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Showing 1 to 20 of 653 for “"Spark"”.

  1. Spark Gap

    "Spark Gap" is an invisible electrical force made visible in spaces between things. This usually describes the space of air between two conductors; a non-conductive gap in an otherwise complete electric circuit, across which a quick luminous disruptive electrical discharge occurs. This interstitial …

    vcu Repository record for Spark Gap (opens in a new tab)

  2. Adaptive scheduling in Spark

    … must be transferred between machines. Currently, Spark, a prominent such system, predetermines the strategies for shuffling this data, but in certain situations, different shuffle strategies would improve performance. We add functionality to track metrics about the data during the job and …

    mit Repository record for Adaptive scheduling in Spark (opens in a new tab)

  3. "Spark" for wind ensemble.

    Spark for Wind Ensemble is an attempt to compose an accessible and exciting piece of concert music for the wind ensemble that possesses a depth and richness rarely achieved within the medium's repertoire. The idea of a spark is expressed in various ways throughout the music, such as: electrical …

    baylor Repository record for "Spark" for wind ensemble. (opens in a new tab)

  4. Knock damage in spark-ignition engines

    … the damage caused by knocking combustion in spark-ignition engines. A literature review indicated that, in general, research into knock has focused on the causes and avoidance of knock, rather than on the damage resulting from knock. The few published works concerning the effects of knock …

    cape-town Repository record for Knock damage in spark-ignition engines (opens in a new tab)

  5. Work-sharing framework for Apache Spark

    Apache Spark is a popular framework for distributed data processing that generalizes the MapReduce model and significantly improves the performance of many use cases. People can use Spark to query enormous data sets faster than before to gain insights for a competitive edge in industry. Often these …

    mit Repository record for Work-sharing framework for Apache Spark (opens in a new tab)

  6. Incremental random forest classifiers in spark

    … existing trees and replacing old trees-in Spark Machine Learning(ML), a commonly used library for running ML algorithms in Spark. My implementation draws from existing methods in online learning literature, but includes several novel refinements. I evaluate the two implementations, as well …

    mit Repository record for Incremental random forest classifiers in spark (opens in a new tab)

  7. Parallel SPARQL Query Execution using Apache Spark

    … computing. Big data ecosystems like Apache Spark provide new opportunities for designing scalable RDF indexing and query processing techniques. In this thesis, we present new ideas on storing, indexing, and query processing of RDF datasets with billions of RDF statements. In our approach, we …

    umkc Repository record for Parallel SPARQL Query Execution using Apache Spark (opens in a new tab)

  8. High-performance compact gas filled spark switches

    Gas filled spark switches are used extensively in pulsed power systems for their high rate of dV/dt, dI/dt, fast closing times with low jitter, and their high voltage and current capability. Recently there has been a renewed interest in designing spark switches that can operate with environmentally …

    strathclyde Repository record for High-performance compact gas filled spark switches (opens in a new tab)

  9. Distributed graph decomposition algorithms on Apache Spark

    … we propose distributed algorithms on Apache Spark for k-truss and k-core decomposition of a graph. We also compare the performance of our algorithm with state-of-the-art Map-Reduce and parallel algorithms using openly available real world network data. Our proposed algorithms have shown …

    iupui Repository record for Distributed graph decomposition algorithms on Apache Spark (opens in a new tab)

  10. Exploration of fault tolerance in Apache Spark

    … fault tolerance for batch processing in Apache Spark. We evaluate the benefits and challenges of these approaches. Apache Spark is a cluster computing system comprised of three main components: the driver program, the cluster manager, and the worker nodes. Spark already tolerates the loss of …

    uiuc Repository record for Exploration of fault tolerance in Apache Spark (opens in a new tab)

  11. The octane requirement of spark ignition engines

    The thesis covers the fundamentals of refining and fuel technology, engine technology as regards parameters which influence knock and the results of engine tests. Definitions of octane number and the interpretation of the system developed to establish these numbers using the CFR engine are given. …

    cape-town Repository record for The octane requirement of spark ignition engines (opens in a new tab)

  12. Particulate matter formation in spark-ignition engines

    … of the mechanisms by which PM is formed in spark ignition (SI) internal combustion engines. A study was undertaken in order to understand the effects of dilution on measured PM, to examine and model the effect of steady state engine operating conditions on engine-out PM, and to characterize …

    mit Repository record for Particulate matter formation in spark-ignition engines (opens in a new tab)

  13. To spark imagination: the American Film Institute

    … newness each time it is visited, thus sparking the imagination. To the user of the institute, the space will each time be new. It takes on this characteristic as its users encounter their own reflection as well as the reflections - sometimes distorted - of others. This is enhanced as …

    vt Repository record for To spark imagination: the American Film Institute (opens in a new tab)

  14. Spark Breakdown Voltage Sampling During Early Stage Compression

    … of the relationships between the value of Spark Break-Down Voltage (SBDV) to gas density and speciation. The methodology presented, applied pulses of voltage to the spark plug, which is normally used only to initiate ignition, to also function as a non-intrusive in-cylinder sensor. …

    oxford-brookes Repository record for Spark Breakdown Voltage Sampling During Early Stage Compression (opens in a new tab)

  15. Modelem řízený vývoj Spark úloh pomocí Eclipse Acceleo

    … vývojom Big Data úloh v prostredí Apache Spark. Na začiatok je čitateľovi predstavený framework Apache Spark a potrebné detaily. Ďalej sa priblíži problematika modelom riadeného vývoja a popíšu sa jeho výhody a nevýhody. V druhej časti je popísaný navrhnutý meta-model pre modelovanie úloh …

    brno-tech Repository record for Modelem řízený vývoj Spark úloh pomocí Eclipse Acceleo (opens in a new tab)

  16. Porous Aluminum-Oxide Coatings by Anodic Spark Deposition

    Made available in DSpace on 2014-12-14T15:24:00Z (GMT). No. of bitstreams: 1 7709222.pdf: 6578359 bytes, checksum: b9cda3c2f7106af6910349246a45062d (MD5) Previous issue date: 1976

    uiuc Repository record for Porous Aluminum-Oxide Coatings by Anodic Spark Deposition (opens in a new tab)

  17. Effects of Turbulence on Spark-Ignition Engine Combustion

    Made available in DSpace on 2014-12-13T19:55:20Z (GMT). No. of bitstreams: 1 7524348.pdf: 10540246 bytes, checksum: dddd6e4708126a30fb8de703e90a1389 (MD5) Previous issue date: 1975

    uiuc Repository record for Effects of Turbulence on Spark-Ignition Engine Combustion (opens in a new tab)

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