Modelli Digitali e Archivi di Progetto. Sistemi integrati di documentazione per l'architettura.

Le tecniche dell'informazione e i metodi della comunicazione hanno modificato il modo di redigere documenti destinati a trasmettere la conoscenza, in un processo che è a tutt'oggi in corso di evoluzione. Anche l'attività progettuale in ingegneria ed architettura, pure in un settore caratterizzato da una notevole inerzia metodologica e restio all'innovazione quale è quello dell'industria edilizia, ha conosciuto profonde trasformazioni in ragione delle nuove espressioni tecnologiche. Da tempo l'informazione necessaria per realizzare un edificio, dai disegni che lo rappresentano sino ai documenti che ne indicano le modalità costruttive, può essere gestita in maniera centralizzata mediante un unico archivio di progetto denominato IPDB (Integrated Project DataBase) pur essendone stata recentemente introdotta sul mercato una variante più operativa chiamata BIM (Building Information Modelling). Tuttavia l'industrializzazione del progetto che questi strumenti esplicano non rende conto appieno di tutti gli aspetti che vedono la realizzazione dell'opera architettonica come collettore di conoscenze proprie di una cultura progettuale che, particolarmente in Italia, è radicata nel tempo. La semantica della rappresentazione digitale è volta alla perequazione degli elementi costitutivi del progetto con l'obiettivo di catalogarne le sole caratteristiche fabbricative. L'analisi della letteratura scientifica pertinente alla materia mostra come non sia possibile attribuire ai metodi ed ai software presenti sul mercato la valenza di raccoglitori omnicomprensivi di informazione: questo approccio olistico costituisce invece il fondamento della modellazione integrata intesa come originale processo di rappresentazione della conoscenza, ordinata secondo il paradigma delle "scatole cinesi", modello evolvente che unifica linguaggi appartenenti ai differenti attori compartecipanti nei settori impiantistici, strutturali e della visualizzazione avanzata. Evidenziando criticamente i pregi e i limiti operativi derivanti dalla modellazione integrata, la componente sperimentale della ricerca è stata articolata con l'approfondimento di esperienze condotte in contesti accademici e professionali. Il risultato conseguito ha coniugato le tecniche di rilevamento alle potenzialità di "modelli tridimensionali intelligenti", dotati cioè di criteri discriminanti per la valutazione del relazionamento topologico dei componenti con l'insieme globale.

Adaptive Neural Translation for Enterprises (ANTE). La traduzione automatica neurale a sostegno delle imprese emiliano-romagnole

Il progetto ANTE riguarda i nuovi sistemi di traduzione automatica (TA) e la loro applicazione nel mondo delle imprese. Lo studio prende spunto dai recenti sviluppi legati all’intelligenza artificiale e ai Big Data che negli ultimi anni hanno permesso alla TA di raggiungere livelli qualitativi molto elevati, al punto tale da essere impiegata da grandi multinazionali per raggiungere nuove quote di mercato. La TA può rispondere positivamente anche ai bisogni delle imprese di piccole dimensioni e a basso tenore tecnologico, migliorando la qualità delle comunicazioni multilingue attraverso delle traduzioni in tempi brevi e a costi contenuti. Lo studio si propone quindi di contribuire al rafforzamento della competitività internazionale delle piccole e medie imprese (PMI) emiliano- romagnole, migliorando la loro capacità di comunicazione in una o più lingue straniere attraverso l’introduzione e l’utilizzo efficace e consapevole di soluzioni ICT di ultima generazione e fornire, così, nuove opportunità di internazionalizzazione.

