Table of Content

23 August 2018, Volume 0 Issue 07

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StorageReplication Technologyof Heterogeneous Database#br# in Regional Network

XIEBin-ming,WANGXiao-dong

2018, 0(07):  1.  doi:10.3969/j.issn.1006-2475.2018.07.001

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Traditionalheterogeneousdatabasestorageandreplicationtechnologyonlyfocusesondatasecurity,ignoringthetimelinessandreliabilityofheterogeneousdatabasestoragereplication.Tosolvethisproblem,anewstoragereplicationtechnologyforheterogeneousdatabaseinregionalnetworkisproposed.First,theheterogeneousdatabasestorageframeworkintheregionalnetworkisconstructed,andtheheterogeneousdataofthepowerenterprisedisasterpreparednesscenterisstoredbythedirectionalrandomwalkmethod,andthedataintheheterogeneousdatabasearequeriedandprocessedonthebasisofthemultiforkindextree.Thenthedataofthelocaldisastercenterarebackedupbytheuniformtreedistributionbackuptechnology,thedatatoberecoveredisdividedintoseveralparts,andthedatarecoveryisrealizedthroughseveraldifferentremotebackupservers.Theproposedtechnologyisappliedtothedisasterrecoverycenterofpowerenterprises.Theresultsshowthattheproposedtechnologyhashighstorage,replicationandbackuprecoveryperformance.


DOP：ASimpleOpenDataFrameworkandItsApplication

MOCheng-wei,FANBing-bing

2018, 0(07):  6.  doi:10.3969/j.issn.1006-2475.2018.07.002

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Open-dataisthetrendoftheeraofbigdata,thustocarryoutopen-dataplatformthroughgeneralengineeringapproachesisthemainproblem.Referringtotheideasofthemetadatamanagementandthebig-datastorage,thepaperproposestheDOP(Data-Open-Pool)frameworkandCDD(Catalog-Dataset-Distribution)datadescriptionmodel,whichrealizestheservicelogicfrompublishingadatasetaftercollectingdatatoopeningtothepublicfinally,aswellasthedescriptionandmanagementofdataresourcesinthethreelevels,andfinallyimplementsaneasyopen-dataapplicationwiththeDOPandCDDhierarchicaldescriptionmodel,givesthegeneralalgorithmtoreleasethestandarddatasetfromunordereddatasources,aswellasthediscussiononsomeproblemsoftheframework.

AlgorithmforMulti-usersSkylineQueryBasedonPriorityofAttribute

SHAOLu-yi,WANGQin-xue,GUOShuai

2018, 0(07):  11.  doi:10.3969/j.issn.1006-2475.2018.07.003

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Skylinequeryprovidedasolutionformulti-objectivedecision-makingandotherissues.However,wheneachuserhaddifferentrequirementsonthepriorityofattributes,thetraditionalalgorithmcouldn’teffectivelysolvethepreferenceSkylinequeryunderthemulti-usersscenario.Tosolvethisproblem,thispaperproposesamulti-userspreferenceSkylinequeryalgorithmbasedonpriorityofattribute,whichnamedMUPSalgorithm.Basedontheweightsofattributes,theoriginalSkylineresultWasprunedbyapplyingthenovelσ-dominatedapproach.Atthesametime,theweightsoftheattributesaredynamicallyamendedthroughtheinteractionbetweenusersandreturnedcandidate,makingthefinalresultmoreinlinewithusers’realpreferenceneeds.Finally,thefeasibilityofMUPSalgorithmisverifiedbysimulationandrealdata,andithasgoodinteractiveperformance.


ImbalancedSVMClassificationMethodBasedonIncrementalLearning

CUILi-na1,GUOHu-sheng2

2018, 0(07):  20.  doi:10.3969/j.issn.1006-2475.2018.07.004

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Thispaperpresentsanimbalancedsupportvectormachine(SVM)basedonincrementallearning,namelyISVM_IL,tosolvetheimbalancedclassificationproblemthatthetraditionalSVMclassificationmethodcannotsolve.Firstly,thismethodextractssomesamplesfromthemajoritynegativeclass,andtheinitialclassifiercanbeobtainedbytrainingSVMonthesesamplesandminoritypositiveclasssample.Then,accordingtotherelationshipbetweentheclassifierandothernegativesamples,thenearestsampletotheclassifierisselectedasanincrementalsampletojointhetrainingsettoparticipateintheSVMtraining.Therefore,thenegativeclasssizeoftheactualtrainingisreducedandtheperformanceofimbalancedclassificationisimproved.TheexperimentresultdemonstratesthattheproposedISVM_ILmethodcanimprovetheclassificationperformanceofimportantminorityclasssampleofimbalancedclassification.

