简介:TheemergenceofB2Belectronicmarketshasgreatlychangedtherelativebargainingpowerofbuyersandsellers.Westudytheequilibriummarketstructureinabuyer’smarket.Wefindthatbuyer-controlledB2BmarketsandneutralB2Bmarketshavedifferentequilibriumstructures,andtheemergenceofB2Bmarketswillincreasesocialwelfare,butitseffectonbuyersandsellerswillbedifferent:B2Bmarketsincreasetheconsumersurplusoftheendmarket,buttheireffectsonbuyerandsellerprofitsaremoderatedbytherelativebargainingpowerofbuyersandsellers.TheprofitsofthesidewithmuchweakerbargainingpowerwilldecreaseduetotheintroductionofB2Bmarkets.
简介:Thispaperconstructedportfoliosaccordingtothegrowthratesandtheirstabilityoffirm'stotalstockholders'equitypershareandnetincomepershare,usingallthefirms'informationofShanghaiA-sharemarket.Wefoundthatthemarketexhibitssomeoverreactiontothegrowthraieoffirm'snetincomepershare,andisn'tsensitivetothestabilityoffirm'sgrowthrates.
简介:摘要随着5G移动通信网络的来临,移动流量得到了大幅度的增长,新型业务面对越来越多的挑战,比如说高回传带宽以及低时延。移动边缘计算MEC在一定程度上可以解决这些问题,对整体的网络架构进行初步的介绍,了解5G在标准化发展的过程当中,如何更加贴合于MEC部署策略。未来5G移动通信网络,将会是一个多级计算协同的网络系统,通过先进技术整体的设计,会使得整体的架构在灵活性和自适应性方面有大幅度的提高。与此同时,在进行通信和相关计算功能展开的过程当中,会充分的应用到虚拟化技术,便于可以对存储资源进行高效的共享。5G移动通信网络,无论是在基础理论还是关键技术方面,都具有一定其他技术无法比拟的优势,通过对于相关理论和具体的展开形式,进行更加精准的研究,希望可以推动通信和计算技术协同发展。
简介:ANEFFICINTIMPLEMENTATIONOFMERRILL'SMETHODYANGBing(DepartmentofManagementEngineeringHarbinEngineeringUniversityHarbin150001)Ab...
简介:Let■Ω=Γ=Γ1+Γ2(seeFig.1),meas(Γ1)>0,V={v|v∈H1(Ω),v|Γ1=0},andV0={ω|Δω=hinΩ,ω|Γ=0,(?)h∈V}.LetV0′=thedualspaceofV0,a(u,v)=∫Ω▽u·▽Δvdx,andF(v)=∫Ωfvdx+∫Γ2g1Δvds-∫Γg2(?)ds,f∈V′0,g1∈H-(1/2)(Γ2),g2∈H-(3/2)(Γ).Considerthevariationalproblem:findu∈Vsuchthata(u,v)=F(v),(?)v∈V0.(1)UsingTartar’slemma,weprovethatforproblem(1)thereexistsauniqueu∈Vsatisfying■
简介:TheMarcinkiewicz-Zygmundinequalitywithderivativeforanalgebraicpoly-nomialoforder≤N=(q+1)n-1isestablishedinaBαspace.Asacorollary,theMarcinkiewicz-Zygmundinequalitywithderivativeforanalgebraicpolynomialinapar-ticularOrliczspaceisobtained.
简介:Inthiseraofadata-drivensociety,usefuldata(BigData)isoftenunintentionallyignoredduetolackofconvenienttoolsandexpensivesoftware.Forexample,weblogfilescanbeusedtoidentifyexplicitinformationofbrowsingpatternswhenusersaccesswebsites.Somehiddeninformation,however,cannotbedirectlyderivedfromthelogfiles.Wemayneedexternalresourcestodiscovermoreknowledgefrombrowsingpatterns.Thepurposeofthisstudyistoinvestigatetheapplicationofwebusageminingbasedonweblogfiles.Theoutcomeofthisstudysetsfurtherdirectionsofthisinvestigationonwhatandhowimplicitinformationembeddedinlogfilescanbeefficientlyandeffectivelyextracted.Furtherworkinvolvescombiningtheuseofsocialmediadatatoimprovebusinessdecisionquality.