The Latest Word, Summer 2012

Newsletter by IPERS about Iowa Public Employees’ Retirement System news for retirees.

Guia per convertir documents Microsoft Word 2003 i 2007 a PDF

Aquest document mostra el procés de transformació d'un arxiu de Microsoft Word a un document PDF de la forma més accessible possible.

Guia de Microsoft Word 2003

Aquest document és una guia de recomanacions per crear contingut accessible amb el programa Microsoft Word 2003.

Guia de Microsoft Word 2007

Aquest document és una guia de recomanacions per crear contingut accessible amb el programa Microsoft Word 2007.

The Latest Word, Summer 2014

Newsletter by IPERS about Iowa Public Employees’ Retirement System news for retirees.

The Latest Word, Spring 2014

Newsletter by IPERS about Iowa Public Employees’ Retirement System news for retirees.

The Latest Word, Fall 2014

Newsletter by IPERS about Iowa Public Employees’ Retirement System news for retirees.

EsPal: One-stop shopping for Spanish word properties

This article introduces EsPal: a Web-accessible repository containing a comprehensive set of properties of Spanish words. EsPal is based on an extensible set of data sources, beginning with a 300 million token written database and a 460 million token subtitle database. Properties available include word frequency, orthographic structure and neighborhoods, phonological structure and neighborhoods, and subjective ratings such as imageability. Subword structure properties are also available in terms of bigrams and trigrams, bi-phones, and bi-syllables. Lemma and part-of-speech information and their corresponding frequencies are also indexed. The website enables users to either upload a set of words to receive their properties, or to receive a set of words matching constraints on the properties. The properties themselves are easily extensible and will be added over time as they become available. It is freely available from the following website: http://www.bcbl.eu/databases/espal

Taking on new challenges in multi-word unit processing for Machine Translation

This paper discusses the qualitativecomparative evaluation performed on theresults of two machine translation systemswith different approaches to the processing ofmulti-word units. It proposes a solution forovercoming the difficulties multi-word unitspresent to machine translation by adopting amethodology that combines the lexicongrammar approach with OpenLogos ontologyand semantico-syntactic rules. The paper alsodiscusses the importance of a qualitativeevaluation metrics to correctly evaluate theperformance of machine translation engineswith regards to multi-word units.

Guia de Microsoft Word 2003

Aquesta guia és una introducció a la creació de documents digitals accessibles amb el processador de textos Microsoft Word 2003.

Guia de Microsoft Word 2007

Aquesta guia és una introducció a la creació de documents digitals accessibles amb el processador de textos Microsoft Word 2007.

Guia per convertir documents Microsoft Word 2003 i 2007 a PDF

Aquesta guia explica com convertir documents Microsoft Word 2003 i 2007 a documents PDF.

Decoding auditory EEG responses in healthy and clinical populations: A comparative study.

BACKGROUND: Analyses of brain responses to external stimuli are typically based on the means computed across conditions. However in many cognitive and clinical applications, taking into account their variability across trials has turned out to be statistically more sensitive than comparing their means. NEW METHOD: In this study we present a novel implementation of a single-trial topographic analysis (STTA) for discriminating auditory evoked potentials at predefined time-windows. This analysis has been previously introduced for extracting spatio-temporal features at the level of the whole neural response. Adapting the STTA on specific time windows is an essential step for comparing its performance to other time-window based algorithms. RESULTS: We analyzed responses to standard vs. deviant sounds and showed that the new implementation of the STTA gives above-chance decoding results in all subjects (in comparison to 7 out of 11 with the original method). In comatose patients, the improvement of the decoding performance was even more pronounced than in healthy controls and doubled the number of significant results. COMPARISON WITH EXISTING METHOD(S): We compared the results obtained with the new STTA to those based on a logistic regression in healthy controls and patients. We showed that the first of these two comparisons provided a better performance of the logistic regression; however only the new STTA provided significant results in comatose patients at group level. CONCLUSIONS: Our results provide quantitative evidence that a systematic investigation of the accuracy of established methods in normal and clinical population is an essential step for optimizing decoding performance.

Quantifying the time for accurate EEG decoding of single value-based decisions.

BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.