简介:Thisarticlepresentsadatamanagementsolutionbasedonthedatadistributionservice(DDS)communicationmodel.ThebasicDDScommunicationmodelconsistsofaunidirectionaldataexchangewhereapplicationsthatpublishdata'push'therelevantdata,whichisupdatedtothelocalcachesofco-locatedsubscriberstothedata[1].DDShasnospecifiedcenternodetoforwarddatapacketsandmaintainthecommunicationdata.Thistypeofpublish-subscribe(P/S)modelpresentsintegrityandconsistencychallengesindatamanagement.Unlikepeer-to-peer(P2P)distributedstorage,DDSapplicationshaveahardreal-timeenvironmentandfewerdatafeatures,andthecoreproblemisensuringtheintegrityandconsistencyofdataindistributedsystemsunderthishardreal-timeenvironment.ThisarticlebeginswithabriefintroductionofthecommunicationmodelusedbyDDS,thenanalyzespersistentdatamanagementproblemscausedbysuchmodel,andprovidesanappropriatesolutiontotheseproblems.Thissolutionhasbeenimplementedinaprototypesystemofthereal-timeservicebus(RTSB)ofTsinghuaUniversity.
简介:Atpresent,itisprojectedthatabout4zettabytes(or10**21bytes)ofdigitaldataarebeinggeneratedperyearbyeverythingfromundergroundphysicsexperimentstoretailtransactionstosecuritycamerastoglobalpositioningsystems.IntheU.S.,majorresearchprogramsarebeingfundedtodealwithbigdatainallfivesectors(i.e.,services,manufacturing,construction,agricultureandmining)oftheeconomy.BigDataisatermappliedtodatasetswhosesizeisbeyondtheabilityofavailabletoolstoundertaketheiracquisition,access,analyticsand/orapplicationinareasonableamountoftime.WhereasTien(2003)forewarnedaboutthedatarich,informationpoor(DRIP)problemsthathavebeenpervasivesincetheadventoflarge-scaledatacollectionsorwarehouses,theDRIPconundrumhasbeensomewhatmitigatedbytheBigDataapproachwhichhasunleashedinformationinamannerthatcansupportinformed-yet,notnecessarilydefensibleorvalid-decisionsorchoices.Thus,bysomewhatovercomingdataqualityissueswithdataquantity,dataaccessrestrictionswithon-demandcloudcomputing,causativeanalysiswithcorrelativedataanalytics,andmodel-drivenwithevidence-drivenapplications,appropriateactionscanbeundertakenwiththeobtainedinformation.Newacquisition,access,analyticsandapplicationtechnologiesarebeingdevelopedtofurtherBigDataasitisbeingemployedtohelpresolvethe14grandchallenges(identifiedbytheNationalAcademyofEngineeringin2008),underpinthe10breakthroughtechnologies(compiledbytheMassachusettsInstituteofTechnologyin2013)andsupporttheThirdIndustrialRevolutionofmasscustomization.
简介:Thedatausedintheprocessofknowledgediscoveryoftenincludesnoiseandincompleteinformation.Theboundariesofdifferentclassesofthesedataareblurandunobvious.Whenthesedataareclusteredorclassified,weoftengetthecoveringsinsteadofthepartitions,anditusuallymakesourinformationsysteminsecure.Inthispaper,optimalpartitioningofincompletedataisresearched.Firstly,therelationshipofsetcoverandsetpartitionisdiscussed,andthedistancebetweensetcoverandsetpartitionisdefined.Secondly,theoptimalpartitioningofgivencoverisresearchedbythecombingandpartingmethod,acquiringtheoptimalpartitionfromthreedifferentpartitionssetfamilyisdiscussed.Finally,thecorrespondingoptimalalgorithmisgiven.Therealwirelesssignalsofftencontainalotofnoise,andtherearemanyerrorsinboundarieswhenthesedataisclusteredbasedonthetradionalmethod.Inourexperimant,theproposedmethodimprovescorrectrategreatly,andtheexperimentalresultsdemonstratethemethod’svalidity.
