Browsing by Type "conference paper and proceedings preprints presentation (communicative events)"
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Item Interstellar scintillation as a probe of microarcsecond scale structure in quasars(2004-12-29) Bignall, H.E.; Jauncey, D.L.; Lovell, J.E.J.; Kedziora-Chudczer, L.; Macquar, J-P.; Tzioumis, A.K.; Rickett, B.J.; Ojha, R.; Carte, S.; Cimo, G.; Ellingsen, S.; McCulloch, P.M.Observations over the last two decades have shown that a significant fraction of all flat-spectrum, extragalactic radio sources exhibit flux density variations on timescales of a day or less at frequencies of several GHz. It has been demonstrated that interstellar scintillation (ISS) is the principal cause of such rapid variability. Observations of ISS can be used to probe very compact, microarcsecond-scale structure in quasar inner jets, as well as properties of turbulence in the local Galactic ISM. A few sources show unusually rapid, intra-hour variations, evidently due to scattering in very nearby, localized turbulence. We present recent findings for the rapidly scintillating quasar PKS 1257−326. The large-scale MASIV VLA Survey showed that such sources are extremely rare, implying that for most scintillating sources, longer-term, dedicated monitoring programs are required to extract detailed information on source structures.Item Kepler + Hadoop: a general architecture facilitating data-intensive applications in scientific workflow systems(ACM, 2009-11-16) Wang, Jianwu; Crawl, Daniel; Altintas, IlkayMapReduce provides a parallel and scalable programming model for data-intensive business and scientific applications. MapReduce and its de facto open source project, called Hadoop, support parallel processing on large datasets with capabilities including automatic data partitioning and distribution, load balancing, and fault tolerance management. Meanwhile, scientific workflow management systems, e.g., Kepler, Taverna, Triana, and Pegasus, have demonstrated their ability to help domain scientists solve scientific problems by synthesizing different data and computing resources. By integrating Hadoop with Kepler, we provide an easy-to-use architecture that facilitates users to compose and execute MapReduce applications in Kepler scientific workflows. Our implementation demonstrates that many characteristics of scientific workflow management systems, e.g., graphical user interface and component reuse and sharing, are very complementary to those of MapReduce. Using the presented Hadoop components in Kepler, scientists can easily utilize MapReduce in their domain-specific problems and connect them with other tasks in a workflow through the Kepler graphical user interface. We validate the feasibility of our approach via a word count use case.