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

自己翻译的部分片上网络资料，原文On-ChipNetworksMarkHill,UniversityofWisconsin,MadisonMorgan&Claypool

1.TheByzantineGeneralsProblem(1982)byLeslieLamport,RobertShostakandMarshallPease2.GoTostatementsconsideredharmfull(1968)-byEdsgerW.Dijkstra3.ANoteonDistributedComputing(1994)-bySamuelC.Kendall,JimWaldo,AnnWollrathandGeoffWyant4.BigBallofMud(1999)-BrianFooteandJosephYoder5.NoSilverBulletEssenceandAccidentsofSoftwareEngineering(1987)-FrederickP.Brooks6.TheOpenClosedPrinciple(1996)-RobertC.Martin(UncleBob)7.IEEE1471-2000Arecommendedpracticeforarchitecturaldescriptionofsoftwareintensivesystems(2000)8.Harvest,Yield,andScalableTolerantSystems(1999)ArmandoFox,EricA.Brewer9.AnIntroductiontoSoftwareArchitecture(1993)-DavidGarlanandMaryShaw10.WhoNeedsanArchitect?(2003)MartinFowler

----------------------------------------------------------------------------READMEfilefornmfpack----------------------------------------------------------------------------PatrikHoyerAugust03,2006Version1.1ThisMatlabpackageimplementsandtestsvariousversionsofnon-negativematrixfactorization(NMF).Thispackageisassociatedwiththearticle:PatrikOHoyer.'Non-negativematrixfactorizationwithsparsenessconstraints'JournalofMachineLearningResearch5:1457-1469,

数据集目录：2dplanes.arffabalone.arffailerons.arffAmazon_initial_50_30_10000.arffanneal.arffanneal.ORIG.arffarrhythmia.arffaudiology.arffaustralian.arffauto93.arffautoHorse.arffautoMpg.arffautoPrice.arffautos.arffauto_price.arffbalance-scale.arffbank.arffbank32nh.arffbank8FM.arffbaskball.arffbodyfat.arffbolts.arffbreast-cancer.arffbreast-w.arffbreastTumor.arffbridges_version1.arffbridges_version2.arffcal_housing.arffcar.arffcholesterol.arffcleveland.arffcloud.arffcmc.arffcolic.arffcolic.ORIG.arffcontact-lenses.arffcpu.arffcpu.with.vendor.arffcpu_act.arffcpu_small.arffcredit-a.arffcredit-g.arffcylinder-bands.arffdelta_ailerons.arffdelta_elevators.arffdermatology.arffdetroit.arffdiabetes.arffdiabetes_numeric.arffechoMonths.arffecoli.arffelevators.arffelusage.arffeucalyptus.arffeye_movements.arfffishcatch.arffflags.arfffried.arfffruitfly.arffgascons.arffglass.arffgrub-damage.arffheart-c.arffheart-h.arffheart-statlog.arffhepatitis.arffhouse_16H.arffhouse_8L.arffhousing.arffhungarian.arffhypothyroid.arffionosphere.arffiris.2D.arffiris.arffkdd_coil_test-1.arffkdd_coil_test-2.arffkdd_coil_test-3.arffkdd_coil_test-4.arffkdd_coil_test-5.arffkdd_coil_test-6.arffkdd_coil_test-7.arffkdd_coil_train-1.arffkdd_coil_train-3.arffkdd_coil_train-4.arffkdd_coil_train-5.arffkdd_coil_train-6.arffkdd_coil_train-7.arffkdd_el_nino-small.arffkdd_internet_usage.arffkdd_ipums_la_97-small.arffkdd_ipums_la_98-small.arffkdd_ipums_la_99-small.arffkdd_JapaneseVowels_test.arffkdd_JapaneseVowels_train.arffkdd_synthetic_control.arffkdd_SyskillWebert-Bands.arffkdd_SyskillWebert-BioMedical.arffkdd_SyskillWebert-Goats.arffkdd_SyskillWebert-Sheep.arffkdd_UNIX_user_data.arffkin8nm.arffkr-vs-kp.arfflabor.arfflandsat_test.arfflandsat_train.arffletter.arffliver-disorders.arfflongley.arfflowbwt.arfflung-cancer.arfflymph.arffmachine_cpu.arffmbagrade.arffmeta.arffmfeat-factors.arffmfeat-fourier.arffmfea

