Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Compositional influence on the electrical performance of zinc indium tin oxide transparent thin-film transistors

In this work, zinc indium tin oxide layers with different compositions are used as the active layer of thin film transistors. This multicomponent transparent conductive oxide is gaining great interest due to its reduced content of the scarce indium element. Experimental data indicate that the incorporation of zinc promotes the creation of oxygen vacancies. In thin-film transistors this effect leads to a higher threshold voltage values. The field-effect mobility is also strongly degraded, probably due to coulomb scattering by ionized defects. A post deposition annealing in air reduces the density of oxygen vacancies and improves the fieldeffect mobility by orders of magnitude. Finally, the electrical characteristics of the fabricated thin-film transistors have been analyzed to estimate the density of states in the gap of the active layers. These measurements reveal a clear peak located at 0.3 eV from the conduction band edge that could be attributed to oxygen vacancies.

The Network Company in Catalonia : ICT, Productivity, Competitiveness, Salaries and Performance in Catalonia's Companies. Research report (synthesis document)

Resum en anglès del projecte de recerca L'empresa xarxa a Catalunya. TIC, productivitat, competitivitat, salaris i beneficis a l'empresa catalana té com a objectiu principal constatar que la consolidació d'un nou model estratègic, organitzatiu i d'activitat empresarial, vinculat amb la inversió i l'ús de les TIC (o empresa xarxa), modifica substancialment els patrons de comportament dels resultats empresarials, en especial la productivitat, la competitivitat, les retribucions dels treballadors i el benefici. La contrastació empírica de les hipòtesis de treball l'hem feta per mitjà de les dades d'una enquesta a una mostra representativa de 2.038 empreses catalanes. Amb la perspectiva de l'impacte de la inversió i l'ús de les TIC no s'aprecia una relació directa entre els processos d'innovació digital i els resultats de l'activitat de l'empresa catalana. En aquest sentit, hem hagut de segmentar el teixit productiu català per a buscar les organitzacions en què el procés de coinnovació tecnològica digital i organitzativa és més present i en què la intensitat de l'ús del coneixement és un recurs molt freqüent per a poder copsar impactes rellevants en els principals resultats empresarials. Això és així perquè l'economia catalana, avui, presenta una estructura productiva dual.

Weber's law in decision making: integrating behavioral data in humans with a neurophysiological model

Recent single-cell studies in monkeys (Romo et al., 2004) show that the activity of neurons in the ventral premotor cortex covaries with the animal's decisions in a perceptual comparison task regarding the frequency of vibrotactile events. The firing rate response of these neurons was dependent only on the frequency differences between the two applied vibrations, the sign of that difference being the determining factor for correct task performance. We present a biophysically realistic neurodynamical model that can account for the most relevant characteristics of this decision-making-related neural activity. One of the nontrivial predictions of this model is that Weber's law will underlie the perceptual discrimination behavior. We confirmed this prediction in behavioral tests of vibrotactile discrimination in humans and propose a computational explanation of perceptual discrimination that accounts naturally for the emergence of Weber's law. We conclude that the neurodynamical mechanisms and computational principles underlying the decision-making processes in this perceptual discrimination task are consistent with a fluctuation-driven scenario in a multistable regime.

Quality of Learners' Time and Learning Performance Beyond Quantitative Time-on-Task

Peer-reviewed

Lossless Image Data Embedding in Plain Areas

This letter presents a lossless data hiding scheme for digital images which uses an edge detector to locate plain areas for embedding. The proposed method takes advantage of the well-known gradient adjacent prediction utilized in image coding. In the suggested scheme, prediction errors and edge values are first computed and then, excluding the edge pixels, prediction error values are slightly modified through shifting the prediction errors to embed data. The aim of proposed scheme is to decrease the amount of modified pixels to improve transparency by keeping edge pixel values of the image. The experimental results have demonstrated that the proposed method is capable of hiding more secret data than the known techniques at the same PSNR, thus proving that using edge detector to locate plain areas for lossless data embedding can enhance the performance in terms of data embedding rate versus the PSNR of marked images with respect to original image.

Threading libraries performance when applied to image acquisition and processing in a forensic application

Peer-reviewed

A performance lower bound for quadratic timing recovery accounting for the symbol transition density

The symbol transition density in a digitally modulated signal affects the performance of practical synchronization schemes designed for timing recovery. This paper focuses on the derivation of simple performance limits for the estimation of the time delay of a noisy linearly modulated signal in the presence of various degrees of symbol correlation produced by the varioustransition densities in the symbol streams. The paper develops high- and low-signal-to-noise ratio (SNR) approximations of the so-called (Gaussian) unconditional Cramér–Rao bound (UCRB),as well as general expressions that are applicable in all ranges of SNR. The derived bounds are valid only for the class of quadratic, non-data-aided (NDA) timing recovery schemes. To illustrate the validity of the derived bounds, they are compared with the actual performance achieved by some well-known quadratic NDA timing recovery schemes. The impact of the symbol transitiondensity on the classical threshold effect present in NDA timing recovery schemes is also analyzed. Previous work on performancebounds for timing recovery from various authors is generalized and unified in this contribution.

