Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

Surface plasmon fluorescence spectroscopy and microscopy studies for biomolecular interaction studies

ABSTARCT Biotechnology has enabled the modification of agricultural materials in a very precise way. Crops have been modified through the insertion of new traits or the inhibition of existing gene functions, named Genetically Modified Organism (GMO), and resulted in improved tolerance of herbicide and/or increased resistance against pests, viruses and fungi. Commercial cultivation of GMO started in 1996 and increased rapidly in 2003 according to a recently released report by the International Service for the Acquisition of Agri-Biotech Applications (ISAAA), depicted continuing consumer resistance in Europe and other part of the world. Upon these developments, the European Union regulations mandated labeling of GMOs containing food and as a consequence, the labeling of GMO containing product in the case of exceeding the1% threshold of alien DNA is required. The aim of the study is to be able to detect and quantify the GMO from the mixture of natural food components. The surface plasmon resonance (SPR) technique combined with fluorescence was used for this purpose. During the presented studies, two key issues are addressed and tried to solve; what is the best strategy to design and built an interfacial architecture of a probe oligonucletide layer either on a two dimensional surface or on an array platform; and what is the best detection method allowing for a sensitive monitoring of the hybridisation events. The study includes two parts: first part includes characterization of different PNAs on a 2D planar surface by defining affinity constants using the very well established optical method “Surface Plasmon Fluorescence Spectroscopy”(SPFS) and on the array platform by “Surface Plasmon Fluorescence Microscopy” (SPFM), and at the end comparison of the sensitivity of these two techniques. The second part is composed of detection of alien DNA in food components by using DNA and PNA catcher probes on the array platform in real-time by SPFM.

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.

Cache-aware development of high integrity real-time systems

Cost, performance and availability considerations are forcing even the most conservative high-integrity embedded real-time systems industry to migrate from simple hardware processors to ones equipped with caches and other acceleration features. This migration disrupts the practices and solutions that industry had developed and consolidated over the years to perform timing analysis. Industry that are confident with the efficiency/effectiveness of their verification and validation processes for old-generation processors, do not have sufficient insight on the effects of the migration to cache-equipped processors. Caches are perceived as an additional source of complexity, which has potential for shattering the guarantees of cost- and schedule-constrained qualification of their systems. The current industrial approach to timing analysis is ill-equipped to cope with the variability incurred by caches. Conversely, the application of advanced WCET analysis techniques on real-world industrial software, developed without analysability in mind, is hardly feasible. We propose a development approach aimed at minimising the cache jitters, as well as at enabling the application of advanced WCET analysis techniques to industrial systems. Our approach builds on:(i) identification of those software constructs that may impede or complicate timing analysis in industrial-scale systems; (ii) elaboration of practical means, under the model-driven engineering (MDE) paradigm, to enforce the automated generation of software that is analyzable by construction; (iii) implementation of a layout optimisation method to remove cache jitters stemming from the software layout in memory, with the intent of facilitating incremental software development, which is of high strategic interest to industry. The integration of those constituents in a structured approach to timing analysis achieves two interesting properties: the resulting software is analysable from the earliest releases onwards - as opposed to becoming so only when the system is final - and more easily amenable to advanced timing analysis by construction, regardless of the system scale and complexity.

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.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

Early Warning For Large Earthquakes: Observations, Models and Real-Time Data Analysis

This thesis is a collection of works focused on the topic of Earthquake Early Warning, with a special attention to large magnitude events. The topic is addressed from different points of view and the structure of the thesis reflects the variety of the aspects which have been analyzed. The first part is dedicated to the giant, 2011 Tohoku-Oki earthquake. The main features of the rupture process are first discussed. The earthquake is then used as a case study to test the feasibility Early Warning methodologies for very large events. Limitations of the standard approaches for large events arise in this chapter. The difficulties are related to the real-time magnitude estimate from the first few seconds of recorded signal. An evolutionary strategy for the real-time magnitude estimate is proposed and applied to the single Tohoku-Oki earthquake. In the second part of the thesis a larger number of earthquakes is analyzed, including small, moderate and large events. Starting from the measurement of two Early Warning parameters, the behavior of small and large earthquakes in the initial portion of recorded signals is investigated. The aim is to understand whether small and large earthquakes can be distinguished from the initial stage of their rupture process. A physical model and a plausible interpretation to justify the observations are proposed. The third part of the thesis is focused on practical, real-time approaches for the rapid identification of the potentially damaged zone during a seismic event. Two different approaches for the rapid prediction of the damage area are proposed and tested. The first one is a threshold-based method which uses traditional seismic data. Then an innovative approach using continuous, GPS data is explored. Both strategies improve the prediction of large scale effects of strong earthquakes.

Intelligenza artificiale per giochi strategici real-time

L'elaborato affronta la progettazione di un'intelligenza artificiale per giochi strategici real-time in cui viene descritta la suddivisione dei livelli di astrazione e vengono prese in considerazione due architetture specifiche, SORTS ed EISBot, facendo particolare attenzione sulle problematiche riscontrate nell'ambiente di gioco.

Progettazione, implementazione e valutazione di un simulatore basato su web real time communication (WebRTC).

Questa tesi tratta della realizzazione e valutazione di un simulatore Web-Based i cui nodi sono connessi tramite Web Real Time Communication (WebRTC) e si testa la sua efficienza mediante la simulazione di un semplice modello di mobilità. Si espongono i principali concetti di simulazione e di WebRTC, fornendo le basi per una maggior comprensione del testo e delle scelte progettuali ed implementative. Si conclude con serie di test comparativi dell’applicativo mettendo in luce pregi e difetti di questo approccio alternativo alla simulazione.

Function Point e Real Time Software: caso di studio reale

La tesi si pone come obiettivo quello di analizzare dal punto di vista funzionale il software embedded real - time installato su di una applicazione industriale, utilizzando la prima release per calibrare il sistema in modo da poter stimare il numero di linee di codice necessarie per lo sviluppo delle versioni successive. Durante questo studio sono stati applicati i metodi indicati dall'ingegneria del software per contare le linee di codice sorgente dell'applicativo e stimarne i function point, analizzando ed individuando le problematiche relative all'utilizzo di tali strumenti su software di tipo real - time.

Data integration, real-time synchronization and RESTful Web Service

Analisi e sviluppo di procedure di importazione dati per un integratore di annunci immobiliari dedicato alla vendita di soggiorni turistici in case vacanza. Il documento tratta inoltre l'implementazione di un Web Service conforme all'architettura RESTful per l'accesso e l'esportazione dei dati a soggetti terzi autorizzati tramite Digest Authentication.

Analisi e applicazione dei processi di data mining al flusso informativo di sistemi real-time: Implementazione e analisi di un algoritmo autoadattivo per la ricerca di frequent patterns su macchine automatiche.

Analisi e applicazione dei processi di data mining al flusso informativo di sistemi real-time. Implementazione e analisi di un algoritmo autoadattivo per la ricerca di frequent patterns su macchine automatiche.