AnImprovedPageRankAlgorithmBasedonAPPSearchSystem

LIChun-sheng,LIUXiao-gang,JIAOHai-tao,ZHANGKe-jia

2018, 0(07):  24.  doi:10.3969/j.issn.1006-2475.2018.07.005

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InordertobetterapplythePageRankalgorithmtoAPPrecommendationsystem,basingontheresearchoftheapplicationmodelofPageRankalgorithminAPPsearchsystem,wefoundoutakindofdisadvantageofPageRankalgorithmappliedinAPPsearchsystem,thatis,similarAPPhasweakindependenceandstrongsimilarity,soweimprovedthealgorithm.Intheend,theTPRvalueofTime-PageRankalgorithmiscomparedwiththePRvalueoftraditionalPageRankalgorithm,andthefeasibilityofTime-PageRankalgorithmintheAPPsearchsystemisobtained.


SensitiveFileDetectionMethodBasedonCNN

LINXue-feng1,XIAYuan-yi2,GUOJin-long1,YUXiao-wen1

2018, 0(07):  28.  doi:10.3969/j.issn.1006-2475.2018.07.006

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Inrecentyears,thepowerindustryinformationconstructionhasmadegreatachievements.Moreandmoreofficedocuments,projectdocuments,projectcontractsandotherdocumentsinvolvingindustrysecrettransmitonInternet,onthetransmissionprocess,enterprise-classsensitivedocumentsmayhavebeenleaked.Traditionalsensitivedatarecognitionmethodbasedonsensitivelexiconforfeaturedetectioncangetdetectionresultquickly,butthereisalowaccuracy,highfalsenegativesrateandfalsepositivesrate.ThispaperproposesasensitivefiledetectionmethodbasedonDeepLearning.Themethodreferstowordembeddingandconvolutionneuralnetworkalgorithmtorealizetheaccurateclassificationofsensitivedocuments.Theapproachinthispapermakesenterprisesensitivefilesdetectionindependentoffeaturekeywords,andreducesthefalsenegativerateandfalsepositiverate.

TFT-LCDCircuitDefectsDetectionBasedonFasterR-CNN

HEJun-jie,XIAOKe,LIUChang,CHENSong-yan

2018, 0(07):  33.  doi:10.3969/j.issn.1006-2475.2018.07.007

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ThedetectionoftinyandcomplexdefectsinthebordercircuitofThinFilmTransistor-LiquidCrystalDisplay(TFT-LCD)hasbeenadifficultpointinAutomaticOpticalInspection(AOI).ThispaperdetectsTFT-LCDbordercircuitdefectsbyusingimprovedFasterRegion-basedConvolutionalNeuralNetwork(FasterR-CNN).Thealgorithmextractsfeaturesfromsharedconvolutionallayersfirstly,andthengeneratescandidateregionsaccuratelythroughthemultilayeredRegionProposalNetwork(RPN),whichcanrecognizeandlocatethetargetscombiningwithclassificationinformation.Weanalyzetheperformancesofthemethodwithdifferentnetworkstructureswedesigned,andcomparewithdifferentalgorithms.Theexperimentstrainedinabordercircuitdatasetshowthatthemethodachievesexcellentperformance,andthedetectionsystemcanrecognizeandlocatesixkindsofTFT-LCDbordercircuitdefectsinoneimagesimultaneouslywithin0.12sandachieveanaccuracyof94.6%.

FractionalOrderControlBasedonImprovedPSOAlgorithmforHeatingSystem

JIANGSu-ying

2018, 0(07):  39.  doi:10.3969/j.issn.1006-2475.2018.07.008

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Forfractionalorderheatingsystem,afractionalordercontrolmethodbasedonimprovedparticleswarmoptimizationalgorithmisproposed.First,thechemotaxismechanismofbacteriaisintroducedintotheparticleswarmoptimizationalgorithmwithconstrictionfactortosolvetheproblemofthePSOpopulationdiversitylost,whichiscausedbecausethereisonlyattractionoperationwithoutexclusionoperationinPSOalgorithm.
ThismethodcanpreventfallingintolocaloptimumbecauseofPSOprematureconvergence.ThentheimprovedPSOalgorithmisusedtooptimizetheparametersoffractionalordercontroller.Finally,takingtheheatingsystemasthecontrolledobject,theimprovedparticleswarmoptimizationalgorithm,thestandardparticleswarmoptimizationalgorithmandthegeneticalgorithmareusedrespectivelytooptimizetheparametersofthefractionalordercontroller.Thesimulationresultsshowthatbyusingtheimprovedalgorithmtosetthefractionalordercontrollerparameters,andthecontrollercaneffectivelyrestraintheperturbationofthemodelparameters,therobustnessofthesystemisbetter.


