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200 10$aU.S. Freight on the move $ehighlights from the 2012 Commodity Flow Survey preliminary data /$fby Michael Margreta, Chester Ford, and Ryan Grube
210  1$a[Washington, DC] :$cU.S. Department of Transportation, Bureau of Transportation Statistics,$d2014.
215   $a1 online resource (8 pages) $ccolor illustrations
225 1 $aSpecial report
300   $aTitle from PDF title page (viewed on Dec. 17, 2014
300   $a"August 2014."
320   $aIncludes bibliographical references.
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702   $aGrube$b Ryan
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200 10$aLarge deviations for Gaussian queues $emodelling communication networks /$fMichel Mandjes
210   $aChichester $cWiley$dc2007
215   $a1 online resource (338 p.)
300   $aDescription based upon print version of record.
311 08$a9780470015230 
311 08$a0470015233 
320   $aIncludes bibliographical references and index.
327   $apt. A. Gaussian traffic and large deviations -- pt. B. Large deviations of Gaussian queues -- pt. C. Applications.
330   $aIn recent years the significance of Gaussian processes to communication networks has grown considerably. The inherent flexibility of the Gaussian traffic model enables the analysis, in a single mathematical framework, of systems with both long-range and short-range dependent input streams. Large Deviations for Gaussian Queues demonstrates how the Gaussian traffic model arises naturally, and how the analysis of the corresponding queuing model can be performed. The text provides a general introduction to Gaussian queues, and surveys recent research into the modelling of communications n
606   $aGaussian processes
606   $aTelecommunication$xTraffic$xMathematical models
615  0$aGaussian processes.
615  0$aTelecommunication$xTraffic$xMathematical models.
676   $a621.38215015192
700   $aMandjes$b Michel$g(Michael Robertus Hendrikus),$f1970-$0755624
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