Sviluppo di un sistema miniaturizzato per il controllo real-time di assetto di nano e microsatelliti

Microsatelliti e nanosatelliti, come ad esempio i Cubesat, sono carenti di sistemi integrati di controllo d’assetto e di manovra orbitale. Lo scopo di questa tesi è stato quello di realizzare un sistema compatibile con Cubesat di una unità, completo di attuatori magnetici e attuatori meccanici, comprendente tutti i sensori e l’elettronica necessaria per il suo funzionamento, creando un dispositivo totalmente indipendente dal veicolo su cui è installato, capace di funzionare sia autonomamente che ricevendo comandi da terra. Nella tesi sono descritte le campagne di simulazioni numeriche effettuate per validare le scelte tecnologiche effettuate, le fasi di sviluppo dell’elettronica e della meccanica, i test sui prototipi realizzati e il funzionamento del sistema finale. Una integrazione così estrema dei componenti può implicare delle interferenze tra un dispositivo e l’altro, come nel caso dei magnetotorquer e dei magnetometri. Sono stati quindi studiati e valutati gli effetti della loro interazione, verificandone l’entità e la validità del progetto. Poiché i componenti utilizzati sono tutti di basso costo e di derivazione terrestre, è stata effettuata una breve introduzione teorica agli effetti dell’ambiente spaziale sull’elettronica, per poi descrivere un sistema fault-tolerant basato su nuove teorie costruttive. Questo sistema è stato realizzato e testato, verificando così la possibilità di realizzare un controller affidabile e resistente all’ambiente spaziale per il sistema di controllo d’assetto. Sono state infine analizzate alcune possibili versioni avanzate del sistema, delineandone i principali aspetti progettuali, come ad esempio l’integrazione di GPS e l’implementazione di funzioni di determinazione d’assetto sfruttando i sensori presenti a bordo.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Ingegneria di sistemi auto‐organizzanti con il paradigma multiagente

Self-organisation is increasingly being regarded as an effective approach to tackle modern systems complexity. The self-organisation approach allows the development of systems exhibiting complex dynamics and adapting to environmental perturbations without requiring a complete knowledge of the future surrounding conditions. However, the development of self-organising systems (SOS) is driven by different principles with respect to traditional software engineering. For instance, engineers typically design systems combining smaller elements where the composition rules depend on the reference paradigm, but typically produce predictable results. Conversely, SOS display non-linear dynamics, which can hardly be captured by deterministic models, and, although robust with respect to external perturbations, are quite sensitive to changes on inner working parameters. In this thesis, we describe methodological aspects concerning the early-design stage of SOS built relying on the Multiagent paradigm: in particular, we refer to the A&A metamodel, where MAS are composed by agents and artefacts, i.e. environmental resources. Then, we describe an architectural pattern that has been extracted from a recurrent solution in designing self-organising systems: this pattern is based on a MAS environment formed by artefacts, modelling non-proactive resources, and environmental agents acting on artefacts so as to enable self-organising mechanisms. In this context, we propose a scientific approach for the early design stage of the engineering of self-organising systems: the process is an iterative one and each cycle is articulated in four stages, modelling, simulation, formal verification, and tuning. During the modelling phase we mainly rely on the existence of a self-organising strategy observed in Nature and, hopefully encoded as a design pattern. Simulations of an abstract system model are used to drive design choices until the required quality properties are obtained, thus providing guarantees that the subsequent design steps would lead to a correct implementation. However, system analysis exclusively based on simulation results does not provide sound guarantees for the engineering of complex systems: to this purpose, we envision the application of formal verification techniques, specifically model checking, in order to exactly characterise the system behaviours. During the tuning stage parameters are tweaked in order to meet the target global dynamics and feasibility constraints. In order to evaluate the methodology, we analysed several systems: in this thesis, we only describe three of them, i.e. the most representative ones for each of the three years of PhD course. We analyse each case study using the presented method, and describe the exploited formal tools and techniques.