ADetectionAlgorithmofHookDeformationBasedonOpeningandTwistingAngle

WULiang-cheng，GUOLing

2018, 0(07):  43.  doi:10.3969/j.issn.1006-2475.2018.07.009

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Aimingattheproblemsofcomplexmeasurementtools,lowmeasurementaccuracy,lowefficiencyandpooraccuracyinthetraditionalartificialhookdetection,ahookdeformationdetectionalgorithmisproposedbasedontheintegratedpointcloudsegmentation,cylindricalaxisextractionandmodelsymmetryplaneextraction.Byredefiningtheopeningdegreeofthehook,thetworeferencepointsoftheopeningdegreeareextractedbycombiningtheabovethreealgorithms,andthetwistangleofthehookisobtainedthroughthecombinationofpointcloudsegmentationandsymmetryplaneextraction.Experimentalresultsshowthatcomparedwiththetraditionalmanualdetection,theproposedalgorithmhastheadvantagesofshortdetectiontime,highmeasurementaccuracy,lesstoolsandtraceability.

QuantumAntColonyOptimizationAlgorithmforReal-time#br# PathPlanningofMobileRobotinUnknownEnvironment

ZHANGGao-lin1,ZHANGJi-yu2,ZHOUMeng3

2018, 0(07):  49.  doi:10.3969/j.issn.1006-2475.2018.07.010

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Thispaperproposesaquantumantcolonyoptimization(QACO)algorithmforsolvingthereal-timepathplanningofmobilerobotsinunknownenvironments.Intheproposedalgorithm,eachantcarriesasetofquantumbitstoincreasethealgorithmsearchspace,andquantumrotationoperationisusedtoincreasethediversityofpopulationlocationstoavoidprematureconvergence,whichisconducivetothealgorithmjumpingoutofthelocaloptimum.Thispaperestablishesalaserdetectionmodelbasedonthegridenvironmentmodel.Whenthelaserdetectionmodeldetectsathreateningobstacle,theproposedmethodiscalledtore-planningthepathuntiltherobotavoidstheobstacle.Finally,simulationexperimentsdemonstratetheeffectiveness,rapidity,andstabilityoftheproposedalgorithm.

LimitedDomainKnowledgeQuestionAnsweringSystemBasedonBI-LSTM-CRF

CHENGShu-dong,HUYing

2018, 0(07):  53.  doi:10.3969/j.issn.1006-2475.2018.07.011

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Withthedevelopmentofopenfieldquestion-answeringsystemandtheurgentneedoftheintegrationofmechanicalindustryandartificialintelligence,itisnecessarytoestablishaknowledgebasequestionansweringsystemformachineryfield.Basedonmechanicalindustrydataandnaturallanguageprocessingtechniques,anetworkmodelbasedonconditionalrandomfieldandlongandshorttermmemoryneuralnetworkisproposedtoimprovetheinformationextractionperformanceandtoestablishaknowledgebasequestion-answeringsysteminmachineryindustry.Throughthecomparativeanalysisofexperimentaldata,themodelhasachievedgoodresults.


AControlSystemforLaserLevelingMachinesBasedonCANBus

BUYi-chen,HUANGHuan,QINHai-peng,JINXin

2018, 0(07):  58.  doi:10.3969/j.issn.1006-2475.2018.07.012

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Becauseofthedatacommunicationrequirementforthelevelingmachinecontrolsystem,thispaperpresentsacommunicationsystembasedontheCAN2.0Bprotocol.Thecommunicationbetweenmasterandslavecontrollersisrealized.Thesystemprovidesafeasibleschemeforcontrolofthelaserlevelingmachine.Anineaxisinertialsensorischosenastheangletransducer.TheSTM32F407processorandtheTMS320F28335processorarechosenrespectivelyasthemasterandslavecontrollers,controllersareconnectedtotheCANBusthroughextendedtransceivers.Experimentsshowthatthesystemcanreliablyoperate.Thehorizontalcontrolofscrapingplateisachievedbytheslavecontrolleraccordingtothecommandfromthemasterone.