简介:Timelyandcost-efficientmulti-hopdatadeliveryamongvehiclesisessentialforvehicularad-hocnetworks(VANETs),andvariousroutingprotocolsareenvisionedforinfrastructure-lessvehicle-to-vehicle(V2V)communications.Generally,whenapacket(oraduplicate)isdeliveredoutoftheroutingpath,itwillbedropped.However,weobservethatthesepackets(orduplicates)mayalsobedeliveredmuchfasterthanthepacketsdeliveredalongtheoriginalroutingpath.Inthispaper,weproposeanoveltreebasedroutingscheme(TBRS)forultilizingthedroppedpacketsinVANETs.InTBRS,thepacketisdeliveredalongaroutingtreewiththedestinationasitsroot.Andwhenthepacketisdeliveredoutitsroutingtree,itwon'tbedroptimmediatelyandwillbedeliveredforawhileifitcanarriveatanotherbranchofthetree.WeconducttheextensivesimulationstoevaluatetheperformanceofTBRSbasedontheroadmapofarealcitycollectedfromGoogleEarth.ThesimulationresultsshowthatTBRScanoutperformtheexistingprotocols,especiallywhenthenetworkresourcesarelimited.
简介:Receiveroperatingcharacteristic(ROC)curvesareoftenusedtostudythetwosampleprobleminmedicalstudies.However,mostdatainmedicalstudiesarecensored.UsuallyanaturalestimatorisbasedontheKaplan-Meierestimator.InthispaperweproposeasmoothedestimatorbasedonkerneltechniquesfortheROCcurvewithcensoreddata.Thelargesamplepropertiesofthesmoothedestimatorareestablished.Moreover,deficiencyisconsideredinordertocomparetheproposedsmoothedestimatoroftheROCcurvewiththeempiricalonebasedonKaplan-Meierestimator.ItisshownthatthesmoothedestimatoroutperformsthedirectempiricalestimatorbasedontheKaplan-Meierestimatorunderthecriterionofdeficiency.Asimulationstudyisalsoconductedandarealdataisanalyzed.
简介:Hidingdatainthedeoxyribosenucleicacid(DNA)canfacilitatetheauthenticationandannotationofimportantplantvarietyrights.Agrantofplantvarietyrightsforanewplantvarietygivesyoutheexclusiverighttoproduceforsaleandsellpropagatingmaterialofthevariety.Digitalwatermarkingtechniqueshavebeenproposedforawiderangeofapplications,includingownershipprotection,copycontrol,annotation,andauthentication.However,existingdatahidingmethodsforDNAchangethefunctionalitiesofDNAsequences,whichinducemorphologicalchangesinbiologicalpatterns.ThispaperproposesahighcapacitydatahidingschemeforDNAwithoutchangingthefunctionalitiesofDNAsequences.Thisschemeadaptivelyvariestheembeddingprocessaccordingtotheamountofhiddendata.Experimentalresultsshowthattheproposedschemegivesasignificantlyimprovedhidingperformancethanpreviousschemes.Andtherobustnessandsecurityissuesarealsoanalyzed.
简介:传统的地震数据采样跟随Nyquist采样定理。在这份报纸,我们介绍压缩察觉到的理论(CS),突破传统的Nyquist采样定理的限制,显示进用随机的undersampling的无害的支离破碎的随机的噪音的常规undersampling的协调别名,并且有效地把重建问题变成一个简单得多的降噪问题。我们介绍设计到凸的集合(POCS)上在数据重建的算法处理,在重复使用指数的腐烂阀值参数,并且修改执行在时空域的前面、反向的变换的传统的重建进程。我们建议使用在空间领域提交并且逆行变换的一个新方法。建议方法使用更少的计算机记忆并且改进计算速度。我们也分析antinoise和建议方法的抗混叠能力,并且比较2D和3D数据重建。理论模型和真实数据证明建议方法是有效的并且实际重要性,它能重建错过踪迹并且减少复杂数据的探索费用获得。
简介:Curvemodelingisoneofthebasicworkincomputeraidedgeometricdesignandcomputergraphics.Fortheimplicitconicfittingprobleminthispaper,theresearchmethodsthattheobjectivefunctionbasedontheminimalalgebraicdistanceandgeometricdistancearesummarized.Theadvantagesanddisadvantagesofeverymethodareanalyzedsimply,andtheapplicationsoftheconicfittingarelisted.
