著名的Netflix智能推荐百万美金大奖赛使用是数据集.因为竞赛关闭,Netflix官网上已无法下载.Netflixprovidedatrainingdatasetof100,480,507ratingsthat480,189usersgaveto17,770movies.Eachtrainingratingisaquadrupletoftheform.TheuserandmoviefieldsareintegerIDs,whilegradesarefrom1to5(integral)stars.[3]Thequalifyingdatasetcontainsover2,817,131tripletsoftheform,withgradesknownonlytothejury.Aparticipatingteam'salgorithmmustpredictgradesontheentirequalifyingset,buttheyareonlyinformedofthescoreforhalfofthedata,thequizsetof1,408,342ratings.Theotherhalfisthetestsetof1,408,789,andperformanceonthisisusedbythejurytodeterminepotentialprizewinners.Onlythejudgesknowwhichratingsareinthequizset,andwhichareinthetestset—thisarrangementisintendedtomakeitdifficulttohillclimbonthetestset.Submittedpredictionsarescoredagainstthetruegradesintermsofrootmeansquarederror(RMSE),andthegoalistoreducethiserrorasmuchaspossible.Notethatwhiletheactualgradesareintegersintherange1to5,submittedpredictionsneednotbe.Netflixalsoidentifiedaprobesubsetof1,408,395ratingswithinthetrainingdataset.Theprobe,quiz,andtestdatasetswerechosentohavesimilarstatisticalproperties.Insummary,thedatausedintheNetflixPrizelooksasfollows:Trainingset(99,072,112ratingsnotincludingtheprobeset,100,480,507includingtheprobeset)Probeset(1,408,395ratings)Qualifyingset(2,817,131ratings)consistingof:Testset(1,408,789ratings),usedtodeterminewinnersQuizset(1,408,342ratings),usedtocalculateleaderboardscoresForeachmovie,titleandyearofreleaseareprovidedinaseparatedataset.Noinformationatallisprovidedaboutusers.Inordertoprotecttheprivacyofcustomers,"someoftheratingdataforsomecustomersinthetrainingandqualifyin

WiththedevelopmentofMEMSsensors,pedestriannavigationhasbeenapopularresearch.Thepaperrealizesstepdetectionandestimationforsteplengthbyonlyverticalaccelerometer.Itdeterminesinitialheadingusingaccelerometersandmagnetometersandcalculateslatterheadingusinggyroscopesbystrap-downinertialnavigationalgorithm.Afterwards,itachievesthepositioninggoalforpedestrianusingdeadreckoningmethod.Definitively,theeffectivenessofthisapproachisdemonstrated

Badclimatechangemaygreatlyincreasethefragilityofthecountry.Howtoevaluatetheimpactofclimatechangeandmitigatetheimpactofclimatechangehasbecomeanurgentproblem.Withregardtotaskone,adataenvelopmentanalysis(DEA)modelisestablishedtogetthecountry'sfragility.Firstofall,weselected4climatefactorsasinputindicatorsand5outputindicators.Then,weusetheentropymethodtodeterminetheweightandthenthenationalvulnerabilityisdivided.Atthesametime,wegettheconclusionthattemperatureaffectsGDPandthetimesofarmedconflictdirectlyandaffectsthefragilityindirectly.Inviewoftasktwo,wechooseSomaliaasanobjectofstudy.First,alltheindexesaredividedinto5levelsbythemethodofclusteranalysis.Second,weselect10countriesincludingSomalia,tosolvethedecisionunitmatrix.Then,usingthemodeloftheproblemone,itisfoundthattheincreaseintemperatureandrainfallwillcausethenationalvulnerabilitytoriseanddecrease,respectively.Finally,weassign4climateindicatorsto0ofthedecisionunits,anddrawtheconclusionthatnationalvulnerabilitywillbereducedwithouttheimpactofclimatefactors.Whenitcomestotaskthree,weusetheroughsettheorytoreducetheoutputindextothenumberofarmedconflicts.Then,weusetheBPneuralnetworkmodeltopredicttheconclusion:Thereisasignificantincreaseinfragilityincasesofmuchmorearmedconflictandabnormaltemperature.Whentheaverageannualarmedconflictiscertain,thenationalvulnerabilityindexwillfaceanincreasingturningpointatthetemperatureof10.01andtherainfallof1823mm.Astotaskfour,threepoliciesonenergyreductionandemissionreductionissuedbythegovernmenthavebeenselected,andamodelofcarboncycleisestablished.TakingChinaasanexample,wecalculatetheextentofthechangeoftheaveragetemperaturebyreducingthecarbondioxideemiss

