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.

Market Index Biases and Minimum Risk Indices

Markets, in the real world, are not efficient zero-sum games where hypotheses of the CAPM are fulfilled. Then, it is easy to conclude the market portfolio is not located on Markowitz"s efficient frontier, and passive investments (and indexing) are not optimal but biased. In this paper, we define and analyze biases suffered by passive investors: the sample, construction, efficiency and active biases and tracking error are presented. We propose Minimum Risk Indices (MRI) as an alternative to deal with to market index biases, and to provide investors with portfolios closer to the efficient frontier, that is, more optimal investment possibilities. MRI (using a Parametric Value-at-Risk Minimization approach) are calculated for three stock markets achieving interesting results. Our indices are less risky and more profitable than current Market Indices in the Argentinean and Spanish markets, facing that way the Efficient Market Hypothesis. Two innovations must be outlined: an error dimension has been included in the backtesting and the Sharpe"s Ratio has been used to select the"best" MRI

The normal distribution in some constrained sample spaces

Phenomena with a constrained sample space appear frequently in practice. This is the case e.g. with strictly positive data, or with compositional data, like percentages or proportions. If the natural measure of difference is not the absolute one, simple algebraic properties show that it is more convenient to work with a geometry different from the usual Euclidean geometry in real space, and with a measure different from the usual Lebesgue measure, leading to alternative models which better fit the phenomenon under study. The general approach is presented and illustrated using the normal distribution, both on the positive real line and on the D-part simplex. The original ideas of McAlister in his introduction to the lognormal distribution in 1879, are recovered and updated

Gaia photometry for white dwarfs

Context. White dwarfs can be used to study the structure and evolution of the Galaxy by analysing their luminosity function and initial mass function. Among them, the very cool white dwarfs provide the information for the early ages of each population. Because white dwarfs are intrinsically faint only the nearby (~ 20 pc) sample is reasonably complete. The Gaia space mission will drastically increase the sample of known white dwarfs through its 5-6 years survey of the whole sky up to magnitude V = 20-25. Aims. We provide a characterisation of Gaia photometry for white dwarfs to better prepare for the analysis of the scientific output of the mission. Transformations between some of the most common photometric systems and Gaia passbands are derived. We also give estimates of the number of white dwarfs of the different galactic populations that will be observed. Methods. Using synthetic spectral energy distributions and the most recent Gaia transmission curves, we computed colours of three different types of white dwarfs (pure hydrogen, pure helium, and mixed composition with H/He = 0.1). With these colours we derived transformations to other common photometric systems (Johnson-Cousins, Sloan Digital Sky Survey, and 2MASS). We also present numbers of white dwarfs predicted to be observed by Gaia. Results. We provide relationships and colourcolour diagrams among different photometric systems to allow the prediction and/or study of the Gaia white dwarf colours. We also include estimates of the number of sources expected in every galactic population and with a maximum parallax error. Gaia will increase the sample of known white dwarfs tenfold to about 200 000. Gaia will be able to observe thousands of very cool white dwarfs for the first time, which will greatly improve our understanding of these stars and early phases of star formation in our Galaxy.

Determinants of science-based cooperation: evidence in a sample of small and micro firms

We study the determining factors of cience-based cooperation in the case of small and micro firms. In this research, we propose an analytical framework based on the resource-based view of the firm and we identify a set of organisational characteristics, which we classify as internal, external and structural factors. Each factor can be linked to at least one reason, from the firm¿s point of view, to cooperate with universities and public research centres. Each reason can, in turn, be used as an indicator of a firm¿s organisational needs or organisational capacities. In order to validate the theoretical model, we estimate a logistic regression that models the propensity to participate in science-based cooperation activities within a sample of 285 small and micro firms located in Barcelona. The results show the key role played by the absorptive capacity of new and small companies.

Exploring the use of mobile communications in a sample of older people: Preliminary results of a case study in Los Angeles

This paper introduces a qualitative case study on mobile communication among the older population (60+ years old) conducted in Great Los Angeles (CA, USA) in autumn 2011. Methodology, fieldwork and preliminary results are discussed.Before, country-level data is presented to better understand the specific characteristics of the studied individuals. The section focus is on demographics and on acceptance and use of information and communication technologies (ICT).Preliminary results show that within the sample under study (20 individuals) there is a high number of mobile phone users (15) while among non-mobile users (5), three of them decide to stop using this technology. A majority of mobile phone adopters describe a very limited use of the device for everyday life communications. Finally,while Internet is really popular within the sample (14 users), just 3 individuals go online through their mobile telephone.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.

