英文版高级数据结构PPT，内容包括：Amortizedcomplexity(Web)Externalsorting&tournamenttrees(Sections7.10.1,7.10.2,and5.8)Buffering(Section7.10.3)Rungeneration&optimalmergepatterns(Huffmantrees)(Sections7.10.4and7.10.5)Priorityqueuesandmerging(Section5.6)Leftisttrees,BinomialheapsandFibonacciheaps(Sections9.2,9.3,and9.4)Pairingheaps(Section9.5)Doubleendedpriorityqueues(Sections9.6and9.7,Web)Staticanddynamicweightedbinarysearchtrees(Section10.1)AVL-trees(Section10.2)Red-blacktrees(Section10.3)Splaytrees(Section10.4)B-,B+andB*-trees(Sections11.1-11.3)Triesanddigitalsearchtrees(Sections12.1-12.3)Triesandpacketforwarding(Section12.5)Suffixtrees(Section12.4)Bloomfilters(Section8.4)Segmenttrees(readings)IntervaltreesPrioritysearchtrees(readings)k-dtrees(readings)Quadandocttrees(readings)BSPtreesR-trees

PartIMetricSearchinginaNutshellOverview31.FOUNDATIONSOFMETRICSPACESEARCHING51TheDistanceSearchingProblem62TheMetricSpace83DistanceMeasures93.1MinkowskiDistances103.2QuadraticFormDistance113.3EditDistance123.4TreeEditDistance133.5Jaccard’sCoefficient133.6HausdorffDistance143.7TimeComplexity144SimilarityQueries154.1RangeQuery154.2NearestNeighborQuery164.3ReverseNearestNeighborQuery174.4SimilarityJoin174.5CombinationsofQueries184.6ComplexSimilarityQueries185BasicPartitioningPrinciples205.1BallPartitioning205.2GeneralizedHyperplanePartitioning215.3ExcludedMiddlePartitioning215.4Extensions216PrinciplesofSimilarityQueryExecution226.1BasicStrategies226.2IncrementalSimilaritySearch257PoliciesforAvoidingDistanceComputations267.1ExplanatoryExample277.2Object-PivotDistanceConstraint287.3Range-PivotDistanceConstraint307.4Pivot-PivotDistanceConstraint317.5Double-PivotDistanceConstraint337.6PivotFiltering348MetricSpaceTransformations358.1MetricHierarchies368.1.1Lower-BoundingFunctions368.2User-DefinedMetricFunctions388.2.1SearchingUsingLower-BoundingFunctions388.3EmbeddingMetricSpace398.3.1EmbeddingExamples398.3.2ReducingDimensionality409ApproximateSimilaritySearch419.1Principles419.2GenericAlgorithms449.3MeasuresofPerformance469.3.1ImprovementinEfficiency469.3.2PrecisionandRecall469.3.3RelativeErroronDistances489.3.4PositionError4910AdvancedIssues5010.1StatisticsonMetricDatasets5110.1.1DistributionandDensityFunctions5110.1.2DistanceDistributionandDensity5210.1.3HomogeneityofViewpoints5410.2ProximityofBallRegions5510.3PerformancePrediction58Contentsix10.4TreeQualityMeasures6010.5ChoosingReferencePoints632.SURVEYOFEXISTINGAPPROACHES671BallPartitioningMethods671.1Burkhard-KellerTree6

解压密码share.weimo.infoFoundationsofModernNetworkingisacomprehensive,unifiedsurveyofmodernnetworkingtechnologyandapplicationsfortoday’sprofessionals,managers,andstudents.Dr.WilliamStallingsoffersclearandwell-organizedcoverageoffivekeytechnologiesthataretransformingnetworks:Software-DefinedNetworks(SDN),NetworkFunctionsVirtualization(NFV),QualityofExperience(QoE),theInternetofThings(IoT),andcloudbasedservices. Dr.Stallingsreviewscurrentnetworkecosystemsandthechallengestheyface–fromBigDataandmobilitytosecurityandcomplexity.Next,heofferscomplete,self-containedcoverageofeachnewsetoftechnologies:howtheywork,howtheyarearchitected,andhowtheycanbeappliedtosolverealproblems.Dr.Stallingspresentsachapter-lengthanalysisofemergingsecurityissuesinmodernnetworks.Heconcludeswithanup-todatediscussionofnetworkingcareers,includingimportantrecentchangesinrolesandskillrequirements. Coverage: ,解压密码share.weimo.info

