swarm安装程序，如果你正在研究多智能体系统（Multi-AgentSystems，MAS），如果恰巧你有一点Java程序设计基础，如果更巧的是你对用SwarmforJava开发MAS抱有浓厚的兴趣，那么请跟随我一起来搭建一个JDK+JCreator+Swarm的轻量级MAS开发环境吧。
不过我们默认你已经安装好JDK和JCreator——没装好的话请自行查找相关资料并安装。
关于JDK，我用的是JDK1.5，不过JDK6早已经发布了；
关于JCreator，我用的同样是古董级的3.5版本，无他，习惯而已。

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

Amulti-focusopticalfiberlensisnumericallydemonstratedbasedonanall-dielectricmetasurfacestructure.Themetasurfaceconsistsofanarrayofrectangularsiliconresonatorswithvaryingwidthsinordertoobtaintherequiredphasedistribution.Thecorediameterofthemultimodefiberislargeenoughtocontainsufficientresonanceunits.Thespatialdistributionofthedielectricresonatorsisdictatedbyspatialmultiplexing,includinginterleavingmeta-atomsandlensaperturedivisio

（狼群算法）Multi-strategyensemblegreywolfoptimizeranditsapplicationtofeatureselec.pdf

Inresponsetotheexponentiallyincreasingneedtoanalyzevastamountsofdata,NeuralNetworksforAppliedSciencesandEngineering:FromFundamentalstoComplexPatternRecognitionprovidesscientistswithasimplebutsystematicintroductiontoneuralnetworks.Beginningwithanintroductorydiscussionontheroleofneuralnetworksinscientificdataanalysis,thisbookprovidesasolidfoundationofbasicneuralnetworkconcepts.Itcontainsanoverviewofneuralnetworkarchitecturesforpracticaldataanalysisfollowedbyextensivestep-by-stepcoverageonlinearnetworks,aswellas,multi-layerperceptronfornonlinearpredictionandclassificationexplainingallstagesofprocessingandmodeldevelopmentillustratedthroughpracticalexamplesandcasestudies.LaterchapterspresentanextensivecoverageonSelfOrganizingMapsfornonlineardataclustering,recurrentnetworksforlinearnonlineartimeseriesforecasting,andothernetworktypessuitableforscientificdataanalysis.Withaneasytounderstandformatusingextensivegraphicalillustrationsandmultidisciplinaryscientificcontext,thisbookfillsthegapinthemarketforneuralnetworksformulti-dimensionalscientificdata,andrelatesneuralnetworkstostatistics.FeaturesxExplainsneuralnetworksinamulti-disciplinarycontextxUsesextensivegraphicalillustrationstoexplaincomplexmathematicalconceptsforquickandeasyunderstanding?Examinesin-depthneuralnetworksforlinearandnonlinearprediction,classification,clusteringandforecastingxIllustratesallstagesofmodeldevelopmentandinterpretationofresults,includingdatapreprocessing,datadimensionalityreduction,inputselection,modeldevelopmentandvalidation,modeluncertaintyassessment,sensitivityanalysesoninputs,errorsandmodelparametersSandhyaSamarasingheobtainedherMScinMechanicalEngineeringfromLumumbaUniversityinRussiaandanMSandPhDinEngineeringfromVirginiaTech,USA.

1.目录1.目录22.绘图函数Plottingfunctions42.1.可视化的统计关系Visualizingstatisticalrelationships42.1.1.用散点图联系变量Relatingvariableswithscatterplots42.1.2.强调线条图的连续性Emphasizingcontinuitywithlineplots102.1.3.显示与切面的多个关系Showingmultiplerelationshipswithfacets212.2.分类数据绘图Plottingwithcategoricaldata242.2.1.分类散点图Categoricalscatterplots262.2.2.分类观测值分布Distributionsofobservationswithincategories312.2.3.分类统计估计Statisticalestimationwithincategories372.2.4.对“wide-form”数据作图Plotting“wide-form”data412.2.5.显示与facet的多个关系Showingmultiplerelationshipswithfacets432.3.可视化数据集的分布Visualizingthedistributionofadataset442.3.1.绘制单变量分布Plottingunivariatedistributions452.3.2.绘制二元分布Plottingbivariatedistributions512.3.3.在数据集中可视化成对关系Visualizingpairwiserelationshipsinadataset552.4.可视化线性关系Visualizinglinearrelationships572.4.1.函数绘制线性模型Functionstodrawlinearregressionmodels582.4.2.拟合不同种类的模型Fittingdifferentkindsofmodels612.4.3.在其他变量上的情况Conditioningonothervariables682.4.4.控制图表的大小和形状Controllingthesizeandshapeoftheplot712.4.5.在其他上下文中绘制回归图Plottingaregressioninothercontexts733.多图网格Multi-plotgrids763.1.构建结构化的多图网格Buildingstructuredmulti-plotgrids763.2.有条件的小倍数Conditionalsmallmultiples773.3.使用定制函数Usingcustomfunctions863.4.绘制成对的数据关系Plottingpairwisedatarelationships904.绘图美学Plotaesthetics994.1.控制图表美学Controllingfigureaesthetics994.1.1.Seaborn图表风格Seabornfigurestyles1014.1.2.删除轴上的小凸起Removingaxesspines1044.1.3.临时设置图表样式Temporarilysettingfigurestyle1054.1.4.覆盖Seaborn样式的元素Overridingelementsoftheseabornstyles1064.1.5.缩放图表元素Scalingplotelements1084.2.选择调色板Choosingcolorpalettes1114.2.1.创建颜色调色板Buildingcolorpalettes1114.2.2.定性调色板Qualitativecolorpalettes1124.2.3.连续调色板Sequentialcolorpalettes1164.2.4.不同颜色的调色板Divergingcolorpalettes1224.2.5.设置默认调色板Settingthedefaultcolorpalette1245.教程中的数据集125

在1998年，MartyRoesch先生用C语言开发了开放源代码(OpenSource)的入侵检测系统Snort.直至今天，Snort已发展成为一个多平台(Multi-Platform),实时(Real-Time)流量分析，网络IP数据包(Pocket)记录等特性的强大的网络入侵检测/防御系统(NetworkIntrusionDetection/PreventionSystem)

多目的蝗虫优化算法，亲测可用。
Multi-objectiveGrasshopperOptimizationAlgorithm

HP93KRF模块详尽教程Lesson1:RFHardwareLesson2:ReviewPortSetups&Multi-siteLesson3:ReviewPortScaleRFSpecificationsLesson4:RFSoftwareLesson5:CWLoopbackLabsLesson6:SetUpSequencingLesson7:ControlRFTriggeringLesson8:ReviewSamplingParametersLesson9:MeasureIntermodulationDistortion(RFtoRF)Lesson10:MeasureIntermodulationDistortion(RFtoRF)Lesson11:CalibrateRFSubsystemLesson12:Multi-TestFlowCalibrationLabLesson13:ModulatedStimulusandMeasurementLesson14:ACLR&EVMLabLesson15:UseRFAPIs.Lesson16:PortScaleFeatureDemoLesson17:MeasureCarrierSuppression(BBtoRF)Lesson18:MeasureIQPhase/AmplitudeImbalance(RFtoBaseband)QuizReviewPortSetups&Multi-site

本书详尽介绍了多智能体抑制的阻滞，接着介绍了一阶以及二阶体系的leader-follower抑制，合围抑制。
离散体系的协同抑制也有详尽介绍。

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。