14,655 research outputs found

    Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors

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    While single measurement vector (SMV) models have been widely studied in signal processing, there is a surging interest in addressing the multiple measurement vectors (MMV) problem. In the MMV setting, more than one measurement vector is available and the multiple signals to be recovered share some commonalities such as a common support. Applications in which MMV is a naturally occurring phenomenon include online streaming, medical imaging, and video recovery. This work presents a stochastic iterative algorithm for the support recovery of jointly sparse corrupted MMV. We present a variant of the Sparse Randomized Kaczmarz algorithm for corrupted MMV and compare our proposed method with an existing Kaczmarz type algorithm for MMV problems. We also showcase the usefulness of our approach in the online (streaming) setting and provide empirical evidence that suggests the robustness of the proposed method to the distribution of the corruption and the number of corruptions occurring.Comment: 13 pages, 6 figure

    An implementation of synthetic generation of wind data series

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    Wind power fluctuation is a major concern of large scale wind power grid integration. To test methods proposed for wind power grid integration, a large amount of wind data with time series are necessary and will be helpful to improve the methods. Meanwhile, due to the short operation history of most wind farms as well as limitations of data collections, the data obtained from wind farms could not satisfy the needs of data analysis. Consequently, synthetic generation of wind data series could be one of the effective solutions for this issue. In this paper, a method is presented for generating wind data series using Markov chain. Due to the high order Markov chain, the possibility matrix designed for a wind farm could cost a lot of memory, which is a problem with current computer technologies. Dynamic list will be introduced in this paper to reduce the memory required. Communication errors are un-avoidable on long way signal transmission between the control centre and wind farms. Missing of data always happens in the historical wind data series. Using these data to generate wind data series may result in some mistakes when searching related elements in the probability matrix. An adaptive method will be applied in this paper to solve the problem. The proposed method will be verified using a set of one-year historical data. The results show that the method could generate wind data series in an effective way. © 2013 IEEE.published_or_final_versio

    Bio-Inspired Aggregation Control of Carbon Nanotubes for Ultra-Strong Composites

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    High performance nanocomposites require well dispersion and high alignment of the nanometer-sized components, at a high mass or volume fraction as well. However, the road towards such composite structure is severely hindered due to the easy aggregation of these nanometer-sized components. Here we demonstrate a big step to approach the ideal composite structure for carbon nanotube (CNT) where all the CNTs were highly packed, aligned, and unaggregated, with the impregnated polymers acting as interfacial adhesions and mortars to build up the composite structure. The strategy was based on a bio-inspired aggregation control to limit the CNT aggregation to be sub 20--50 nm, a dimension determined by the CNT growth. After being stretched with full structural relaxation in a multi-step way, the CNT/polymer (bismaleimide) composite yielded super-high tensile strengths up to 6.27--6.94 GPa, more than 100% higher than those of carbon fiber/epoxy composites, and toughnesses up to 117--192 MPa. We anticipate that the present study can be generalized for developing multifunctional and smart nanocomposites where all the surfaces of nanometer-sized components can take part in shear transfer of mechanical, thermal, and electrical signals

    MOBILE and the provision of total joint replacement

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    Modern joint replacements have been available for 45 years, but we still do not have clear indications for these interventions, and we do not know how to optimize the outcome for patients who agree to have them done. The MOBILE programme has been investigating these issues in relation to primary total hip and knee joint replacements, using mixed methods research

    Wide-Range Tunable Dynamic Property of Carbon Nanotube-Based Fibers

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    Carbon nanotube (CNT) fiber is formed by assembling millions of individual tubes. The assembly feature provides the fiber with rich interface structures and thus various ways of energy dissipation, as reflected by the non-zero loss tangent (>0.028--0.045) at low vibration frequencies. A fiber containing entangled CNTs possesses higher loss tangents than a fiber spun from aligned CNTs. Liquid densification and polymer infiltration, the two common ways to increase the interfacial friction and thus the fiber's tensile strength and modulus, are found to efficiently reduce the damping coefficient. This is because the sliding tendency between CNT bundles can also be well suppressed by the high packing density and the formation of covalent polymer cross-links within the fiber. The CNT/bismaleimide composite fiber exhibited the smallest loss tangent, nearly as the same as that of carbon fibers. At a higher level of the assembly structure, namely a multi-ply CNT yarn, the inter-fiber friction and sliding tendency obviously influence the yarn's damping performance, and the loss tangent can be tuned within a wide range, as similar to carbon fibers, nylon yarns, or cotton yarns. The wide-range tunable dynamic properties allow new applications ranging from high quality factor materials to dissipative systems

    Directional emission of light from a nano-optical Yagi-Uda antenna

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    The plasmon resonance of metal nanoparticles can enhance and direct light from optical emitters in much the same way that radio frequency (RF) antennas enhance and direct the emission from electrical circuits. In the RF regime, a typical antenna design for high directivity is the Yagi-Uda antenna, which basically consists of a one-dimensional array of antenna elements driven by a single feed element. Here, we present the experimental demonstration of directional light emission from a nano-optical Yagi-Uda antenna composed of an array of appropriately tuned gold nanorods. Our results indicate that nano-optical antenna arrays are a simple but efficient tool for the spatial control of light emission.Comment: 4 pages, including 4 figure

    Discovery of the progenitor of the type Ia supernova 2007on

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    Type Ia supernovae are exploding stars that are used to measure the accelerated expansion of the Universe and are responsible for most of the iron ever produced. Although there is general agreement that the exploding star is a white dwarf in a binary system, the exact configuration and trigger of the explosion is unclear, which could hamper their use for precision cosmology. Two families of progenitor models have been proposed. In the first, a white dwarf accretes material from a companion until it exceeds the Chandrasekhar mass, collapses and explodes. Alternatively, two white dwarfs merge, again causing catastrophic collapse and an explosion. It has hitherto been impossible to determine if either model is correct. Here we report the discovery of an object in pre-supernova archival X-ray images at the position of the recent type Ia supernova (2007on) in the elliptical galaxy NGC 1404. Deep optical images (also archival) show no sign of this object. From this we conclude that the X-ray source is the progenitor of the supernova, which favours the accretion model for this supernova, although the host galaxy is older (6-9 Gyr) than the age at which the explosions are predicted in the accreting models.Comment: Published in Nature See also the two follow-up papers: Roelofs, Bassa, Voss, Nelemans Nelemans, Voss, Roelofs, Bassa both on astro-ph 02/15/0
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