Interpreting Judgements using Knowledge Representation Methods and Computational Models of Argument

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

Libertà di espressione e sorveglianza globale

La presente tesi ha come scopo quello di individuare alcune problematiche relative all’esercizio e alla limitazione del diritto alla libertà di espressione nel contesto delle attività globali di sorveglianza e controllo delle tecnologie dell’informazione e della comunicazione. Tali attività, poste in essere da parte degli Stati e da parte degli operatori privati, sono favorite dal nebuloso rapporto tra norme di fonte pubblica, privata e informatica, e sono invece osteggiate dal ricorso, collettivo e individuale, alle possibilità offerte dalle tecnologie stesse per la conduzione di attività in anonimato e segretezza. La sorveglianza globale nel contesto delle privatizzazioni si serve del codice e dell’autonomia privata, così come la resistenza digitale ricorre alle competenze informatiche e agli spazi di autonomia d’azione dell’individuo. In questo contesto, la garanzia dell’esistenza e dell’esercizio dei diritti fondamentali dell’individuo, tra tutti il diritto alla libertà di espressione e il diritto alla tutela della riservatezza, passa per l’adozione di tecniche e pratiche di autotutela attraverso l’utilizzo di sistemi di cifratura e comunicazioni anonime. L’individuo, in questo conflitto tecnico e sociale, si trova a dover difendere l’esercizio dei propri diritti e finanche l’adempimento ai propri doveri, quando attinenti a particolari figure professionali o sociali, quali avvocati, operatori di giustizia, giornalisti, o anche semplicemente genitori. In conclusione dell’elaborato si propongono alcune riflessioni sulla formazione della cittadinanza e del mondo professionale, da parte dei giuristi delle nuove tecnologie, all’uso cosciente, consapevole e responsabile delle nuove tecnologie dell’informazione, con lo stimolo ad orientare altresì le proprie attività alla tutela e alla promozione dei diritti umani fondamentali, democratici, costituzionali, civili e sociali.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.