DesignandVerificationofChildren-orientedEducationalApplication#br# BasedonEyeMovementInteractiveTechnology

WANGShu,WANGQing,CHENHong

2018, 0(07):  62.  doi:10.3969/j.issn.1006-2475.2018.07.013

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Inrecentyears,gamesandeducationalproductsforchildrenhaveemerged.However,mostapplicationsdonotmeetthelevelofchildren’scognitivedevelopmentandoperatingpractices,andlackingoftheattractivenessforchildren.Aimingatthebehaviorhabitsofchildren’susergroups,thispaperproposedadesignprincipleoftheinteractivesystembasedoneye-movementunderthemodeofeducationalgamesandbuiltanEBEIbasedontheinteractionbetweeneyesandeyes.Onthisbasis,wedesignedakindofinsectsciencepopulareducationalapplicationbasedontheeye-eyeinteractionmode.ThepracticalapplicationeffectofthegameisanalyzedbyT-testmethod.Theresultoftheexperimentisthatthegamehasstrongusabilityandcanbetterenhancechildren’slearninginterestininsectknowledgeandachievetheeffectofentertaining.

MeteorologicalCloudResourceSchedulingSystemBasedonBPNeuralNetwork

YANGLi-yuan,HUJia-jun,LIXian-feng,ZHOUXue-ying,ZOUHai-yan

2018, 0(07):  68.  doi:10.3969/j.issn.1006-2475.2018.07.014

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Schedulingmeteorologicalcloudresourcemanuallycanleadtothewasteofresources.ThispaperdesignsameteorologicalcloudresourceschedulingsystembasedonBPneuralnetwork.ThissystemusesBPneuralnetworktolearnthehistoricalworkloadofvirtualmachines,andthenpredictstheirworkloads.Basedontheworkloadpredictionofvirtualmachines,amulti-resource-orientedstrategyforvirtualmachineswhichissortednon-increasinglyisdesigned.ThissystemusesFirst-Fitalgorithmtoallocatecloudresourcetosortedvirtualmachines.ThissystemisexperimentedandverifiedontheJiangximeteorologicalcloudplatform.


ApplicationofEulerianVideoMagnificationTechnologyinFlameWeakSignalsDetection

AOYu,YANGJian-sheng

2018, 0(07):  73.  doi:10.3969/j.issn.1006-2475.2018.07.015

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Inordertomeasuretheflameflickingfrequencyofflameweaksignals,thispaperproposesamethodforflamemeasurementandenhancementbasedonEulervideomagnificationtechnique.Andthefeasibilityandeffectivenessoftheproposedmethodareverifiedbysimulations.Acombustionplatformisbuiltforexperimentaltests.ThedifferentinterferenceintensityflamevideosarecaughtandprocessedbytheproposedmethodviaMatlab.Theexperimentalresultsareanalyzedanddiscussedinbothtimeandfrequencydomain.Itdemonstratesthattheproposedmethodcanextractthemainfrequencyofflameeffectively.

LithiumBatteryRemainingUsefulLifePredictionBasedonIUPF

LILi-min,WENZong-zhou,SONGYu-qin

2018, 0(07):  77.  doi:10.3969/j.issn.1006-2475.2018.07.016

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Withthevigorousdevelopmentofnewenergyvehicles,thehealthassessmentoflithiumbatteriesforpowersupplydeviceshasgraduallybeentakenintoconsideration.Researchgraduallyshiftedfromthecurrentremainingchargeoflithiumbatteriesconcernedtothecalculationoftheirremainingusefullife.InordertoestimatetheremainingservicelifeofLi-ionbatteryefficientlyandaccurately,amethodofpredictingremaininglifetimeoflithiumbatterybasedonImprovedUnscentedParticleFilter(IUPF)isproposed.Basedonthestatisticequationoflithium-ionbatteryandtheequationofobservation,thetwoparameterswhichreflecttheinternalresistanceofthebatteryandthetwoparameterswhichreflectthedegradationrateofthebatteryperformanceareestimatedtoobtainthelithiumbatterycapacityformulaincludingthefailuretime.Thelifecycledataoflithium-ionbatteriesprovidedbyNASA’sAmespredictiondatabaseareverifiedbysimulation.Theperformanceoftheevaluationresultsisevaluatedbythreekindsofevaluationindexes.Theresultsshowthattheproposedmethodcanbeappliedtolithium-ionbatteryremaininglifeestimation,alsoimprovestheaccuracyoftheUPFmethodtopredict.