Power supply noise and logic error probability

Voltage fluctuations caused by parasitic impedances in the power supply rails of modern ICs are a major concern in nowadays ICs. The voltage fluctuations are spread out to the diverse nodes of the internal sections causing two effects: a degradation of performances mainly impacting gate delays anda noisy contamination of the quiescent levels of the logic that drives the node. Both effects are presented together, in thispaper, showing than both are a cause of errors in modern and future digital circuits. The paper groups both error mechanismsand shows how the global error rate is related with the voltage deviation and the period of the clock of the digital system.

Error probability in synchronous digital circuits due to power supply noise

This paper presents a probabilistic approach to model the problem of power supply voltage fluctuations. Error probability calculations are shown for some 90-nm technology digital circuits.The analysis here considered gives the timing violation error probability as a new design quality factor in front of conventional techniques that assume the full perfection of the circuit. The evaluation of the error bound can be useful for new design paradigms where retry and self-recoveringtechniques are being applied to the design of high performance processors. The method here described allows to evaluate the performance of these techniques by means of calculating the expected error probability in terms of power supply distribution quality.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

Error en el consentimiento: swaps y preferentes

La problemàtica jurídica-social que ha sorgit aquests darrers anys amb les permutes financeres i les participacions preferents ha fet plantejar si s'ha produït un error en el consentiment contractual amb aquest tipus de productes financers. A partir del contingut del Codi Civil espanyol i la doctrina, s'han analitzat els elements essencials del contracte, així com, la legislació aplicable als instruments financers. Amb l’ ajuda de la jurisprudència s'ha pogut comprovar que en la majoria de casos portats als tribunals en relació a aquests contractes, en els quals, es demana l'anul·labilitat contractual, el fonament principal es basa en la vulneració de les entitats de crèdit dels seus deures legals . En el present treball queda palesa la importància d'enllaçar l'element contractual del consentiment amb l'obligació que tenen les entitats de crèdit d'informar els seus clients. Així, la incorrecta formació sobre la realitat contractual que els clients manifesten amb el consentiment, passa sense cap dubte per la necessitat d'obtenir tota la informació rellevant del contracte. L’obligació d’informació està estretament lligada al deure de classificar als clients, totes dues són un compromís legal que tenen les entitats en la seva funció de lleialtat empresària. Les entitats financeres deuen per tant classificar els seus clients i proporcionals la informació, amb més rigor si cap , en el cas de clients minoristes. Per tot això, veiem que en aquells casos de clients minoristes en els quals no s'ha pogut demostrar per part de les entitats de crèdit que es va proporcionar tota la informació necessària, s'ha produït un error en el consentiment. Els clients no coneixien l’autèntic abast de la vinculació ni els costos als quals s'havia obligat , no hi ha dubte que en molts dels casos d'haver conegut la realitat, no haguessin contractat.

Error en el posicionamiento indoor en dispositivos mo¿viles

Location information is becoming increasingly necessary as every new smartphone incorporates a GPS (Global Positioning System) which allows the development of various applications based on it. However, it is not possible to properly receive the GPS signal in indoor environments. For this reason, new indoor positioning systems are being developed.As indoors is a very challenging scenario, it is necessary to study the precision of the obtained location information in order to determine if these new positioning techniques are suitable for indoor positioning.

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.

Prediction of rabbit meat and bone weight using measurements and sample cuts

Regression equations predicting dissectable muscle weight in rabbits from external measurements were presented. Bone weight and weight of muscle groups were also carcass predicted. Predictive capacity of external measurements, retail cuts and muscle groups on total muscle, percent muscle, total bone and muscle to bone ratio were studied separately. Measurements on dissected retail cuts should be included in ordcr to obtain good equations for prediction of percent muscle in the carcass. Equations for predicting the muscle to bone ratio using external mcasurcments and data from the dissection of one hind leg were suggested. The equations had generally high coefficients of determination. The coefficient of determination for prediction of dissectable muscle was 0.91, and for percent muscle in the carcass 0.79.

Influence of sample processing on the analysis of carotenoids in maize

We performed a number of tests with the aim to develop an effective extraction method for the analysis of carotenoid content in maize seed. Mixtures of methanol–ethyl acetate (6:4, v/v) and methanol–tetrahydrofuran (1:1, v/v) were the most effective solvent systems for carotenoid extraction from maize endosperm under the conditions assayed. In addition, we also addressed sample preparation prior to the analysis of carotenoids by liquid chromatography (LC). The LC response of extracted carotenoids and standards in several solvents was evaluated and results were related to the degree of solubility of these pigments. Three key factors were found to be important when selecting a suitable injection solvent: compatibility between the mobile phase and injection solvent, carotenoid polarity and content in the matrix.