Distributedsourcecodingisoneofthekeyenablersforefficientcooperativecommunication.Thepotentialapplicationsrangefromwirelesssensornetworks,ad-hocnetworks,andsurveillancenetworks,torobustlow-complexityvideocoding,stereo/Multiviewvideocoding,HDTV,hyper-spectralandmultispectralimaging,andbiometrics.Thebookisdividedintothreesections:theory,algorithms,andapplications.PartonecoversthebackgroundofinformationtheorywithanemphasisonDSC;parttwodiscussesdesignsofalgorithmicsolutionsforDSCproblems,coveringthethreemostimportantDSCproblems:Slepian-Wolf,Wyner-Ziv,andMTsourcecoding;andpartthreeisdedicatedtoavarietyofpotentialDSCapplications.Keyfeatures:Clearexplanationofdistributedsourcecodingtheoryandalgorithmsincludingbothlosslessandlossydesigns.Richapplicationsofdistributedsourcecoding,whichcoversmultimediacommunicationanddatasecurityapplications.Self-containedcontentforbeginnersfrombasicinformationtheorytopracticalcodeimplementation.Thebookprovidesfundamentalknowledgeforengineersandcomputerscientiststoaccessthetopicofdistributedsourcecoding.Itisalsosuitableforseniorundergraduateandfirstyeargraduatestudentsinelectricalengineering;computerengineering;signalprocessing;image/videoprocessing;andinformationtheoryandcommunications.TableofContentsChapter1:IntroductionPartI:TheoryofDistributedSourceCodingChapter2:LosslessCompressionofCorrelatedSourcesChapter3:Wyner–ZivCodingTheoryChapter4:LossyDistributedSourceCodingPartII:ImplementationChapter5:Slepian–WolfCodeDesignsBasedonChannelCodingChapter6:DistributedArithmeticCodingChapter7:Wyner–ZivCodeDesignPartIII:ApplicationsChapter8:Wyner–ZivVideoCodingChapter9:CorrelationEstimationinDVCChapter10:DSCforSolarImageCompressionChapter11:SecureDistributedImageCodingChapter12:Se

四个GOF的设计模式核心的三种类型：Creational=＞处理对象创建的复杂性prototype=＞要复制或克隆的完全初始化的实例builder=＞将对象构造与其表示形式分离Singleton=＞将创建一个实例，无论请求对象的对象是哪个实例，都会发送该实例=＞Connection实例工厂=＞创建对象族。
-Structural=＞结构处理类的结构-Decorator=＞Addresponsibilitytotheobjectdynamically-Facade=＞Asingleclassrepresentstheentiresubsystem -Proxy=＞Proxyishidingthecomplexityoftheoriginalimplementationbyprovidingthe

TheNexusFrameworkforScalingScrum:ContinuouslyDeliveringanIntegratedProductwithMultipleScrumTeamsImproveandAccelerateSoftwareDeliveryforLarge,Distributed,ComplexProjectsTheNexusFrameworkisthesimplest,mosteffectiveapproachtoapplyingScrumatscaleacrossmultipleteams,sites,andtimezones.CreatedbyScrum.org—thepioneeringScrumtrainingandcertificationorganizationfoundedbyScrumco-creatorKenSchwaber—Nexusdrawsondecadesofexperiencetoaddresstheuniquechallengesteamsfaceincomingtogether,sharingwork,andmanagingandminimizingdependencies.TheNexus™FrameworkforScalingScrumisaconcisebookthatshowshowNexushelpsteamstodeliveracomplex,multi-platform,software-basedproductinshort,frequentcycles,withoutsacrificingconsistencyorquality,andwithoutaddingunnecessarycomplexityorstrayingfromScrum’scoreprinciples.Usinganextendedcasestudy,theauthorsillustratehowNexushelpsteamssolvecommonscalingchallengeslikereducingcross-teamdependencies,preservingteamself-organizationandtransparency,andensuringaccountability.Understandthechallengesofdeliveringworking,integratedproductincrementswithmultipleteams,andhowNexusaddressesthemFormaNexusaroundaneworexistingproductandlearnhowthatNexussetsgoalsandplansitsworkRunSprintswithinaNexus,providetransparencyintoprogress,conducteffectiveNexusSprintreviews,anduseNexusSprintRetrospectivestocontinuouslyimproveOvercomethedistributedteamcollaborationchallengesTableofContentsChapter1IntroductiontoScalingAgileChapter2IntroducingNexusChapter3FormingaNexusChapter4PlanninginNexusChapter5RunningaSprintinNexusChapter6EvolvingtheNexusChapter7TheNexusinEmergencyModeChapter8RetrospectiveontheNexusJourney