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

Formanycomputervisionproblems,themosttimeconsumingcomponentconsistsofnearestneighbormatchinginhigh-dimensionalspaces.Therearenoknownexactalgorithmsforsolvingthesehigh-dimensionalproblemsthatarefasterthanlinearsearch.Approximatealgorithmsareknowntoprovidelargespeedupswithonlyminorlossinaccuracy,butmanysuchalgorithmshavebeenpublishedwithonlyminimalguidanceonselectinganalgorithmanditsparametersforanygivenproblem.Inthispaper,wedescribeasystemthatanswersthequestion,“Whatisthefastestapproximatenearest-neighboralgorithmformydata?”Oursystemwilltakeanygivendatasetanddesireddegreeofprecisionandusethesetoautomaticallydeterminethebestalgorithmandparametervalues.Wealsodescribeanewalgorithmthatappliesprioritysearchonhierarchicalk-meanstrees,whichwehavefoundtoprovidethebestknownperformanceonmanydatasets.Aftertestingarangeofalternatives,wehavefoundthatmultiplerandomizedk-dtreesprovidethebestperformanceforotherdatasets.Wearereleasingpublicdomaincodethatimplementstheseapproaches.Thislibraryprovidesaboutoneorderofmagnitudeimprovementinquerytimeoverthebestpreviouslyavailablesoftwareandprovidesfullyautomatedparameterselection.

KDD2018滴滴派单算法论文。
Wepresentanovelorderdispatchalgorithminlarge-scaleon-demandride-hailingplatforms.Whiletraditionalorderdispatchapproachesusuallyfocusonimmediatecustomersatisfaction,theproposedalgorithmisdesignedtoprovideamoreefficientwaytooptimizeresourceutilizationanduserexperienceinaglobalandmorefarsightedview.Inparticular,wemodelorderdispatchasalarge-scalesequentialdecision-makingproblem,wherethedecisionofassigninganordertoadriverisdeterminedbyacentralizedalgo-rithminacoordinatedway.Theproblemissolvedinalearningandplanningmanner:1)basedonhistoricaldata,wefirstsummarizedemandandsupplypatternsintoaspatiotemporalquantization,eachofwhichindicatestheexpectedvalueofadriverbeinginaparticularstate;2)aplanningstepisconductedinreal-time,whereeachdriver-order-pairisvaluedinconsiderationofbothimmedi-aterewardsandfuturegains,andthendispatchissolvedusingacombinatorialoptimizingalgorithm.ThroughextensiveofflineexperimentsandonlineABtests,theproposedapproachdeliversremarkableimprovementontheplatform’sefficiencyandhasbeensuccessfullydeployedintheproductionsystemofDidiChuxing.

leetcodepython题解，包含大量leetcode题目的解法，源代码，python实现CourseSchedule21.4.4Numberofislands14.5HeapsMergeKSortedLinkedLists1.5.1KthLargestElementinanArray1.5.2Arrays1.62sum‖l1.62SumⅢ1.6.2ContainsDuplicate1.6.3RotateArray1.643SumSmaller1.653Sumclosest1.663Sum1.6.7TwoSum1.68PlusOne1.6.9BestTimetoBuyandSellStock1.6.10Shortestworddistance1.6.11Movezeroes1.6.12ContainsDuplicate1.6.13MajorityElement1.6.14RemoveDuplicatesfromSortedArray1.6.15NestedListWeightSum1.6.16NestedListWeightedSumIl1.6.17Removeelement1.6.18IntersectionofTwoArraysll1.6.19MergeSortedArrays1.6.20ReverseVowelsofaString1.6.21IntersectionofTwoArrays1.6.22Containerwithmostwater1.6.23ProductofArrayExceptSelf1.6.24TrappingRainWater1.6.25MaximumSubarray1.6.26BestTimetoBuyandSellStockIl1.6.27FindMinimuminRotatedSortedArray1.6.28Pascal'sTriangle1.6.29Pascal'sTriangle‖l1.6.30SummaryRanges1.6.31MissingNumber1.6.32StringsValidAnagram1.7.1Validpalindrome1.7.2WordPattern1.7.3ValidParentheses1.7.4IsomorphicStrings1.7.5ReverseString1.7.6BitManipulationSumofTwoIntegers18.1SingleNumber18.2Singlenumber‖18.3SingleNumberIll1.8.4Maths1.9ReverseInteger1.9.1Palindromenumber19.2Pow(x,n)19.3Subsets1.94Subsets‖195FractiontoRecurringDecimal19.6Excelsheetcolumnnumber19.7Excelsheetcolumntitle19.8FactorialTrailingzeros199HappyNumber1.9.10Countprimes1.9.11Plusone19.12DivideTwoIntegers19.13MultiplyStrings1.9.14MaxPointsonaline1.9.15ProductofArrayExceptSelf19.16Powerofthree19.17IntegerBreak1.9.18Poweroffour9.19Adddigits1.9.20UglyNumber1.9.21glyNumberll1.9.22SuperUglyNumber19.23FindKpairswithsmallestsums1.924SelfCrossing1.9.25Paintfence1.9.26Bulbswitcher19.27Nimgame1.9.28Matrix1.10RotateImage1.10.1SetmatrixZeroes1.10.2Searcha2DMatrix1.10.3Searcha2dMatrixl1.10.4SpiralMatrix1.10.5SpiralMatrix‖l1.10.6DesignLRUCache1.11.1IntroductionMyLeetcodeSolutionsinPythonThisbookwillcontainmysolutionsinPythontotheleetcodeproblems.Currently,willjusttrytoposttheacceptedsolutions.TheplanistoeventuallyincludedetailedexplanationsofeachandeverysolutionamdoingthisjustforfunLinkedListCycleLinkedListCvcleGivenalinkedlist,determineifithasacycleinitFollowup:Canyousolveitwithoutusingextraspace?Url:https://leetcode.com/problems/linked-list-cycle/Definitionforsingly-linkedlistclassListNodeobject)###definit(self,x)self,val=xself,nextNoneclassSolution(object):defhasCycle(self,head)IItypehead:ListNodertype:boolIIIIifhead=nonereturnfalseelsefastheadslow=headWhilefastnoneandfast.nextnonesloW=slownextfastfast.nextnextiffast=slow:breaki千fastNoneorfast.next=nonereturnFalseeliffast=slowreturntruereturnfalseLinkedListCycleReverseLinkedListReverseLinkedlistReverseasinglylinkedlistUrl:https://eetcode.com/problems/reverse-linked-list/definitionforsingly-linkedlist#tclassListNode(object):##def-init(self,x)self.∨al=xselfnextnoneclassSolution(object):defreverseList(self,head)11IIl1typehead:ListNodertype:ListNodeifhead=nonereturnnoneelifhead!=noneandheadnext=nonereturnheadelsetempNonenextnodenoneWhileheadNonenextnodeheadnexthead.nexttemptemp=headheadnextnodereturntempDeletenodeinalinkedlistDeletenodeinalinkedlistWriteafunctiontodeleteanode(exceptthetail)inasinglylinkedlist,givenonlyaccesstothatnodeSupposedthelinkedlistis1->2->3->4andyouaregiventhethirdnodewithvalue3,thelinkedlistshouldbecome1->2->4aftercallingyourfunctionUrl:https://eetcode.com/problems/delete-node-in-a-linked-list/Definitionforsingly-linkedlistclassListNode(object):#def-init(self,x)#self,valxself,nextNoneclasssolution(object):defdeleteNode(self,node):IIlIItypenode:ListNodertype:voidDonotreturnanythingmodifynodein-placeinsteadI111fnode=nonepasse⊥se:nextnodenode.nextnodevalnextnodevalnode.nextnextnode,next

