简介:Anincreasingnumberofcomputersystemsarebeingviewedintermsofautonomousagents.Mostpeoplebelievethatagent-orientedapproachiswellsuitedtodesigningandbuildingcomplexsystems.Yet,todate,littleefforthadbeendevotedtodiscussingtheadvantagesofagent-orientedapproachasamainstreamsoftwareengineeringparadiam.Herebothofthisissuesandtherelationbetweenobject-orientedandagentorientedwillbeargued.Wedescribeanagent-orientedmethodologyandprovideaquotefordesigningaauctionsystem.
简介:INTRODUCTIONSincetheirintroductioninmid-1980s,polyamidoamide(PAMAM)dendrimershaveattractedconsiderableattentionbecauseoftheiruniquestructuresandproperties.Accordingtopreliminarystudiesinanimals,PAMAMdendrimersarenon-immunogenic,verylowinvivotoxicityandcanbeexcretedbyurineandfeces.
简介:Anincreasingnumberofcomputersystemsarebeingviewedintermsofautonomousagents.Mostpeoplebelievethatagent-orientedapproachiswellsuitedtodesignandbuildcomplexsystems.Yet.todate,littleefforthadbeendevotedtodiscusstheadvantagesofagent-orientedapproachasamainstreamsoftwareengineeringparadigm.Herebothofthisissuesandtherelationbetweenobject-orientedandagent-orientedwillbeargued.wedescribeanagent-orientedmethodologyandprovideaquotefordesigninganauctionsystem.
简介:包分类被学习十年了;它基于一个给定的规则集合分类包进特定的流动。当定义软件的网络被建议,包分类的一个最近的趋势是放大五元组的模型到多元组。一般来说,多重地上的包分类是一个复杂问题。尽管大多数存在softwarebased算法在实践被证明非凡,他们对经典五元组的模型仅仅合适并且对困难被扩大规模。同时,硬件特定的答案不可弯曲、昂贵,并且他们中的一些是消费的力量。在这份报纸,我们为多核心系统建议一条通用的多维的包分类途径。在我们的途径,新奇数据结构和四个基于分解的算法被设计优化分类并且规则更新。为多地规则,一个规则集合根据领域的数字被切成几部分。每部分独立地工作。这样,这些地在平行被寻找,所有部分结果最后一起被合并。表明我们的途径的可行性,我们实现一个原型并且评估它的产量和潜伏。试验性的结果证明我们的途径比另外的分解底的算法和43%更低的潜伏的完成40%更高的产量平均比另外的算法的统治增长更改。而且,我们的途径平均节省39%记忆消费并且有好可伸缩性。
简介:Aprototypesystemforagent-baseddistributeddynamicservicesthatwillbeappliedtothedevelopmentofDataGridsforhigh-energyphysicsispresented.Theagent-basedsystemswearedesigninganddevelogpinggather,disseminateandcoordinateconfiguration,time-dependentstateandotherinformationintheGridsystemasawhole.Thesesystemsarebeingdevelopedasanenablingtechnologyforworkflow-managementandotherformsofend-to-endGridsystemmonitoringandmanagement.ThisprototypeisbeingdevelopedinJavaandisbasedontheJINI,MobileAgents,Self-OrganizingNeuralNetworks.
简介:Toenhancethesecurityofnetworksystems,putsforwardakindofsoftwareagentisputforward,whichhastheinductionabilityofnetworkframeworksandtheabilityofbehaviorindependence.Itismobilescanningagent.Moreattentionsispaidtoexpoundhowtodesignandrealizemobilescanningagent.Besides,itisalsoexplainedtheprogramsofmobilescanningagentsystem.Intheend,itexpectsmobilescanningagent.
简介:ThispaperintroducesasoftwareagentasavirtualplayerofthebusinessgamecalledBakeryGame.Thebusinessgameisatooltounderstandbusinessandmanagementprinciplesthroughexperienceinavirtualworld.Inordertoconstructsoftwareagentsforthegamingsimulation,whichisabletoparticipateinagameandbecomehumanplayers'worthyrival,wecombineasimplemodelthatconsidersthepropertyofBakeryGamewithastrategyadjustmentmodel.Theagenthasso-calledstrategyparametersthatareupdatedthroughtheexperience.Theagentchangeshisstrategydependingonparticularsituation.Theagentparticipatesinthegamethatisregeneratedfromlogdatainvarioussituations.
简介:AIMTo调查vasoactive的角色在形式剥夺的肠的肽(贵宾)近视(频分多路复用).METHODSFDM被放在三组八只小鸡创造一半透明在他们的右眼睛上更弥漫。Intravitreal注射盐并且贵宾一天被使用一次进组的堵塞眼睛2和3分别地。视网膜镜检法和轴的长度(AL)大小在第一和8th天更弥漫穿。在三个组的右眼睛和白天8上的第一个组的左眼睛的VIP受体和ZENK蛋白质的视网膜mRNA层次用在权利的中部的最后的折射(D)看的.RESULTSThe是的实时聚合酶链反应(PCR)被决定-13.75(-16.00,-12.00),-11.50(-12.50,-7.50),和-1.50(在组的-4.75,-0.75)1,2,和3,分别地(P<0.001)。在右眼睛的中部的AL(公里)是10.65(10.00,11.10),9.90(9.70,10.00),并且9.20(9.15,9.25)在组1,2,和3,分别地(P<0.001)。为VIP2受体的中部的三角洲三角洲周期阀值(CT)价值是1.07(0.82,1.43),1.22(0.98,1.65),0.29(0.22,0.45)在组的右眼睛1,2,和3,和1.18(0.90,1.37)在组1的左眼睛,分别地(P=0.001)。为ZENK蛋白质的中部的三角洲三角洲CT价值是1.07(0.63,5.03),3.55(2.20,5.55),在组的右眼睛无法发现1,2,和3和1.89(0.21,4.73)在组1的左眼睛,(P=0.001)分别地,.CONCLUSIONVIP在频分多路复用的发展有潜在的禁止的效果。
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