Studio e sviluppo di sistemi RFID in banda UHF

The recent widespread diffusion of radio-frequency identification (RFID) applications operating in the UHF band has been supported by both the request for greater interrogation ranges and greater and faster data exchange. UHF-RFID systems, exploiting a physical interaction based on Electromagnetic propagation, introduce many problems that have not been fully explored for the previous generations of RFID systems (e.g. HF). Therefore, the availability of reliable tools for modeling and evaluating the radio-communication between Reader and Tag within an RFID radio-link are needed. The first part of the thesis discuss the impact of real environment on system performance. In particular an analytical closed form formulation for the back-scattered field from the Tag antenna and the formulation for the lower bound of the BER achievable at the Reader side will be presented, considering different possible electromagnetic impairments. By means of the previous formulations, of the analysis of the RFID link operating in near filed conditions and of some electromagnetic/system-level co-simulations, an in-depth study of the dimensioning parameters and the actual performance of the systems will be discussed and analyzed, showing some relevant properties and trade-offs in transponder and reader design. Moreover a new low cost approach to extend the read range of the RFID UHF passive systems will be discussed. Within the scope to check the reliability of the analysis approaches and of innovative proposals, some reference transponder antennas have been designed and extensive measurement campaign has been carried out with satisfactory results. Finally, some commercial ad-hoc transponder for industrial application have been designed within the cooperation with Datalogic s.p.a., some guidelines and results will be briefly presented.

Costrutti ed Applicazioni di Programmazione Generica in Linguaggi Object-Oriented

Generic programming is likely to become a new challenge for a critical mass of developers. Therefore, it is crucial to refine the support for generic programming in mainstream Object-Oriented languages — both at the design and at the implementation level — as well as to suggest novel ways to exploit the additional degree of expressiveness made available by genericity. This study is meant to provide a contribution towards bringing Java genericity to a more mature stage with respect to mainstream programming practice, by increasing the effectiveness of its implementation, and by revealing its full expressive power in real world scenario. With respect to the current research setting, the main contribution of the thesis is twofold. First, we propose a revised implementation for Java generics that greatly increases the expressiveness of the Java platform by adding reification support for generic types. Secondly, we show how Java genericity can be leveraged in a real world case-study in the context of the multi-paradigm language integration. Several approaches have been proposed in order to overcome the lack of reification of generic types in the Java programming language. Existing approaches tackle the problem of reification of generic types by defining new translation techniques which would allow for a runtime representation of generics and wildcards. Unfortunately most approaches suffer from several problems: heterogeneous translations are known to be problematic when considering reification of generic methods and wildcards. On the other hand, more sophisticated techniques requiring changes in the Java runtime, supports reified generics through a true language extension (where clauses) so that backward compatibility is compromised. In this thesis we develop a sophisticated type-passing technique for addressing the problem of reification of generic types in the Java programming language; this approach — first pioneered by the so called EGO translator — is here turned into a full-blown solution which reifies generic types inside the Java Virtual Machine (JVM) itself, thus overcoming both performance penalties and compatibility issues of the original EGO translator. Java-Prolog integration Integrating Object-Oriented and declarative programming has been the subject of several researches and corresponding technologies. Such proposals come in two flavours, either attempting at joining the two paradigms, or simply providing an interface library for accessing Prolog declarative features from a mainstream Object-Oriented languages such as Java. Both solutions have however drawbacks: in the case of hybrid languages featuring both Object-Oriented and logic traits, such resulting language is typically too complex, thus making mainstream application development an harder task; in the case of library-based integration approaches there is no true language integration, and some “boilerplate code” has to be implemented to fix the paradigm mismatch. In this thesis we develop a framework called PatJ which promotes seamless exploitation of Prolog programming in Java. A sophisticated usage of generics/wildcards allows to define a precise mapping between Object-Oriented and declarative features. PatJ defines a hierarchy of classes where the bidirectional semantics of Prolog terms is modelled directly at the level of the Java generic type-system.

