仿QQ消息列表左滑弹出菜单，标记已读和删除；
含entity、adapter等，如有问题请联系我。
谢谢支持

ContextCapture用户说明-中文版.zip。
帮助英文不好的朋友进行阅读！帮助英文不好的朋友进行阅读！

CONTENTPART1BASICSOFINFERENCEOVERNETWORKSCHAPTER1AsynchronousAdaptiveNetworksCHAPTER2EstimationandDetectionOverAdaptiveNetworksCHAPTER3MultitaskLearningOverAdaptiveNetworksWithGroupingCHAPTER4BayesianApproachtoCollaborativeInferenceinNetworksCHAPTER5MultiagentDistributedOptimizationCHAPTER6DistributedKalmanandParticleFilteringCHAPTER7GameTheoreticLearningPART2SIGNALPROCESSINGONGRAPHSCHAPTER8GraphSignalProcessing.CHAPTER9SamplingandRecoveryofGraphSignalsCHAPTER10BayesianActivelearningonGraphs.CHAPTER11DesignofGraphFiltersandFilterbanksCHAPTER12StatisticalGraphSignalProcessing:StationarityandSpectralEstimationCHAPTER13InferenceofGraphTopologyCHAPTER14PartiallyAbsorbingRanclomWalks:AUnifieclFrameworkforLearningonGraphsPART3DISTRIBUTEDCOMMUNICATIONS,NETWORKING,ANDSENSING.....

利用python语言cgi模块搭建间的网络服务器编写简单的cgi脚本

配合Captura使用的ffmpeg-N-100560-g5f9632e491-win64-gpl-shared.zip

FSCapture8.3破解版，里面带有用户名和注册码，好用好用。

用C语言实现了高斯白噪声数据的产生Routinemrandom:Togeneratetherandomnumber(pseudo-whitenoise).inputParameters:n:therandomdatanumberrequested;integer.iseed:theseedforpseudo-randomdatageneration.itmustbeinitializedbymainprogram(suggestedvalueisISEED=12357),andtherandomnumberiscycled,thecyclelength=1,048,576itype:randomdatadistributiontype,seebelow:itype=1:Uniformdistributed,from0.0to1.0itype=2:Uniformdistributed,Mean=0.0,Variance(方差)(Power)p=1.0itype=3:Uniformdistributed,Mean=0.0,Variance(Power)p=p.itype=4:Gaussiandistributed,Mean=0.0,Variance(Power)p=1.0itype=5:Gaussiandistributed,Mean=0.0,Variance(Power)p=p.p:variance(Power)ofrandom,onlyusedwhenitype=3oritype=5.outparameters:u:ndimensionedrealarray,dataisstoredinu(0)tou(n-1).inChapter1

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

DatabaseSystemConcepts——数据库系统概念第六版（英文版）作者：AbrahamSilberschatz(YaleUniversity)HenryF.Korth(LehighUniversity)S.Sudarshan(IndianInstituteofTechnology,Bombay)本书目录：Chapter1Introduction1.1Database-SystemApplications11.2PurposeofDatabaseSystems31.3ViewofData61.4DatabaseLanguages91.5RelationalDatabases121.6DatabaseDesign151.7DataStorageandQuerying201.8TransactionManagement221.9DatabaseArchitecture231.10DataMiningandInformationRetrieval251.11SpecialtyDatabases261.12DatabaseUsersandAdministrators271.13HistoryofDatabaseSystems291.14Summary31Exercises33BibliographicalNotes35Chapter2IntroductiontotheRelationalModel2.1StructureofRelationalDatabases392.2DatabaseSchema422.3Keys452.4SchemaDiagrams462.5RelationalQueryLanguages472.6RelationalOperations482.7Summary52Exercises53BibliographicalNotes55Chapter3IntroductiontoSQL3.1OverviewoftheSQLQueryLanguage573.2SQLDataDefinition583.3BasicStructureofSQLQueries633.4AdditionalBasicOperations743.5SetOperations793.6NullValues833.7AggregateFunctions843.8NestedSubqueries903.9ModificationoftheDatabase983.10Summary104Exercises105BibliographicalNotes112Chapter4IntermediateSQL4.1JoinExpressions1134.2Views1204.3Transactions1274.4IntegrityConstraints1284.5SQLDataTypesandSchemas1364.6Authorization1434.7Summary150Exercises152BibliographicalNotes156Chapter5AdvancedSQL5.1AccessingSQLFromaProgrammingLanguage1575.2FunctionsandProcedures1735.3Triggers1805.4RecursiveQueries1875.5AdvancedAggregationFeatures1925.6OLAP1975.7Summary209Exercises211BibliographicalNotes216Chapter6FormalRelationalQueryLanguages6.1TheRelationalAlgebra2176.2TheTupleRelationalCalculus2396.3TheDomainRelationalCalculus2456.4Summary248Exercises249BibliographicalNotes254Chapter7Datab

提出一种车载自组织网络(VANET)中考虑节点质量的机会路由协议——QAOR(QualityofnodebasedAdaptiveOpportunisticRoutingProtocol)。
针对以往协议均没考虑到节点历史接触频繁性的问题,该协议在路口根据距离目的最近和反映节点接触频繁性的质量两个指标机会选择下一跳,改善了GPSR在路口下一跳没有后续节点的情况;在直路上运用加入携带转发机制的贪婪算法。
NS-2仿真显示,在城市场景中,QAOR自适应选路,比传统贪婪算法GPSR投递率增加,延时减少。

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。