AHydrologicForecastMethodBasedonLSTM-BP

FENGJun,PANFei

2018, 0(07):  82.  doi:10.3969/j.issn.1006-2475.2018.07.017

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Hydrologicaldataissequentialandnon-linear,withhighuncertaintyandcomplexity.Theresultsofhydrologicalforecastingusingasinglemodelareoftendissatisfactory.Therefore,thispaperputsforwordamulti-modelcombinationforecastmodel,basedonLSTMandBPneuralnetwork,toforecasttheflood.ThemodeltakeshydrologicaldatarecordsofthepastyearobtainedfromtheZiwuheRiverasanexample,thetestresultsshowthattheeffectsofmulti-modelcombinationforecastmodelarebetterthanthatofasinglemodel,andthestabilityandaccuracyofforecastingarealsoimproved,whichprovidesanewideaforhydrologicalforecasting.

ApplicationofLoadBalancingTechnologyinParallelSymbolExecution

LIHang，ZANGLie，GANLu

2018, 0(07):  86.  doi:10.3969/j.issn.1006-2475.2018.07.018

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Dynamicsymbolexecutioncanbeparallelundercertainparallelalgorithms,andthestudyfindsthatthereisnopartialorderrelationshipbetweenthepathsearchtasksunderparallel.Paralleltaskschedulingoftenusescentralizedstrategy.However,duetotheproblemoftaskdistribution,thetraditionalcentralizedstrategyeasilycausesthecomputingunittowaitfortask.Basedontheaboveanalysis,thispaperfirstusesthebuffertostorethetasktosolvetheproblemofcomputingunitwaitingfortask.Secondly,wegraspthecharacteristicsthatparalleltasksdon’thavepartialorderrelationship,regardlessofthepriorityofthetask,butbalancetheworkloadofeachcomputingunitbyloadbalancingtechnology.Experimentsshowthatloadbalancingtechniquesandimprovedcentralizedstrategiessignificantlyimproveparallelefficiency.

LogisticRegression-basedSoftwareFaultLocalizationinFunctionLevel

ZHOUMing-quan,JIANGGuo-hua

2018, 0(07):  93.  doi:10.3969/j.issn.1006-2475.2018.07.019

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Themethodoffaultlocalizationbasedonspectrumdeterminesthecheckorderbycalculatingthesuspicious
ofthecoverageinformationofstatements.However,duringthesystemtest,thesizeoftheobjecttobelocatedislarge,whichleadstothepooreffectofthosemethods.Thispaperproposedamethodtolocatethefunctionsfaultsduringsystemtest.Inordertonarrowtherangeoflocation,weanalyzedtheexecutioninformationoffailedtestcasessubsystemandmodule,anddistinguishedthefailedtestcaseswithdifferentfaults.Thecorrelationdegreeiscalculatedforeachmoduleandfunction,andtheorderoffunctionstobecheckedisdeterminedbylocatingthefaultsatmodulelevelandfunctionlevelinsequence.Theexperimentsshowthattheproposedmethodcanreducetherangeoffaultlocalizationandimprovetheefficiencyoffaultlocalization.

ARobustMovingTargetShadowRemovalandRepairAlgorithm

ZHANGZe-hong,XUGui-li,XUYang,CHENGYue-hua,WANGZheng-sheng

2018, 0(07):  98.  doi:10.3969/j.issn.1006-2475.2018.07.020

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Fortheproblemsofshadowregionsinterferencetothemotionforegroundandthelimitationsofthenormalizedcross-correlationshadowdetectionmethod,thispaperproposesashadowdetectionmethodthatnormalizesthecross-correlationcoefficientfusionsymmetrycrossentropy,andaccordingtothedistributionlawoftheforegroundofeachneighborhoodbasedontheshadowareaandmisdetection,ashadowmisdetectionremovalmethodbasedonshadowcontourpixelneighborhoodinformationisproposed.Theforegroundvoidsandfracturesformedbyshadowremovalarerecovered,andthecompleteandaccuratemotionforegroundisfinallyobtained.Comparedwiththenormalizedcross-correlationmethodandtheSVMsupportvectormachinemethod,theforegroundreservationrateisrespectivelyincreasedby40.4%and6.3%,andthetime-consumingisapproximately1/153oftheSVMsupportvectormachinemethod.