《快学Scala》英文第二版：ScalafortheImpatientSecondEditionCayS.Horstmann目录：1THEBASICSA111.1TheScalaInterpreter11.2DeclaringValuesandVariables41.3Co妹妹onlyUsedTypes51.4ArithmeticandOperatorOverloading61.5MoreaboutCallingMethods81.6TheapplyMethod91.7Scaladoc10Exercises152CONTROLSTRUCTURESANDFUNCTIONSA1172.1ConditionalExpressions182.2StatementTermination192.3BlockExpressionsandAssignments20viiContents2.4InputandOutput212.5Loops222.6AdvancedforLoops242.7Functions252.8DefaultandNamedArgumentsL1262.9VariableArgumentsL1262.10Procedures282.11LazyValuesL1282.12Exceptions29Exercises313WORKINGWITHARRAYSA1353.1Fixed-LengthArrays353.2Variable-LengthArrays:ArrayBuffers363.3TraversingArraysandArrayBuffers373.4TransformingArrays383.5Co妹妹onAlgorithms403.6DecipheringScaladoc413.7MultidimensionalArrays423.8InteroperatingwithJava43Exercises444MAPSANDTUPLESA1474.1ConstructingaMap484.2AccessingMapValues484.3UpdatingMapValues494.4IteratingoverMaps504.5SortedMaps504.6InteroperatingwithJava504.7Tuples514.8Zipping52Exercises52viiiContents5CLASSESA1555.1SimpleClassesandParameterlessMethods555.2PropertieswithGettersandSetters565.3PropertieswithOnlyGetters595.4Object-PrivateFields605.5BeanPropertiesL1615.6AuxiliaryConstructors625.7ThePrimaryConstructor635.8NestedClassesL166Exercises686OBJECTSA1716.1Singletons716.2CompanionObjects726.3ObjectsExtendingaClassorTrait736.4TheapplyMethod736.5ApplicationObjects746.6Enumerations75Exercises777PACKAGESANDIMPORTSA1797.1Packages807.2ScopeRules817.3ChainedPackageClauses837.4Top-of-FileNotation837.5PackageObjects837.6PackageVisibility847.7Imports857.8ImportsCanBeAnywhere857.9RenamingandHidingMembers867.10ImplicitImports86Exercises87ixContents8INHERITANCEA1918.1ExtendingaClass918.2OverridingMethods928.3TypeChecksandCasts938.4ProtectedFieldsandMethods948.5SuperclassConstruction948.6OverridingFields958.7AnonymousSubclasses978.8AbstractClasses978.9AbstractFields978.10ConstructionOrderandEarlyDefinitionsL3988.11TheScalaInheritanceHierarchy1008.12ObjectEqualityL11028.13ValueClassesL2103Exercises1059FILESANDREGULAREXPRESSIONSA11099.1ReadingLines1099.2ReadingCharacters1109.3ReadingTokensandNumbers1119.4ReadingfromURLsandOtherSources1119.5ReadingBinaryFiles1129.6WritingTextFiles1129.7VisitingDirectories1129.8Serialization1139.9ProcessControlA21149.10RegularExpressions1169.11RegularExpressionGroups117Exercises11810TRAITSL112110.1WhyNoMultipleInheritance?12110.2TraitsasInterfaces12310