Architetture di interconnessione per sistemi su singolo chip e per sistemi ad integrazione tridimensionale

I continui sviluppi nel campo della fabbricazione dei circuiti integrati hanno comportato frequenti travolgimenti nel design, nell’implementazione e nella scalabilità dei device elettronici, così come nel modo di utilizzarli. Anche se la legge di Moore ha anticipato e caratterizzato questo trend nelle ultime decadi, essa stessa si trova a fronteggiare attualmente enormi limitazioni, superabili solo attraverso un diverso approccio nella produzione di chip, consistente in pratica nella sovrapposizione verticale di diversi strati collegati elettricamente attraverso speciali vias. Sul singolo strato, le network on chip sono state suggerite per ovviare le profonde limitazioni dovute allo scaling di strutture di comunicazione condivise. Questa tesi si colloca principalmente nel contesto delle nascenti piattaforme multicore ad alte prestazioni basate sulle 3D NoC, in cui la network on chip viene estesa nelle 3 direzioni. L’obiettivo di questo lavoro è quello di fornire una serie di strumenti e tecniche per poter costruire e aratterizzare una piattaforma tridimensionale, cosi come dimostrato nella realizzazione del testchip 3D NOC fabbricato presso la fonderia IMEC. Il primo contributo è costituito sia una accurata caratterizzazione delle interconnessioni verticali (TSVs) (ovvero delle speciali vias che attraversano l’intero substrato del die), sia dalla caratterizzazione dei router 3D (in cui una o più porte sono estese nella direzione verticale) ed infine dal setup di un design flow 3D utilizzando interamente CAD 2D. Questo primo step ci ha permesso di effettuare delle analisi dettagliate sia sul costo sia sulle varie implicazioni. Il secondo contributo è costituito dallo sviluppo di alcuni blocchi funzionali necessari per garantire il corretto funziomento della 3D NoC, in presenza sia di guasti nelle TSVs (fault tolerant links) che di deriva termica nei vari clock tree dei vari die (alberi di clock indipendenti). Questo secondo contributo è costituito dallo sviluppo delle seguenti soluzioni circuitali: 3D fault tolerant link, Look Up Table riconfigurabili e un sicnronizzatore mesocrono. Il primo è costituito fondamentalmente un bus verticale equipaggiato con delle TSV di riserva da utilizzare per rimpiazzare le vias guaste, più la logica di controllo per effettuare il test e la riconfigurazione. Il secondo è rappresentato da una Look Up Table riconfigurabile, ad alte prestazioni e dal costo contenuto, necesaria per bilanciare sia il traffico nella NoC che per bypassare link non riparabili. Infine la terza soluzione circuitale è rappresentata da un sincronizzatore mesocrono necessario per garantire la sincronizzazione nel trasferimento dati da un layer and un altro nelle 3D Noc. Il terzo contributo di questa tesi è dato dalla realizzazione di un interfaccia multicore per memorie 3D (stacked 3D DRAM) ad alte prestazioni, e dall’esplorazione architetturale dei benefici e del costo di questo nuovo sistema in cui il la memoria principale non è piu il collo di bottiglia dell’intero sistema. Il quarto ed ultimo contributo è rappresentato dalla realizzazione di un 3D NoC test chip presso la fonderia IMEC, e di un circuito full custom per la caratterizzazione della variability dei parametri RC delle interconnessioni verticali.

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.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Sistemi tecnologici innovativi di involucro per il recupero del patrimonio edilizio recente. L'edilizia scolastica nel Comune di Bologna