简介:Inthispaper,anewbiasestimationmethodisproposedandappliedinaregionalensembleKalmanfilter(EnKF)basedontheWeatherResearchandForecasting(WRF)Model.Themethodisbasedonahomogeneouslinearbiasmodel,andthemodelbiasisestimatedusingstatisticsateachassimilationcycle,whichisdifferentfromthestateaugmentationmethodsproposedinpreviousliteratures.Thenewmethodprovidesagoodestimationforthemodelbiasofsomespecificvariables,suchassealevelpressure(SLP).AseriesofnumericalexperimentswithEnKFareperformedtoexaminethenewmethodunderasevereweathercondition.Resultsshowthepositiveeffectofthemethodontheforecastingofcirculationpatternandmeso-scalesystems,andthereductionofanalysiserrors.ThebackgrounderrorcovariancestructuresofsurfacevariablesandtheeffectsofmodelsystembiasonEnKFarealsostudiedundertheerrorcovariancestructuresandanewconcept‘correlationscale’isintroduced.However,thenewmethodneedsfurtherevaluationwithmorecasesofassimilation.
简介:Losslessdatahidingcanrestoretheoriginalstatusofcovermediaafterembeddedsecretdataareextracted.In2010,Wangetal.proposedalosslessdatahidingschemewhichhidessecretdatainvectorquantization(VQ)indices,buttheencodingstrategiesadoptedbytheirschemeexpandthefinalcodestream.ThispaperdesignsfourembeddingandencodingstrategiestoimproveWangetal.'sscheme.TheexperimentresultoftheproposedschemecomparedwiththatoftheWangetal.'sschemereducesthebitratesofthefinalcodestreamby4.6%andraisesthepayloadby1.09%onaverage.
简介:Physicalpropertiesofseawater,suchassalinity,temperature,densityandacousticvelocity,couldbedemarcatedthroughdegradationofenergycausedbywaterabsorption,attenuationandotherfactors.Toovercomethechallengingdifficultiesinthequickmonitoringofthesephysicalproperties,wehaveexploredthehighresolutionmarineseismicsurveytoinstantlycharacterizethem.Basedontheuniquewavefieldpropagatingintheseawater,wehavedevelopedanewapproachtosuppressthenoisecausedbytheshallowseawaterdisturbanceandobtainusefulinformationforestimatingtheseawaterstructure.Thisapproachimprovesseismicdatawithhighsignal-to-noiseratioandresolution.Theseismicreflectionimagingcanmaptheseawaterstructureacoustically.Combinedwiththeknowledgeoflocalwaterbodystructureprofileoveryears,theinstantmodelforpredictingtheseawaterpropertiescouldbebuiltusingtheseismicdataacquiredfromthespeciallydesignedhighprecisionmarineseismicacquisition.Thismodelcanalsobeupdatedwithinstantobservationandthecompletedataprocessingsystem.Thepresentstudyhasthepotentialvaluetomanyapplications,suchas3Dseawatermonitoring,engineeringevaluation,geologicaldisasterassessmentandenvironmentalassessment.
简介:Recurrenteventdataoftenarisesinbiomedicalstudies,andindividualswithinaclustermightnotbeindependent.Weproposeasemiparametricadditiveratesmodelforclusteredrecurrenteventdata,whereinthecovariatesareassumedtoaddtotheunspecifiedbaselinerate.Fortheinferenceonthemodelparameters,estimatingequationapproachesaredeveloped,andbothlargeandfinitesamplepropertiesoftheproposedestimatorsareestablished.