GloVeisanunsupervisedlearningalgorithmforobtainingvectorrepresentationsforwords.Trainingisperformedonaggregatedglobalword-wordco-occurrencestatisticsfromacorpus,andtheresultingrepresentationsshowcaseinterestinglinearsubstructuresofthewordvectorspace.

DistributedSystems(3rd)英文无水印原版pdf第3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Copyright@2017MaartenvanSteenandAndrewS.TanenbaumPublishedbyMaartenvanSteenThisbookwaspreviouslypublishedby:PearsonEducation,IncISBN:978-15-430573-8-6(printedversion)ISBN:978-90-815406-2-9(digitalversion)Edition:3.Version:01(February2017)AllrightstotextandillustrationsarereservedbyMaartenvanSteenandAndrewS.Tanenbaum.Thisworkmaynotbecopied,reproduced,ortranslatedinwholeorpartwithoutwrittenpermissionofthepublisher,exceptforbriefexcerptsinreviewsorscholanyformofinformationstorageadaptationorwhatever,computersoftware,orbysimilarordissimilarmethodsnowknownordevelopedinthefutureisstrictlyforbiddenwithoutwrittenpermissionofthepublisherToMarielle,max,andelkeMVSToSuzanneBarbara,Marvin,Aronnathan,olivia,andmirteASTCONTENTSPreface1Introduction1.1Whatisadistributedsystem?Characteristic1:Collectionofautonomouscomputingelements2Characteristic2:SinglecoherentsystemMiddlewareanddistributedsystems1.2DesigngoalsSupportingresourcesharingMakingdistributiontransparent12Beingscalable15Pitfalls243Typesofdistributedsystems24Highperformancedistributedcomputing25Distributedinformationsystems34Pervasivesystems1.4Summary522Architectures552.1Architecturalstyles56Layeredarchitectures.57Object-basedandservice-orientedarchitectures62Resource-basedarchitectures64Publish-subscribearchitectures2.2MiddlewareorganizationWrappersInterceptors垂番Modifiablemiddleware752.3SystemarchitectureCONTENTSCentralizedorganizations76Decentralizedorganizations:peer-to-peersystemsHybridarchitectures2.4Examplearchitectures94TheNetworkFilesystem94TheWeb982.5Summary3Processes1033.1Threads..104Introductiontothreads104Threadsindistributedsystems1113.2Virtualization116Principleofvirtualizationapplicationofvirtualmachinestodistributedsystems,1223.3Clients124Networkeduserinterfaces124Client-sidesoftwarefordistributiontransparency1273.4Servers128Generaldesignissues129Objectservers133Example:TheApacheWebserver139Serverclusters,,,,,,,1413.5Codemigration152Reasonsformigratingcode152Migrationinheterogeneoussystems1583.6Summary1614Communication4.1Foundations164LayeredProtocols164TypesofCommunication.1724.2Remoteprocedurecall..173Basicrpcoperation174Parameterpassing178RPC-basedapplicationsupport182VariationsonrPc185Example:dCErPc,.1884.3Message-orientedcommunication193Simpletransientmessagingwithsockets.193Advancedtransientmessaging198Message-orientedpersistentcommunication206Example:IBM'sWebSpheremessage-queuingsystem212Example:AdvancedMessageQueuingProtocol(AMQP)....218DS3.01DOWNLOADEDBYTEWIGOMIXMAIL.INFOCONTENTS4.4Multicastcommunication221Application-leveltree-basedmulticasting221Flooding-basedmulticasting225Gossip-baseddatadissemination2294.5Summary2345Naming2375.1Names,identifiersandaddresses2385.2Flatnaming.241Simplesolutions241Home-basedapproaches245Distributedhashtables246Hierarchicalapproaches2515.3Structurednaming256Namespaces.256Nameresolution259Theimplementationofanamespace264Example:TheDomainNameSystem271Example:TheNetworkFileSystem2785.4Attribute-basednaming283Directoryservices283Hierarchicalimplementations:LDAP285Decentralizedimplementations2885.5Summary2946Coordination2976.1Clocksynchronization.298Physicalclocks299Clocksynchronizationalgorithms3026.2Logicalclocks310Lamport'slogicalclocks310Vectorclocks3166.3Mutualexclusion321322acentralizedalgorithm.322adistributedalgorithm323atoken-ringalgorithm.325adecentralizedalgorithm3266.4Electionalgorithms329Thebullyalgorithm.,..330Aringalgorithm332Electionsinwirelessenvironments333Electionsinlarge-scalesystems.3356.5Locationsystems336DOWNLOADEDBYTEWIGOMIXMAIL.INFODS301VIllCONTENTSGPS:GlobalPositioningSystem337WhengPsisnotanoption339Logicalpositioningofnodes3396.6Distributedeventmatching..343Centralizedimplementations3436.7Gossip-basedcoordination349asgregation349Apeer-samplingservice350Gossip-basedoverlayconstruction3526.8Summary3537Consistencyandreplication3557.1Introduction356Reasonsforreplication356Replicationasscalingtechnique3577.2Data-centricconsistencymodels358Continuousconsistency359Consistentorderingofoperations364Eventualconsistency3737.3Client-centricconsistencymodels375MonotonicreadsMonotonicwrites.379Readyourwrite380Writesfollowreads3827.4ReplicamanagementFindingthebestserverlocation383Contentreplicationandplacement..385Contentdistribution..388Managingreplicatedobjects3937.5Consistencyprotocols.396Continuousconsistency..........396Primary-basedprotocols398Replicated-writeprotocolsCache-coherence403Implementingclient-centricconsistency,,...4077.6Example:CachingandreplicationintheWeb4097.7Summar4208Faulttoleran4238.1Introductiontofaulttolerance424Basicconcepts.424Failuodels427Failuremaskingbyredundancy8.2Processresilience432DS3.01DOWNLOADEDBYTEWIGOMIXMAIL.INFO

压缩包主要包括部分恒润资料如：CAN基础、汽车CAN总线通信矩阵设计、FlashBootloader、VectorTraining_tutorial等，都是些基本知识，仅提供给初学者学习。

LIN-Spec_2.2.pdfLIN2.1.pptLIN2.1协议培训_恒润.pdfLIN总线介绍.pptLIN规范1.2中文版.pdfLIN规范2.0中文版.pdfVector_LIN_Spec.pdf

本源代码借助标准C++STL中的vector,list和heap等已封装的数据结构，优化了A星算法搜索地图、检索开始列表过程，减小了程序的时间和空间花费。
经检验，检索20000*20000的随机障碍物地图时，程序在规划路径部分的平均耗时在两秒左右。

Usetheautocorrelationfunctiononsegmentsofthesignal(windowsize:100ms)andcomputethefundamentalfrequency.Useamax_time_lagof100msintheautocorrelationfunctionandawindowshiftof25ms.Createafundamentalfrequencyvectorandplotyourpitchcontour.

Byapplyingsupportvectorregression,themodelingdataofriceleavescollectedinourstudyweregroupedintosampletrainingsetandtestset,andthreemachinelearningpredictionmodelsonricegrowingenvironmentagainstleafbladelength,widthandSPADvaluewereconstructed..

Thispracticalguideprovidesnearly200self-containedrecipestohelpyousolvemachinelearningchallengesyoumayencounterinyourdailywork.Ifyou’recomfortablewithPythonanditslibraries,includingpandasandscikit-learn,you’llbeabletoaddressspecificproblemssuchasloadingdata,handlingtextornumericaldata,modelselection,anddimensionalityreductionandmanyothertopics.Eachrecipeincludescodethatyoucancopyandpasteintoatoydatasettoensurethatitactuallyworks.Fromthere,youcaninsert,combine,oradaptthecodetohelpconstructyourapplication.Recipesalsoincludeadiscussionthatexplainsthesolutionandprovidesmeaningfulcontext.Thiscookbooktakesyoubeyondtheoryandconceptsbyprovidingthenutsandboltsyouneedtoconstructworkingmachinelearningapplications.You’llfindrecipesfor:Vectors,matrices,andarraysHandlingnumericalandcategoricaldata,text,images,anddatesandtimesDimensionalityreductionusingfeatureextractionorfeatureselectionModelevaluationandselectionLinearandlogicalregression,treesandforests,andk-nearestneighborsSupportvectormachines(SVM),naïveBayes,clustering,andneuralnetworksSavingandloadingtrainedmodels

