Lengthandgirtharecentraltomeasurethesizeoftubeshapedobjects.Thispaperextendscircularhelicalcurvestogeneraltubularshapesandproposesanovelmethodformeasuringtheirlengthandgirth.Wecalltheextendedcircularhelixesquasi-helicalcurves.Aformaldefinition,aswellas

pdf版的数据结构必读书Datastructure+Algorithm=ProgrammingThetoolsandtechniquestodesignandimplementlarge-scalecomputersystems:DataabstractionAlgorithmspecificationPerformanceanalysisPerformancemeasurement

Matlabcodeforcomputingandvisualization:ConfusionMatrix,Precision/Recall,ROC,Accuracy,F-Measureetc.forClassification

Inopticalscatteringparticlesizing,anumericaltransformissoughtsothataparticlesizedistributioncanbedeterminedfromangularmeasurementsofnearforwardscattering,whichhasbeenadoptedinthemeasurementofbloodcells.Inthispaperanewmethodofcountingandclassificationofbloodcell,laserlightscatteringmethodfromstationarysuspensions,ispresented.Thegeneticalgorithmcombinedwithnonnegativeleastsquaredalgorithmisemployedtoinversethesizedistribution

这是一篇来自science杂志的论文，极其典型！介绍了测地距离在流行降维中的使用。
Scientistsworkingwithlargevolumesofhigh-dimensionaldata,suchasglobalclimatepatterns,stellarspectra,orhumangenedistributions,regularlyconfronttheproblemofdimensionalityreduction:Þndingmeaningfullow-dimensionalstructureshiddenintheirhigh-dimensionalobservations.Thehumanbrainconfrontsthesameproblemineverydayperception,extractingfromitshigh-dimensionalsensoryinputsÑ30,000auditorynerveÞbersor106opticnerveÞbersÑamanageablysmallnumberofperceptuallyrelevantfeatures.Herewedescribeanapproachtosolvingdimensionalityreductionproblemsthatuseseasilymeasuredlocalmetricinformationtolearntheunderlyingglobalgeometryofadataset.Unlikeclassicaltechniquessuchasprincipalcomponentanalysis(PCA)andmultidimensionalscaling(MDS),ourapproachiscapableofdiscoveringthenonlineardegreesoffreedomthatunderliecomplexnaturalobservations,suchashumanhandwritingorimagesofafaceunderdifferentviewingconditions.Incontrasttopreviousalgorithmsfornonlineardimensionalityreduction,oursefÞcientlycomputesagloballyoptimalsolution,and,foranimportantclassofdatamanifolds,isguaranteedtoconvergeasymptoticallytothetruestructure.

2019-2区-UnsupervisedAnomalyDetectionBasedonMinimumSpanningTreeApproximatedDistanceMeasuresandItsApplicationtoHydropowerTurbines

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

Thisisthefirstdefinitiveintroductiontobehavioraleconomicsaimedatadvancedundergraduateandpostgraduatestudents.Authoritative,cuttingedge,yetaccessible,itguidesthereaderthroughtheoryandevidence,providingengagingandrelevantapplicationsthroughout.Itisdividedintoninepartsand24chapters:PartIisonbehavioraleconomicsofrisk,uncertainty,andambiguity.Theevidenceagainstexpectedutilitytheoryisexamined,andthebehavioralresponseisoutlined;thebestempiricallysupportedtheoryisprospecttheory.PartIIconsidersother-regardingpreferences.Theevidencefromexperimentalgamesonhumansocialityisgiven,followedbymodelsandapplicationsofinequityaversion,intentionsbasedreciprocity,conditionalcooperation,humanvirtues,andsocialidentity.PartIIIisontimediscounting.Itconsiderstheevidenceagainsttheexponentialdiscountedutilitymodelanddescribesseveralbehavioralmodelssuchashyperbolicdiscounting,attributebasedmodelsandthereferencetimetheory.PartIVdescribestheevidenceonclassicalgametheoryandconsidersseveralmodelsofbehavioralgametheory,includinglevel-kandcognitivehierarchymodels,quantalresponseequilibrium,andpsychologicalgametheory.PartVconsidersbehavioralmodelsoflearningthatincludeevolutionarygametheory,classicalmodelsoflearning,experienceweightedattractionmodel,learningdirectiontheory,andstochasticsocialdynamics.PartVIstudiestheroleofemotions;amongothertopicsitconsidersprojectionbias,temptationpreferences,happinesseconomics,andinteractionbetweenemotionsandcognition.PartVIIconsidersboundedrationality.Thethreemaintopicsconsideredarejudgmentheuristicsandbiases,mentalaccounting,andbehavioralfinance.PartVIIIconsidersbehavioralwelfareeconomics;themaintopicsaresoftpaternalism,andchoice-basedmeasuresofwelfare.Finally,PartIXgivesanabbreviatedtast

Thedatasignalobtainedbyusingthenear-infraredspectroscopydetectorincludestheinformationofthecomponenttobetested,includingthenoiseofvariousinstruments,suchashigh-frequencyrandomnoise,baselinedrift,spuriousinformation,backgroundofthesample.Therefore,beforedataanalysis,thespecificsignalmeasurementandsamplesystemshouldbeprocessedreasonably,andtheinfluenceofvariousnon-targetfactorsonthedetectionsignalinformationshouldbeweakenedoreveneliminated,whichlaysafoundationforestablishingastableandreliablemathematicalmodel.Co妹妹onlyuseddatapreprocessingmethodsincludedatanormalizationprocessing(meancentering,normalization,standardnormaltransformation,etc.),highfrequencynoisefiltering(convolutionsmoothing,Fouriertransform,wavelettransform,etc.),differentialderivationofsignals,andBaselinecorrection,etc.

用C#以及measurementStudio，编写的一个AD转换的法度圭表标准。
MeasurementStudio做界面，比组态软件要好，松散了labview以及C#的益处

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。