The dominant error source of mobile terminal location in wireless sensor networks (WSNs) is the non-line-of-sight (NLOS) propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagati...The dominant error source of mobile terminal location in wireless sensor networks (WSNs) is the non-line-of-sight (NLOS) propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagation error, residual test (RT) is an efficient one, however with high computational complexity (CC). An improved algorithm that memorizes the light of sight (LOS) range measurements (RMs) identified memorize LOS range measurements identified residual test (MLSI-RT) is presented in this paper to address this problem. The MLSI-RT is based on the assumption that when all RMs are from LOS propagations, the normalized residual follows the central Chi-Square distribution while for NLOS cases it is non-central. This study can reduce the CC by more than 90%.展开更多
Friction coefficients(static friction coefficient(SFC)and dynamic friction coefficient(DFC))of pomegranate seed on different structural surfaces(glass,aluminum,plywood,galvanized steel and rubber)as affected by moistu...Friction coefficients(static friction coefficient(SFC)and dynamic friction coefficient(DFC))of pomegranate seed on different structural surfaces(glass,aluminum,plywood,galvanized steel and rubber)as affected by moisture content(4-21.9%(d.b.))and sliding velocity(1.4-16(cm/s))were investigated.Analysis of variance(ANOVA)was performed to determine the effect of main treatments and their interactions on SFC and DFC.Significance of single or multiple effect of the main treatments with five levels was assessed using Duncan’s multiple range test(DMRT).To predict SFC and DFC,multiple linear regression(MLR)modeling technique was applied for each type of structural surface.The goodness of fit of each MLR model was evaluated using statistical parameters:coefficient of determination,root mean square error and mean relative deviation modulus.Results showed that the minimum and maximum SFC or DFC were in minimum and maximum moisture content on glass and rubber surface,respectively.ANOVA table indicated the significant effect of main treatments and their interactions on SFC and DFC at significance level of 1%(P<0.01).According to DMRT results,SFC linearly increased as moisture content increased and DFC increased also linearly as individual or simultaneous increment of moisture content and sliding velocity occurred,for all experimental conditions.According to the obtained statistical parameters,both SFC and DFC were properly predicted by means of MLR modeling technique.展开更多
基金supported by the State Key Program of National Natural Science of China (Grant No.60532030)the New Century Excellent Talents in University (Grant No.NCET-08-0333)the Natural Science Foundation of Shandong Province (Grant No.Y2007G10)
文摘The dominant error source of mobile terminal location in wireless sensor networks (WSNs) is the non-line-of-sight (NLOS) propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagation error, residual test (RT) is an efficient one, however with high computational complexity (CC). An improved algorithm that memorizes the light of sight (LOS) range measurements (RMs) identified memorize LOS range measurements identified residual test (MLSI-RT) is presented in this paper to address this problem. The MLSI-RT is based on the assumption that when all RMs are from LOS propagations, the normalized residual follows the central Chi-Square distribution while for NLOS cases it is non-central. This study can reduce the CC by more than 90%.
文摘Friction coefficients(static friction coefficient(SFC)and dynamic friction coefficient(DFC))of pomegranate seed on different structural surfaces(glass,aluminum,plywood,galvanized steel and rubber)as affected by moisture content(4-21.9%(d.b.))and sliding velocity(1.4-16(cm/s))were investigated.Analysis of variance(ANOVA)was performed to determine the effect of main treatments and their interactions on SFC and DFC.Significance of single or multiple effect of the main treatments with five levels was assessed using Duncan’s multiple range test(DMRT).To predict SFC and DFC,multiple linear regression(MLR)modeling technique was applied for each type of structural surface.The goodness of fit of each MLR model was evaluated using statistical parameters:coefficient of determination,root mean square error and mean relative deviation modulus.Results showed that the minimum and maximum SFC or DFC were in minimum and maximum moisture content on glass and rubber surface,respectively.ANOVA table indicated the significant effect of main treatments and their interactions on SFC and DFC at significance level of 1%(P<0.01).According to DMRT results,SFC linearly increased as moisture content increased and DFC increased also linearly as individual or simultaneous increment of moisture content and sliding velocity occurred,for all experimental conditions.According to the obtained statistical parameters,both SFC and DFC were properly predicted by means of MLR modeling technique.