支持向量机源码，可在www.csie.ntu.edu.tw/~cjlin/libsvm/下载到最新版本，该版本是2013年4月更新的，3.17版。
压缩包里面有源代码和文档。
以下摘自前述网站：IntroductionLIBSVMisanintegratedsoftwareforsupportvectorclassification,(C-SVC,nu-SVC),regression(epsilon-SVR,nu-SVR)anddistributionestimation(one-classSVM).Itsupportsmulti-classclassification.Sinceversion2.8,itimplementsanSMO-typealgorithmproposedinthispaper:R.-E.Fan,P.-H.Chen,andC.-J.Lin.WorkingsetselectionusingsecondorderinformationfortrainingSVM.JournalofMachineLearningResearch6,1889-1918,2005.Youcanalsofindapseudocodethere.(howtociteLIBSVM)OurgoalistohelpusersfromotherfieldstoeasilyuseSVMasatool.LIBSVMprovidesasimpleinterfacewhereuserscaneasilylinkitwiththeirownprograms.MainfeaturesofLIBSVMincludeDifferentSVMformulationsEfficientmulti-classclassificationCrossvalidationformodelselectionProbabilityestimatesVariouskernels(includingprecomputedkernelmatrix)WeightedSVMforunbalanceddataBothC++andJavasourcesGUIdemonstratingSVMclassificationandregressionPython,R,MATLAB,Perl,Ruby,Weka,CommonLISP,CLISP,Haskell,OCaml,LabVIEW,andPHPinterfaces.C#.NETcodeandCUDAextensionisavailable.It'salsoincludedinsomedataminingenvironments:RapidMiner,PCP,andLIONsolver.Automaticmodelselectionwhichcangeneratecontourofcrossvaliationaccuracy.

MIMOOFDMSimulator:OFDM.m:OFDMSimulator(outerfunction)create_channel.m:GeneratesaRayleighfadingfrequency-selectivechannel,parametrizedbytheantennaconfiguration,theOFDMconfiguration,andthepower-delayprofile.svd_decompose_channel.m:Sincefullchannelknowledgeisassumed,transmissionisacrossparallelsingularvaluemodes.Thisfunctiondecomposesthechannelintothesemodes.BitLoad.m:Applythebit-loadingalgorithmtoachievethedesiredbitandenergyallocationforthecurrentchannelinstance.ComputeSNR.m:Giventhesubcarriergains,thissimplefunctiongeneratestheSNRvaluesofeachchannel(eachsingularvalueoneachtoneisaseparatechannel).chow_algo.m:ApplyChow'salgorithmtogenerateaparticularbitandenergyallocation.EnergyTableInit.m:GiventheSNRvalues,formatableofenergyincrementsforeachchannel.campello_algo.m:ApplyCampello'salgorithmtoconvergetotheoptimalbitandenergyallocationforthegivenchannelconditions.ResolvetheLastBit.m:Anoptimalbit-loadingofthelastbitrequiresauniqueoptimization.modulate.m:Modulatetherandominputsequenceaccordingtothebitallocationsforeachchannel.ENC2.mat:BPSKModulatorENC4.mat:4-QAMModulator(Graycoded)ENC16.mat:16-QAMModulator(Graycoded)ENC64.mat:64-QAMModulator(Graycoded)ENC256.mat:256-QAMModulator(Graycoded)precode.m:Precodethetransmittedvectorateachtimeinstancebyfilteringthemodulatedvectorwiththeright-inverseofthechannel'srightsingluarmatrix.ifft_cp_tx_blk.m:IFFTblockoftheOFDMsystem.channel.m:ApplythechanneltotheOFDMframe.fft_cp_rx_blk.m:FFTblockoftheOFDMsystem.shape.m:Completethediagonalizationofthechannelbyfilteringthereceivedvectorwiththeleft-inverseofthechannel'sleftsingularmatrix.demodulate.m:Performanearestneighborsearchknowingthetransmitconstellationused.

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。