Tecniche di progettazione tollerante alle variazioni per circuiti digitali in tecnologie nanometriche

The digital electronic market development is founded on the continuous reduction of the transistors size, to reduce area, power, cost and increase the computational performance of integrated circuits. This trend, known as technology scaling, is approaching the nanometer size. The lithographic process in the manufacturing stage is increasing its uncertainty with the scaling down of the transistors size, resulting in a larger parameter variation in future technology generations. Furthermore, the exponential relationship between the leakage current and the threshold voltage, is limiting the threshold and supply voltages scaling, increasing the power density and creating local thermal issues, such as hot spots, thermal runaway and thermal cycles. In addiction, the introduction of new materials and the smaller devices dimension are reducing transistors robustness, that combined with high temperature and frequently thermal cycles, are speeding up wear out processes. Those effects are no longer addressable only at the process level. Consequently the deep sub-micron devices will require solutions which will imply several design levels, as system and logic, and new approaches called Design For Manufacturability (DFM) and Design For Reliability. The purpose of the above approaches is to bring in the early design stages the awareness of the device reliability and manufacturability, in order to introduce logic and system able to cope with the yield and reliability loss. The ITRS roadmap suggests the following research steps to integrate the design for manufacturability and reliability in the standard CAD automated design flow: i) The implementation of new analysis algorithms able to predict the system thermal behavior with the impact to the power and speed performances. ii) High level wear out models able to predict the mean time to failure of the system (MTTF). iii) Statistical performance analysis able to predict the impact of the process variation, both random and systematic. The new analysis tools have to be developed beside new logic and system strategies to cope with the future challenges, as for instance: i) Thermal management strategy that increase the reliability and life time of the devices acting to some tunable parameter,such as supply voltage or body bias. ii) Error detection logic able to interact with compensation techniques as Adaptive Supply Voltage ASV, Adaptive Body Bias ABB and error recovering, in order to increase yield and reliability. iii) architectures that are fundamentally resistant to variability, including locally asynchronous designs, redundancy, and error correcting signal encodings (ECC). The literature already features works addressing the prediction of the MTTF, papers focusing on thermal management in the general purpose chip, and publications on statistical performance analysis. In my Phd research activity, I investigated the need for thermal management in future embedded low-power Network On Chip (NoC) devices.I developed a thermal analysis library, that has been integrated in a NoC cycle accurate simulator and in a FPGA based NoC simulator. The results have shown that an accurate layout distribution can avoid the onset of hot-spot in a NoC chip. Furthermore the application of thermal management can reduce temperature and number of thermal cycles, increasing the systemreliability. Therefore the thesis advocates the need to integrate a thermal analysis in the first design stages for embedded NoC design. Later on, I focused my research in the development of statistical process variation analysis tool that is able to address both random and systematic variations. The tool was used to analyze the impact of self-timed asynchronous logic stages in an embedded microprocessor. As results we confirmed the capability of self-timed logic to increase the manufacturability and reliability. Furthermore we used the tool to investigate the suitability of low-swing techniques in the NoC system communication under process variations. In this case We discovered the superior robustness to systematic process variation of low-swing links, which shows a good response to compensation technique as ASV and ABB. Hence low-swing is a good alternative to the standard CMOS communication for power, speed, reliability and manufacturability. In summary my work proves the advantage of integrating a statistical process variation analysis tool in the first stages of the design flow.

I beni relazionali nella ricerca sociologica: che cosa sono e quali effetti producono

This paper studies relational goods as immaterial assets creating real effects in society. The work starts answering to this question: what kind of effects do relational goods produce? After an accurate literature examination we suppose relational goods are social relations of second order. In the hypotesis they come from the emergence of two distinct social relations: interpersonal and reflexive relations. We describe empirical evidences of these emergent assets in social life and we test the effects they produce with a model. In the work we focus on four targets. First of all we describe the emergence of relational goods through a mathematical model. Then we individualize social realities where relational goods show evident effects and we outline our scientific hypotesis. The following step consists in the formulation of empirical tests. At last we explain final results. Our aim is to set apart the constitutive structure of relational goods into a checkable model coherently with the empirical evidences shown in the research. In the study we use multi-variate analysis techniques to see relational goods in a new way and we use qualitative and quantitative strategies. Relational goods are analysed both as dependent and independent variable in order to consider causative factors acting in a black-box model. Moreover we analyse effects of relational goods inside social spheres, especially in third sector and capitalistic economy. Finally we attain to effective indexes of relational goods in order to compare them with some performance indexes.

