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Now showing items 29017-29036 of 45129
"M'agenollo en el fons de la meva paraula". La religiositat de Màrius Torres: del llegat espiritista a l'elaboració d'una poesia i un pensament propi
L’objectiu general d’aquesta tesi és contribuir a omplir el buit bibliogràfic que existeix al voltant de la religiositat de Màrius Torres (1910-1942). La primera part està dedicada als seus antecedents religiosos. Es ...
m-RESIST: Atención Terapéutica Móvil para la Esquizofrenia Resistente al Tratamiento Estudio prospectivo multicéntrico de viabilidad y aceptabilidad
A la Unió Europea, entre el 0,2 i el 2,6% de la població té un diagnòstic de trastorn psicòtic. Malgrat els avenços en el tractament farmacològic, al voltant del 40% de les persones amb diagnòstic d’esquizofrènia és resistent ...
MAC design and analysis for MU-MIMO and full-duplex enabled wireless networks
IEEE 802.11 based wireless networks, especially the infrastructure based Wireless Local Area Networks (WLANs) or Wi-Fi networks, are hugely successful, and have become an indispensable part of our life at homes and working ...
Mac-Phy Cross-Layer analysis and design of Mimo-Ofdm Wlans based on fast link adaptation
The latestWLAN standard, known as IEEE 802.11n, has notably increased the network capacity with respect to its predecessors thanks to the incorporation of the multipleinput multiple-output (MIMO) technology. Nonetheless, ...
Machine learning algorithms for 5G optical networks
(English) Throughout this thesis we addressed 5G network challenges. The non-coherent optical modulation tradeoff has been addressed, as we proposed FBMC and artificial intelligence-based schemes. The proposed schemes ...
Machine learning and deep neural networks approach to modelling musical gestures
Gestures can be defined as a form of non-verbal communication associated with an intention or an emotional state articulation. They are not only intrinsically part of the human language, but also explain specific details ...
A machine learning approach to computer modeling of musical expression for performance learning and practice
Aquesta tesi tracta sobre el disseny i la implementació de sistemes informàtics per a l'execució musical expressiva (CSEMP), explorant diferents mètodes de l'aprenentatge automàtic i reflexionant sobre el paper de l'estructura ...
Machine learning approach to the study of chromatin
Des de l’aparició de les tecnologies de seqüenciació d’alt rendiment, els conjunts de dades biològiques han esdevingut cada cop més grans i complexes, la qual cosa els fa pràcticament impossibles d’interpretar manualment. ...
Machine Learning Approaches for Comprehensive Analysis of Population Cancer Registry Data
Els registres de càncer basats poblacionals són crucials per controlar i estudiar la incidència, mortalitat i supervivència del càncer. A més, explorar fonts d'informació externes per complementar aquests registres permet ...
Machine learning assisted QoT estimation for optical networks optimization
The tremendous increase in data traffic has spurred a rapid evolution of the optical networks for a reliable, affordable, cost effective and scalable network infrastructure. To meet some of these requirements, network ...
A machine learning based methodology for anomaly detection in dam behaviour
Dam behaviour is difficult to predict with high accuracy. Numerical models for structural calculation solve the equations of continuum mechanics, but are subject to considerable uncertainty as to the characterisation of ...
Machine learning for aircraft trajectory prediction: a solution for pre-tactical air traffic flow management
(English) The goal of air traffic flow and capacity management (ATFCM) is to ensure that airport and airspace capacity meet traffic demand while optimising traffic flows to avoid exceeding the available capacity when it ...
Machine Learning for predicting Immunotherapy response from routine Medical Imaging
[eng] HYPOTHESIS: Precision oncology has revolutionized the landscape of cancer treatment. Emerging therapeu- tic approaches, such as immunotherapy or anti-angiogenic agents, have exhibited remarkable outcomes in solid ...
Machine learning for quantum physics and quantum physics for machine learning
Research at the intersection of machine learning (ML) and quantum physics is a recent growing field due to the enormous expectations and the success of both fields. ML is arguably one of the most promising technologies ...
Machine learning in multiscale modeling and simulations of molecular systems
Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. ...
Machine learning in structural biology and chemoinformatics : Driving drug discovery one epoch at a time
Deep learning approaches have become increasingly popular in the last years thanks to their state-of the-art performance in fields such as computer vision and natural language understanding. The first goal of this thesis ...
Machine learning methods for predicting days to discharge in Intensive Care Units patients
Les UCI donen atenció especialitzada per a pacients crítics, amb monitorització constant i equips d'atenció mèdica dedicats fins a la seva estabilitat per ser traslladats o donats d'alta. Una planificació inadequada pot ...
Machine learning methods for the analysis of liquid chromatography-mass spectrometry datasets in metabolomics
Liquid Chromatography-Mass Spectrometry (LC/MS) instruments are widely used in Metabolomics. To analyse their output, it is necessary to use computational tools and algorithms to extract meaningful biological information. ...
Machine learning methods for the characterization and classification of complex data
This thesis work presents novel methods for the analysis and classification of medical images and, more generally, complex data. First, an unsupervised machine learning method is proposed to order anterior chamber OCT ...
Machine learning methods for understanding social media communication: modeling irony and emojis
In this dissertation we propose algorithms for the analysis of social media texts, focusing on two particular aspects: irony and emojis. We propose novel automatic systems, based on machine learning methods, able to recognize ...
