33 resultados para Systems and data security

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The thesis represents the conclusive outcome of the European Joint Doctorate programmein Law, Science & Technology funded by the European Commission with the instrument Marie Skłodowska-Curie Innovative Training Networks actions inside of the H2020, grantagreement n. 814177. The tension between data protection and privacy from one side, and the need of granting further uses of processed personal datails is investigated, drawing the lines of the technological development of the de-anonymization/re-identification risk with an explorative survey. After acknowledging its span, it is questioned whether a certain degree of anonymity can still be granted focusing on a double perspective: an objective and a subjective perspective. The objective perspective focuses on the data processing models per se, while the subjective perspective investigates whether the distribution of roles and responsibilities among stakeholders can ensure data anonymity.

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Agriculture market instability impedes achieving the global goal of sustainable and resilient food systems. Currently, the support to producers reaches the mammoth USD 540 billion a year and is projected to reach USD 1.8 trillion by 2030. This gigantic increase requires a repurposing agricultural support strategy (RASS), considering the market country-specific circumstances. These circumstances may vary with geographic locations, marketing structures, and product value chains. The fruit production system is crucial for health-conscious consumers and profit-oriented producers for food and nutritional security. Export is one of the main driving forces behind the expansion of the fruit sector, and during the year 2010-2018, trade significantly outpaced production increases. The previous literature states that irregular and unpredictable behaviour — Chaos — can arise from entirely rational economic decision-making within markets. Different markets' direct/indirect linkages through trade create trade hubs, and uncertainty may function as an avenue to transmit adverse shocks and increase vulnerability rather than contribute to resilience. Therefore, distinguishing Chaos into an endogenous and exogenous pattern of behaviour is cradled to formulate an effective RASS for resilient food systems and to understand global food crises. The present research is aimed at studying the market dynamics of three regional trade hubs, i.e., Brazil (South America), Italy (Europe), and Pakistan (Asia), each representing advanced to traditional value chains to control uncertainty (risks). The present research encompasses 1) a systematic review to highlight the research dynamism and identify grey-areas of research. Based on the findings, we have investigated the 2) nonlinear impacts of climate-induced price responsiveness in monopsony markets. Once we highlighted the importance of marketing structures/arrangements, 3) we developed a risk transmission framework to address the co-evolving impacts in complex dynamic interactions.

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The thesis is divided into two main parts. In the first one organocatalysis is briefly introduced. Then, new enantiopure trityl pyrrolidines modified with an ionic tag are described. All the catalysts are tested in the benchmark Michael addition reaction to prove their activity and stereoselectivity. In the second part, photocatalysis is first introduced. Then, four different research projects are described. At first, the construction of a hybrid metal-organo-photoredox catalyst is described. The hybrid photocatalysts obtained were employed in the benchmark photoredox alkylation of aldehydes. Then, the use of visible light and a photocatalytic system for the cyclization of iodoaryl vinyl derivatives to tetrahydroquinoline structures is described. In addition, the reaction can also be performed using flow-chemistry. Finally, a mechanistic proposal based on some mechanistic studies is described. Third, a new photoredox catalyzed transformation for the synthesis of 2,3-dihydrofurans is reported. Depending on the involved starting materials, different pathways have arisen. A mechanistic proposal based on reported literatures and experimental data is described. At last, a new photoredox catalyzed transformation for the synthesis of 2-aminofurans is described. Electrophilic radical addition on allenamides and subsequential intramolecular cyclization are exploited. The reaction proceeds under very mild conditions and in 2-aminofurans are obtained in good to high yield. It represents one of the few applications of allenamides in photoredox catalysis. A mechanistic proposal is described. Finally, preliminary investigations on the applicability of the developed transformation under flow chemistry conditions.

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Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) are becoming essential in many application contexts, e.g. civil, industrial, aerospace etc., to reduce structures maintenance costs and improve safety. Conventional inspection methods typically exploit bulky and expensive instruments and rely on highly demanding signal processing techniques. The pressing need to overcome these limitations is the common thread that guided the work presented in this Thesis. In the first part, a scalable, low-cost and multi-sensors smart sensor network is introduced. The capability of this technology to carry out accurate modal analysis on structures undergoing flexural vibrations has been validated by means of two experimental campaigns. Then, the suitability of low-cost piezoelectric disks in modal analysis has been demonstrated. To enable the use of this kind of sensing technology in such non conventional applications, ad hoc data merging algorithms have been developed. In the second part, instead, imaging algorithms for Lamb waves inspection (namely DMAS and DS-DMAS) have been implemented and validated. Results show that DMAS outperforms the canonical Delay and Sum (DAS) approach in terms of image resolution and contrast. Similarly, DS-DMAS can achieve better results than both DMAS and DAS by suppressing artefacts and noise. To exploit the full potential of these procedures, accurate group velocity estimations are required. Thus, novel wavefield analysis tools that can address the estimation of the dispersion curves from SLDV acquisitions have been investigated. An image segmentation technique (called DRLSE) was exploited in the k-space to draw out the wavenumber profile. The DRLSE method was compared with compressive sensing methods to extract the group and phase velocity information. The validation, performed on three different carbon fibre plates, showed that the proposed solutions can accurately determine the wavenumber and velocities in polar coordinates at multiple excitation frequencies.

