简介:Biomimetics(orbionics)istheengineeringdisciplinethatconstructsartificialsystemsusingbiologicalprinciples.Theidealfinalresultinbiomimeticsistocreatealivingmachine.Butwhatarethedesirableandnon-desirablepropertiesofbiomimeticproduct?Wherecannaturalprototypesbefound?Howcantechnicalsolutionsbetransferredfromnaturetotechnology?CanweuselivingnaturelikeLEGObricksforconstructionourmachines?Howcanbiologyhelpus?Whatisalivingmachine?Inbiomimeticpracticeonlysome"part"(organ,partoforgan,tissue)oftheobservedwholeorganismisutilized.Apossibletemplateforfuturesuper-organismextensionforbiomimeticmethodsmightbedrawnfromexperimentsinholisticecologicalagriculture(ecologicaldesign,permaculture,ecologicalengineering,etc.).ThenecessarytranslationoftheserulestopracticalactioncanbeachievedwiththeRussianTheoryofInventiveProblemSolving(TRIZ),specificallyadjustedtobiology.Thus,permaculture,reinforcedbyaTRIZconceptualframework,mightprovidethebasisforSuper-OrganismicBionics,whichishypothesizedasnecessaryforeffectiveecologicalengineering.Thishypothesisissupportedbyacasestudy-thedesignofasustainableartificialnaturereserveforwildpollinatorsasalivingmachine.
简介:Adigitalman-machineinteractionsystemcontrolledbycommunicationsbetweentwoprocessorsofTMS320F240andAT98C2051wasresearchedinthepaper.Thesystemiseasytosetandmodifyweldingprocessparametersbykeyboards,anddisplayinformationofweldingsitebyLCD(LiquidCrystalDisplay).Asonepartofmulti-tasksystemaboutTIGweldingmachine,thecoordinationofman-machineinteractionsystemwithothertasksisthemainpointtothestabilityandreliabilityofitsoperation.Experimentsresultindicatesthatthesystemisstable,operation-flexible,highprecision,andanti-interfering.
简介:Basedonexperimentmodalanalysis(EMA)andoperationmodalanalysis(OMA),thedynamiccharacteristicsofcylindricalgrindingmachineweremeasuredandprovidedabasisforfurtherfailureanalysis.Theinfluencesofgrindingparametersondynamiccharacteristicswerestudiedbyanalyzingthediagnosticsignalsextractedfromracingandgrindingexperiments.Thesignificantfrequencyof38Hzrelatedtogrindingwheelspindlespeedof2307r/minshowedthatthewheelspindlesystemwasinastateofimbalan...
简介:AbstractMachine learning shows enormous potential in facilitating decision-making regarding kidney diseases. With the development of data preservation and processing, as well as the advancement of machine learning algorithms, machine learning is expected to make remarkable breakthroughs in nephrology. Machine learning models have yielded many preliminaries to moderate and several excellent achievements in the fields, including analysis of renal pathological images, diagnosis and prognosis of chronic kidney diseases and acute kidney injury, as well as management of dialysis treatments. However, it is just scratching the surface of the field; at the same time, machine learning and its applications in renal diseases are facing a number of challenges. In this review, we discuss the application status, challenges and future prospects of machine learning in nephrology to help people further understand and improve the capacity for prediction, detection, and care quality in kidney diseases.
简介:Dataclusteringisasignificantinformationretrievaltechniqueintoday’sdataintensivesociety.Overthelastfewdecadesavastvarietyofhugenumberofdataclusteringalgorithmshavebeendesignedandimplementedforallmostalldatatypes.Thequalityofresultsofclusteranalysismainlydependsontheclusteringalgorithmusedintheanalysis.Architectureofaversatile,lessuserdependent,dynamicandscalabledataclusteringmachineispresented.Themachineselectsforanalysis,thebestavailabledataclusteringalgorithmonthebasisofthecredentialsofthedataandpreviouslyuseddomainknowledge.Thedomainknowledgeisupdatedoncompletionofeachsessionofdataanalysis.