La ricerca è volta a presentare un nuovo approccio integrato, a supporto di operatori e progettisti, per la gestione dell’intero processo progettuale di interventi di riqualificazione energetica e architettonica del patrimonio edilizio recente, mediante l’impiego di soluzioni tecnologiche innovative di involucro edilizio. Lo studio richiede necessariamente l’acquisizione di un repertorio selezionato di sistemi costruttivi di involucro, come base di partenza per l’elaborazione di soluzioni progettuali di recupero delle scuole appartenenti al secondo dopoguerra, in conglomerato cementizio armato, prevalentemente prefabbricate. Il progetto individua procedimenti costruttivi ecocompatibili per la progettazione di componenti prefabbricati di involucro “attivo”, adattabile ed efficiente, da assemblare a secco, nel rispetto dei requisiti prestazionali richiesti dalle attuali normative. La ricerca è finalizzata alla gestione dell’intero processo, supportato da sistemi di rilevazione geometrica, collegati a software di programmazione parametrica per la modellazione di superfici adattabili alla morfologia dei fabbricati oggetto di intervento. Tali strumenti informatizzati CAD-CAM sono connessi a macchine a controllo numerico CNC per la produzione industrializzata degli elementi costruttivi “su misura”. A titolo esemplificativo dell’approccio innovativo proposto, si formulano due possibili soluzioni di involucro in linea con i paradigmi della ricerca, nel rispetto dei principi di sostenibilità, intesa come modularità, rapidità di posa, reversibilità, recupero e riciclo di materiali. In particolare, le soluzioni innovative sono accomunate dall’applicazione di una tecnica basata sull’assemblaggio di elementi prefabbricati, dall’adozione di una trama esagonale per la tassellazione della nuova superficie di facciata, e dall’utilizzo del medesimo materiale termico isolante, plastico e inorganico, riciclato ed ecosostenibile, a basso impatto ambientale (AAM - Alkali Activated Materials). Le soluzioni progettuali proposte, sviluppate presso le due sedi coinvolte nella cotutela (Università di Bologna, Université Paris-Est) sono affrontate secondo un protocollo scientifico che prevede: progettazione del sistema costruttivo, analisi meccanica e termica, sperimentazione costruttiva, verifica delle tecniche di messa in opera e dei requisiti prestazionali.

Sviluppo di mezzi e sistemi di sorveglianza e monitoraggio dei ditteri culicidi di importanza sanitaria

Nel corso degli ultimi anni le problematiche legate al ruolo vettore delle zanzare stanno emergendo sia per quanto riguarda l’uomo che gli animali allevati e selvatici. Diversi arbovirus come West Nile, Chikungunya, Usutu e Dengue, possono facilmente spostarsi a livello planetario ed essere introdotti anche nei nostri territori dove possono dare avvio a episodi epidemici. Le tecniche di monitoraggio e sorveglianza dei Culicidi possono essere convenientemente utilizzate per il rilevamento precoce dell’attività virale sul territorio e per la stima del rischio di epidemie al fine dell’adozione delle opportune azioni di Sanità Pubblica. Io scopo della ricerca del dottorato è inserito nel contesto dei temi di sviluppo del Piano regionale sorveglianza delle malattie trasmesse da vettori in Emilia Romagna. La ricerca condotta è inquadrata prevalentemente sotto l’aspetto entomologico applicativo di utilizzo di dispositivi (trappole) che possano catturare efficacemente possibili insetti vettori. In particolare questa ricerca è stata mirata allo studio comparativo in campo di diversi tipi di trappole per la cattura di adulti di zanzara, cercando di interpretare i dati per capire un potenziale valore di efficacia/efficienza nel rilevamento della circolazione virale e come supporto alla pianificazione della rete di sorveglianza dal punto di vista operativo mediante dispositivi adeguati alle finalità d’indagine. Si è cercato di trovare un dispositivo idoneo, approfondendone gli aspetti operativi/funzionali, ai fini di cattura del vettore principale del West Nile Virus, cioè la zanzara comune, da affiancare all’unica tipologia di trappola usata in precedenza. Le prove saranno svolte sia in campo che presso il laboratorio di Entomologia Medica Veterinaria del Centro Agricoltura Ambiente “G. Nicoli” di Crevalcore, in collaborazione con il Dipartimento di Scienze e Tecnologie Agroambientali della Facoltà di Agraria dell’Università di Bologna.