Rapid economic development in recent decades has resulted in environmental degradation of Liaodong Bay, North China, where eutrophication is becoming more evident because of excess nutrients inputs. To assess the bent...Rapid economic development in recent decades has resulted in environmental degradation of Liaodong Bay, North China, where eutrophication is becoming more evident because of excess nutrients inputs. To assess the benthic ecological status in Liaodong Bay, AZTI＇s Marine Biotic Index （AMBI） and multivariate-AMBI （MoAMBI） were applied using both benthic macroinvertebrate density and biomass data collected from Liaodong Bay in July 2007. This first application of AMBI and M-AMBI in Liaodong Bay showed that the nearshore areas of the bay, especially near river estuaries, were severely disturbed, with a clear gradient of disturbance decreasing seaward. Ecological status assessed from density and biomass data was quite similar. Significant relationships were also found between both indices and environmental variables in Liaodong Bay. Moreover, the spatial distributions of both AMBI and M-AMBI matched those of plotted eutrophication indices （EI） in the surface water layer, and significant linear correlations were found between both benthic indices and EI. In general, both AMBI and M-AMBI worked well on assessing the ecological status of Liaodong Bay under eutrophication stress due to excess nutrients inputs.展开更多
To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesi...To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.展开更多
The expression of residual is obtained according to its dynamic response to mean shift, then the distribu- tion of T2 statistic applied to the residual is derived, thus the probability of the 7a statistic lying outsid...The expression of residual is obtained according to its dynamic response to mean shift, then the distribu- tion of T2 statistic applied to the residual is derived, thus the probability of the 7a statistic lying outside the control limit is calculated. The above-mentioned results are substituted into the infinite definition expression of the average run length （ARL）, and then the final finite ARL expression is obtained. An example is used to demonstrate the procedures of the proposed method. In the comparative study, eight autocorrelated processes and four different mean shifts are performed, and the ARL values of the proposed method are compared with those obtained by simulation method with 50 000 replications. The accuracy of the proposed method can be illustrated through the comparative results.展开更多
基金Supported by the Special Foundation of Chinese Research Academy of Environmental Sciences(No.gyk5091201) the State Environmental Protection,Research and Public Service Industry,a special program(No.201309007)
文摘Rapid economic development in recent decades has resulted in environmental degradation of Liaodong Bay, North China, where eutrophication is becoming more evident because of excess nutrients inputs. To assess the benthic ecological status in Liaodong Bay, AZTI＇s Marine Biotic Index （AMBI） and multivariate-AMBI （MoAMBI） were applied using both benthic macroinvertebrate density and biomass data collected from Liaodong Bay in July 2007. This first application of AMBI and M-AMBI in Liaodong Bay showed that the nearshore areas of the bay, especially near river estuaries, were severely disturbed, with a clear gradient of disturbance decreasing seaward. Ecological status assessed from density and biomass data was quite similar. Significant relationships were also found between both indices and environmental variables in Liaodong Bay. Moreover, the spatial distributions of both AMBI and M-AMBI matched those of plotted eutrophication indices （EI） in the surface water layer, and significant linear correlations were found between both benthic indices and EI. In general, both AMBI and M-AMBI worked well on assessing the ecological status of Liaodong Bay under eutrophication stress due to excess nutrients inputs.
基金supported by the National Natural Science Foundation of China under Grants No.60973110,No.61003307the Natural Science Foundation of Beijing City of China under Grant No.4102059the Major Projects of Ministry of Industry and Information Technology under Grants No.2010ZX03006-002-03,No.2011ZX03005-005
文摘To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment,a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper.It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons.To reduce the time complexity of the IMR algorithm,Spatial Correlation Filter (SCF) is also proposed,which can remove the most serious NLoS distance with low calculation cost.Combined with the proposed SCF and IMR algorithm,nodes can be localized with high accuracy and low time complexity.Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.
基金Supported by National Natural Science Foundation of China (No.70931004 and No. 70802043)
文摘The expression of residual is obtained according to its dynamic response to mean shift, then the distribu- tion of T2 statistic applied to the residual is derived, thus the probability of the 7a statistic lying outside the control limit is calculated. The above-mentioned results are substituted into the infinite definition expression of the average run length （ARL）, and then the final finite ARL expression is obtained. An example is used to demonstrate the procedures of the proposed method. In the comparative study, eight autocorrelated processes and four different mean shifts are performed, and the ARL values of the proposed method are compared with those obtained by simulation method with 50 000 replications. The accuracy of the proposed method can be illustrated through the comparative results.