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Persistent food insecurity and famines have continued to significantly shape the development policies of Ethiopia for decades. Over the decades, frequent famines caused not only the death of hundreds of thousands of victims but also significantly contributed to two revolutions that swept away the Haile Selassie and Derg regimes, as well as significantly taxing the legitimacy of the incumbent regime. As a result, agriculture and food security have become increasingly the top policy priorities for all political regimes in Ethiopia. However, the development policies of the ruling elites of Ethiopia have consistently failed to transform backward agriculture and ensure food security. The failures of the development policies of the Ethiopian governments over the years were attributed to several factors. Ethiopian authoritarian politics, centralized rule with a lack of transparency and accountability; the isolation of peasants from the development and governance process, and the lack of coherent agricultural development strategies that invest in peasant agriculture and create synergy among sectors are identified as key issues that have contributed to the persistence of food insecurity in the country. The literature on the failure of Ethiopia's political regimes to address food insecurity and famine has two major gaps that this study aims to fill. First, the cumulative and path-dependent food security and agricultural development policy environment were not adequately considered. Second, the strategy of extraversion by subsequent political regimes to use external support as a relief to prevent the famine-induced political crisis. This study used a mixed approach to collect data and present the evolution of the interplays of development policies and food security in three regimes within the context of international food security discourses. This study found out how the historical patterns of approaches of Ethiopia’s regimes to development and governance led to frequent famines and persistent food insecurity.

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The term Artificial intelligence acquired a lot of baggage since its introduction and in its current incarnation is synonymous with Deep Learning. The sudden availability of data and computing resources has opened the gates to myriads of applications. Not all are created equal though, and problems might arise especially for fields not closely related to the tasks that pertain tech companies that spearheaded DL. The perspective of practitioners seems to be changing, however. Human-Centric AI emerged in the last few years as a new way of thinking DL and AI applications from the ground up, with a special attention at their relationship with humans. The goal is designing a system that can gracefully integrate in already established workflows, as in many real-world scenarios AI may not be good enough to completely replace its humans. Often this replacement may even be unneeded or undesirable. Another important perspective comes from, Andrew Ng, a DL pioneer, who recently started shifting the focus of development from “better models” towards better, and smaller, data. He defined his approach Data-Centric AI. Without downplaying the importance of pushing the state of the art in DL, we must recognize that if the goal is creating a tool for humans to use, more raw performance may not align with more utility for the final user. A Human-Centric approach is compatible with a Data-Centric one, and we find that the two overlap nicely when human expertise is used as the driving force behind data quality. This thesis documents a series of case-studies where these approaches were employed, to different extents, to guide the design and implementation of intelligent systems. We found human expertise proved crucial in improving datasets and models. The last chapter includes a slight deviation, with studies on the pandemic, still preserving the human and data centric perspective.

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The purpose of this research study is to discuss privacy and data protection-related regulatory and compliance challenges posed by digital transformation in healthcare in the wake of the COVID-19 pandemic. The public health crisis accelerated the development of patient-centred remote/hybrid healthcare delivery models that make increased use of telehealth services and related digital solutions. The large-scale uptake of IoT-enabled medical devices and wellness applications, and the offering of healthcare services via healthcare platforms (online doctor marketplaces) have catalysed these developments. However, the use of new enabling technologies (IoT, AI) and the platformisation of healthcare pose complex challenges to the protection of patient’s privacy and personal data. This happens at a time when the EU is drawing up a new regulatory landscape for the use of data and digital technologies. Against this background, the study presents an interdisciplinary (normative and technology-oriented) critical assessment on how the new regulatory framework may affect privacy and data protection requirements regarding the deployment and use of Internet of Health Things (hardware) devices and interconnected software (AI systems). The study also assesses key privacy and data protection challenges that affect healthcare platforms (online doctor marketplaces) in their offering of video API-enabled teleconsultation services and their (anticipated) integration into the European Health Data Space. The overall conclusion of the study is that regulatory deficiencies may create integrity risks for the protection of privacy and personal data in telehealth due to uncertainties about the proper interplay, legal effects and effectiveness of (existing and proposed) EU legislation. The proliferation of normative measures may increase compliance costs, hinder innovation and ultimately, deprive European patients from state-of-the-art digital health technologies, which is paradoxically, the opposite of what the EU plans to achieve.

