4,320 research outputs found

    A Computationally Light Pruning Strategy for Single Layer Neural Networks based on Threshold Function

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    Embedded machine learning relies on inference functions that can fit resource-constrained, low-power computing devices. The literature proves that single layer neural networks using threshold functions can provide a suitable trade off between classification accuracy and computational cost. In this regard, the number of neurons directly impacts both on computational complexity and on resources allocation. Thus, the present research aims at designing an efficient pruning technique that can take into account the peculiarities of the threshold function. The paper shows that feature selection criteria based on filter models can effectively be applied to neuron selection. In particular, valuable outcomes can be obtained by designing ad-hoc objective functions for the selection process. An extensive experimental campaign confirms that the proposed objective function compares favourably with state-of-the-art pruning techniques

    From empty pews to empty cradles: Fertility decline among european catholics

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    Total fertility in the Catholic countries of Southern Europe has dropped to remarkably low rates (=1.4) despite continuing low rates female labor force participation and high historic fertility. We model three ways in which religion affects the demand for children-Through norms, market wages, and childrearing costs. We estimate these effects using new panel data on church attendance and clergy employment for 13 European countries from 1960 to 2000, spanning the Second Vatican Council (1962-65). Using nuns per capita as a proxy for service provision, we estimate fertility effects on the order of 300 to 400 children per nun. Moreover, nuns outperform priests as a predictor of fertility, suggesting that changes in childrearing costs dominate changes in theology and norms. Reduced church attendance also predicts fertility decline, but only for Catholics, not for Protestants. Service provision and attendance complement each other, a finding consistent with club models of religion

    A survey on deep learning in image polarity detection: Balancing generalization performances and computational costs

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    Deep convolutional neural networks (CNNs) provide an effective tool to extract complex information from images. In the area of image polarity detection, CNNs are customarily utilized in combination with transfer learning techniques to tackle a major problem: the unavailability of large sets of labeled data. Thus, polarity predictors in general exploit a pre-trained CNN as the feature extractor that in turn feeds a classification unit. While the latter unit is trained from scratch, the pre-trained CNN is subject to fine-tuning. As a result, the specific CNN architecture employed as the feature extractor strongly affects the overall performance of the model. This paper analyses state-of-the-art literature on image polarity detection and identifies the most reliable CNN architectures. Moreover, the paper provides an experimental protocol that should allow assessing the role played by the baseline architecture in the polarity detection task. Performance is evaluated in terms of both generalization abilities and computational complexity. The latter attribute becomes critical as polarity predictors, in the era of social networks, might need to be updated within hours or even minutes. In this regard, the paper gives practical hints on the advantages and disadvantages of the examined architectures both in terms of generalization and computational cost

    Spin Polarizabilities of the Nucleon from Polarized Low Energy Compton Scattering

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    As guideline for forthcoming experiments, we present predictions from Chiral Effective Field Theory for polarized cross sections in low energy Compton scattering for photon energies below 170 MeV, both on the proton and on the neutron. Special interest is put on the role of the nucleon spin polarizabilities which can be examined especially well in polarized Compton scattering. We present a model-independent way to extract their energy dependence and static values from experiment, interpreting our findings also in terms of the low energy effective degrees of freedom inside the nucleon: The polarizabilities are dominated by chiral dynamics from the pion cloud, except for resonant multipoles, where contributions of the Delta(1232) resonance turn out to be crucial. We therefore include it as an explicit degree of freedom. We also identify some experimental settings which are particularly sensitive to the spin polarizabilities.Comment: 30 pages, 19 figure

    Low-energy and low-momentum representation of the virtual Compton scattering amplitude

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    We perform an expansion of the virtual Compton scattering amplitude for low energies and low momenta and show that this expansion covers the transition from the regime to be investigated in the scheduled photon electroproduction experiments to the real Compton scattering regime. We discuss the relation of the generalized polarizabilities of virtual Compton scattering to the polarizabilities of real Compton scattering.Comment: 13 pages, LaTeX2e/RevTeX, no figure

    Structure analysis of the virtual Compton scattering amplitude at low energies

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    We analyze virtual Compton scattering off the nucleon at low energies in a covariant, model-independent formalism. We define a set of invariant functions which, once the irregular nucleon pole terms have been subtracted in a gauge-invariant fashion, is free of poles and kinematical zeros. The covariant treatment naturally allows one to implement the constraints due to Lorentz and gauge invariance, crossing symmetry, and the discrete symmetries. In particular, when applied to the epepγep\to e'p'\gamma reaction, charge-conjugation symmetry in combination with nucleon crossing generates four relations among the ten originally proposed generalized polarizabilities of the nucleon.Comment: 19 pages, LaTeX2e/RevTeX, no figures, original sections IV.-VI. removed, to be discussed in a separate publication, none of the conclusions change

    Complete one-loop analysis of the nucleon's spin polarizabilities

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    We present a complete one-loop analysis of the four nucleon spin polarizabilities in the framework of heavy baryon chiral perturbation theory. The first non-vanishing contributions to the isovector and first corrections to the isoscalar spin polarizabilities are calculated. No unknown parameters enter these predictions. We compare our results to various dispersive analyses. We also discuss the convergence of the chiral expansion and the role of the delta isobar.Comment: 4 pp, REVTE

    Generalized polarizabilities of the nucleon studied in the linear sigma model (II)

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    In a previous paper virtual Compton scattering off the nucleon has been investigated in the one-loop approximation of the linear sigma model in order to determine the 3 scalar generalized polarizabilities. We have now extended this work and calculated the 7 vector polarizabilities showing up in the spin-dependent amplitude of virtual Compton scattering. The results fulfill 3 model-independent constraints recently derived. Compared to the constituent quark model there exist enormous differences for some of the vector polarizabilities. At vanishing three-momentum of the virtual photon, the analytical results of the sigma model and of chiral perturbation theory can be related. The influence of the π0\pi^{0} exchange in the tt channel has been discussed in some detail. Besides, the vector polarizabilities determine 2 linear combinations of the third order spin-polarizabilities appearing in real Compton scattering.Comment: 17 pages, 4 figures, latex2e (Revtex), submitted to Z. Phys.
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