.3TraitswithConcreteImplementations124xContents10.4ObjectswithTraits12510.5LayeredTraits12510.6OverridingAbstractMethodsinTraits12710.7TraitsforRichInterfaces12710.8ConcreteFieldsinTraits12810.9AbstractFieldsinTraits13010.10TraitConstructionOrder13010.11InitializingTraitFields13210.12TraitsExtendingClasses13310.13SelfTypesL213410.14WhatHappensundertheHood135Exercises13711OPERATORSL114111.1Identifiers14211.2InfixOperators14311.3UnaryOperators14311.4AssignmentOperators14411.5Precedence14411.6Associativity14511.7TheapplyandupdateMethods14611.8ExtractorsL214711.9ExtractorswithOneorNoArgumentsL214911.10TheunapplySeqMethodL214911.11DynamicInvocationL2150Exercises15312HIGHER-ORDERFUNCTIONSL115712.1FunctionsasValues15712.2AnonymousFunctions15912.3FunctionswithFunctionParameters16012.4ParameterInference16012.5UsefulHigher-OrderFunctions16112.6Closures162xiContents12.7SAMConversions16312.8Currying16412.9ControlAbstractions16612.10ThereturnExpression167Exercises16813COLLECTIONSA217113.1TheMainCollectionsTraits17213.2MutableandI妹妹utableCollections17313.3Sequences17413.4Lists17513.5Sets17713.6OperatorsforAddingorRemovingElements17813.7Co妹妹onMethods18013.8MappingaFunction18213.9Reducing,Folding,andScanningA318413.10Zipping18713.11Iterators18813.12StreamsA318913.13LazyViewsA319013.14InteroperabilitywithJavaCollections19113.15ParallelCollections193Exercises19414PATTERNMATCHINGANDCASECLASSESA219714.1ABetterSwitch19814.2Guards19914.3VariablesinPatterns19914.4TypePatterns20014.5MatchingArrays,Lists,andTuples20114.6Extractors20214.7PatternsinVariableDeclarations20314.8PatternsinforExpressions20414.9CaseClasses205xiiContents14.10ThecopyMethodandNamedParameters20514.11InfixNotationincaseClauses20614.12MatchingNestedStructures20714.13AreCaseClassesEvil?20814.14SealedClasses20914.15SimulatingEnumerations20914.16TheOptionType21014.17PartialFunctionsL2211Exercises21215ANNOTATIONSA221515.1WhatAreAnnotations?21615.2WhatCanBeAnnotated?21615.3AnnotationArguments21715.4AnnotationImplementations21815.5AnnotationsforJavaFeatures21915.5.1JavaModifiers21915.5.2MarkerInterfaces22015.5.3CheckedExceptions22015.5.4VariableArguments22115.5.5JavaBeans22115.6AnnotationsforOptimizations22215.6.1TailRecursion22215.6.2JumpTableGenerationandInlining22315.6.3ElidingMethods22415.6.4SpecializationforPrimitiveTypes22515.7AnnotationsforErrorsandWarnings226Exercises22716XMLPROCESSINGA222916.1XMLLiterals23016.2XMLNodes23016.3ElementAttributes23216.4EmbeddedExpressions233xiiiContents16.5ExpressionsinAttributes23416.6Unco妹妹onNodeTypes23516.7XPath-likeExpressions23516.8PatternMatching23716.9ModifyingElementsandAttributes23816.10TransformingXML23916.11LoadingandSaving23916.12Namespaces242Exercises24317FUTURESA224717.1RunningTasksintheFuture24817.2WaitingforResults25017.3TheTryClass25117.4