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Questo lavoro di tesi è stato suddiviso in tre parti. L’argomento principale è stato lo “Studio della componente antiossidante di oli ottenuti da olive mediante l’utilizzo di diversi sistemi e parametri tecnologici”. E’ ben noto come la qualità ossidativa di un olio di oliva dipenda oltre che dalla sua composizione in acidi grassi, dalla presenza di composti caratterizzati da un elevata attività antiossidante, ovvero le sostanze fenoliche. I composti fenolici contribuiscono quindi in maniera preponderante alla shelf life dell’olio extravergine di oliva. Inoltre sono state riscontrate delle forti correlazione tra alcune di queste sostanze e gli attributi sensoriali positivi di amaro e piccante. E’ poi da sottolineare come il potere antiossidante dei composti fenolici degli oli vergini di oliva, sia stato negli ultimi anni oggetto di considerevole interesse, poiché correlato alla protezione da alcune patologie come ad esempio quelle vascolari, degenerative e tumorali. Il contenuto delle sostanze fenoliche negli oli di oliva dipende da diversi fattori: cultivar, metodo di coltivazione, grado di maturazione delle olive e ovviamente dalle operazioni tecnologiche poiché possono variare il quantitativo di questi composti estratto. Alla luce di quanto appena detto abbiamo valutato l’influenza dei fattori agronomici (metodi di agricoltura biologica, integrata e convenzionale) e tecnologici (riduzione della temperatura della materia prima, aggiunta di coadiuvanti in fase di frangitura e di gramolatura, confronto tra tre oli extravergini di oliva ottenuti mediante diversi sistemi tecnologici) sul contenuto in composti fenolici di oli edibili ottenuti da olive (paper 1-3-4). Oltre alle sostanze fenoliche, negli oli di oliva sono presenti altri composti caratterizzati da proprietà chimiche e nutrizionali, tra questi vi sono i fitosteroli, ovvero gli steroli tipici del mondo vegetale, che rappresentano la frazione dell’insaponificabile quantitativamente più importante dopo gli idrocarburi. La composizione quali-quantitativa degli steroli di un olio di oliva è una delle caratteristiche analitiche più importanti nella valutazione della sua genuinità; infatti la frazione sterolica è significativamente diversa in funzione dell’origine botanica e perciò viene utilizzata per distinguere tra di loro gli oli e le loro miscele. Il principale sterolo nell’olio di oliva è il β- sitosterolo, la presenza di questo composto in quantità inferiore al 90% è un indice approssimativo dell’aggiunta di un qualsiasi altro olio. Il β-sitosterolo è una sostanza importante dal punto di vista della salute, poiché si oppone all’assorbimento del colesterolo. Mentre in letteratura si trovano numerosi lavori relativi al potere antiossidante di una serie di composti presenti nell’olio vergine di oliva (i già citati polifenoli, ma anche carotenoidi e tocoferoli) e ricerche che dimostrano invece come altri composti possano promuovere l’ossidazione dei lipidi, per quanto riguarda il potere antiossidante degli steroli e dei 4- metilsteroli, vi sono ancora poche informazioni. Per questo è stata da noi valutata la composizione sterolica in oli extravergini di oliva ottenuti con diverse tecnologie di estrazione e l’influenza di questa sostanza sulla loro stabilità ossidativa (paper 2). E’ stato recentemente riportato in letteratura come lipidi cellulari evidenziati attraverso la spettroscopia di risonanza nucleare magnetica (NMR) rivestano una importanza strategica da un punto di vista funzionale e metabolico. Questi lipidi, da un lato un lato sono stati associati allo sviluppo di cellule neoplastiche maligne e alla morte cellulare, dall’altro sono risultati anche messaggeri di processi benigni quali l’attivazione e la proliferazione di un normale processo di crescita cellulare. Nell’ambito di questa ricerca è nata una collaborazione tra il Dipartimento di Biochimica “G. Moruzzi” ed il Dipartimento di Scienze degli Alimenti dell’Università di Bologna. Infatti, il gruppo di lipochimica del Dipartimento di Scienze degli Alimenti, a cui fa capo il Prof. Giovanni Lercker, da sempre si occupa dello studio delle frazioni lipidiche, mediante le principali tecniche cromatografiche. L’obiettivo di questa collaborazione è stato quello di caratterizzare la componente lipidica totale estratta dai tessuti renali umani sani e neoplastici, mediante l’utilizzo combinato di diverse tecniche analitiche: la risonanza magnetica nucleare (1H e 13C RMN), la cromatografia su strato sottile (TLC), la cromatografia liquida ad alta prestazione (HPLC) e la gas cromatografia (GC) (paper 5-6-7)

