Search results for "Machine learning"
showing 10 items of 1464 documents
Selection Task and Computer-Based Feedback to Improve the Searching Process in Task-Oriented Reading Situations
2015
Adaptive feedback has showed to be effective to enhance strategic reading behaviors and performance in task-oriented reading situations, but it is difficult to be implemented in classroom environments. Computer-based systems allow overcoming these challenges. We conducted an experiment in which secondary-school students read two texts, answered comprehension questions and selected relevant text information while receiving automatic feedback about selection accuracy and performance. Two experimental conditions were designed to assess the effects of feedback and selection attempts. Then, students perform a transfer task without any of these elements. We found that one-attempt and two-attempt …
MAVIE-Lab Sports: a mHealth for Injury Prevention and Risk Management in Sport
2018
International audience; Smart-phones technology and the development of mHealth (Mobile Health) applications offer an opportunity to design intervention tools to influence health behavior changes. The MAVIE-Lab is a mHealth application including a DSS (Desicion Support System) to assist in the personalized evaluation of HLIs (Home, Leisure and Sport Injuries) risk and to promote the adoption of prevention measures. MAVIE-Lab Sports will be the first module of the mobile application. The purpose of this PhD project is to improve a particular module of MAVIE-Lab, devoted to sports (MAVIE-Lab Sports), in different aspects: statistical modeling, design and ergonomics. It also aims to evaluate sy…
The extensive and intensive margins of Spanish trade
2011
Recent empirical research highlights that differences in trade flows across countries, products and years are governed by two margins: the intensive margin and the extensive margin. The analysis of the relative contribution of each margin is very important to determine which policies can be more efficient to foster trade at the aggregate, geographic, product or firm level. We use the whole universe of firm level transaction data to analyse the relative contribution of these margins to changes in Spanish trade flows during the 1997–2007 period. We first apply the methodology proposed by Bernard et al. (2009) to decompose trade variation over time into three components: net entry of firms, pr…
An adaptive approach to learning the preferences of users in a social network using weak estimators
2012
Published version of an article in the journal: Journal of Information Processing Systems. Also available from the publisher at: http://dx.doi.org/10.3745/JIPS.2012.8.2.191 - Open Access Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked i…
Computer-Aided Diagnosis for Prostate Cancer using Multi-Parametric Magnetic Resonance Imaging
2016
Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world.CaP growth is characterized by two main types of evolution: (i) the slow-growing tumours progress slowly and usually remain confined to the prostate gland; (ii) the fast-growing tumours metastasize from prostate gland to other organs, which might lead to incurable diseases.Therefore, early diagnosis and risk assessment play major roles in patient treatment and follow-up.In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexit…
Getting Docking into Shape Using Negative Image-Based Rescoring
2019
The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the molecular docking algorithms used in the structure-based drug discovery. To remedy this problem, elaborate rescoring and post-processing schemes have been developed with a varying degree of success, specificity, and cost. The negative imagebased rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets.The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein’s ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is dir…
Experimental Evaluation of Protein Secondary Structure Predictors
2009
Understanding protein biological function is a key issue in modern biology, which is largely determined by its 3D shape. Protein 3D shape, in its turn, is functionally implied by its amino acid sequence. Since the direct inspection of such 3D structures is rather expensive and time consuming, a number of software techniques have been developed in the last few years that predict a spatial model, either of the secondary or of the tertiary form, for a given target protein starting from its amino acid sequence. This paper offers a comparison of several available automatic secondary structure prediction tools. The comparison is of the experimental kind, where two relevant sets of proteins, a non…
Identification of Trans-Golgi Network Proteins in Arabidopsis thaliana Root Tissue
2014
Knowledge of protein subcellular localization assists in the elucidation of protein function and understanding of different biological mechanisms that occur at discrete subcellular niches. Organelle-centric proteomics enables localization of thousands of proteins simultaneously. Although such techniques have successfully allowed organelle protein catalogues to be achieved, they rely on the purification or significant enrichment of the organelle of interest, which is not achievable for many organelles. Incomplete separation of organelles leads to false discoveries, with erroneous assignments. Proteomics methods that measure the distribution patterns of specific organelle markers along densit…
A Proposed Knowledge Based Approach for Solving Proteomics Issues
2010
In this paper we present a novel knowledge-based approach that aims at helping scientists to face and resolve a large number of proteomics problem. The system architecture is based on an ontology to model the knowledge base, a reasoner that starting from the user's request and a set of rules builds the workflow of tasks to be done, and an executor that runs the algorithms and software scheduled by the reasoner. The system can interact with the user showing him intermediate results and several options in order to refine the workflow and supporting him to choose among different forks. Thanks to the presence of the knowledge base and the modularity provided by the ontology, the system can be e…
Design of a Neural Network Model as a Decision Making Aid in Renal Transplant
2004
This paper presents the application of this new tool of data processing in the study of the problem that arises when a renal transplant is indicated for a paediatric patient. Its aim is the development and validation of a neural network based model which can predict the success of the transplant over the short, medium and long term, using pre-operative characteristics of the patient (recipient) and implant organ (donor). When compared to results of logistic regression, the results of the proposed model showed better performance. Once the model is obtained, it will be converted into a tool for predicting the efficiency of the transplant protocol in order to optimise the donor-recipient pair …