联络人作者-谢尔盖·彭科夫斯基（SergeyPenkovsky）（）网站-https:总览Erlymon是适用于各种GPS跟踪设备的开源GPS跟踪系统。
执照GNUAfferoGeneralPublicLicense,Version3.0Thisprogramisfreesoftware:youcanredistributeitand/ormodifyitunderthetermsoftheGNUGeneralPublicLicenseaspublishedbytheFreeSoftwareFoundati

工程技术类的期刊缩写列表，可以导入endnotetermlist，来自不列颠哥伦比亚大学图书馆网站（多达6500多期刊），更新自2018年10月

计算机组成与设计第五版英文书+答案Webelievethatlearningincomputerscienceandengineeringshouldreflectthecurrentstateofthefield,aswellasintroducetheprinciplesthatareshapingcomputing.Wealsofeelthatreadersineveryspecialtyofcomputingneedtoappreciatetheorganizationalparadigmsthatdeterminethecapabilities,performance,energy,and,ultimately,thesuccessofcomputersystems.Moderncomputertechnologyrequiresprofessionalsofeverycomputingspecialtytounderstandbothhardwareandsoftware.Theinteractionbetweenhardwareandsoftwareatavarietyoflevelsalsooffersaframeworkforunderstandingthefundamentalsofcomputing.Whetheryourprimaryinterestishardwareorsoftware,computerscienceorelectricalengineering,thecentralideasincomputerorganizationanddesignarethesame.Thus,ouremphasisinthisbookistoshowtherelationshipbetweenhardwareandsoftwareandtofocusontheconceptsthatarethebasisforcurrentcomputers.Therecentswitchfromuniprocessortomulticoremicroprocessorsconfirmedthesoundnessofthisperspective,givensincethefirstedition.Whileprogrammerscouldignoretheadviceandrelyoncomputerarchitects,compilerwriters,andsiliconengineerstomaketheirprogramsrunfasterorbemoreenergy-efficientwithoutchange,thateraisover.Forprogramstorunfaster,theymustbecomeparallel.Whilethegoalofmanyresearchersistomakeitpossibleforprogrammerstobeunawareoftheunderlyingparallelnatureofthehardwaretheyareprogramming,itwilltakemanyyearstorealizethisvision.Ourviewisthatforatleastthenextdecade,mostprogrammersaregoingtohavetounderstandthehardware/softwareinterfaceiftheywantprogramstorunefficientlyonparallelcomputers.Theaudienceforthisbookincludesthosewithlittleexperienceinassemblylanguageorlogicdesignwhoneedtounderstandbasiccomputerorganizationaswellasreaderswithbackgroundsinassemblyl

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。