1.OFDM的基本原理2.SynthesisofBand-LimitedOrthogonalSignalsforMultichannelDataTransmission3.Peled_Ruiz_Frequencydomaindatatransmissionusingreducedcomputationalcomplexityalgorithms4.Weinstein_Ebert_DataTransmissionbyFrequency-DivisionMultiplexingUsingtheDiscreteFourierTransform

WiththeintroductionofvehiclestabilitysystemslikeESP®,andpassivesafetysystemslikeseatbeltsandairbags,drivingsafetyhasbeenimprovedandthenumberofroadtrafficfatalitiesandsevereinjurieshavebeensignificantlyreducedinthelastdecades.Althoughthesesafetysystemsarestateoftheartfornewpassengercars,inGermanythenumberoffatalitiesremainsonasimilarlevelinthelatestyears.Atthesametime,theneedofthepeopleforindividualmobilityisstillincreasingandthisisresultinginhighertrafficdensity,trafficcomplexity,andincreasingstressforthedrivers.Statisticaldatashowsthatthedriverremainsasanessentialsourceforaccidents.Tofurtherincreasethedrivingsafetyandtorelievethedriverofthecomplextaskofvehicleguidance,todaynearlyallOEMsandsuppliersaredealingwithideasforselfdrivingvehiclesorareengagedwithhighlyautomateddriving(HAD)functionalities.

文章作者写的matlab源代码，该文章发表在DigitalSignalProcessing:Ke-KunHuang,HuiLiu,Chuan-XianRen,Yu-FengYuandZhao-RongLai.Remotesensingimagecompressionbasedonbinarytreeandoptimizedtruncation.DigitalSignalProcessing,vol.64,pp.96-106,2017.(http://dx.doi.org/10.1016/j.dsp.2017.02.008)遥感图像数据非常广泛，因此需要通过空间设备上的低复杂度算法进行压缩。
具有自适应扫描顺序（BTCA）的二叉树编码是一个的有效算法。
然而，对于大规模遥感图像，BTCA需要大量的内存，而且不能随机存取。
在本文中，我们提出了一种基于BTCA的新的编码方法。
小波图像首先划分为几个块，并由BTCA单独编码的。
根据BTCA的属性，仔细选择每个块的有效截断点，以优化速率失真的比例，从而获得更高的压缩比、更低的内存要求和随机访问性能。
由于没有任何熵编码，所提出的方法简单快速，非常适合于空间设备。
对三个遥感图像集进行实验，结果表明它可以显着提高PSNR、SSIM和VIF，以及主观视觉体验。
Theremotesensingimagedataissovastthatitrequirescompressionbylow-complexityalgorithmonspace-borneequipment.Binarytreecodingwithadaptivescanningorder(BTCA)isaneffectivealgorithmforthemission.However,forlarge-scaleremotesensingimages,BTCArequiresalotofmemory,anddoesnotproviderandomaccessproperty.Inthispaper,weproposeanewcodingmethodbasedonBTCAandoptimizetruncation.ThewaveletimageisfirstdividedintoseveralblockswhichareencodedindividuallybyBTCA.AccordingthepropertyofBTCA,weselectthevalidtruncationpointsforeachblockcarefullytooptimizetheratioofrate-distortion,sothatahighercompressionratio,lowermemoryrequirementandrandomaccesspropertyareattained.Withoutanyentropycoding,theproposedmethodissimpleandfast,whichisverysuitableforspace-borneequipment.Experimentsareconductedonthreeremotesensingimagesets,andtheresultsshowthatitcansignificantlyimprovePSNR,SSIMandVIF,aswellassubjectivevisualexperience.

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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。