简介：Page-basedsoftwareDSMsystemssufferfromfalsesharingcausedbythelargesharinggranularity,andonlysupportone-dimensionBlockorCyclicblockdatadistributionschemes,Thusapplicationsrunningonthemwillsufferfrompoordatalocalityandwillbeabletoexploitparallelismonlywhenusingalargenumberofprocessors,Inthispaper.awaytowardssupportingflexibledatadistribution(FDD)onsoftwareDSMsystemispresented.Smallgranularity-tunableblocks,thesizeofwhichcanbesetbycompilerorprogrammer,areusedtooverlaptheworkingdatasetsdistributedamongprocessors.TheFDDwasimplmentedonasoftwareDSMsystemcalledJIAJIA.ComparedwithBlock/Cyclic-blockdistributionschemesusedbymostDSMsystemsnow,experimentsshowthattheproposedwayofflexibledatadistributionismoreeffective.Theperformanceoftheapplicationsusedintheexperimentsissignificantlyimproved.

简介：Recentextensivemeasurementsofreal-lifetrafficdemonstratethattheprobabilitydensityfunctionofthetrafficinnon-Gaussian.Ifatrafficmodeldoesnotcapturethischaracteristics,anyanalyticalorsimulationresultswillnotbeaccurate.Inthiswork,westudytheimpactofnon-Gaussiantrafficonnetworkperformance,andpresentanapproachthatcanaccuratelymodelthemarginaldistributionofreal-lifetraffic.Boththelong-andshort-rangeautocorrelationsarealsoaccounted.Weshowthattheremovalofnon-Gaussiancomponentsoftheprocessdoesnotchangeitscorrelationstructure,andwevalidateourpromisingprocedurebysimulations.

简介：Thispapershowsthemethodofestimatingspatiotemporaldistributionofpedestriansbyusingwatchcameras.Weestimatethedistributionwithouttrackingtechnology,withpedestrian’sprivacyprotectedandinUmedaundergroundmall.Latelyspatiotemporaldistributionofpedestrianshasbeingincreasinglyimportantinthefieldofurbanplanning,disasterpreventionplanning,marketingandsoon.Althoughmanyresearchershavetriedtocapturetheinformationoflocationasdealingwithsomesensors,someproblemsstillremain,suchastheinvestmentofsensors,therestrictionofthenumberofpeoplewhohasthedevicetheyareabletocapture.Fromsuchbackground,wedevelopanoriginallabellingalgorithmandestimatethespatiotemporaldistributionofpedestriansandtheinformationofthepassingtimeandthedirectionofpedestriansfromsequentialimagesofawatchcamera.

简介：Basedonthenichegeneticalgorithm,theintelligentandoptimizingmodelfortherollingforcedistributioninhotstripmillswasputforward.Theresearchshowedthatthemodelhadmanyadvantagessuchasfastsearchingspeed,highcalculatingprecisionandsuitingforon-linecalculation.Agoodstripshapecouldbeachievedbyusingthemodelanditisappropriateandpracticableforrollingproducing.

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简介：Whilecloud-basedBPM(BusinessProcessManagement)showspotentialsofinherentscalabilityandexpenditurereduction,suchissuesasuserautonomy,privacyprotectionandefficiencyhavepoppedupasmajorconcerns.Usersmayhavetheirownrudimentaryorevenfull-edgedBPMsystems,whichmaybeembodiedbylocalEAIsystems,attheirend,butstillintendtomakeuseofcloud-sideinfrastructureservicesandBPMcapabilities,whichmayappearasPaaS(Platform-as-a-Service)services,atthesametime.Awholebusinessprocessmaycontainanumberofnon-compute-intensiveactivities,forwhichcloudcomputingisover-provision.Moreover,someusersfeardataleakageandlossofprivacyiftheirsensitivedataisprocessedinthecloud.Thispaperproposesandanalyzesanovelarchitectureofcloud-basedBPM,whichsupportsuser-enddistributionofnon-compute-intensiveactivitiesandsensitivedata.Anapproachtooptimaldistributionofactivitiesanddataforsyntheticallyutilizingbothuser-endandcloud-sideresourcesisdiscussed.Experimentalresultsshowthatwiththehelpofsuitabledistributionschemes,dataprivacycanbesatisfactorilyprotected,andresourcesonbothsidescanbeutilizedatlowercost.