The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

Novel techniques for the remote sensing of photosynthetic processes

Remote sensing (RS) techniques have evolved into an important instrument to investigate forest function. New methods based on the remote detection of leaf biochemistry and photosynthesis are being developed and applied in pilot studies from airborne and satellite platforms (PRI, solar-induced fluorescence; N and chlorophyll content). Non-destructive monitoring methods, a direct application of RS studies, are also proving increasingly attractive for the determination of stress conditions or nutrient deficiencies not only in research but also in agronomy, horticulture and urban forestry (proximal RS). In this work I will focus on some novel techniques recently developed for the estimation of photochemistry and photosynthetic rates based (i) on the proximal measurement of steady-state chlorophyll fluorescence yield, or (ii) the remote sensing of changes in hyperspectral leaf reflectance, associated to xanthophyll de-epoxydation and energy partitioning, which is closely coupled to leaf photochemistry and photosynthesis. I will also present and describe a mathematical model of leaf steady-state fluorescence and photosynthesis recently developed in our group. Two different species were used in the experiments: Arbutus unedo, a schlerophyllous Mediterranean species, and Populus euroamericana, a broad leaf deciduous tree widely used in plantation forestry. Results show that ambient fluorescence could provide a useful tool for testing photosynthetic processes from a distance. These results confirm also the photosynthetic reflectance index (PRI) as an efficient remote sensing reflectance index estimating short-term changes in photochemical efficiency as well as long-term changes in leaf biochemistry. The study also demonstrated that RS techniques could provide a fast and reliable method to estimate photosynthetic pigment content and total nitrogen, beside assessing the state of photochemical process in our plants’ leaves in the field. This could have important practical applications for the management of plant cultivation systems, for the estimation of the nutrient requirements of our plants for optimal growth.

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Aminoxyl radicals - pure organic materials with tunable magnetic and sensing properties

Stabile Radikale haben in vielen Bereichen der Chemie, Physik, Biologie und Biomedizin ihren Nutzen unter Beweis gestellt. Gerade im letzten Jahrzehnt erlebte diese Substanzklasse vor allem wegen den Anwendungsmöglichkeiten von Nitroxiden als Red-Ox-Sensoren oder magnetischen Materialen ein erneutes Interesse. Das erste Kapitel beschäftigt sich mit der grundlegenden Theorie zur Entwicklung magnetischer Materialien. Des Weiteren sollen anhand einiger Beispiele Radikale im Komplex mit paragmagnetischen Metallen, Biradikale und Polyradikale beschrieben werden. rnrnIm zweiten Kapitel soll auf die Synthese von Hybrid Fluorophore-Nitrononyl-Nitroxid und Iminonitroxidradiale, sowie ihre Charakterisierung über IR, CV, EPR und Röntgenstrukturanalyse eingegangen werden. Mittels UV/Vis-Spektroskopie soll hierbei eine mögliche Anwendung als Red-Ox-Sensoren festgestellt werden. Hierbei werden über anschließende PL Untersuchungen eben diese Sensoreigenschaften der dargestellten Radikale bestätigt werden. Vielmehr noch soll die Möglichkeit von Pyren-Pyrazol-Nitronyl-Nitroxid als NO-Nachweis erläutert werden.rnrnFortschritte sowohl im Design als auch in der Analyse von magnetischen Materialen auf der Basis von Nitroxiden ist Thema des dritten Kapitels. Über ein klassisches Ullmann-Protokoll wurden verschiedene Nitronyl-Nitroxid und Iminonitroxid Biradiale mit unterschiedlichen π-Brücken zwischen den Radikalzentren synthetisiert. Magnetische Messungen belegen einen relativ starken antiferromagnetischen intramolekularen Austausch für den Großteil der untersuchten Biradikale. Hierbei zeigte sich jedoch eine außergewöhnliche hohe Austausch-Kupplung für 3,3‘-Diazatolandiradikale, die nur über die Existenz von starken intermolekularen Wechselwirkungen beschrieben werden kann. Durch Kombination der Röntgenstrukturanalyse mit DFT Berechnungen konnte im Fall des Tolan verbrückten Diradikals 87c die Intra-Dimer-Kupplung auf Jintra = -8,6 K bestimmt werden. Ein direkter Beweis für eine intermolekulare Anlagerung von Jinter ~- 2K konnte über eine Tieftemperatur AC-Messung von 87c erhalten werden. Bezüglich der magnetischen Messung ist das Nitronyl Biradikal 87c ein vielversprechender Kandidat für einen rein organischen eindimensionalen Quantenmagnet.rnrnAbsicht dieser Untersuchungen ist es zu zeigen, dass über die Kombination verschiedener struktureller Elemente die Sensitivität von Nitroxid basierten Sensoren und die intramolekulare Austauschwechselwirkung in π-konjugierten Spinsystemen so eingestellt werden kann, dass es möglich ist Moleküle mit gezielten Sensor- oder Magneteigenschaften zu entwickeln. rn

