As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning...As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning,it can not achieve lane level positioning accuracy.Motivated by the mature ranging technologies such as radar and ultra-wideband(UWB),several cooperative positioning(CP)methods have been proposed to enhance the accuracy and robustness of GPS.In this paper,we proposed a twostage CP algorithm that combines multidimensional scaling(MDS)and Procrustes analysis for vehicles with GPS information.Specifically,the optimized MDS based on the scaling by majorizing a complicated function(SMACOF)algorithm is first proposed to get the relative coordinates of vehicles which can tackle measurements of different error distributions,then Procrustes analysis is carried out to transform the relative coordinates of vehicles to their absolute coordinates based on GPS information.All the computations are performed at the mobile edge computing node(MECN)for the request of ultra-reliable and low latency communications(URLLC).Simulation results validate that the proposed algorithm can greatly improve the positioning accuracy and robustness for vehicles.展开更多
The soil insect community was studied in grey desert soil district in September 2004. 90 soil samples and 100 pitfalls were collected from 10 treatments, i.e., abandonment （Aband.）, CK, N, NP, NK, PK, NPK, MNPK （fe...The soil insect community was studied in grey desert soil district in September 2004. 90 soil samples and 100 pitfalls were collected from 10 treatments, i.e., abandonment （Aband.）, CK, N, NP, NK, PK, NPK, MNPK （fertilizer N：organic N = 3：7）, 1.5MNPK, and SNPK. 4915 soil insects （128 unknown）, as individuals belonging to 9 orders and 33 families, were obtained by pitfall traps and modified Tullgren methods. The results showed that, based on the number of individuals and groups, the macro fauna in total reached their peaks in abandonment, whereas meso and micro fauna in N and PK, respectively. Of the 10 treatments, the most dominant of soil insect composition was in MNPK and most evenness was N. The result by Kruskal-Wallis test indicated that the distribution of the arable soil insect was significantly impacted by different fertilizer treatments （X0.05（9） = 23.38, P 〈 0.005）, and soil insect group of the abandonment was significantly different from that of other fertilizer treatments. The soil insect community was divided into five groups by non-metric- MDS analysis： （1） NPK, MNPK, 1.5MNPK, CK, （2） NP and PK, （3） NK and N, （4） SNPK, and （5） abandonment, which indicated that distribution of soil insect was related to the character of the fertilizer. In the principal component analysis, two factors explained 98.51% of the total variation among the 10 treatments, and the factor one explained that N and SNPK positively affected soil insect community, whereas factor two explained that 1.5MNPK positively affected soil insect community, which showed that the diversified fertilizer did not evenly affect the soil insect community.展开更多
基金This work was supported in part by the National Key Research and Development Program of China(2019YFB1600100)in part by the Foundation of Shaanxi Key Laboratory of Integrated and Intelligent Navigation under Grant SKLIIN-20190103.
文摘As the basis of location-based services(LBS),positioning is one of the most essential parts in intelligent transportation systems(ITS).Although global positioning system(GPS)has been widely used in vehicle positioning,it can not achieve lane level positioning accuracy.Motivated by the mature ranging technologies such as radar and ultra-wideband(UWB),several cooperative positioning(CP)methods have been proposed to enhance the accuracy and robustness of GPS.In this paper,we proposed a twostage CP algorithm that combines multidimensional scaling(MDS)and Procrustes analysis for vehicles with GPS information.Specifically,the optimized MDS based on the scaling by majorizing a complicated function(SMACOF)algorithm is first proposed to get the relative coordinates of vehicles which can tackle measurements of different error distributions,then Procrustes analysis is carried out to transform the relative coordinates of vehicles to their absolute coordinates based on GPS information.All the computations are performed at the mobile edge computing node(MECN)for the request of ultra-reliable and low latency communications(URLLC).Simulation results validate that the proposed algorithm can greatly improve the positioning accuracy and robustness for vehicles.
文摘The soil insect community was studied in grey desert soil district in September 2004. 90 soil samples and 100 pitfalls were collected from 10 treatments, i.e., abandonment （Aband.）, CK, N, NP, NK, PK, NPK, MNPK （fertilizer N：organic N = 3：7）, 1.5MNPK, and SNPK. 4915 soil insects （128 unknown）, as individuals belonging to 9 orders and 33 families, were obtained by pitfall traps and modified Tullgren methods. The results showed that, based on the number of individuals and groups, the macro fauna in total reached their peaks in abandonment, whereas meso and micro fauna in N and PK, respectively. Of the 10 treatments, the most dominant of soil insect composition was in MNPK and most evenness was N. The result by Kruskal-Wallis test indicated that the distribution of the arable soil insect was significantly impacted by different fertilizer treatments （X0.05（9） = 23.38, P 〈 0.005）, and soil insect group of the abandonment was significantly different from that of other fertilizer treatments. The soil insect community was divided into five groups by non-metric- MDS analysis： （1） NPK, MNPK, 1.5MNPK, CK, （2） NP and PK, （3） NK and N, （4） SNPK, and （5） abandonment, which indicated that distribution of soil insect was related to the character of the fertilizer. In the principal component analysis, two factors explained 98.51% of the total variation among the 10 treatments, and the factor one explained that N and SNPK positively affected soil insect community, whereas factor two explained that 1.5MNPK positively affected soil insect community, which showed that the diversified fertilizer did not evenly affect the soil insect community.
