DatabaseSystemConcepts——数据库系统概念第六版(英文版)作者:AbrahamSilberschatz(YaleUniversity)HenryF.Korth(LehighUniversity)S.Sudarshan(IndianInstituteofTechnology,Bombay)本书目录:Chapter1Introduction1.1Database-SystemApplications11.2PurposeofDatabaseSystems31.3ViewofData61.4DatabaseLanguages91.5RelationalDatabases121.6DatabaseDesign151.7DataStorageandQuerying201.8TransactionManagement221.9DatabaseArchitecture231.10DataMiningandInformationRetrieval251.11SpecialtyDatabases261.12DatabaseUsersandAdministrators271.13HistoryofDatabaseSystems291.14Summary31Exercises33BibliographicalNotes35Chapter2IntroductiontotheRelationalModel2.1StructureofRelationalDatabases392.2DatabaseSchema422.3Keys452.4SchemaDiagrams462.5RelationalQueryLanguages472.6RelationalOperations482.7Summary52Exercises53BibliographicalNotes55Chapter3IntroductiontoSQL3.1OverviewoftheSQLQueryLanguage573.2SQLDataDefinition583.3BasicStructureofSQLQueries633.4AdditionalBasicOperations743.5SetOperations793.6NullValues833.7AggregateFunctions843.8NestedSubqueries903.9ModificationoftheDatabase983.10Summary104Exercises105BibliographicalNotes112Chapter4IntermediateSQL4.1JoinExpressions1134.2Views1204.3Transactions1274.4IntegrityConstraints1284.5SQLDataTypesandSchemas1364.6Authorization1434.7Summary150Exercises152BibliographicalNotes156Chapter5AdvancedSQL5.1AccessingSQLFromaProgrammingLanguage1575.2FunctionsandProcedures1735.3Triggers1805.4RecursiveQueries1875.5AdvancedAggregationFeatures1925.6OLAP1975.7Summary209Exercises211BibliographicalNotes216Chapter6FormalRelationalQueryLanguages6.1TheRelationalAlgebra2176.2TheTupleRelationalCalculus2396.3TheDomainRelationalCalculus2456.4Summary248Exercises249BibliographicalNotes254Chapter7Datab
2024/5/17 10:55:55 10.51MB Database Concepts PDF 英文版
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ApacheThriftisanopensourcecrosslanguageserializationandRPCframework.Withsupportforover15programminglanguages,ApacheThriftcanplayanimportantroleinarangeofdistributedapplicationdevelopmentenvironments.AsaserializationplatformApacheThriftenablesefficientcrosslanguagestorageandretrievalofawiderangeofdatastructures.AsanRPCframework,ApacheThriftenablesrapiddevelopmentofcompletepolyglotservicesinafewlinesofcode.Part1ofthisbooktakesyouonaguidedtourthroughtherangeofdistributeddevelopmentsolutionsempoweredbyApacheThrift.You’llseehowtheApacheThriftframeworkfitsintovariouscommunicationsschemesandalsogetahighlevelpictureoftheoverallApacheThriftarchitecture.
