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

2020--SDUWH--计算机图形学实验共20个实验实验1直线的绘制实验2直线的DDA生成算法实验3直线中点生成算法实验4直线Bresenham生成算法实验5中点画圆算法 实验6中点画椭圆算法实验7多边形有序边表算法实验8边标志多边形填充算法实验9种子填充算法实验10直线的裁剪实验11多边形的裁剪算法实验12Weiler-Athenton多边形裁剪算法实验13视窗实验143D房屋绘制实验15金字塔实验16交互技术应用实验17光照模型实例实验18阴影Shade实验19纹理实验实验20贝塞尔曲线

R_training_Project_1使用R项目1进行数据分析：使用NHTS2017数据集进行探索性数据分析调查名称：017全国家庭旅行调查-加利福尼亚附加项目资料来源：:团队Spreasheet数据说明包含CSV文件1.householddata2.locationdata3.persondata4.Tripsdata5.vehiclesdata贴标尝试使用thsc-nhts17-caltranscodebook.xlsx标记值使用字典tsdc-nhts17-caltrans-datadictionary.pdf了解数据缺失值缺少的值已编码为lile-9，-8，-7等。
检查标签是否正确指示1.Importingandunderstandingthedata2.Examplesofdataaggreg

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Byapplyingsupportvectorregression,themodelingdataofriceleavescollectedinourstudyweregroupedintosampletrainingsetandtestset,andthreemachinelearningpredictionmodelsonricegrowingenvironmentagainstleafbladelength,widthandSPADvaluewereconstructed..

开发环境：WIN7+QT4.7+QTCREATOR2.8+MINGW已编译通过测试平台：XP、Win7、ubuntu、tiny210技术实现：通过第三方串口通信类，解析协议并作出处理基本功能：1：支持16进制数据发送与接收。
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Sharinghealthcaredatabetweeninstitutionsischallenging.Heterogeneousdatastructuresmayprecludecompatibility,whiledisparateuseofhealthcareterminologylimitsdatacomprehension.Evenifstructureandsemanticscouldbeagreedupon,bothsecurityanddataconsistencyconcernsabound.Centralizeddatastoresandauthorityprovidersareattractivetargetsforcyberattack,andestablishingaconsistentviewofthepatientrecordacrossadatasharingnetworkisproblematic.InthisworkwepresentaBlockchain-basedapproachtosharingpatientdata.Thisapproachtradesasinglecentralizedsourceoftrustinfavorofnetworkconsensus,andpredicatesconsensusonproofofstructuralandsemanticinteroperability.

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.

liangbarsky裁剪算法实现以及运行exe多直线多裁剪窗口同时裁剪线段分明画线方式使用DDA算法

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