8,779 research outputs found

    3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching

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    We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor. Both the free-hand case, in which the hand is isolated from the surrounding environment, and the hand-object case, in which the different types of interactions are classified, have been considered. The hand-object case is clearly the most challenging task having to deal with multiple tracks. The approach proposed here belongs to the class of partial pose estimation where the estimated pose in a frame is used for the initialization of the next one. The pose estimation is obtained by applying a modified version of the Iterative Closest Point (ICP) algorithm to synthetic models to obtain the rigid transformation that aligns each model with respect to the input data. The proposed framework uses a "pure" point cloud as provided by the Kinect sensor without any other information such as RGB values or normal vector components. For this reason, the proposed method can also be applied to data obtained from other types of depth sensor, or RGB-D camera

    CFD Analysis of Helicopter Wakes in Ground Effect

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    The paper presents CFD results for the wake of a helicopter flying a low altitude at different advance ratios. The wakes are assessed in terms of topology and velocity magnitudes. The structure of the wake near ground changes rapidly with the advance ratio and its decay appears to be faster than what is suggested by theoretical analyses. The results show clear the potential of modern CFD for use in helicopter safety and highlights the need for detailed surveys of helicopter wakes using full-scale physical experiments

    Probing the Structure of Jet Driven Core-Collapse Supernova and Long Gamma Ray Burst Progenitors with High Energy Neutrinos

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    Times of arrival of high energy neutrinos encode information about their sources. We demonstrate that the energy-dependence of the onset time of neutrino emission in advancing relativistic jets can be used to extract important information about the supernova/gamma-ray burst progenitor structure. We examine this energy and time dependence for different supernova and gamma-ray burst progenitors, including red and blue supergiants, helium cores, Wolf-Rayet stars, and chemically homogeneous stars, with a variety of masses and metallicities. For choked jets, we calculate the cutoff of observable neutrino energies depending on the radius at which the jet is stalled. Further, we exhibit how such energy and time dependence may be used to identify and differentiate between progenitors, with as few as one or two observed events, under favorable conditions

    Hierarchical Self-Assembly of Halogen-Bonded Block Copolymer Complexes into Upright Cylindrical Domains

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    Self-assembly of block copolymers into well-defined, ordered arrangements of chemically distinct domains is a reliable strategy for preparing tailored nanostructures. Microphase separation results from the system, minimizing repulsive interactions between dissimilar blocks and maximizing attractive interactions between similar blocks. Supramolecular methods have also achieved this separation by introducing small-molecule additives binding specifically to one block by noncovalent interactions. Here, we use halogen bonding as a supramolecular tool that directs the hierarchical self-assembly of low-molecular-weight perfluorinated molecules and diblock copolymers. Microphase separation results in a lamellar-within-cylindrical arrangement and promotes upright cylindrical alignment in films upon rapid casting and without further annealing. Such cylindrical domains with internal lamellar self-assemblies can be cleaved by solvent treatment of bulk films, resulting in separated and segmented cylindrical micelles stabilized by halogen-bond-based supramolecular crosslinks. These features, alongside the reversible nature of halogen bonding, provide a robust modular approach for nanofabricatio

    The flash flood of the Bisagno Creek on 9th October 2014: An “unfortunate” combination of spatial and temporal scales

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    SummaryOn the 9th October, 2014 a strong event hit the central part of Liguria Region producing disastrous consequences to the city of Genoa where the Bisagno Creek flooded causing one death and lots of damage. The precipitation pattern responsible for the event had peculiar spatial and temporal characteristics that led to an unexpected flash flood. The temporal sequence of rainfall intensities and the particular severity of rainfall showers at small temporal scale, together with the size of the sub-basin hit by the most intense part of the rainfall were the unfortunate concurrent ingredients that led to an “almost perfect” flash flood. The peak flow was estimated to be a 100–200years order return period.The effects of the spatial and temporal scales of the precipitation pattern were investigated by coupling a rainfall downscaling model with a hydrological model setting up an experiment that follows a probabilistic approach.Supposing that the correct volume of precipitation at different spatial and temporal scales is known, the experiment provided the probability of generating events with similar effects in terms of streamflow.Furthermore, the study gives indications regarding the goodness and reliability of the forecasted rainfall field needed, not only in terms of total rainfall volume, but even in spatial and temporal pattern, to produce the observed ground effects in terms of streamflow

    Multiple Instance Learning for Emotion Recognition using Physiological Signals

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    The problem of continuous emotion recognition has been the subject of several studies. The proposed affective computing approaches employ sequential machine learning algorithms for improving the classification stage, accounting for the time ambiguity of emotional responses. Modeling and predicting the affective state over time is not a trivial problem because continuous data labeling is costly and not always feasible. This is a crucial issue in real-life applications, where data labeling is sparse and possibly captures only the most important events rather than the typical continuous subtle affective changes that occur. In this work, we introduce a framework from the machine learning literature called Multiple Instance Learning, which is able to model time intervals by capturing the presence or absence of relevant states, without the need to label the affective responses continuously (as required by standard sequential learning approaches). This choice offers a viable and natural solution for learning in a weakly supervised setting, taking into account the ambiguity of affective responses. We demonstrate the reliability of the proposed approach in a gold-standard scenario and towards real-world usage by employing an existing dataset (DEAP) and a purposely built one (Consumer). We also outline the advantages of this method with respect to standard supervised machine learning algorithms

    Single chain structure in thin polymer films: Corrections to Flory's and Silberberg's hypotheses

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    Conformational properties of polymer melts confined between two hard structureless walls are investigated by Monte Carlo simulation of the bond-fluctuation model. Parallel and perpendicular components of chain extension, bond-bond correlation function and structure factor are computed and compared with recent theoretical approaches attempting to go beyond Flory's and Silberberg's hypotheses. We demonstrate that for ultrathin films where the thickness, HH, is smaller than the excluded volume screening length (blob size), ξ\xi, the chain size parallel to the walls diverges logarithmically, R2/2N≈b2+clog⁡(N)R^2/2N \approx b^2 + c \log(N) with c∼1/Hc \sim 1/H. The corresponding bond-bond correlation function decreases like a power law, C(s)=d/sωC(s) = d/s^{\omega} with ss being the curvilinear distance between bonds and ω=1\omega=1. % Upon increasing the film thickness, HH, we find -- in contrast to Flory's hypothesis -- the bulk exponent ω=3/2\omega=3/2 and, more importantly, an {\em decreasing} d(H)d(H) that gives direct evidence for an {\em enhanced} self-interaction of chain segments reflected at the walls. Systematic deviations from the Kratky plateau as a function of HH are found for the single chain form factor parallel to the walls in agreement with the {\em non-monotonous} behaviour predicted by theory. This structure in the Kratky plateau might give rise to an erroneous estimation of the chain extension from scattering experiments. For large HH the deviations are linear with the wave vector, qq, but are very weak. In contrast, for ultrathin films, H<ξH<\xi, very strong corrections are found (albeit logarithmic in qq) suggesting a possible experimental verification of our results.Comment: 16 pages, 7 figures. Dedicated to L. Sch\"afer on the occasion of his 60th birthda
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