Geomorphological and statistical analysis on Ravenna dune fields changes, based on Terrestrial Laser Technology

Coastal sand dunes represent a richness first of all in terms of defense from the sea storms waves and the saltwater ingression; moreover these morphological elements constitute an unique ecosystem of transition between the sea and the land environment. The research about dune system is a strong part of the coastal sciences, since the last century. Nowadays this branch have assumed even more importance for two reasons: on one side the born of brand new technologies, especially related to the Remote Sensing, have increased the researcher possibilities; on the other side the intense urbanization of these days have strongly limited the dune possibilities of development and fragmented what was remaining from the last century. This is particularly true in the Ravenna area, where the industrialization united to the touristic economy and an intense subsidence, have left only few dune ridges residual still active. In this work three different foredune ridges, along the Ravenna coast, have been studied with Laser Scanner technology. This research didn’t limit to analyze volume or spatial difference, but try also to find new ways and new features to monitor this environment. Moreover the author planned a series of test to validate data from Terrestrial Laser Scanner (TLS), with the additional aim of finalize a methodology to test 3D survey accuracy. Data acquired by TLS were then applied on one hand to test some brand new applications, such as Digital Shore Line Analysis System (DSAS) and Computational Fluid Dynamics (CFD), to prove their efficacy in this field; on the other hand the author used TLS data to find any correlation with meteorological indexes (Forcing Factors), linked to sea and wind (Fryberger's method) applying statistical tools, such as the Principal Component Analysis (PCA).

Dal Bes ad Urbes: I piani di performance e di trasparenza nelle citta'

Obiettivo del lavoro è quello di legare tra di loro due aspetti che storicamente sono sempre stati scollegati. Il primo è il lungo dibattito sul tema “oltre il PIL”, che prosegue ininterrottamente da circa mezzo secolo. Il secondo riguarda l’utilizzo dei sistemi di misurazione e valutazione della performance nel settore pubblico italiano. Si illustra l’evoluzione del dibattito sul PIL facendo un excursus storico del pensiero critico che si è sviluppato nel corso di circa cinquanta anni analizzando le ragioni assunte dagli studiosi per confutare l’utilizzo del PIL quale misura universale del benessere. Cogliendo questa suggestione l’Istat, in collaborazione con il CNEL, ha avviato un progetto per individuare nuovi indicatori da affiancare al PIL, in grado di misurare il livello non solo della crescita economica, ma anche del benessere sociale e sostenibile, con l’analisi degli indicatori riferiti a 12 domini di benessere individuati. Al progetto Istat-CNEL si è affiancato il progetto UrBES, promosso dall’Istat e dal Coordinamento dei sindaci metropolitani dell’ANCI, che hanno costituito una rete di città metropolitane per sperimentare la misurazione e il confronto sulla base di indicatori di benessere urbano equo e sostenibile, facendo proprio un progetto del Comune di Bologna e di Laboratorio Urbano (Centro di documentazione, ricerca e proposta sulle città), che ha sottoposto a differenti target un questionario on line, i cui risultati, con riferimento alle risposte fornite alle domande aperte, sono stati elaborati attraverso l’utilizzo di Taltac, un software per l’analisi dei testi, al fine di individuare i “profili” dei rispondenti, associando i risultati dell’elaborazione alle variabili strutturali del questionario. Nell’ultima parte i servizi e progetti erogati dal comune di Bologna sono stati associati alle dimensioni UrBES, per valutare l’impatto delle politiche pubbliche sulla qualità della vita e sul benessere dei cittadini, indicando le criticità legate alla mancanza di dati adeguati.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.