2024/4/30 11:02:25 6.11MB thrift 开发 apache 开发人员
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RadiativeTransferCodesforAtmosphericCorrectionandAerosolRetrievals:IntercomparisonStudy。
对比了蒙特卡洛、SHARM\RT3\6SV\MODTRAN等模型在大气校正与气溶胶反演方面的优劣。
2024/2/6 12:44:28 5.46MB 6S MODTRAN SHARM RT3
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DifferentialEquationsandLinearAlgebra(4th)英文无水印原版pdf第4版pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开本资源转载自网络,如有侵权,请联系上传者或csdn删除查看此书详细信息请在美国亚马逊官网搜索此书EditorialDirector,Mathematics:ChristinehoagEditor-in-Chief:DeirdreLynchAcquisitionsEditor:WilliamHoffmaProjectTeamLead:ChristinaleProjectmanager:LaurenMorseEditorialAssistant:JenniferSnyderProgramTeamLead:KarenwernholmProgramManagerDaniellesimbajonCoverandillustrationDesign:StudioMontageProgramDesignLead:BethPaquinProductMarketingManagerClaireKozarProductMarketingCoordiator:BrookesmithFieldMarketingManager:EvanStCyrSeniorAuthorSupport/TechnologySpecialist:JoevetereSeniorProcurementSpecialist:CarolMelvilleInteriorDesign,ProductionManagement,AnswerArt,andCompositioneNergizerAptara,LtdCoverImage:LighttrailsonmodernbuildingbackgroundinShanghai,China-hxdyl/123RFCopyrightO2017,2011,2005PearsonEducation,Inc.oritsaffiliates.AllRightsReserved.PrintedintheUnitedStatesofAmerica.Thispublicationisprotectedbycopyright,andpermissionshouldbeobtainedfromthepublisherpriortoanyprohibitedreproduction,storageinaretrievalsystem,ortransmissioninanyformorbyanymeans,electronic,mechanical,photocopyingrecording,orotherwise.Forinformationregardingpermissions,requestformsandtheappropriatecontactswithinthePearsonEducationGlobalRights&Permissionsdepartmentpleasevisitwww.pearsoned.com/permissions/PEARSONandALWAYSLEARNINGareexclusivetrademarksintheU.s.and/orothercountriesownedbyPearsonEducation,Inc.oritsaffiliatesUnlessotherwiseindicatedherein,anythird-partytrademarksthatmayappearinthisworkarethepropertyoftheirrespectiveowandanyreferencestothird-partytrademarks,logosorothertradedressarefordemonstrativeordescriptivepurposesonly.SuchofsuchmarksoranyrelationshipbetweentheownerandPearsonEducation,Inc.oritsaffiliates,authors,licenseesordistributortreferencesarenotintendedtoimplyanysponsorship,endorsement,authorization,orpromotionofPearsonsproductsbytheownersLibraryofCongressCataloging-in-PublicationDataGoode.StephenwDifferentialequationsandlinearalgebra/StephenW.GoodeandScottA.AnninCaliforniastateUniversity,Fullerton.-4theditionpagescmIncludesindexISBN978-0-321-96467-0—ISBN0-32196467-51.Differentialequations.2.Algebras,Linear.I.Annin,Scott.II.TitleQA371.G6442015515’.35-dc23201400601512345678910V031-1918171615PEARSONISBN10:0-321-96467-5www.pearsonhighered.comISBN13:978-0-321-96467-0ContentsPrefacevii1First-OrderDifferentialEquations1.1DifferentialEquationsEverywhere11.2BasicIdeasandTerminology131.3TheGeometryofFirst-OrderDifferentialEquations231.4SeparableDifferentialEquations341.5SomeSimplePopulationModels451.6First-OrderLinearDifferentialEquations531.7ModelingProblemsUsingFirst-OrderLinearDifferentialEquations61.8Changeofvariables711.9ExactDifferentialEquations821.10Numericalsolutiontofirst-OrderDifferentialEquations931.11SomeHigher-OrderDifferentialEquations1011.12ChapterReview1062MatricesandSystemsofLinearEquations1142.1Matrices:Definitionsandnotation1152.2MatrixAlgebra1222.3TerminologyforSystemsofLinearEquations13824R。
w-EchelonMatricesandElementaryR。