Callbacks25117.5ComposingFutureTasks25217.6OtherFutureTransformations25517.7MethodsintheFutureObject25617.8Promises25817.9ExecutionContexts260Exercises26018TYPEPARAMETERSL226518.1GenericClasses26618.2GenericFunctions26618.3BoundsforTypeVariables26618.4ViewBounds26818.5ContextBounds26818.6TheClassTagContextBound26918.7MultipleBounds26918.8TypeConstraintsL326918.9Variance27118.10Co-andContravariantPositions272xivContents18.11ObjectsCan’tBeGeneric27418.12Wildcards275Exercises27519ADVANCEDTYPESL227919.1SingletonTypes28019.2TypeProjections28119.3Paths28219.4TypeAliases28319.5StructuralTypes28319.6CompoundTypes28419.7InfixTypes28519.8ExistentialTypes28619.9TheScalaTypeSystem28719.10SelfTypes28819.11DependencyInjection28919.12AbstractTypesL329119.13FamilyPolymorphismL329319.14Higher-KindedTypesL3296Exercises29920PARSINGA330320.1Gra妹妹ars30420.2CombiningParserOperations30520.3TransformingParserResults30720.4DiscardingTokens30820.5GeneratingParseTrees30920.6AvoidingLeftRecursion31020.7MoreCombinators31120.8AvoidingBacktracking31420.9PackratParsers31420.10WhatExactlyAreParsers?31520.11RegexParsers316Contentsxv20.12Token-BasedParsers31720.13ErrorHandling319Exercises32021IMPLICITSL332321.1ImplicitConversions32421.2UsingImplicitsforEnrichingExistingClasses32421.3ImportingImplicits32521.4RulesforImplicitConversions32621.5ImplicitParameters32821.6ImplicitConversionswithImplicitParameters32921.7ContextBounds32921.8TypeClasses33121.9Evidence33321.10The@implicitNotFoundAnnotation33421.11CanBuildFromDemystified334Exercises336Index338

圣马特奥县增强人命方式传单舆图这是在传单中建树的约莫收集舆图，使用户无需GIS软件或者本领就可查验可果真患上到的效率。
它使用Esri插件来使用矢量图块。
该舆图表普通ParksConservancyArcGISOnline结构页面上果真托管的矢量图块效率。
瓷砖效率是圣马特奥县增强型生涯舆图，是圣马特奥县的26类土地使用以及土地拆穿包围图，反映了2018年夏日的景不雅情景。
在2021年宣告小规模植被图时举行更新以及定稿。
增强的人命方式图是小规模植被图的底子输入。
大雅比例的植被图将比增强的人命方式图具备更多的植物品种。
大雅比例图中的木质植被群落将被映射到国度植被分类的联盟级别。
无关更多信息，请查阅

Thisisthefirstdefinitiveintroductiontobehavioraleconomicsaimedatadvancedundergraduateandpostgraduatestudents.Authoritative,cuttingedge,yetaccessible,itguidesthereaderthroughtheoryandevidence,providingengagingandrelevantapplicationsthroughout.Itisdividedintoninepartsand24chapters:PartIisonbehavioraleconomicsofrisk,uncertainty,andambiguity.Theevidenceagainstexpectedutilitytheoryisexamined,andthebehavioralresponseisoutlined;thebestempiricallysupportedtheoryisprospecttheory.PartIIconsidersother-regardingpreferences.Theevidencefromexperimentalgamesonhumansocialityisgiven,followedbymodelsandapplicationsofinequityaversion,intentionsbasedreciprocity,conditionalcooperation,humanvirtues,andsocialidentity.PartIIIisontimediscounting.Itconsiderstheevidenceagainsttheexponentialdiscountedutilitymodelanddescribesseveralbehavioralmodelssuchashyperbolicdiscounting,attributebasedmodelsandthereferencetimetheory.PartIVdescribestheevidenceonclassicalgametheoryandconsidersseveralmodelsofbehavioralgametheory,includinglevel-kandcognitivehierarchymodels,quantalresponseequilibrium,andpsychologicalgametheory.PartVconsidersbehavioralmodelsoflearningthatincludeevolutionarygametheory,classicalmodelsoflearning,experienceweightedattractionmodel,learningdirectiontheory,andstochasticsocialdynamics.PartVIstudiestheroleofemotions;amongothertopicsitconsidersprojectionbias,temptationpreferences,happinesseconomics,andinteractionbetweenemotionsandcognition.PartVIIconsidersboundedrationality.Thethreemaintopicsconsideredarejudgmentheuristicsandbiases,mentalaccounting,andbehavioralfinance.PartVIIIconsidersbehavioralwelfareeconomics;themaintopicsaresoftpaternalism,andchoice-basedmeasuresofwelfare.Finally,PartIXgivesanabbreviatedtast

scons-2.3.1.tar.gzopenwrt中用到的源码之一，假如openwrt下载不下来，请下载本网站的！

Thisbookintroducesyoutotheworldofdatastructuresandalgorithms.Datastructuredefinesthewaydataisarrangedincomputermemoryforfastandefficientaccesswhilealgorithmisasetofinstructiontosolveproblemsbymanipulatingthesedatastructures.DataStructuresalgorithmsInGoHemantjainCopyrightoHemantJain2017.AllRightReservedHemantJainassertsthemoralrighttobeidentifiedasheauthorofthisworkAllrightsreserved.Nopartofthispublicationmaybereproduced,storedinorintroducedintoaretrievalsystem,ortransmitted,inanyform,orbyanymeans(electrical,mechanical,photocopying,recordingorotherwise)withoutthepriorwrittenpermissionoftheauthor,exceptinthecaseofverybriefquotationsembodiedincriticalreviewsandcertainothernonco妹妹ercialusespermittedbycopyrightlaw.AnypersonwhodoesanyunauthorizedactinrelationtothispublicationmaybeliabletocriminalprosecutionandcivilclaimsfordamagesACKNOWLEDGEMENTTheauthorisverygratefultoGodALMIGhTYforhisgraceandblessingDeepestgratitudeforthehelpandsupportofmybrotherDrSumantJain.ThisbookwouldnothavebeenpossiblewithoutthesupportandencouragementheprovidedIwouldliketoexpressprofoundgratitudetomyguide/myfriendNaveenKaushikforhisinvaluableencouragement,supervisionandusefulsuggestionthroughoutthisbookwritingwork.hissupportandcontinuousguidanceenablemetocompletemyworksuccessfuFinallyyetimportantly,IamthankfultoLoveSinghal,AnilberryandotherswhohelpedmedirectlyorindirectlyincompletingthisbookHemantJainTABLEOFCONTENTSACKNOWLEDGEMENTTABLEOFCONTENTSChAPTERO:HOWTOUSETHISBOOKWHATTHISBOOKISABOUTPREPARATIONPLANSSUMMARYChAPTER1:NTRODUCTION-PROGRAMMIINGOVERVIEWINTRODUCTIONFIRSTGOPROGRAMvariablesconstantsBASICDATATYPESSTRINGCONDITIONSANDLOOPSFUNCTIONPARAMETERPASSINGCALLBYVALUEPOINTERSPARAMETERPASSING.CALLBYPOINTER/REFERENCESTRUCTURESMETHODSINTERFACEARRaySLICEMAP/DICTIONARYARRAYINTERVIEWQUESTIONSCONCEPTOFSTACKSYSTEMSTACKANDMETHODCALLSRECURSIVEFUNCTIONEXERCISESCHAPTER2:ALGORITHMSANALYSISINTRODUCTIONALGORITHMASYMPTOTICANALYSISBIG-ONOTATIONOMEGA-QNOTATIONTHETA-⊙NOTATIONCOMPLEXITYANALYSISOFALGORITHMSTIMECOMPLEXITYORDERDERIVINGTHERUNTIMEFUNCTIONOFANALGORITHMTIMECOMPLEXITYEXAMPLESMASTERTHEOREMMODIFIEDMASTERTHEOREMEXERCISECHAPTER3:APPROACHTOSOLVEALGORITHMDESIGNPROBLEMSINTRODUCTIONCONSTRAINTSIDEAGENERATIONCOMPLEXITIESCODINGTESTINGEⅹAMPLESUMMARYChaPTER4:ABSTRACTDATATYPEGOCollECtIonsABSTRACTDATATYPE(ADTDATA-STRUCTUREGOCOLLECTIONFRAMEWORKACKQUEUETREEBINARYTREEBINARYSEARCHTREES(BSTPRIORITYQUEUE(HEAPHASH-TABLEDICTIONARY/SYMBOLTABLEGRAPHSGRAPHALGORITHMSSORTINGALGORITHMSCOUNTINGSORTENDNOTEchaPTER5:SEARCHINGINTRODUCTIONWHYSEARCHING?DIFFERENTSEARCHINGALGORITHMSLINEARSEARCH-UNSORTEDINPUTLINEARSEARCH-SORTEDBINARYSEARCHSTRINGSEARCHINGALGORITHMSHASHINGANDSYMBOLTABLESHOWSORTINGISUSEFULINSELECTIONALGORITHM?PROBLEMSINSEARCHINGEXERCISECHAPTER6:SORTINGINTRODUCTIONTYPEOFSORTINGBUBBLE-SORTMODIFIED(IMPROVED)BUBBLE-SORTINSERTION-SORTSELECTION-SORTMERGE-SORTQUICK-SORTQUICKSELECTBUCKETSORTGENERALIZEDBUCKETSORTHEAP-SORTTREESORTINGEXTERNALSORT(EXTERNALMERGE-SORTICOMPARISONSOFTHEVARIOUSSORTINGALGORITHMSSELECTIONOFBESTSORTINGALGORITHMEXERCISEChAPTER7:LINKEDLISTINTRODUCTIONLINKEDLISTTYPESOFLINKEDLISTSINGLYLINKEDLISTDOUBLYLINKEDLISTCIRCULARLINKEDLISTDOUBLYCIRCULARLISTEXERCISEchapter8:STACKINTRODUCTIONTHESTACKABSTRACTDATATYPESTACKUSINGSLICESSTACKGENERICIMPLEMENTATIONSTACKUSINGLINKEDLISTPROBLEMSINSTACKUSESOFSTACKEXERCISEchaPTER9:QUEUEINTRODUCTIONTHEQUEUEABSTRACTDATATYPEQUEUEUSINGLISTQUEUEUSINGLINKEDLISTPROBLEMSINQUEUEEXERCISECHAPTER10:TREEINTRODUCTIONTERMINOLOGYINTREEBINARYTREETYPESOFBINARYTREESPROBLEMSINBINARYTREEBINARYSEARCHTREE(BST)PROBLEMSINBINARYSEARCHTREE(BSTISEGMENTTREEAVLTREESRED-BLACKTREESPLAYTREEB-TREEB+TREEB*TREEEXERCISECHAPTERIl:PRIORITYQUEUEINTRODUCTIONTYPESOFHEAPHEAPADTOPERATIONSOPERATIONONHEAPHEAP-SORTUSESOFHEAPPROBLEMSINHEAPPRIORITYQUEUEGENERICIMPLEMENTATION.PRIORITYQUEUEUSINGHEAPFROMCONTAINER.EXERCISECHAPTER12:HASH-TABLEINTRODUCTIONHASH-TABLEHASHIINGWITHOPENADDRESSINGHASHINGWITHSEPARATECHAININGPROBLEMSINHASHINGEXERCISEChaPTER13:GRAPHSINTRODUCTIONGRAPHREPRESENTATIONADJACENCYMATRIXADJACENCYLISTGRAPHTRAVERSALSDEPTHFIRSTTRAVERSALBREADTHFIRSTTRAVERSALPROBLEMSINGRAPHDIRECTEDACYCLICGRAPHTOPOLOGICALSORTMINIMUMSPANNINGTREES(MST)SHORTESTPATHALGORITHMSINGRAPHEXERCISEChAPTER14:STRINGALGORITHMSTRODUCTIONSTRINGMATCHINGDICTIONARY/SYMBOLTABLEPROBLEMSINSTRINGEXERCISECHAPTER15:ALGORITHMDESIGNTECHNIQUESNTRODUCTIONBRUTEFORCEALGORITHMGREEDYALGORITHMDIVIDE-AND-CONQUER,DECREASE-AND-CONQUERDYNAMICPROGRAMMINGREDUCTIONTRANSFORM-AND-CONQUERBACKTRACKINGBRANCH-AND-BOUNDAALGORITHMCONCLUSIONCHAPTER16:BRUTEFORCEALGORITHMINTRODUCTIONPROBLEMSINBRUTEFORCEALGORITHMCONCLUSIONCHAPTER17:GREEDYALGORITHMINTRODUCTIONPROBLEMSONGREEDYALGORITHMCHAPTER18:DIVIDE-AND-CONQUER,DECREASE-AND-CONQUER

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。