Valorizzazione di cartografia storica attraverso moderne tecniche geomatiche: recupero metrico, elaborazione e consultazione in ambiente digitale

“Cartographic heritage” is different from “cartographic history”. The second term refers to the study of the development of surveying and drawing techniques related to maps, through time, i.e. through different types of cultural environment which were background for the creation of maps. The first term concerns the whole amount of ancient maps, together with these different types of cultural environment, which the history has brought us and which we perceive as cultural values to be preserved and made available to many users (public, institutions, experts). Unfortunately, ancient maps often suffer preservation problems of their analog support, mostly due to aging. Today, metric recovery in digital form and digital processing of historical cartography allow preserving map heritage. Moreover, modern geomatic techniques give us new chances of using historical information, which would be unachievable on analog supports. In this PhD thesis, the whole digital processing of recovery and elaboration of ancient cartography is reported, with a special emphasis on the use of digital tools in preservation and elaboration of cartographic heritage. It is possible to divide the workflow into three main steps, that reflect the chapter structure of the thesis itself: • map acquisition: conversion of the ancient map support from analog to digital, by means of high resolution scanning or 3D surveying (digital photogrammetry or laser scanning techniques); this process must be performed carefully, with special instruments, in order to reduce deformation as much as possible; • map georeferencing: reproducing in the digital image the native metric content of the map, or even improving it by selecting a large number of still existing ground control points; this way it is possible to understand the projection features of the historical map, as well as to evaluate and represent the degree of deformation induced by the old type of cartographic transformation (that can be unknown to us), by surveying errors or by support deformation, usually all errors of too high value with respect to our standards; • data elaboration and management in a digital environment, by means of modern software tools: vectorization, giving the map a new and more attractive graphic view (for instance, by creating a 3D model), superimposing it on current base maps, comparing it to other maps, and finally inserting it in GIS or WebGIS environment as a specific layer. The study is supported by some case histories, each of them interesting from the point of view of one digital cartographic elaboration step at least. The ancient maps taken into account are the following ones: • three maps of the Po river delta, made at the end of the XVI century by a famous land-surveyor, Ottavio Fabri (he is single author in the first map, co-author with Gerolamo Pontara in the second map, co-author with Bonajuto Lorini and others in the third map), who wrote a methodological textbook where he explains a new topographical instrument, the squadra mobile (mobile square) invented and used by himself; today all maps are preserved in the State Archive of Venice; • the Ichnoscenografia of Bologna by Filippo de’ Gnudi, made in the 1702 and today preserved in the Archiginnasio Library of Bologna; it is a scenographic view of the city, captured in a bird’s eye flight, but also with an icnographic value, as the author himself declares; • the map of Bologna by the periti Gregorio Monari and Antonio Laghi, the first map of the city derived from a systematic survey, even though it was made only ten years later (1711–1712) than the map by de’ Gnudi; in this map the scenographic view was abandoned, in favor of a more correct representation by means of orthogonal projection; today the map is preserved in the State Archive of Bologna; • the Gregorian Cadastre of Bologna, made in 1831 and updated until 1927, now preserved in the State Archive of Bologna; it is composed by 140 maps and 12 brogliardi (register volumes). In particular, the three maps of the Po river delta and the Cadastre were studied with respect to their acquisition procedure. Moreover, the first maps were analyzed from the georeferencing point of view, and the Cadastre was analyzed with respect to a possible GIS insertion. Finally, the Ichnoscenografia was used to illustrate a possible application of digital elaboration, such as 3D modeling. Last but not least, we must not forget that the study of an ancient map should start, whenever possible, from the consultation of the precious original analogical document; analysis by means of current digital techniques allow us new research opportunities in a rich and modern multidisciplinary context.

L'adeguamento di tradizionali laboratori europei di restauro fotochimico alle tecniche digitali

La presente ricerca ha avuto come obbietivo studiare come stia avvenendo l'adattamento dei tradizionali laboratori fotochimici di film alle tecniche digitali attraverso l'analisi delle politiche di preservazione, del restauro, dei costi relativi all’acquisto di nuove apparecchiature e della migrazione ai nuovi media presso il British Film Institute (BFI), lo Svenska Filminstitutet (SFI), l’Eye Filmmuseum, L'Immagine Ritrovata e ANIM - Cinemateca Portuguesa. A questo scopo è stato utilizzato il metodo dello studio di caso, in cui sono state effettuate interviste con gestori e tecnici delle istituzioni citate al fine di rispondere al quesito della presente ricerca: quali sono l’impatto e le implicazioni di questo adattamento? Quali sono i risultati raggiunti con le nuove attrezzature e metodi di restauro e preservazione? Per arrivare a rispondere a queste domande lo studio è stato diviso in due sezioni. Nella prima parte, sono riportate le interviste svolte presso SFI, BFI, Eye e L'Immagine Ritrovata, realizzate al fine di ottenere dati che permettessero di formulare un'intervista più completa e approfondita. Successivamente, questa intervista più dettagliata è stata condotta con una sola istituzione, la Cinemateca Portuguesa. Pertanto, nella seconda parte dello studio di caso, sono state realizzate interviste a tecnici e dirigenti di ANIM - Cinemateca Portuguesa e dei suoi laboratori partner. L'analisi dei risultati comprende tutte le informazioni provenienti dalle cinque istituzioni intervistate. È stato notato che l'adattamento al digitale ha effettivamente apportato miglioramenti nella preservazione e nel recupero del materiale fotochimico, ma ciò ha anche fatto sorgere alcuni dilemmi nei laboratori. C'è apprensione per la scarsità di materiale della filiera fotochimica e per una sua ipotetica fine nel prossimo futuro, poiché non ci sono ancora sufficienti conoscenze sulla filiera digitale e sul comportamento di questi media con il passare del tempo. Gli intervistati hanno altresì dimostrato positività riguardo alle tecnologie digitali.