wOperations1462.5Gaussianelimination1562.6TheInverseofasquarematrix1682.7ElementaryMatricesandtheLUFactorization1792.8TheInvertiblematrixtheoremi1882.9ChapterReview1903Determinants1963.1TheDefinitionofthedeterminant1963.2PropertiesofDeterminants2093.3CofactorExpansions2223.4SummaryofDeterminants2353.5ChapterReview242iyContents4VectorSpaces2464.1Vectorsinrn2484.2DefinitionofaVectorSpace2524.3Subspaces2634.4SpanningSets2744.5LinearDependenceandLinearIndependence2844.6Basesanddimension2984.7Changeofbasis3114.8RowSpaceandColumnSpace3194.9TheRank-NullityTheorem3254.10InvertibleMatrixTheoremll3314.11ChapterReview3325InnerProductSpaces3395.1DefinitionofanInnerproductspace3405.2OrthogonalSetsofvectorsandorthogonalProjections3525.3Thegram-Schmidtprocess3625.4LeastSquaresApproximation3665.5ChapterReview3766LinearTransformations3796.1Definitionofalineartransformation3806.2Transformationsofr23916.3TheKernelandrangeofalineartransformation3976.4AdditionalPropertiesofLinearTransformations4076.5Thematrixofalineartransformation4196.6Chaiterreview4287EigenvaluesandEigenvectors4337.1TheEigenvalue/EigenvectorProblem4347.2GeneralResultsforEigenvaluesandEigenvectors4467.3Diagonalization4547.4AnIntroductiontotheMatrixExponentialFunction4627.5OrthogonalDiagonalizationandQuadraticforms4667.6Jordancanonicalforms4757.7Chapterreview4888LinearDifferentialEquationsofOrdern4938.1GeneralTheoryforLinearDifferentialEquations4958.2ConstantCoefficientHomogeneousLinearDifferentialEquations5058.3ThemethodofundeterminedcoefficientsAnnihilators5158.4Complex-ValuedTrialSolutions5268.5OscillationsofaMechanicalSystem529Contentsv8.6RLCCircuits5428.7TheVariationofparametersmethod5478.8ADifferentialEquationwithNonconstantCoefficients5578.9Reductionoforder5688.10ChapterReview5739SystemsofDifferentialEquations5809.1First-OrderLinearSystems5829.2VectorFormulation5889.3GeneralResultsforfirst-OrderLinearDifferentialystems5939.4VectorDifferentialEquations:NondefectiveCoefficientMatrix5999.5VectorDifferentialEquations:DefectiveCoefficientMatrix6089.6Variation-of-ParametersforLinearSystems6209.7SomeApplicationsofLinearSystemsofDifferentialEquations6259.8MatrixExponentialFunctionandSystemsofDifferentialEquations6359.9ThePhasePlaneforLinearAutonomousSystems6439.10NonlinearSystems6559.11ChapterReview66310TheLaplaceTransformandSomeElementaryApplications67010.1DefinitionoftheLaplaceTransform67010.2TheExistenceofthelaplacetransformandtheInversetransform67610.3PeriodicFunctionsandtheLaplacetransform68210.4ThetransformofderivativesandsolutionofInitial-Valueproblems68510.5TheFirstShiftingTheorem69010.6TheUnitStepFunction69510.7TheSecondShiftingTheorem69910.8ImpulsiveDrivingTerms:TheDiracDeltaFunction70610.9TheConvolutionIntegral71110.10ChapterReview71711SeriesSolutionstoLinearDifferentiaEquations72211.1AReviewofpowerseries72311.2SeriesSolutionsaboutanOrdinaryPoint73111.3TheLegendreEquation74111.4SeriesSolutionsaboutaRegularSingularPoint75011.5Frobeniustheory75911.6Bessel'sEquationofOrderp77311.7Chapterreview785ViContentsAReviewofComplexNumbers791BReviewofPartialFractions797CReviewofIntegrationTechniques804DLinearlyIndependentSolutionstox2y+xp(x)y+g(x)y=0811Answerstoodd-NumberedExercises814Index849S.W.GoodededicatesthisbooktomeganandtobiS.A.annindedicatesthisbooktoarthurandJuliannthebestparentsanyonecouldaskforPretraceLikethefirstthreeeditionsofDifferentialEquationsandLinearalgebra,thisfourtheditionisintendedforasophomorelevelcoursethatcoversmaterialinbothdifferentialequationsandlinearalgebra.Inwritingthistextwehaveendeavoredtodevelopthestudentsappreciationforthepowerofthegeneralvectorspaceframeworkinformulatingandsolvinglinearproblems.Thematerialisaccessibletoscienceandengineeringstu-dentswhohavecompletedthreesemestersofcalculusandwhobringthematurityofthatsuccesswiththemtothiscourseThistextiswrittenaswewouldnaturallyteachblendinganabundanceofexamplesandillustrations,butnotattheexpenseofadeliberateandrigoroustreatment.MostresultsareprovenindetailHowever,manyofthesecanbeskippedinfavorofamoreproblem-solvingorientedapproachdependingonthereader'sobjectives.Somereadersmayliketoincorporatesomeformoftechnology(computeralgebrasystem(CAS)orgraphingcalculator)andthereareseveralinstancesinthetextwherethepoweroftechnologyisillustratedusingtheCasMaple.Furthermore,manyexercisesetshaveproblemsthatrequiresomeformoftechnologyfortheirsolutionTheseproblemsaredesignatedwithaoIndevelopingthefourtheditionwehaveoncemorekeptmaximumflexibilityofthematerialinmind.Insodoing,thetextcaneffectivelyaccommodatethedifferentemphasesthatcanbeplacedinacombineddifferentialequationsandlinearalgebracourse,thevaryingbackgroundsofstudentswhoenrollinthistypeofcourse,andthefactthatdifferentinstitutionshavedifferentcreditvaluesforsuchacourse.Thewholetextcanbecoveredinafivecredit-hourcourse.Forcourseswithalowercredit-hourvalue,someselectivitywillhavetobeexercised.Forexample,much(orall)ofChapterImaybeomittedsincemoststudentswillhaveseenmanyofthesedifferentialequationstopicsinanearliercalculuscourse,andtheremainderofthetextdoesnotdependonthetechniquesintroducedinthischapter.Alternatively,whileoneofthemajorgoalsofthetextistointerweavethematerialondifferentialequationswiththetoolsfromlinearalgebrainasymbioticrelationshipasmuchaspossible,thecorematerialonlinearalgebraisgiveninChapters2-7sothatitispossibletousethisbookforacoursethatfocusessolelyonthelinearalgebrapresentedinthesesixchapters.ThematerialondifferentialequationsiscontainedprimarilyinChapters1and8-1l,andreaderswhohavealreadytakenafirstcourseinlinearalgebracanchoosetoproceeddirectlytothesechaptersThereareothermeansofeliminatingsectionstoreducetheamountofmaterialtobecoveredinacourse.Section2.7containsmaterialthatisnotrequiredelsewhereinthetext,Chapter3canbecondensedtoasinglesection(Section3.4)forreadersneedingonlyacursoryoverviewofdeterminants,andSections4.7,5.4,andthelatersectionsofChapters6and7couldallbereservedforasecondcourseinlinearalgebra.InChapter8Sections8.4,8.8,and8.9canbeomitted,and,dependingonthegoalsofthecourse,Sections8.5and8.6couldeitherbede-emphasizedoromittedcompletelySimilarremarksapplytoSections9.7-9.10.AtCaliforniaStateUniversity,Fullertonwehaveafourcredit-hourcourseforsophomoresthatisbasedaroundthematerialinChapters1-9viiiPrefaceMajorChangesintheFourthEditionSeveralsectionsofthetexthavebeenmodifiedtoimprovetheclarityofthepresentationandtoprovidenewexamplesthatreflectinsightfulillustrationswehaveusedinourowncoursesatCaliforniaStateUniversity,Fullerton.OthersignificantchangeswithinthetextarelistedbeleOW1.ThechapteronvectorspacesinthepreviouseditionhasbeensplitintotwochaptersChapters4and5)inthepresentedition,inordertofocusseparateattentiononvectorspacesandinnerproductspaces.Theshorterlengthofthesetwochaptersisalsointendedtomakeeachofthemlessdaunting2.Thechapteroninnerproductspaces(Chapter5)includesanewsectionprovidinganapplicationoflinearalgebratothesubjectofleastsquaresapproximation3.Thechapteronlineartransformationsinthepreviouseditionhasbeensplitintotwochapters(Chapters6and7)inthepresentedition.Chapter6isfocusedonlineartransformations,whileChapter7placesdirectemphasisonthetheoryofeigenvaluesandeigenvectors.Oncemore,readersshouldfindtheshorterchapterscoveringthesetopicsmoreapproachableandfocused4.Mostexercisesetshavebeenenlargedorrearranged.Over3,000problemsarenowcontainedwithinthetext,andmorethan600concept-orientedtrue/falseitemsarealsoincludedinthetext5.Everychapterofthebookincludesoneormoreoptionalprojectsthatallowformorein-depthstudyandapplicationofthetopicsfoundinthetext6.ThebackofthebooknowincludestheanswertoeveryTrue-FalsereviewitemcontainedinthetextAcknowledgmentsWewouldliketoacknowledgethethoughtfulinputfromthefollowingreviewersofthefourthedition:JameyBassofCityCollegeofSanFrancisco,TamarFriedmannofUniversityofrochester,andlinghaiZhangofLehighUniversityAlloftheircommentswereconsideredcarefullyinthepreparationofthetextS.A.Annin:Ioncemorethankmyparents,ArthurandJuliannAnnin,fortheirloveandencouragementinallofmyprofessionalendeavors.Ialsogratefullyacknowledgethemanystudentswhohavetakenthiscoursewithmeovertheyearsand,insodoinghaveenhancedmyloveforthesetopicsanddeeplyenrichedmycareerasaprofessorFirst-OrderDifferentiaEquations1.1DifferentialEquationsEverywhereadifferentialequationisanyequationthatinvolvesoneormorederivativesofanunknownfunction.Forexample(1.1.1dxds(S-1)(1.1.2)aredifferentialequations.Inthedifferentialequation(1.1.1)theunknownfunctionordependentvariableisy,andxistheindependentvariable;inthedifferentialequation(1.1.2)thedependentandindependentvariablesareSandt,respectively.Differentialequationssuchas(1.1.1)and(1.1.)inwhichtheunknownfunctiondependsonlyonasingleindependentvariablearecalledordinarydifferentialequations.Bycontrast,thedifferentialequationLaplace'sequation)0involvespartialderivativesoftheunknownfunctionu(x,y)oftwoindependentvariablesxandy.SuchdifferentialequationsarecalledpartialdifferentialequationsOnewayinwhichdifferentialequationscanbecharacterizedisbytheorderofthehighestderivativethatoccursinthedifferentialequationThisnumberiscalledtheorderofthedifferentialequation.Thus,(l1.1)hasordertwo,whereas(1.1.2)isafirst-orderdifferentialequation1
2024/1/26 14:10:04 16.51MB Differential Equations Linear Algebra
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近年来,随着互联网的发展以及现代的、廉价的图形用户界面和大容量存储设备的出现,信息检索(informationretrieval,IR)领域已经发生了巨大的变化,这使得传统的信息检索教材变得过时,所以很有必要通过竞赛来提高研究人员对技术的认识,trec是信息检索领域十分重要的一个竞赛,本课程是以2017年的trec竞赛为例。
2024/1/4 1:39:54 141KB trec 国科大 现代信息检索
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主开发的英文论文下载软件V4.0,软件集论文关键词检索,检索关键词过滤,论文下载,文章文字识别,论文全文译功能于一身。
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V4.0增加翻译本地pdf的功能
2023/12/19 8:32:50 34.31MB 外文 论文下载 翻译 scihub
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压缩包中包含几个加密图像检索的文献:EPCBIRAnEfficientandPrivacy-preservingContent-basedImageRetrievalSchemeinCloudComputingAPrivacy-preservingandCopy-deterrenceContent-basedImageRetrievalSchemeinCloudComputing等
2023/11/15 8:13:16 12.72MB LSH 加密图像检索 文献
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nmanydataanalysistasks,oneisoftenconfrontedwithveryhighdimensionaldata.Featureselectiontechniquesaredesignedtofindtherelevantfeaturesubsetoftheoriginalfeatureswhichcanfacilitateclustering,classificationandretrieval.Thefeatureselectionproblemisessentiallyacombinatorialoptimizationproblemwhichiscomputationallyexpensive.Traditionalfeatureselectionmethodsaddressthisissuebyselectingthetoprankedfeaturesbasedoncertainscorescomputedindependentlyforeachfeature.Theseapproachesneglectthepossiblecorrelationbetweendifferentfeaturesandthuscannotproduceanoptimalfeaturesubset.InspiredfromtherecentdevelopmentsonmanifoldlearningandL1-regularizedmodelsforsubsetselection,weproposehereanewapproach,called{\emMulti-Cluster/ClassFeatureSelection}(MCFS),forfeatureselection.Specifically,weselectthosefeaturessuchthatthemulti-cluster/classstructureofthedatacanbebestpreserved.Thecorrespondingoptimizationproblemcanbeefficientlysolvedsinceitonlyinvolvesasparseeigen-problemandaL1-regularizedleastsquaresproblem.ItisimportanttonotethatMCFScanbeappliedinsuperised,unsupervisedandsemi-supervisedcases.Ifyoufindthesealgoirthmsuseful,weappreciateitverymuchifyoucanciteourfollowingworks:PapersDengCai,ChiyuanZhang,XiaofeiHe,"UnsupervisedFeatureSelectionforMulti-clusterData",16thACMSIGKDDConferenceonKnowledgeDiscoveryandDataMining(KDD'10),July2010.BibtexsourceXiaofeiHe,DengCai,andParthaNiyogi,"LaplacianScoreforFeatureSelection",AdvancesinNeuralInformationProcessingSystems18(NIPS'05),Vancouver,Canada,2005Bibtexsource
2023/11/13 1:03:27 5KB featur
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LearnhowtomodelandtrainadvancedneuralnetworkstoimplementavarietyofComputerVisiontasksKeyFeaturesTraindifferentkindsofdeeplearningmodelfromscratchtosolvespecificproblemsinComputerVisionCombinethepowerofPython,Keras,andTensorFlowtobuilddeeplearningmodelsforobjectdetection,imageclassification,similaritylearning,imagecaptioning,andmoreIncludestipsonoptimizingandimprovingtheperformanceofyourmodelsundervariousconstraintsBookDescriptionDeeplearninghasshownitspowerinseveralapplicationareasofArtificialIntelligence,especiallyinComputerVision.ComputerVisionisthescienceofunderstandingandmanipulatingimages,andfindsenormousapplicationsintheareasofrobotics,automation,andsoon.Thisbookwillalsoshowyou,withpracticalexamples,howtodevelopComputerVisionapplicationsbyleveragingthepowerofdeeplearning.Inthisbook,youwilllearndifferenttechniquesrelatedtoobjectclassification,objectdetection,imagesegmentation,captioning,imagegeneration,faceanalysis,andmore.YouwillalsoexploretheirapplicationsusingpopularPythonlibrariessuchasTensorFlowandKeras.Thisbookwillhelpyoumasterstate-of-the-art,deeplearningalgorithmsandtheirimplementation.WhatyouwilllearnSetupanenvironmentfordeeplearningwithPython,TensorFlow,andKerasDefineandtrainamodelforimageandvideoclassificationUsefeaturesfromapre-trainedConvolutionalNeuralNetworkmodelforimageretrievalUnderstandandimplementobjectdetectionusingthereal-worldPedestrianDetectionscenarioLearnaboutvariousproblemsinimagecaptioningandhowtoovercomethembytrainingimagesandtexttogetherImplementsimilaritymatchingandtrainamodelforfacerecognitionUnderstandtheconceptofgenerativemodelsandusethemforimagegenerationDeployyourdeeplearningmodelsandoptimizethemforhighperformanceWhoThisBookIsForThisbookistargeted
2023/9/23 19:18:42 81.94MB 深度学习 tensorflow keras
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InformationRetrievalforMusicandMotion
2023/5/6 14:32:04 21.04MB Information Retrieval Music Motion
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在日常工作中,钉钉打卡成了我生活中不可或缺的一部分。然而,有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚,我总是得牢记打开钉钉应用,点击"工作台",再找到"考勤打卡"进行签到。有时候因为工作忙碌,会忘记打卡,导致考勤异常,影响当月的工作评价。而且,由于我使用的是苹果手机,有时候系统更新后,钉钉的某些功能会出现异常,使得打卡变得更加麻烦。 另外,我的家人使用的是安卓手机,他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说,每次打卡都是一次挑战。他们总是担心自己会操作失误,导致打卡失败。 为了解决这些烦恼,我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习,我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。
2024-04-09 15:03 15KB 钉钉 钉钉打卡