638 research outputs found

    Swarm shape manipulation through connection control

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    The control of a large swarm of distributed agents is a well known challenge within the study of unmanned autonomous systems. However, it also presents many new opportunities. The advantages of operating a swarm through distributed means has been assessed in the literature for efficiency from both operational and economical aspects; practically as the number of agents increases, distributed control is favoured over centralised control, as it can reduce agent computational costs and increase robustness on the swarm. Distributed architectures, however, can present the drawback of requiring knowledge of the whole swarm state, therefore limiting the scalability of the swarm. In this paper a strategy is presented to address the challenges of distributed architectures, changing the way in which the swarm shape is controlled and providing a step towards verifiable swarm behaviour, achieving new configurations, while saving communication and computation resources. Instead of applying change at agent level (e.g. modify its guidance law), the sensing of the agents is addressed to a portion of agents, differentially driving their behaviour. This strategy is applied for swarms controlled by artificial potential functions which would ordinarily require global knowledge and all-to-all interactions. Limiting the agents' knowledge is proposed for the first time in this work as a methodology rather than obstacle to obtain desired swarm behaviour

    3-D interactive visualisation tools for HI spectral line imaging

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    Upcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we present SlicerAstro\tt{SlicerAstro}, an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling

    Finding faint HI structure in and around galaxies: scraping the barrel

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    Soon to be operational HI survey instruments such as APERTIF and ASKAP will produce large datasets. These surveys will provide information about the HI in and around hundreds of galaxies with a typical signal-to-noise ratio of \sim 10 in the inner regions and \sim 1 in the outer regions. In addition, such surveys will make it possible to probe faint HI structures, typically located in the vicinity of galaxies, such as extra-planar-gas, tails and filaments. These structures are crucial for understanding galaxy evolution, particularly when they are studied in relation to the local environment. Our aim is to find optimized kernels for the discovery of faint and morphologically complex HI structures. Therefore, using HI data from a variety of galaxies, we explore state-of-the-art filtering algorithms. We show that the intensity-driven gradient filter, due to its adaptive characteristics, is the optimal choice. In fact, this filter requires only minimal tuning of the input parameters to enhance the signal-to-noise ratio of faint components. In addition, it does not degrade the resolution of the high signal-to-noise component of a source. The filtering process must be fast and be embedded in an interactive visualization tool in order to support fast inspection of a large number of sources. To achieve such interactive exploration, we implemented a multi-core CPU (OpenMP) and a GPU (OpenGL) version of this filter in a 3D visualization environment (SlicerAstro\tt{SlicerAstro}).Comment: 17 pages, 9 figures, 4 tables. Astronomy and Computing, accepte

    High performance astrophysics computing

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    The application of high end computing to astrophysical problems, mainly in the galactic environment, is under development since many years at the Dep. of Physics of Sapienza Univ. of Roma. The main scientific topic is the physics of self gravitating systems, whose specific subtopics are: i) celestial mechanics and interplanetary probe transfers in the solar system; ii) dynamics of globular clusters and of globular cluster systems in their parent galaxies; iii) nuclear clusters formation and evolution; iv) massive black hole formation and evolution; v) young star cluster early evolution. In this poster we describe the software and hardware computational resources available in our group and how we are developing both software and hardware to reach the scientific aims above itemized.Comment: 2 pages paper presented at the Conference "Advances in Computational Astrophysics: methods, tools and outcomes", to be published in the ASP Conference Series, 2012, vol. 453, R. Capuzzo-Dolcetta, M. Limongi and A. Tornambe' ed

    How environmental sustainability labels affect food choices: Assessing consumer preferences in southern Italy