TrafficSignRecognitionBasedonConvolutionalNeuralNetwork

CHENBai-li，LINNan

2018, 0(07):  103.  doi:10.3969/j.issn.1006-2475.2018.07.021

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Withthedevelopmentofscienceandtechnology,therecognitionoftrafficsignsforunpilotedvehicleisbecomingmoreandmorepractical.Andthemostpopularmethodtorecognizethetrafficsignistousetheconvolutionalneuralnetwork.Theexperimentismadebasedonthismethod.Afterthecollectionofactualtrafficsignsimagedata,weusethehistogram-equalizationandothermethodstoachieveimagepreprocessingandconstitutethetrainingsetandtestset.ThenwebuildtheconvolutionneuralnetworkofLeNet5bythetrainingset,andusethetestsettotesttheaccuracyofthemodel.Inthefirstexperiment,therecognitionaccuracyofthemodelishigherthanothertraditionalidentificationmethods,butonly87.5%.Aftertheadjustmentoftheneuralnetwork’sbatchsize,theconvolutionkernel,thenumberoftrainingandotheraspects,therecognitionaccuracyisincreasedto93.2%.

KeyNodeIdentificationofNavigationNetworkBasedonStructuralCentrality

JIANGYi-sen

2018, 0(07):  108.  doi:10.3969/j.issn.1006-2475.2018.07.022

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Aimingattheproblemofkeynodesidentificationinroutenetwork,thispaperconstructsacompleteroutenetworkstructureandacomplextopologymodelfromthepointofviewofroutenetworkstructurecentrality,analyzesroutenetworkfromthreeaspects:degreecentrality,betweenesscentralityandstructurecentrality.AndrelyingonPAJEKvisualizationplatform,thispapersimulatestheaboveanalysisresults.Basedonthis,usingAutoCADgeographicinformationplatformtoidentifythekeynodesoftheroutefromtheperspectiveofbetweenessandclosenessvisualization,wecangetthewaypointsthatplayanimportantroleintheperformanceoftheroutenetwork.Thesimulationresultsshowthattheextractedkeynodeshaveanimportantroleofconvergencehubandtrafficdistributionintheactualroutenetworkoperation,andhaveaninnovationadvantageinthestudyofimportantnodeidentificationoftheroadnetwork.

Attribute-basedEncryptionSchemewithEfficientRevocation

ZHANGXing-lan,LIJian-nan

2018, 0(07):  114.  doi:10.3969/j.issn.1006-2475.2018.07.023

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Attribute-BasedEncryption(ABE)associatesthekeyandtheciphertextwithaseriesofattributes,canrealizeaccesscontrolflexibly,andiswidelyusedincloudcomputingenvironment.Sincemostoftheexistingattributerevocationschemesdonotmakegooduseofthecomputingpowerofthecloudserver,thispaperproposesanefficientandfine-grainedaccesscontrolscheme.TheaccesscontrolstructureadoptedinthisschemecanexpressanyaccessstrategyinvolvingBooleanoperators.BycombiningABEwithattributeusergrouprandomkeydistributiontoimplementdoubleencryption,ittransfersallundooperationstoattribute-levelfine-grainedrevocation.What’smore,becausethedataalwaysexistontheserverinciphertextsoastoreducethesecurityrestrictionontheserver,itcantransfermostofthesecondciphertextencryptiontaskstothecloudserver,whichreducesthecomputationalcostofthedataownerandgreatlyenhancestheefficiencyofcomputingsystems.

MessageProcessingMechanismforPowerDistributionSecurityInteractiveGateway

GUOJiang-tao,SHENJia,LIUKun,ZOUYue-lin

2018, 0(07):  121.  doi:10.3969/j.issn.1006-2475.2018.07.024

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Withthepopularityofdistributionnetworkcoverage,thenumberofdistributionterminalsisincreasing.Asakeynetworkdeviceofdistributionnetwork,thedistributionsecurityinteractiongatewaytakesalotofsecurityinteractionbusinessbetweendistributionterminalanddistributionmainstation.Aimingattheproblemoflowefficiencyofdistributionsecurityinteractivegatewaymessageprocessing,wedesignandimplementaschemeofapplyingtheDPDKtechnologyandTCPtransparentproxyintothegateway.Itcanquicklyhandlealargenumberofdistributionterminalsecurityaccessbusinesses,andachieveasecurecommunicationwithmassservicemessageprocessing.Theperformancetestresultsshowthattheperformanceofthedistributedsecurityinteractivegatewaymessageprocessingmechanismdesignedinthispaperhasobviousadvantages.