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Aplicació per a la predicció automàtica de la data d'adquisició d'una imatge

En aquesta memòria es presenta un projecte que té com a objectiu principal la creació d'una aplicació que, donada una imatge d'entrada, retorni en quina dècada va ser adquirida la imatge. Apart es pretén millorar els resultats obtinguts en altres estudis sobre la classificació d'imatges segons la seva data d'adquisició. En la memòria s'explica l'estudi realitzat anteriorment sobre el tema i quin ha estat el mètode escollit per millorar els seus resultats. També s'explica com hem creat l'aplicació i els passos que segueix l'aplicació en la seva execució.

A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

A user-friendly web portal for T-Coffee on supercomputers

Background: Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers. Results: In this paper we show how PTC can be easily deployed and controlled on a super computer architecture using a web portal developed using Rapid. Rapid is a tool for efficiently generating standardized portlets for a wide range of applications and the approach described here is generic enough to be applied to other applications, or to deploy PTC on different HPC environments. Conclusions: The PTC portal allows users to upload a large number of sequences to be aligned by the parallel version of TC that cannot be aligned by a single machine due to memory and execution time constraints. The web portal provides a user-friendly solution.

The Impact of Catechol-O-Methyltransferase and Dopamine D4 Receptor Genotypes on Neurophysiological Markers of Performance Monitoring

Dynamic adaptations of one"s behavior by means of performance monitoring are a central function of the human executive system, that underlies considerable interindividual variation. Converging evidence from electrophysiological and neuroimaging studies in both animals and humans hints atthe importance ofthe dopaminergic system forthe regulation of performance monitoring. Here, we studied the impact of two polymorphisms affecting dopaminergic functioning in the prefrontal cortex [catechol-O-methyltransferase (COMT) Val108/158Met and dopamine D4 receptor (DRD4) single-nucleotide polymorphism (SNP)-521] on neurophysiological correlates of performance monitoring. We applied a modified version of a standard flanker task with an embedded stop-signal task to tap into the different functions involved, particularly error monitoring, conflict detection and inhibitory processes. Participants homozygous for the DRD4 T allele produced an increased error-related negativity after both choice errors and failed inhibitions compared with C-homozygotes. This was associated with pronounced compensatory behavior reflected in higher post-error slowing. No group differences were seen in the incompatibility N2, suggesting distinct effects of the DRD4 polymorphism on error monitoring processes. Additionally, participants homozygous for the COMTVal allele, with a thereby diminished prefrontal dopaminergic level, revealed increased prefrontal processing related to inhibitory functions, reflected in the enhanced stop-signal-related components N2 and P3a. The results extend previous findings from mainly behavioral and neuroimaging data on the relationship between dopaminergic genes and executive functions and present possible underlying mechanisms for the previously suggested association between these dopaminergic polymorphisms and psychiatric disorders as schizophrenia or attention deficit hyperactivity disorder.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Hippocampal Theta-Phase Modulation of Replay Correlates with Configural-Relational Short-Term Memory Performance

Thereis now growing evidencethatthe hippocampus generatestheta rhythmsthat can phase biasfast neural oscillationsinthe neocortex, allowing coordination of widespread fast oscillatory populations outside limbic areas. A recent magnetoencephalographic study showed that maintenance of configural-relational scene information in a delayed match-to-sample (DMS) task was associated with replay of that information during the delay period. The periodicity of the replay was coordinated by the phase of the ongoing theta rhythm, and the degree of theta coordination during the delay period was positively correlated with DMS performance. Here, we reanalyzed these data to investigate which brain regions were involved in generating the theta oscillations that coordinated the periodic replay of configural- relational information. We used a beamformer algorithm to produce estimates of regional theta rhythms and constructed volumetric images of the phase-locking between the local theta cycle and the instances of replay (in the 13- 80 Hz band). We found that individual differences in DMS performancefor configural-relational associations were relatedtothe degree of phase coupling of instances of cortical reactivations to theta oscillations generated in the right posterior hippocampus and the right inferior frontal gyrus. This demonstrates that the timing of memory reactivations in humans is biased toward hippocampal theta phase