Search results for "Cognition"
showing 10 items of 7054 documents
Defining classifier regions for WSD ensembles using word space features
2006
Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…
Betweenness Centrality for Networks with Non-Overlapping Community Structure
2018
Evaluating the centrality of nodes in complex networks is one of the major research topics being explored due to its wide range of applications. Among the various measures that have been developed over the years, Betweenness centrality is one of the most popular. Indeed, it has proved to be efficient in many real-world situations. In this paper, we propose an extension of the Betweenness centrality designed for networks with nonoverlapping community structure. It is a linear combination of the so-called “local” and “global” Betweenness measures. The Local measure takes into account the influence of a node at the community level while the global measure depends only on the interactions betwe…
Building an Optimal WSD Ensemble Using Per-Word Selection of Best System
2006
In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method c…
Efficient Online Laplacian Eigenmap Computation for Dimensionality Reduction in Molecular Phylogeny via Optimisation on the Sphere
2019
Reconstructing the phylogeny of large groups of large divergent genomes remains a difficult problem to solve, whatever the methods considered. Methods based on distance matrices are blocked due to the calculation of these matrices that is impossible in practice, when Bayesian inference or maximum likelihood methods presuppose multiple alignment of the genomes, which is itself difficult to achieve if precision is required. In this paper, we propose to calculate new distances for randomly selected couples of species over iterations, and then to map the biological sequences in a space of small dimension based on the partial knowledge of this genome similarity matrix. This mapping is then used …
genuMet: distinguish genuine untargeted metabolic features without quality control samples
2019
AbstractMotivationLarge-scale untargeted metabolomics experiments lead to detection of thousands of novel metabolic features as well as false positive artifacts. With the incorporation of pooled QC samples and corresponding bioinformatics algorithms, those measurement artifacts can be well quality controlled. However, it is impracticable for all the studies to apply such experimental design.ResultsWe introduce a post-alignment quality control method called genuMet, which is solely based on injection order of biological samples to identify potential false metabolic features. In terms of the missing pattern of metabolic signals, genuMet can reach over 95% true negative rate and 85% true posit…
An optimal population code for global motion estimation in local direction-selective cells
2021
AbstractNervous systems allocate computational resources to match stimulus statistics. However, the physical information that needs to be processed depends on the animal’s own behavior. For example, visual motion patterns induced by self-motion provide essential information for navigation. How behavioral constraints affect neural processing is not known. Here we show that, at the population level, local direction-selective T4/T5 neurons in Drosophila represent optic flow fields generated by self-motion, reminiscent to a population code in retinal ganglion cells in vertebrates. Whereas in vertebrates four different cell types encode different optic flow fields, the four uniformly tuned T4/T5…
Genome Wide Association Scan identifies new variants associated with a cognitive predictor of dyslexia
2018
AbstractDevelopmental dyslexia (DD) is one of the most prevalent learning disorders among children and is characterized by deficits in different cognitive skills, including reading, spelling, short term memory and others. To help unravel the genetic basis of these skills, we conducted a Genome Wide Association Study (GWAS), including nine cohorts of reading-impaired and typically developing children of European ancestry, recruited across different countries (N=2,562-3,468).We observed a genome-wide significant effect (p<1×10−8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2 withinMIR924HG (micro-RNA 924 host gene;p= 4.73×10−9), and a suggestive association on 8q1…
Musicianship can be decoded from magnetic resonance images
2020
AbstractLearning induces structural changes in the brain. Especially repeated, long-term behaviors, such as extensive training of playing a musical instrument, are likely to produce characteristic features to brain structure. However, it is not clear to what extent such structural features can be extracted from magnetic resonance images of the brain. Here we show that it is possible to predict whether a person is a musician or a non-musician based on the thickness of the cerebral cortex measured at 148 brain regions en-compassing the whole cortex. Using a supervised machine-learning technique, we achieved a significant (κ = 0.321, p < 0.001) agreement between the actual and predicted par…
How the country-of-origin impacts wine traders’ mental representation about wines: A study in a world wine trade fair
2020
Using data collected at a world wine trade fair, we study how the country-of-origin impacts wine traders’ mental representation about wines. In the analysis we use traditional exporters in Old (France) and New (Argentina) world wine countries in comparison to non-traditional exporters in Old (Switzerland) and New (Brazil) world wine countries. Three main findings are reported. First, the country-of-origin of wines was more important on guiding participants’ representations, than the category of countries the traders came from. Second, participants’ evocations were more precise and specific for traditional wine-exporting countries than for less traditional wine exporting countries. Finally, …
Enhancing daily living skills in four adults with autism spectrum disorder through an embodied digital technology-mediated intervention
2019
Abstract Background The acquisition of daily living skills is fundamental in the education of people with Autism Spectrum Disorder (ASD), especially of those with Intellectual Disability (ID), because this can significantly contribute to their autonomy, self-confidence and overall life satisfaction. The purpose of this study was to assess the impact of an embodied Digital Technology (DT)-mediated intervention, compared to a Treatment-As-Usual (TAU) intervention, for enhancing two daily living skills: washing dishes and doing laundry. Method Four males of between 25 and 37 years old with ASD and ID participated in the study. The two interventions were based on audio and picture prompting ins…