Programa de Doctorat en Tecnologies de la Informació i les Comunicacions: Envíos recientes
Mostrando ítems 1-20 de 389
Normalizing flows for neuroimaging research
Psychotic disorders are characterized by poorly understood pathophysiological mechanisms, with a remarkable heterogeneity among patients, both cross-sectionally and longitudinally. This results in a lack of definitive ...
Cinematic volume rendering solutions for the advanced exploration of medical images
Medical visualization, commonly used in clinical routine for exploring cardiac data, is based on traditional techniques including multiplanar reformations, maximum intensity projection, and volume rendering that rely ...
Contributions to fully homomorphic encryption
In recent years, the field of Fully Homomorphic Encryption (FHE) has become one of the main pilars for privacy-preserving technologies. However, many challenges still remain to be tackled before this technology can be ...
Promoting socio-emotional interactions and regulation in computer supported collaborative learning: design, implementation and evaluation of technology features and affordances to facilitate the socio-emotional side of CSCL
This thesis, a compendium of publications, aims at contributing knowledge to better design CSCL tools for promoting socioemotional interactions and regulation. We started with a field study in which we observed groups ...
Beyond the spectrum: prosodic, noise-enhanced and self-supervised features for speech recognition
This dissertation investigates three methods for improving speech recognition in challenging conditions, focusing on feature enhancement and extending beyond spectral features. First, it demonstrates that incorporating ...
Blockchains in the real world: an interdisciplinary perspective on enchancing security and adoption
This thesis investigates the complex nature of the blockchain ecosystem, where technology, law, and economics intersect across layers and applications. By offering an interdisciplinary perspective on blockchains, we seek ...
Characterization of left atrial hemodynamics with 4D flow magnetic resonance imaging, in-silico models and deep learning
Although the left ventricle has traditionally held the spotlight as the primary determinant of cardiovascular disease prognosis, the characterization of left atrial hemodynamics is increasingly being recognized as a ...
Large scale off-policy and offline learning
Reinforcement Learning (RL), a subfield of machine learning and artifical intelligence, is a learning paradigm where an artificial agent learns to reach a predefined goal by trying to maximize a reward signal while ...
Prediction of mental health crises based on electronic health records: probabilistic and machine learning models for clinical applications
This thesis delves into the transformative potential of Electronic Health Records and Machine Learning in the prevention of mental health crisis relapses. Our work focuses on the prediction of these relapses throughout the ...
Toward a new model of borderline personality disorder: a psychophysiological approach on the link between emotional and behavioural dysregulation
Borderline personality disorder (BPD) is one of the most studied personality disorders, given its prevalence and the severity of its symptoms. In the last years, several models of the disorder were presented, however, no ...
The role of conflict in perception: case studies in binocular rivalry, cinema and flavour
Our everyday perception of the world is remarkably unambiguous, considering that it stems from a multitude of ambiguous sensory signals. This feat is believed to be achieved by a set of perceptual and cognitive mechanisms ...
A journey in representation learning textual emotion detection and structural graph encodings
Representation learning is the field of modern machine learning focused on automatically producing useful representations from data. This thesis studies the impact of data volumes, annotation perspectives, and structural ...
Computational analysis of fetal brain development with patient-specific modelling and deep learning techniques
This dissertation presents a novel computational pipeline for creating patient-specific models of brain development. Initially, the human brain develops from a smooth to a convoluted cortical surface, with abnormal ...
Computer-supported scripting mechanisms to support adolescents' development of social media self-protection skills
In recent years, there's been increasing concern over potential negative experiences for adolescents on social media. Despite efforts in social media literacy education, traditional approaches often neglect crucial ...
The Role of inhibitory plasticity in the formation and the long-term maintenance of neural assemblies and memories
Brain circuits display modular architecture at different scales of organization. Such neural assemblies are typically associated to functional specialization that favours both the segregation and the integration of ...
The Functional role of theta oscillations in visual working memory performance
Oscillations at theta frequency (4-7 Hz) have been hypothesized to play an important functional role in brain processes associated to working memory. In this thesis, I investigate how the systematic manipulation of different ...
Phase-based signal analysis measures applied to electroencephalographic recordings from epilepsy patients
This thesis presents new phase-based signal analysis techniques to study brain dynamics from patients with pharmacoresistant focalonset epilepsy. We analyze electroencephalographic (EEG) recordings from seizure and ...
Motivation-driven mechanics in computer-supported collaborative learning scripts
This dissertation explores motivation within Collaborative Learning Flow Patterns (CLFP), focusing on the Pyramid CLFP. It investigates how incorporating game mechanics (GM) can foster both intrinsic and extrinsic motivation ...
Mechano-biochemical systems modelling for patient stratification in osteoarthritis
This doctoral thesis presents two different computational approaches to explore mechanistically chondrocyte dysregulation and identify biomarkers, to better understand patient stratification systems in primary knee ...
A Comprehensive study of arithmetic circuits and elliptic curves for efficient and scalable zero-knowledge proof systems
In recent years, zero-knowledge proofs have come to play a crucial role in distributed systems where there is no trust between the parties involved. Most popular proof systems are for the NP-complete language of arithmetic ...