Multiple pathogen detection using nanoplasmonic sensing

Opportunistic diseases caused by Human Immunodeficiency Virus (HIV) and Hepatitis B Virus (HBV) is an omnipresent global challenge. In order to manage these epidemics, we need to have low cost and easily deployable platforms at the point-of-care in high congestions regions like airports and public transit systems. In this dissertation we present our findings in using Localized Surface Plasmon Resonance (LSPR)-based detection of pathogens and other clinically relevant applications using microfluidic platforms at the point-of-care setting in resource constrained environment. The work presented here adopts the novel technique of LSPR to multiplex a lab-on-a-chip device capable of quantitatively detecting various types of intact viruses and its various subtypes, based on the principle of a change in wavelength occurring when metal nano-particle surface is modified with a specific surface chemistry allowing the binding of a desired pathogen to a specific antibody. We demonstrate the ability to detect and quantify subtype A, B, C, D, E, G and panel HIV with a specificity of down to 100 copies/mL using both whole blood sample and HIV-patient blood sample discarded from clinics. These results were compared against the gold standard Reverse Transcriptase Polymerase Chain Reaction (RT-qPCR). This microfluidic device has a total evaluation time for the assays of about 70 minutes, where 60 minutes is needed for the capture and 10 minutes for data acquisition and processing. This LOC platform eliminates the need for any sample preparation before processing. This platform is highly multiplexable as the same surface chemistry can be adapted to capture and detect several other pathogens like dengue virus, E. coli, M. Tuberculosis, etc.

The use of satellite remote sensing for flood risk management

Over the last decades the impact of natural disasters to the global environment is becoming more and more severe. The number of disasters has dramatically increased, as well as the cost to the global economy and the number of people affected. Among the natural disaster, flood catastrophes are considered to be the most costly, devastating, broad extent and frequent, because of the tremendous fatalities, injuries, property damage, economic and social disruption they cause to the humankind. In the last thirty years, the World has suffered from severe flooding and the huge impact of floods has caused hundreds of thousands of deaths, destruction of infrastructures, disruption of economic activity and the loss of property for worth billions of dollars. In this context, satellite remote sensing, along with Geographic Information Systems (GIS), has become a key tool in flood risk management analysis. Remote sensing for supporting various aspects of flood risk management was investigated in the present thesis. In particular, the research focused on the use of satellite images for flood mapping and monitoring, damage assessment and risk assessment. The contribution of satellite remote sensing for the delineation of flood prone zones, the identification of damaged areas and the development of hazard maps was explored referring to selected cases of study.

Teoria del consenso e applicazione al problema del coordinamento del moto di robot.

Il sempre crescente numero di applicazioni di reti di sensori, robot cooperanti e formazioni di veicoli, ha fatto sì che le problematiche legate al coordinamento di sistemi multi-agente (MAS) diventassero tra le più studiate nell’ambito della teoria dei controlli. Esistono numerosi approcci per affrontare il problema, spesso profondamente diversi tra loro. La strategia studiata in questa tesi è basata sulla Teoria del Consenso, che ha una natura distribuita e completamente leader-less; inoltre il contenuto informativo scambiato tra gli agenti è ridotto al minimo. I primi 3 capitoli introducono ed analizzano le leggi di interazione (Protocolli di Consenso) che permettono di coordinare un Network di sistemi dinamici. Nel capitolo 4 si pensa all'applicazione della teoria al problema del "loitering" circolare di più robot volanti attorno ad un obiettivo in movimento. Si sviluppa a tale scopo una simulazione in ambiente Matlab/Simulink, che genera le traiettorie di riferimento di raggio e centro impostabili, a partire da qualunque posizione iniziale degli agenti. Tale simulazione è stata utilizzata presso il “Center for Research on Complex Automated Systems” (CASY-DEI Università di Bologna) per implementare il loitering di una rete di quadrirotori "CrazyFlie". I risultati ed il setup di laboratorio sono riportati nel capitolo 5. Sviluppi futuri si concentreranno su algoritmi locali che permettano agli agenti di evitare collisioni durante i transitori: il controllo di collision-avoidance dovrà essere completamente indipendente da quello di consenso, per non snaturare il protocollo di Consenso stesso.

