19,566 research outputs found

    Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features

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    The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In our previous work, we explored the feasibility of extracting pose-based features from video sequences to automatically classify infant body movement into two categories, normal and abnormal. The classification was based upon the GMA, which was carried out on the video data by an independent expert reviewer. In this paper we extend our previous work by extracting the normalised pose-based feature sets, Histograms of Joint Orientation 2D (HOJO2D) and Histograms of Joint Displacement 2D (HOJD2D), for use in new deep learning architectures. We explore the viability of using these pose-based feature sets for automated classification within a deep learning framework by carrying out extensive experiments on five new deep learning architectures. Experimental results show that the proposed fully connected neural network FCNet performed robustly across different feature sets. Furthermore, the proposed convolutional neural network architectures demonstrated excellent performance in handling features in higher dimensionality. We make the code, extracted features and associated GMA labels publicly available

    Mariner Mars 1971 optical navigation demonstration

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    The feasibility of using a combination of spacecraft-based optical data and earth-based Doppler data to perform near-real-time approach navigation was demonstrated by the Mariner Mars 71 Project. The important findings, conclusions, and recommendations are documented. A summary along with publications and papers giving additional details on the objectives of the demonstration are provided. Instrument calibration and performance as well as navigation and science results are reported

    Constraints on the Progenitor System of the Type Ia Supernova SN 2011fe/PTF11kly

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    Type Ia supernovae (SNe) serve as a fundamental pillar of modern cosmology, owing to their large luminosity and a well-defined relationship between light-curve shape and peak brightness. The precision distance measurements enabled by SNe Ia first revealed the accelerating expansion of the universe, now widely believed (though hardly understood) to require the presence of a mysterious "dark" energy. General consensus holds that Type Ia SNe result from thermonuclear explosions of a white dwarf (WD) in a binary system; however, little is known of the precise nature of the companion star and the physical properties of the progenitor system. Here we make use of extensive historical imaging obtained at the location of SN 2011fe/PTF11kly, the closest SN Ia discovered in the digital imaging era, to constrain the visible-light luminosity of the progenitor to be 10-100 times fainter than previous limits on other SN Ia progenitors. This directly rules out luminous red giants and the vast majority of helium stars as the mass-donating companion to the exploding white dwarf. Any evolved red companion must have been born with mass less than 3.5 times the mass of the Sun. These observations favour a scenario where the exploding WD of SN 2011fe/PTF11kly, accreted matter either from another WD, or by Roche-lobe overflow from a subgiant or main-sequence companion star.Comment: 22 pages, 6 figures, submitte

    Calibration Challenges for Future Radio Telescopes

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    Instruments for radio astronomical observations have come a long way. While the first telescopes were based on very large dishes and 2-antenna interferometers, current instruments consist of dozens of steerable dishes, whereas future instruments will be even larger distributed sensor arrays with a hierarchy of phased array elements. For such arrays to provide meaningful output (images), accurate calibration is of critical importance. Calibration must solve for the unknown antenna gains and phases, as well as the unknown atmospheric and ionospheric disturbances. Future telescopes will have a large number of elements and a large field of view. In this case the parameters are strongly direction dependent, resulting in a large number of unknown parameters even if appropriately constrained physical or phenomenological descriptions are used. This makes calibration a daunting parameter estimation task, that is reviewed from a signal processing perspective in this article.Comment: 12 pages, 7 figures, 20 subfigures The title quoted in the meta-data is the title after release / final editing

    Keck Observations of the Young Metal-Poor Host Galaxy of the Super-Chandrasekhar-Mass Type Ia Supernova SN 2007if

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    We present Keck LRIS spectroscopy and gg-band photometry of the metal-poor, low-luminosity host galaxy of the super-Chandrasekhar mass Type Ia supernova SN 2007if. Deep imaging of the host reveals its apparent magnitude to be mg=23.15±0.06m_g=23.15\pm0.06, which at the spectroscopically-measured redshift of zhelio=0.07450±0.00015z_{helio}=0.07450\pm0.00015 corresponds to an absolute magnitude of Mg=14.45±0.06M_g=-14.45\pm0.06. Galaxy grg-r color constrains the mass-to-light ratio, giving a host stellar mass estimate of log(M/M)=7.32±0.17\log(M_*/M_\odot)=7.32\pm0.17. Balmer absorption in the stellar continuum, along with the strength of the 4000\AA\ break, constrain the age of the dominant starburst in the galaxy to be tburst=12377+165t_\mathrm{burst}=123^{+165}_{-77} Myr, corresponding to a main-sequence turn-off mass of M/M=4.61.4+2.6M/M_\odot=4.6^{+2.6}_{-1.4}. Using the R23_{23} method of calculating metallicity from the fluxes of strong emission lines, we determine the host oxygen abundance to be 12+log(O/H)KK04=8.01±0.0912+\log(O/H)_\mathrm{KK04}=8.01\pm0.09, significantly lower than any previously reported spectroscopically-measured Type Ia supernova host galaxy metallicity. Our data show that SN 2007if is very likely to have originated from a young, metal-poor progenitor.Comment: 15 pages, 9 figures; accepted for publication in Ap

    Similar self-organizing scale-invariant properties characterize early cancer invasion and long range species spread

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    Occupancy of new habitats through dispersion is a central process in nature. In particular, long range dispersal is involved in the spread of species and epidemics, although it has not been previously related with cancer invasion, a process that involves spread to new tissues. We show that the early spread of cancer cells is similar to the species individuals spread and that both processes are represented by a common spatio-temporal signature, characterized by a particular fractal geometry of the boundaries of patches generated, and a power law-scaled, disrupted patch size distribution. We show that both properties are a direct result of long-distance dispersal, and that they reflect homologous ecological processes of population self-organization. Our results are significant for processes involving long-range dispersal like biological invasions, epidemics and cancer metastasis.Comment: 21 pages, 2 figure
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