2,532 research outputs found

    Affine Extractors and AC0-Parity

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    We study a simple and general template for constructing affine extractors by composing a linear transformation with resilient functions. Using this we show that good affine extractors can be computed by non-explicit circuits of various types, including AC0-Xor circuits: AC0 circuits with a layer of parity gates at the input. We also show that one-sided extractors can be computed by small DNF-Xor circuits, and separate these circuits from other well-studied classes. As a further motivation for studying DNF-Xor circuits we show that if they can approximate inner product then small AC0-Xor circuits can compute it exactly - a long-standing open problem

    Face Detection with Effective Feature Extraction

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    There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for frontal face detection. In this work, we show that simple features other than Haar-like features can also be applied for training an effective face detector. Since, single feature is not discriminative enough to separate faces from difficult non-faces, we further improve the generalization performance of our simple features by introducing feature co-occurrences. We demonstrate that our proposed features yield a performance improvement compared to Haar-like features. In addition, our findings indicate that features play a crucial role in the ability of the system to generalize.Comment: 7 pages. Conference version published in Asian Conf. Comp. Vision 201

    Measuring the Temperature of Hot Nuclear Fragments

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    A new thermometer based on fragment momentum fluctuations is presented. This thermometer exhibited residual contamination from the collective motion of the fragments along the beam axis. For this reason, the transverse direction has been explored. Additionally, a mass dependence was observed for this thermometer. This mass dependence may be the result of the Fermi momentum of nucleons or the different properties of the fragments (binding energy, spin etc..) which might be more sensitive to different densities and temperatures of the exploding fragments. We expect some of these aspects to be smaller for protons (and/or neutrons); consequently, the proton transverse momentum fluctuations were used to investigate the temperature dependence of the source

    Ensemble of Hankel Matrices for Face Emotion Recognition

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    In this paper, a face emotion is considered as the result of the composition of multiple concurrent signals, each corresponding to the movements of a specific facial muscle. These concurrent signals are represented by means of a set of multi-scale appearance features that might be correlated with one or more concurrent signals. The extraction of these appearance features from a sequence of face images yields to a set of time series. This paper proposes to use the dynamics regulating each appearance feature time series to recognize among different face emotions. To this purpose, an ensemble of Hankel matrices corresponding to the extracted time series is used for emotion classification within a framework that combines nearest neighbor and a majority vote schema. Experimental results on a public available dataset shows that the adopted representation is promising and yields state-of-the-art accuracy in emotion classification.Comment: Paper to appear in Proc. of ICIAP 2015. arXiv admin note: text overlap with arXiv:1506.0500

    Magnomechanical backaction corrections due to coupling to higher order Walker modes and Kerr nonlinearities

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    The radiation pressure-like coupling between magnons and phonons in magnets can modify the phonon frequency (magnomechanical spring effect) and decay rate (magnomechanical decay) via dynamical backaction. Such effects have been recently observed by coupling the uniform magnon mode of a magnetic sphere (the Kittel mode) to a microwave cavity. In particular, the ability to evade backaction effects was demonstrated [C.A. Potts et al., arXiv:2211.13766 [quant-ph] (2022)], a requisite for applications such as magnomechanical based thermometry. However, deviations were observed from the predicted magnomechanical decay rate within the standard theoretical model. In this work, we account for these deviations by considering corrections due to (i) magnetic Kerr nonlinearities and (ii) the coupling of phonons to additional magnon modes. Provided that such additional modes couple weakly to the driven cavity, our model yields a correction proportional to the average Kittel magnon mode occupation. We focus our results on magnetic spheres, where we show that the magnetostatic Walker modes couple to the relevant mechanical modes as efficiently as the Kittel mode. Our model yields excellent agreement with the experimental data.Comment: 20 pages, 9 figure

    Dynamical Backaction Evading Magnomechanics

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    The interaction between magnons and mechanical vibrations dynamically modify the properties of the mechanical oscillator, such as its frequency and decay rate. Known as dynamical backaction, this effect is the basis for many theoretical protocols, such as entanglement generation or mechanical ground-state cooling. However, dynamical backaction is also detrimental for specific applications. Here, we demonstrate the implementation of a cavity magnomechanical measurement that fully evades dynamical backaction effects. Through careful engineering, the magnomechanical scattering rate into the hybrid magnon-photon modes can be precisely matched, eliminating dynamical backaction damping. Backaction evasion is confirmed via the measurement of a drive-power-independent mechanical linewidth.Comment: 6 pages, 5 figure

    Automated segmentation by pixel classification of retinal layers in ophthalmic OCT images

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    Current OCT devices provide three-dimensional (3D) in-vivo images of the human retina. The resulting very large data sets are difficult to manually assess. Automated segmentation is required to automatically process the data and produce images that are clinically useful and easy to interpret. In this paper, we present a method to segment the retinal layers in these images. Instead of using complex heuristics to define each layer, simple features are defined and machine learning classifiers are trained based on manually labeled examples. When applied to new data, these classifiers produce labels for every pixel. After regularization of the 3D labeled volume to produce a surface, this results in consistent, three-dimensionally segmented layers that match known retinal morphology. Six labels were defined, corresponding to the following layers: Vitreous, retinal nerve fiber layer (RNFL), ganglion cell layer & inner plexiform layer, inner nuclear layer & outer plexiform layer, photoreceptors & retinal pigment epithelium and choroid. For both normal and glaucomatous eyes that were imaged with a Spectralis (Heidelberg Engineering) OCT system, the five resulting interfaces were compared between automatic and manual segmentation. RMS errors for the top and bottom of the retina were between 4 and 6 ÎĽm, while the errors for intra-retinal interfaces were between 6 and 15 ÎĽm. The resulting total retinal thickness maps corresponded with known retinal morphology. RNFL thickness maps were compared to GDx (Carl Zeiss Meditec) thickness maps. Both maps were mostly consistent but local defects were better visualized in OCT-derived thickness maps

    General entanglement

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    The paper contains a brief review of an approach to quantum entanglement based on analysis of dynamic symmetry of systems and quantum uncertainties, accompanying the measurement of mean value of certain basic observables. The latter are defined in terms of the orthogonal basis of Lie algebra, corresponding to the dynamic symmetry group. We discuss the relativity of entanglement with respect to the choice of basic observables and a way of stabilization of robust entanglement in physical systems.Comment: 7 pages, 1 figure,1 tabe, will be published in special issue of Journal of Physics (Conference Series) with Proceedings of CEWQO-200
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