简介:Astructuralbionicdesignprocessissystematicallypresentedforlightweightmechanicalstructures.Bymimickingbiologicalexcellentstructuralprinciples,thestiffeningribsofamachiningtableandamovingcolumnwereredesignedforbetterload-bearingefficiency.Finiteelementmethod(FEM)simulationandmodelexperimentswerecarriedoutforperformanceverification,whichshowedtheincreaseofstructuralstaticanddynamicperformance.Structuralbionicoffersanewsolutiontochangeconventionalstructuresforhighspecificstiffness.
简介:Arobustsystemforbacklitkeyboardinspectionisrevealed.Thebacklitkeyboardnotonlyhaschangeablediversecolorsbutalsohasthelasermarkingkeys.Thekeysonthekeyboardcanbedividedintoregionsoffunctionkeys,normalkeys,andnumberkeys.However,theremighthavesometypesofdefects:incorrectilluminatingarea,non-uniformilluminationofspecifiedinspectionregion(IR),andincorrectluminanceandintensityofindividualkey.Sincetheilluminationfeaturesofbacklitkeyboardaretoocomplextoinspectforhumaninspectorintheproductionline,anauto-matedinspectionsystemforthebacklitkeyboardisproposedinthispaper.Thesystemwasdesignedintotheoperationmoduleandinspectionmodule.Asetofimageprocessingmethodsweredevelopedforthesedefectsinspection.Someexperimentalresultsdemonstratetherobustnessandeffectivenessoftheproposedsystem.
简介:为了改进表面的用机器制造的精确磨擦,用机器制造,有高效的amicropositioning细工品桌子被用作辅助在喂机制实现纳米水平放和动态赔偿。为了更好理解磨擦机器的特征,与微放调制了细工品桌子,磨擦系统的动态模型与形式的合成和Lagrange被建立“s方程方法。磨擦系统被划分成五个分系统。为每个分系统,概括运动学并且势能被获得。因此,磨擦系统的动态模型在形式的域被给。磨擦过程的起浪基于车轮和细工品颤动被完成。有微分追踪者的一个非线性的比例的不可分的衍生物(PID)控制器被开发认识到动态控制。模拟结果证明细工品的用机器制造的精确性能被利用微放细工品桌子实现动态赔偿有效地改进。试验性的测试被执行验证建议方法,并且细工品的起浪能从0.46下午被归结为0.10亩m。
简介:BasedonKKTcomplementaryconditioninoptimizationtheory,anunconstrainednon-differentialoptimizationmodelforsupportvectormachineisproposed.AnadjustableentropyfunctionmethodisgiventodealwiththeproposedoptimizationproblemandtheNewtonalgorithmisusedtofigureouttheoptimalsolution.Theproposedmethodcanfindanoptimalsolutionwitharelativelysmallparameterp,whichavoidsthenumericaloverflowinthetraditionalentropyfunctionmethods.Itisanewapproachtosolvesupportvectormachine.Thetheoreticalanalysisandexperimentalresultsillustratethefeasibilityandeffciencyoftheproposedalgorithm.
简介:Thispaperintroducesthemethodofsupportvectormachine(SVM)intothefieldofsyntheticearthquakepre-diction,whichisanon-linearandcomplexseismogenicsystem.Asanexample,weapplythismethodtopredictthelargestannualmagnitudefortheNorthChinaarea(30°E-42°E,108°N-125°N)andthecapitalregion(38°E-41.5°E,114°N-120°N)onthebasisofseismicityparametersandobservedprecursorydata.ThecorrespondingpredictionratesfortheNorthChinaareaandthecapitalregionare64.1%and75%,respectively,whichshowsthatthemethodisfeasible.
简介:Parallelmachineproblemswithasingleserverandreleasetimesaregeneralizationsofclassicalparallelmachineproblems.Beforeprocessing,eachjobmustbeloadedonamachine,whichtakesacertainreleasetimesandacertainsetuptimes.Allthesesetupshavetobedonebyasingleserver,whichcanhandleatmostonejobatatime.Inthispaper,wecontinuestudyingthecomplexityresultforparallelmachineproblemwithasingleandreleasetimes.Newcomplexityresultsarederivedforspecialcases.