina (GDC) e a Cordone Libero nei riguardi della meccanizzazione. La ricerca ha considerato gli interventi di potatura invernale, di gestione della chioma (spollonatura, cimatura, defogliazione e pettinatura della doppia cortina) e di vendemmia. Un’operazione particolarmente seguita è stata la potatura invernale realizzando differenti livelli di meccanizzazione. Tutti gli interventi sono stati eseguiti sia manualmente che meccanicamente, confrontando i tempi d’impiego, la qualità del lavoro svolto e gli impegni di manodopera. I risultati sono stati sintetizzati in una valutazione economica, ipotizzando differenti livelli di costo della manodopera impiegata, per ottenere giudizi di convenienza per i singoli interventi e per costruire una valutazione completa e più organica della linea di lavoro proposta. Nelle due forme d’allevamento la meccanizzazione della potatura invernale e della gestione della chioma hanno rispettato pienamente gli obbiettivi tecnici prefissati, dimostrando di essere un valido mezzo per ridurre tempi e costi di gestione. Per questi interventi l’acquisto delle macchine risulta conveniente anche per vigneti di piccola dimensione. Ancor più evidenti in queste due forme d’allevamento sono i vantaggi economici offerti dalla vendemmia meccanica, realizzata con pochi maltrattamenti e perdite di prodotto. La tendenza a meccanizzare integralmente gli interventi di gestione del ciclo colturale della vite, può essere nei prossimi anni un motivo di interesse e di scelta nella realizzazione di nuovi impianti con queste due forme di allevamento, che hanno dimostrato di essere un’espressione completa di sinergia tra macchina e pianta.

Mercato dell'informazione, posizionamento dei media e distorsioni: Un'analisi attraverso l'algoritmo Wordfish

Una stampa libera e plurale è un elemento fondante di ogni sistema democratico ed è fondamentale per la creazione di un’opinione pubblica informata e in grado di esercitare controllo e pressione sulle classi dirigenti. Dal momento della loro creazione i giornali si sono imposti come un’importantissima fonte di informazione per l’opinione pubblica. La seconda metà del Novecento, inoltre, ha conosciuto innovazioni tecnologiche che hanno portato grandi cambiamenti nel ruolo della carta stampata come veicolo di trasmissione delle notizie. Partendo dalla diffusione della televisione fino ad arrivare alla rivoluzione digitale degli anni ’90 e 2000, la velocità di creazione e di trasmissione delle informazioni è aumentata esponenzialmente, i costi di produzione e di acquisizione delle notizie sono crollati e una quantità enorme di dati, che possono fornire moltissime informazioni relative alle idee e ai contenuti proposti dai diversi autori nel corso del tempo, è ora a disposizione di lettori e ricercatori. Tuttavia, anche se grazie alla rivoluzione digitale i costi materiali dei periodici si sono notevolmente ridotti, la produzione di notizie comporta altre spese e pertanto si inserisce in un contesto di mercato, sottoposto alle logiche della domanda e dell'offerta. In questo lavoro verrà analizzato il ruolo della domanda e della non perfetta razionalità dei lettori nel mercato delle notizie, partendo dall’assunto che la differenza di opinioni dei consumatori spinge le testate a regolare l’offerta di contenuti, per venire incontro alla domanda di mercato, per verificare l’applicabilità del modello utilizzato (Mullainhatan e Shleifer, 2005) al contesto italiano. A tale scopo si è analizzato il comportamento di alcuni quotidiani nazionali in occasione di due eventi che hanno profondamente interessato l'opinione pubblica italiana: il fenomeno dei flussi migratori provenienti dalla sponda sud del Mediterraneo nel mese di ottobre 2013 e l'epidemia di influenza H1N1 del 2009.