Studio di un algoritmo per confrontare documenti xml

Tesi sullo studio di algoritmi per il confronto di documenti XML, panoramica sui vari algoritmi. Focalizzazione sull'algoritmo NDiff e in particolare sulla gestione degli attributi.

Metodi di map-matching per l'identificazione degli itinerari dei ciclisti

Negli ultimi anni si è assistito al considerevole aumento della disponibilità di dati GPS e della loro precisione, dovuto alla diffusione e all’evoluzione tecnologica di smartphone e di applicazioni di localizzazione. Il processo di map-matching consiste nell’integrare tali dati - solitamente una lista ordinata di punti, identificati tramite coordinate geografiche ricavate mediante un sistema di localizzazione, come il GPS - con le reti disponibili; nell’ambito dell’ingegneria dei trasporti, l’obiettivo è di identificare il percorso realmente scelto dall’utente per lo spostamento. Il presente lavoro si propone l’obiettivo di studiare alcune metodologie di map-matching per l’identificazione degli itinerari degli utenti, in particolare della mobilità ciclabile. Nel primo capitolo è esposto il funzionamento dei sistemi di posizionamento e in particolare del sistema GPS: ne sono discusse le caratteristiche, la suddivisione nei vari segmenti, gli errori di misurazione e la cartografia di riferimento. Nel secondo capitolo sono presentati i vari aspetti del procedimento di map-matching, le sue principali applicazioni e alcune possibili classificazioni degli algoritmi di map-matching sviluppati in letteratura. Nel terzo capitolo è esposto lo studio eseguito su diversi algoritmi di map-matching, che sono stati testati su un database di spostamenti di ciclisti nell’area urbana di Bologna, registrati tramite i loro smartphone sotto forma di punti GPS, e sulla relativa rete. Si analizzano altresì i risultati ottenuti in un secondo ambiente di testing, predisposto nell’area urbana di Catania, dove sono state registrate in modo analogo alcune tracce di prova, e utilizzata la relativa rete. La comparazione degli algoritmi è eseguita graficamente e attraverso degli indicatori. Vengono inoltre proposti e valutati due algoritmi che forniscono un aggiornamento di quelli analizzati, al fine di migliorarne le prestazioni in termini di accuratezza dei risultati e di costo computazionale.

Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Coronary collateral function in the transplanted heart: propensity score matching with coronary artery disease

The function of the coronary collateral circulation in heart transplant patients has not been investigated in a controlled fashion. Since it partly belongs to the microcirculation, which is affected by transplant vasculopathy, the hypothesis was tested that the coronary collateral circulation in heart transplant recipients is less developed than in coronary artery disease (CAD) patients.

The Design of XML-Based Model and Experiment Description Languages for Network Simulation

The Simulation Automation Framework for Experiments (SAFE) is a project created to raise the level of abstraction in network simulation tools and thereby address issues that undermine credibility. SAFE incorporates best practices in network simulationto automate the experimental process and to guide users in the development of sound scientific studies using the popular ns-3 network simulator. My contributions to the SAFE project: the design of two XML-based languages called NEDL (ns-3 Experiment Description Language) and NSTL (ns-3 Script Templating Language), which facilitate the description of experiments and network simulationmodels, respectively. The languages provide a foundation for the construction of better interfaces between the user and the ns-3 simulator. They also provide input to a mechanism which automates the execution of network simulation experiments. Additionally,this thesis demonstrates that one can develop tools to generate ns-3 scripts in Python or C++ automatically from NSTL model descriptions.

A 3-center comparison of 1-year mortality outcomes between transcatheter aortic valve implantation and surgical aortic valve replacement on the basis of propensity score matching among intermediate-risk surgical patients

This study sought to compare all-cause mortality in patients at intermediate surgical risk undergoing transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR).

Change mechanisms of schema-centered group psychotherapy with personality disorder patients

Background This study addressed the temporal properties of personality disorders and their treatment by schema-centered group psychotherapy. It investigated the change mechanisms of psychotherapy using a novel method by which psychotherapy can be modeled explicitly in the temporal domain. Methodology and Findings 69 patients were assigned to a specific schema-centered behavioral group psychotherapy, 26 to social skills training as a control condition. The largest diagnostic subgroups were narcissistic and borderline personality disorder. Both treatments offered 30 group sessions of 100 min duration each, at a frequency of two sessions per week. Therapy process was described by components resulting from principal component analysis of patients' session-reports that were obtained after each session. These patient-assessed components were Clarification, Bond, Rejection, and Emotional Activation. The statistical approach focused on time-lagged associations of components using time-series panel analysis. This method provided a detailed quantitative representation of therapy process. It was found that Clarification played a core role in schema-centered psychotherapy, reducing rejection and regulating the emotion of patients. This was also a change mechanism linked to therapy outcome. Conclusions/Significance The introduced process-oriented methodology allowed to highlight the mechanisms by which psychotherapeutic treatment became effective. Additionally, process models depicted the actual patterns that differentiated specific diagnostic subgroups. Time-series analysis explores Granger causality, a non-experimental approximation of causality based on temporal sequences. This methodology, resting upon naturalistic data, can explicate mechanisms of action in psychotherapy research and illustrate the temporal patterns underlying personality disorders.