Recent Submissions

  • Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns 

    König, Caroline; Alquézar Mancho, René; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (2014-10-23)
    Article
    Open Access
    G protein-coupled receptors (GPCRs) are a large and heterogeneous superfamily of receptors that are key cell players for their role as extracellular signal transmitters. Class C GPCRs, in particular, are of great interest ...
  • Predicting fecal sources in waters with diverse pollution loads using general and molecular host-specific indicators and applying machine learning methods 

    Casanovas Massana, Arnau; Gómez Doñate, Marta; Sánchez, David; Belanche Muñoz, Luis Antonio; Muniesa, Maite; Blanch, Anicet R. (2015-03-15)
    Article
    Restricted access - publisher's policy
    In this study we use a machine learning software (Ichnaea) to generate predictive models for water samples with different concentrations of fecal contamination (point source, moderate and low). We applied several MST methods ...
  • Visual interpretation of class C GPCR subtype overlapping from the nonlinear mapping of transformed primary sequences 

    Cárdenas Dominguez, Martha Ivón; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Conference report
    Restricted access - publisher's policy
    This brief paper addresses the problem of visually assessing the natural discriminability of the different subtypes that characterize class C G-Protein-Coupled Receptors, which are membrane proteins of interest in pharmacology, ...
  • Assessment of electrocardiograms with pretraining and shallow networks 

    Ribas Ripoll, Vicent; Wojdel, Anna; Ramos, Pablo; Romero Merino, Enrique; Brugada Terradellas, Josep (Computing in Cardiology, 2014)
    Conference report
    Open Access
    Objective: Clinical Decision Support Systems normally resort to annotated signals for the automatic assessment of ECG signals. In this paper we put forward a new method for the assessment of normal/abnormal heart function ...
  • Using the Fuzzy Inductive Reasoning methodology to improve coherence in algorithmic musical beat patterns 

    Paz Ortiz, Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique (IOS Press, 2014-10-23)
    Part of book or chapter of book
    Open Access
    In the present work, the Fuzzy Inductive Reasoning methodology (FIR) is used to improve coherence among beat patterns, structured in a musical A-B form. Patterns were generated based on a probability matrix, encoding a ...
  • Stopping criteria in contrastive divergence: Alternatives to the reconstruction error 

    Buchaca, David; Romero Merino, Enrique; Mazzanti Castrillejo, Fernando Pablo; Delgado Pin, Jordi (2014)
    Conference report
    Open Access
    Restricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an ...
  • Fuzzy models: Easier to understand and an easier way to handle uncertainties in climate change research 

    Gay García, Carlos; Sánchez Meneses, Oscar; Martínez-López, Benjamín; Nebot Castells, M. Àngela; Estrada, Francisco (2014)
    Part of book or chapter of book
    Restricted access - publisher's policy
    Greenhouse gas emission scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change when converted to concentrations and atmospheric temperatures through the use of climate models result in a wide ...
  • Small-particle pollution modeling using fuzzy approaches 

    Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2014)
    Part of book or chapter of book
    Restricted access - publisher's policy
    Air pollution caused by small particles is a major public health problem in many cities of the world. One of the most contaminated cities is Mexico City. The fact that it is located in a volcanic crater surrounded by ...
  • PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques 

    Escobet Canal, Antoni; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2014-08)
    Article
    Open Access
    In this work, a fault diagnosis methodology termed VisualBlock-Fuzzy Inductive Reasoning, i.e. VisualBlock-FIR, based on fuzzy and pattern recognition approaches is presented and applied to PEM fuel cell power systems. The ...
  • Developing professional skills at tertiary level: A model to integrate competencies across the curriculum 

    Sánchez Carracedo, Fermín; Soler Cervera, Antonia; López Álvarez, David; Martín Escofet, Carme; Ageno Pulido, Alicia; Belanche Muñoz, Luis Antonio; Cabré Garcia, José M.; Cobo Valeri, Erik; Farré Cirera, Rafael; García Almiñana, Jordi; Marès Martí, Pere (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Conference report
    Open Access
    In the context of the European Higher Education Area, curriculum design needs to be based on the defined competencies of each degree programs, including both domain specific and professional competencies. In this educational ...

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