5g mobile communications systems

Un sistema mobile di comunicazione è un sistema di telecomunicazioni in cui è possibile mantenere la connessione o legame tra due o più utenti, anche nelle situazioni di mobilità totale o parziale degli stessi utenti. I sistemi radiomobili si stanno evolvendo dalla creazione del 1G (prima generazione) al 4G (quarta generazione). I telefoni di ogni generazione si differenziano in quattro aspetti principali : accesso radio, velocità di trasmissione dati, larghezza di banda e sistemi di commutazione. In questa tesi si affronta il tema dei sistemi 5G , negli ambienti terrestri e satellitari , in quanto sono l'ultima evoluzione dei sistemi mobili . Si introduce il passaggio dalla prima alla connessione di quarta generazione , al fine di capire perché 5G sta per cambiare la nostra vita . Quello che mi colpisce è il sito italiano www.Repubblica.it che dice : " con la nuova generazione 5 possiamo affidare le intere porzioni nette di vita". La tecnologia cellulare , infatti , ha cambiato radicalmente la nostra società e il nostro modo di comunicare . In primo luogo è cambiata la telefonia vocale , per poi trasferirsi all' accesso dati , applicazioni e servizi. Tuttavia , Internet non è stato ancora pienamente sfruttato dai sistemi cellulari. Con l'avvento del 5G avremo l'opportunità di scavalcare le capacità attuali di Internet . Il sistema di comunicazione di quinta generazione è visto come la rete wireless reale , in grado di supportare applicazioni web wireless a livello mondiale ( wwww ). Ci sono due punti di vista dei sistemi 5G : evolutivo e rivoluzionario. Dal punto di vista evolutivo, i sistemi 5G saranno in grado di supportare wwww permettendo una rete altamente flessibile come un Adhoc rete wireless dinamica ( DAWN ) . In questa visione tecnologie avanzate, tra cui antenna intelligente e modulazione flessibile , sono le chiavi per ottimizzare le reti wireless ad hoc. Dal punto di vista rivoluzionario, i sistemi 5G dovrebbe essere una tecnologia intelligente in grado di interconnettere tutto il mondo senza limiti . Un esempio di applicazione potrebbe essere un robot wireless con intelligenza artificiale .

The NreABC system of Staphylococcus carnosus combines nitrate and oxygen sensing by an NreA,NreB sensor complex

Staphylococcus carnosus is a facultative anaerobic bacterium which features the cytoplasmic NreABC system. It is necessary for regulation of nitrate respiration and the nitrate reductase gene narG in response to oxygen and nitrate availability. NreB is a sensor kinase of a two-component system and represents the oxygen sensor of the system. It binds an oxygen labile [4Fe-4S]2+ cluster under anaerobic conditions. NreB autophosphorylates and phosphoryl transfer activates the response regulator NreC which induces narG expression. The third component of the Nre system is the nitrate receptor NreA. In this study the role of the nitrate receptor protein NreA in nitrate regulation and its functional and physiological effect on oxygen regulation and interaction with the NreBC two-component system were detected. In vivo, a reporter gene assay for measuring expression of the NreABC regulated nitrate reductase gene narG was used for quantitative evaluation of NreA function. Maximal narG expression in wild type S. carnosus required anaerobic conditions and the presence of nitrate. Deletion of nreA allowed expression of narG under aerobic conditions, and under anaerobic conditions nitrate was no longer required for maximal induction. This indicates that NreA is a nitrate regulated inhibitor of narG expression. Purified NreA and variant NreA(Y95A) inhibited the autophosphorylation of anaerobic NreB in part and completely, respectively. Neither NreA nor NreA(Y95A) stimulated dephosphorylation of NreB-phosphate, however. Inhibition of phosphorylation was relieved completely when NreA with bound nitrate (NreA•[NO3-]) was used. The same effects of NreA were monitored with aerobically isolated Fe-S-less NreB, which indicates that NreA does not have an influence on the iron-sulfur cluster of NreB. In summary, the data of this study show that NreA interacts with the oxygen sensor NreB and controls its phosphorylation level in a nitrate dependent manner. This modulation of NreB-function by NreA and nitrate results in nitrate/oxygen co-sensing by an NreA/NreB sensory unit. It transmits the regulatory signal from oxygen and nitrate in a joint signal to target promoters. Therefore, nitrate and oxygen regulation of nitrate dissimilation follows a new mode of regulation not present in other facultative anaerobic bacteria.

