Browsing by Author "Béjar Alonso, Javier"
Now showing items 1-20 of 31
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A visual embedding for the unsupervised extraction of abstract semantics
(2017-05-01)
Article
Open AccessVector-space word representations obtained from neural network models have been shown to enable semantic operations based on vector arithmetic. In this paper, we explore the existence of similar information on vector ... -
An approach to gait analysis from human-rollator interaction: the i-Walker
(Ios Press, 2018)
Conference report
Open AccessFalls are one of the main causes of injury and injury-related deaths in the older demographic sector. During the last decade, several solutions have been proposed for fall detection or prevention, but also to assist old ... -
Aprendizaje autómatico
(Asociación de Técnicos de Informática, 1998-01)
Article
Open Access -
APRENENTATGE (Examen 1r quadrim.)
(Universitat Politècnica de Catalunya, 2002-01-23)
Exam
Restricted access to the UPC academic community -
Automatic classification of gait patterns using a smart rollator and the BOSS model
(Association for Computing Machinery (ACM), 2018)
Conference lecture
Open AccessNowadays, the risk of falling in older adults is a major concern due to the severe consequences it brings to socio-economic and public health systems. Some pathologies cause mobility problems in the aged population, leading ... -
Collaboration between human and artificial societies
(1997-09)
External research report
Open AccessThis research report is a preliminary publication of the proceedings of the European VIM project Workshop on Collaboration between Human and Artificial Societies, hold in Lanjaron (Granada), Spain, in May 1-3, . The report ... -
Deep learning is blowing in the wind. Deep models applied to wind prediction at turbine level
(Institute of Physics (IOP), 2019)
Conference report
Open AccessWind Energy generation depends on the existence of wind, a meteorological phenomena intermittent by nature, with the consequence of generating uncertainty on the availability of wind energy in the future. The grid stability ... -
Discovery of spatio-temporal patterns from location based social networks
(IOS Press, 2014)
Conference report
Restricted access - publisher's policyLocation Based Social Networks (LBSN) have become an interesting source for mining user behavior. These networks (e.g. Twitter, Instagram or Foursquare) collect spatio-temporal data from users in a way that they can be ... -
Discovery of spatio-temporal patterns from location-based social networks
(2015-07-20)
Article
Open AccessLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior. These networks collect data from users in such a way that they can be seen as a set of collective and ... -
“Dust in the wind...”, deep learning application to wind energy time series forecasting
(2019-06-21)
Article
Open AccessTo balance electricity production and demand, it is required to use different prediction techniques extensively. Renewable energy, due to its intermittency, increases the complexity and uncertainty of forecasting, and the ... -
Extracting user spatio-temporal profiles from location based social networks
(2014-11-14)
External research report
Open AccessLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior. These social network provide a low rate sampling of user's location information during large intervals ... -
Forecastability measures that describe the complexity of a site for deep learning wind predictions
(2021-05-29)
Article
Open AccessThe application of deep learning to wind time series for multi-step prediction obtains good results at short horizons. The accuracy of a wind forecast is highly dependent on the specific structure of wind in the specific ... -
Go with the flow: Recurrent networks for wind time series multi-step forecasting
(IOS Press, 2018)
Conference report
Open AccessOne of the ways of reducing the effects of Climate Change is to rely on renewable energy sources. Their intermittent nature makes necessary to obtain a mid-long term accurate forecasting. Wind Energy prediction is based ... -
Intersegmental synchronization of spontaneous cord dorsum potentials as a clinical parameter to evaluate changes in neuronal connectivity produced by peripheral nerve and spinal cord damage
(Springer, 2012)
Conference report
Restricted access - publisher's policyWe describe here automatic selection method to retrieve spontaneous cord dorsum potentials from the spiral cord in the anesthetized cat. Previous studies have indicated that some of these potentials appear synchronized in ... -
K-means vs Mini Batch K-means: a comparison
(2013-05-17)
External research report
Open AccessMini Batch K-means (cite{Sculley2010}) has been proposed as an alternative to the K-means algorithm for clustering massive datasets. The advantage of this algorithm is to reduce the computational cost by not using all the ... -
Kernel alignment for identifying objective criteria from brain MEG recordings in schizophrenia
(Elsevier, 2016-08-02)
Article
Open AccessThe current wide access to data from different neuroimaging techniques has permitted to obtain data to explore the possibility of finding objective criteria that can be used for diagnostic purposes. In order to decide which ... -
LINNEO+: a classification methodology for ill-structured domains
(1993-04)
External research report
Open AccessIn this work we present a methodology oriented to domains with a weak structure (ill-domains) for, using inductive conceptual learning techniques (descriptive generalization) and classification, discover concepts through ... -
Markovian analysis of the sequential behavior of the spontaneous spinal cord dorsum potentials induced by acute nociceptive stimulation in the anesthetized cat
(2017-05-01)
Article
Open AccessIn a previous study we developed a Machine Learning procedure for the automatic identification and classification of spontaneous cord dorsum potentials (CDPs). This study further supported the proposal that in the anesthetized ... -
Mining frequent spatio-temporal patterns from location based social networks
(2014-10-09)
External research report
Open AccessLocation Based Social Networks (LBSN) like Twitter or Instagram are a good source for user spatio-temporal behavior. These social network provide a low rate sampling of user's location information during large intervals ...