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings.

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Advanced Techniques for Face Recognition under Challenging Environments

Automatically recognizing faces captured under uncontrolled environments has always been a challenging topic in the past decades. In this work, we investigate cohort score normalization that has been widely used in biometric verification as means to improve the robustness of face recognition under challenging environments. In particular, we introduce cohort score normalization into undersampled face recognition problem. Further, we develop an effective cohort normalization method specifically for the unconstrained face pair matching problem. Extensive experiments conducted on several well known face databases demonstrate the effectiveness of cohort normalization on these challenging scenarios. In addition, to give a proper understanding of cohort behavior, we study the impact of the number and quality of cohort samples on the normalization performance. The experimental results show that bigger cohort set size gives more stable and often better results to a point before the performance saturates. And cohort samples with different quality indeed produce different cohort normalization performance. Recognizing faces gone after alterations is another challenging problem for current face recognition algorithms. Face image alterations can be roughly classified into two categories: unintentional (e.g., geometrics transformations introduced by the acquisition devide) and intentional alterations (e.g., plastic surgery). We study the impact of these alterations on face recognition accuracy. Our results show that state-of-the-art algorithms are able to overcome limited digital alterations but are sensitive to more relevant modifications. Further, we develop two useful descriptors for detecting those alterations which can significantly affect the recognition performance. In the end, we propose to use the Structural Similarity (SSIM) quality map to detect and model variations due to plastic surgeries. Extensive experiments conducted on a plastic surgery face database demonstrate the potential of SSIM map for matching face images after surgeries.

Governing algorithms in the big data era for balancing new digital rights - designing GDPR compliant and trustworthy XAI systems

This thesis investigates the legal, ethical, technical, and psychological issues of general data processing and artificial intelligence practices and the explainability of AI systems. It consists of two main parts. In the initial section, we provide a comprehensive overview of the big data processing ecosystem and the main challenges we face today. We then evaluate the GDPR’s data privacy framework in the European Union. The Trustworthy AI Framework proposed by the EU’s High-Level Expert Group on AI (AI HLEG) is examined in detail. The ethical principles for the foundation and realization of Trustworthy AI are analyzed along with the assessment list prepared by the AI HLEG. Then, we list the main big data challenges the European researchers and institutions identified and provide a literature review on the technical and organizational measures to address these challenges. A quantitative analysis is conducted on the identified big data challenges and the measures to address them, which leads to practical recommendations for better data processing and AI practices in the EU. In the subsequent part, we concentrate on the explainability of AI systems. We clarify the terminology and list the goals aimed at the explainability of AI systems. We identify the reasons for the explainability-accuracy trade-off and how we can address it. We conduct a comparative cognitive analysis between human reasoning and machine-generated explanations with the aim of understanding how explainable AI can contribute to human reasoning. We then focus on the technical and legal responses to remedy the explainability problem. In this part, GDPR’s right to explanation framework and safeguards are analyzed in-depth with their contribution to the realization of Trustworthy AI. Then, we analyze the explanation techniques applicable at different stages of machine learning and propose several recommendations in chronological order to develop GDPR-compliant and Trustworthy XAI systems.

Advancing digital healthcare research and machine learning-aided knowledge extraction amidst the COVID-19 pandemic

The rapid progression of biomedical research coupled with the explosion of scientific literature has generated an exigent need for efficient and reliable systems of knowledge extraction. This dissertation contends with this challenge through a concentrated investigation of digital health, Artificial Intelligence, and specifically Machine Learning and Natural Language Processing's (NLP) potential to expedite systematic literature reviews and refine the knowledge extraction process. The surge of COVID-19 complicated the efforts of scientists, policymakers, and medical professionals in identifying pertinent articles and assessing their scientific validity. This thesis presents a substantial solution in the form of the COKE Project, an initiative that interlaces machine reading with the rigorous protocols of Evidence-Based Medicine to streamline knowledge extraction. In the framework of the COKE (“COVID-19 Knowledge Extraction framework for next-generation discovery science”) Project, this thesis aims to underscore the capacity of machine reading to create knowledge graphs from scientific texts. The project is remarkable for its innovative use of NLP techniques such as a BERT + bi-LSTM language model. This combination is employed to detect and categorize elements within medical abstracts, thereby enhancing the systematic literature review process. The COKE project's outcomes show that NLP, when used in a judiciously structured manner, can significantly reduce the time and effort required to produce medical guidelines. These findings are particularly salient during times of medical emergency, like the COVID-19 pandemic, when quick and accurate research results are critical.