Swarm constructability: designing through embedded tectonic behaviors in swarm robotic systems

Con questa tesi di laurea si muovono i primi passi di una ricerca applicata finalizzata alla costruzione-deposizione di materiale da parte di sciami di mini-robot dal comportamento indipendente che si coordinano tramite segnali lasciati e rilevati nell’ambiente in cui si muovono. Lo sviluppo di tecniche di progettazione e fabbricazione digitale ha prodotto un aumento nel grado di interconnessione tra tecnologia e design, dunque, di nuove possibilità tettoniche. Le relazioni tettoniche tradizionali stanno infatti subendo una trasformazione radicale, potendo essere esplicitamente informate e dunque mediate attraverso gli strumenti digitali dall’ideazione alla produzione. Questa mediazione informata del contenuto tettonico (che opera costantemente) è distintivo di un approccio material-based alla progettazione che aumenta l’integrazione tra struttura, materia e forma entro le tecnologie di fabbricazione (R.Oxman). Dei numerosi processi di fabbricazione per l’architettura che si servono di tecnologia robotica, pochi sono capaci di superare la logica gerarchica, rigida e lineare-sequenziale che serve di fatto agli obiettivi di automazione ed ottimizzazione. La distribuzione di forme di intelligenza semplificata ad un numero elevato di unità robot è quindi qui proposta come alternativa al modello appena descritto. Incorporando semplici decisioni di carattere architettonico negli agenti-robot che costituiscono il sistema distribuito di entità autonome, la loro interazione e le decisioni prese individualmente producono comportamento collettivo e l’integrazione delle suddette relazioni tettoniche. Nello sviluppo del progetto, si è fatto così riferimento a modelli comportamentali collettivi (di sciame) osservabili in specie comunitarie che organizzano strutture materiali -come termiti e vespe- ed in organismi semplici -come le muffe cellulari della specie Physarum polycephalum. Per queste specie biologiche il processo di costruzione non dipende da un ‘piano generale’ ma è guidato esclusivamente da azioni dei singoli individui che comunicano lasciando tracce chimiche nell’ambiente e modificano il loro comportamento rilevando le tracce lasciate dagli altri individui. A questo scopo, oltre alle simulazioni in digitale, è stato indispensabile sviluppare dei prototipi funzionali di tipo fisico, ovvero la realizzazione di mini-robot dal movimento indipendente, in grado di coordinarsi tra loro tramite segnali lasciati nell’ambiente e capaci di depositare materiale.

Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Compressed sensing approach to ultra-wideband receiver design

One of the scarcest resources in the wireless communication system is the limited frequency spectrum. Many wireless communication systems are hindered by the bandwidth limitation and are not able to provide high speed communication. However, Ultra-wideband (UWB) communication promises a high speed communication because of its very wide bandwidth of 7.5GHz (3.1GHz-10.6GHz). The unprecedented bandwidth promises many advantages for the 21st century wireless communication system. However, UWB has many hardware challenges, such as a very high speed sampling rate requirement for analog to digital conversion, channel estimation, and implementation challenges. In this thesis, a new method is proposed using compressed sensing (CS), a mathematical concept of sub-Nyquist rate sampling, to reduce the hardware complexity of the system. The method takes advantage of the unique signal structure of the UWB symbol. Also, a new digital implementation method for CS based UWB is proposed. Lastly, a comparative study is done of the CS-UWB hardware implementation methods. Simulation results show that the application of compressed sensing using the proposed method significantly reduces the number of hardware complexity compared to the conventional method of using compressed sensing based UWB receiver.