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Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

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The miniaturization race in the hardware industry aiming at continuous increasing of transistor density on a die does not bring respective application performance improvements any more. One of the most promising alternatives is to exploit a heterogeneous nature of common applications in hardware. Supported by reconfigurable computation, which has already proved its efficiency in accelerating data intensive applications, this concept promises a breakthrough in contemporary technology development. Memory organization in such heterogeneous reconfigurable architectures becomes very critical. Two primary aspects introduce a sophisticated trade-off. On the one hand, a memory subsystem should provide well organized distributed data structure and guarantee the required data bandwidth. On the other hand, it should hide the heterogeneous hardware structure from the end-user, in order to support feasible high-level programmability of the system. This thesis work explores the heterogeneous reconfigurable hardware architectures and presents possible solutions to cope the problem of memory organization and data structure. By the example of the MORPHEUS heterogeneous platform, the discussion follows the complete design cycle, starting from decision making and justification, until hardware realization. Particular emphasis is made on the methods to support high system performance, meet application requirements, and provide a user-friendly programmer interface. As a result, the research introduces a complete heterogeneous platform enhanced with a hierarchical memory organization, which copes with its task by means of separating computation from communication, providing reconfigurable engines with computation and configuration data, and unification of heterogeneous computational devices using local storage buffers. It is distinguished from the related solutions by distributed data-flow organization, specifically engineered mechanisms to operate with data on local domains, particular communication infrastructure based on Network-on-Chip, and thorough methods to prevent computation and communication stalls. In addition, a novel advanced technique to accelerate memory access was developed and implemented.

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The present PhD thesis summarizes the three-years study about the neutronic investigation of a new concept nuclear reactor aiming at the optimization and the sustainable management of nuclear fuel in a possible European scenario. A new generation nuclear reactor for the nuclear reinassance is indeed desired by the actual industrialized world, both for the solution of the energetic question arising from the continuously growing energy demand together with the corresponding reduction of oil availability, and the environment question for a sustainable energy source free from Long Lived Radioisotopes and therefore geological repositories. Among the Generation IV candidate typologies, the Lead Fast Reactor concept has been pursued, being the one top rated in sustainability. The European Lead-cooled SYstem (ELSY) has been at first investigated. The neutronic analysis of the ELSY core has been performed via deterministic analysis by means of the ERANOS code, in order to retrieve a stable configuration for the overall design of the reactor. Further analyses have been carried out by means of the Monte Carlo general purpose transport code MCNP, in order to check the former one and to define an exact model of the system. An innovative system of absorbers has been conceptualized and designed for both the reactivity compensation and regulation of the core due to cycle swing, as well as for safety in order to guarantee the cold shutdown of the system in case of accident. Aiming at the sustainability of nuclear energy, the steady-state nuclear equilibrium has been investigated and generalized into the definition of the ``extended'' equilibrium state. According to this, the Adiabatic Reactor Theory has been developed, together with a New Paradigm for Nuclear Power: in order to design a reactor that does not exchange with the environment anything valuable (thus the term ``adiabatic''), in the sense of both Plutonium and Minor Actinides, it is required indeed to revert the logical design scheme of nuclear cores, starting from the definition of the equilibrium composition of the fuel and submitting to the latter the whole core design. The New Paradigm has been applied then to the core design of an Adiabatic Lead Fast Reactor complying with the ELSY overall system layout. A complete core characterization has been done in order to asses criticality and power flattening; a preliminary evaluation of the main safety parameters has been also done to verify the viability of the system. Burn up calculations have been then performed in order to investigate the operating cycle for the Adiabatic Lead Fast Reactor; the fuel performances have been therefore extracted and inserted in a more general analysis for an European scenario. The present nuclear reactors fleet has been modeled and its evolution simulated by means of the COSI code in order to investigate the materials fluxes to be managed in the European region. Different plausible scenarios have been identified to forecast the evolution of the European nuclear energy production, including the one involving the introduction of Adiabatic Lead Fast Reactors, and compared to better analyze the advantages introduced by the adoption of new concept reactors. At last, since both ELSY and the ALFR represent new concept systems based upon innovative solutions, the neutronic design of a demonstrator reactor has been carried out: such a system is intended to prove the viability of technology to be implemented in the First-of-a-Kind industrial power plant, with the aim at attesting the general strategy to use, to the largest extent. It was chosen then to base the DEMO design upon a compromise between demonstration of developed technology and testing of emerging technology in order to significantly subserve the purpose of reducing uncertainties about construction and licensing, both validating ELSY/ALFR main features and performances, and to qualify numerical codes and tools.

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The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.