La credibilitat de les webs i els mecanismes d'avaluació

Internet va creixent i pot implicar que no sempre es garanteixi la qualitat de continguts. Aquest treball planteja veure com els individus usen una sèrie de mètodes (o etnomètodes) (Garfinkel, 1968), que poden ser més o menys sistemàtics, o més o menys informals, i que fan servir per a trobar la informació més vàlida. Gràcies a aquests mètodes, els individus quotidianament avaluen la credibilitat de les pàgines web.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Power transformations in correspondence analysis

Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.

Impacte d'un programa d'activitat física basat en el mètode Klapp i Stretching Global Actiu sobre la postura de persones adultes amb escoliosi idiopàtica

La simetria entre espatlles i l’alçada de les dues crestes ilíaques es perd quan es pateix escoliosi. Aquest empitjorament de la bona postura té conseqüències negatives per a la salut, especialment en el sistema musculoesquelètic. L’objecte principal d’aquest treball és avaluar l’impacte d’un programa d’activitat física basat en la combinació dels mètodes “Klapp” i l’“Stretching Global Actiu” sobre la postura en bipedestació de persones adultes que pateixen escoliosi idiopàtica. L’aplicació d’ambdós mètodes de forma individual no obtenen millores en aquests paràmetres en persones adultes, però en canvi en nens i nenes sí. El treball és un estudi experimental en el qual es va assignar un subjecte al grup intervenció i un subjecte al grup control. El subjecte del grup intervenció va realitzar un programa de 20 sessions de 45 – 60 minuts de treball amb aquests dos mètodes de treball físic. El subjecte del grup control va seguir la seva activitat habitual. Abans i després de la intervenció, es varen mesurar les variables dependents principals i secundaries respectivament. Els resultats obtinguts han revelat una petita millora en la simetria de les espatlles (+0,2 cms.) en el grup intervenció però no en la simetria de l’altura de les crestes ilíaques. El grup control no ha presentat canvis. Per tant, podem dir que és útil utilitzar la combinació dels dos mètodes físics per a millorar la postura en persones adultes que pateixen escoliosi idiopàtica.

Post-Nonlinear Mixtures and Beyond

Although sources in general nonlinear mixturm arc not separable iising only statistical independence, a special and realistic case of nonlinear mixtnres, the post nonlinear (PNL) mixture is separable choosing a suited separating system. Then, a natural approach is based on the estimation of tho separating Bystem parameters by minimizing an indcpendence criterion, like estimated mwce mutual information. This class of methods requires higher (than 2) order statistics, and cannot separate Gaarsian sources. However, use of [weak) prior, like source temporal correlation or nonstationarity, leads to other source separation Jgw rithms, which are able to separate Gaussian sourra, and can even, for a few of them, works with second-order statistics. Recently, modeling time correlated s011rces by Markov models, we propose vcry efficient algorithms hmed on minimization of the conditional mutual information. Currently, using the prior of temporally correlated sources, we investigate the fesihility of inverting PNL mixtures with non-bijectiw non-liacarities, like quadratic functions. In this paper, we review the main ICA and BSS results for riunlinear mixtures, present PNL models and algorithms, and finish with advanced resutts using temporally correlated snu~sm