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    This paper assesses consumer preferences and willingness to pay for three different environmental sustainability labels (EU Organic Farming, Rainforest Alliance, ‘Per il Clima-Legambiente’) and information cues about the origin displayed on a processed food product, namely tomato puree. Using a choice experiment and conditional logit models, the results show that: i) preferences for the environmental sustainability labelled product increase when consumers have proper knowledge about the meaning of the labels; ii) the information cue about the product’s domestic origin is important for all consumers, regardless of their education, unlike environmental sustainability labels that are more appreciated by well-educated consumers; iii) consumers’ willingness to pay is higher for labels with greater market penetration, regardless of certification by private or public organisations. Findings suggest that the adoption of environmental sustainability labels by food producers should be combined with effective information policies aimed at increasing consumer awareness

    On the asymptotic behaviour of solutions to the fractional porous medium equation with variable density

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    We are concerned with the long time behaviour of solutions to the fractional porous medium equation with a variable spatial density. We prove that if the density decays slowly at infinity, then the solution approaches the Barenblatt-type solution of a proper singular fractional problem. If, on the contrary, the density decays rapidly at infinity, we show that the minimal solution multiplied by a suitable power of the time variable converges to the minimal solution of a certain fractional sublinear elliptic equation.Comment: To appear in DCDS-

    Network communities of dynamical influence

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    Fuelled by a desire for greater connectivity, networked systems now pervade our society at an unprecedented level that will affect it in ways we do not yet understand. In contrast, nature has already developed efficient networks that can instigate rapid response and consensus when key elements are stimulated. We present a technique for identifying these key elements by investigating the relationships between a system’s most dominant eigenvectors. This approach reveals the most effective vertices for leading a network to rapid consensus when stimulated, as well as the communities that form under their dynamical influence. In applying this technique, the effectiveness of starling flocks was found to be due, in part, to the low outdegree of every bird, where increasing the number of outgoing connections can produce a less responsive flock. A larger outdegree also affects the location of the birds with the most influence, where these influentially connected birds become more centrally located and in a poorer position to observe a predator and, hence, instigate an evasion manoeuvre. Finally, the technique was found to be effective in large voxel-wise brain connectomes where subjects can be identified from their influential communities

    SlicerAstro: a 3-D interactive visual analytics tool for HI data

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    SKA precursors are capable of detecting hundreds of galaxies in HI in a single 12 hours pointing. In deeper surveys one will probe more easily faint HI structures, typically located in the vicinity of galaxies, such as tails, filaments, and extraplanar gas. The importance of interactive visualization has proven to be fundamental for the exploration of such data as it helps users to receive immediate feedback when manipulating the data. We have developed SlicerAstro, a 3-D interactive viewer with new analysis capabilities, based on traditional 2-D input/output hardware. These capabilities enhance the data inspection, allowing faster analysis of complex sources than with traditional tools. SlicerAstro is an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing. We demonstrate the capabilities of the current stable binary release of SlicerAstro, which offers the following features: i) handling of FITS files and astronomical coordinate systems; ii) coupled 2-D/3-D visualization; iii) interactive filtering; iv) interactive 3-D masking; v) and interactive 3-D modeling. In addition, SlicerAstro has been designed with a strong, stable and modular C++ core, and its classes are also accessible via Python scripting, allowing great flexibility for user-customized visualization and analysis tasks.Comment: 18 pages, 11 figures, Accepted by Astronomy and Computing. SlicerAstro link: https://github.com/Punzo/SlicerAstro/wiki#get-slicerastr

    The Kuznets curve of the rich

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    A long-standing interest in the relationship between inequality and sustainable growth continues to fascinate economists among other social scientists. It must be noted, however, that most empirical efforts have focussed on the income inequality–growth nexus, while studies on wealth inequality are much scarcer. This study attempts to fill such a gap in the literature by assessing the correspondence between the top 1 percent's wealth share and economic growth. Employing time series cointegration techniques, we study the experience of France and the United States from 1950 to 2014. Our estimates suggest that the output growth rate is an inverted-U-shaped function of the wealth share of the top 1 percent. The estimated relationship is robust to variations in control variables and estimation methods. We compute the local optimal wealth share, understood as the share of wealth compatible with the maximum growth rate, and show that France is growing close to its long-run potential, while the United States is significantly below its
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