The spatio-temporal patterns of macrofaunal fouling assemblages were quantitatively investigated in the nearshore waters of the South China Sea.The work was undertaken by deploying seasonal panels at two sites(H-site,...The spatio-temporal patterns of macrofaunal fouling assemblages were quantitatively investigated in the nearshore waters of the South China Sea.The work was undertaken by deploying seasonal panels at two sites(H-site,L-site) for one year,and the fouling communities on the panels were examined and analyzed.The results indicated that species composition of assemblages was obviously different between the two sites.At both sites the assemblages were characteristic with solitary dominant species throughout the year,with Amphibalanus reticulates dominating at H-site and Hydroides elegans at L-site.Shannon index and biomass of the assemblages varied with depth and season at both sites.At H-site the total biomass in summer and autumn were significantly higher than those in spring and winter,while at L-site the assemblage biomass also differed significantly among the four seasons,and the greatest biomass occurred at the depth of 2.0 m in winter.The abundance of all seasonal samples in non-metric multidimensional scaling was clustered as one group at L-site and three groups at H-site.The environmental factors were more likely to be related to the variation of fouling assemblages.Furthermore,it also suggests that in tropical seas the integrated adaptability would qualify a species for dominating a fouling assemblage despite its short life cycle,rather than the usually assumed only species with long life span.This study reveals the complexity and characteristic dynamics of macrofaunal fouling assemblages in the tropical habitats,and the results would provide valuable knowledge for biodiversity and antifouling research.展开更多
The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot s...The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot spot”problem in WSNs,we propose an unequal clustering routing algorithm based on genetic algorithm(UCR-GA).In the cluster head election phase,the fitness function is constructed based on the residual energy,density and distance between nodes and base station,and the appropriate node is selected as the cluster head.In the data transmission phase,the cluster head selects single-hop or multi-hop communication mode according to the distance to the base station.After we comprehensively consider the residual energy of the cluster head and its communication energy consumption with the base station,an appropriate relay node is selected.The designed protocal is simulated under energy homogeneous and energy heterogeneity conditions,and the results show that the proposed routing protocal can effectively balance energy consumption,prolong the life cycle of network,and is appicable to heterogeneous networks.展开更多
The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. T...The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.展开更多
基金supported by the National Natural Science Foundation of China(Nos.31660128,31360105 and 31160098)the Hainan University(Nos.kypd 1046 and Hdcxcyxm201715)
文摘The spatio-temporal patterns of macrofaunal fouling assemblages were quantitatively investigated in the nearshore waters of the South China Sea.The work was undertaken by deploying seasonal panels at two sites(H-site,L-site) for one year,and the fouling communities on the panels were examined and analyzed.The results indicated that species composition of assemblages was obviously different between the two sites.At both sites the assemblages were characteristic with solitary dominant species throughout the year,with Amphibalanus reticulates dominating at H-site and Hydroides elegans at L-site.Shannon index and biomass of the assemblages varied with depth and season at both sites.At H-site the total biomass in summer and autumn were significantly higher than those in spring and winter,while at L-site the assemblage biomass also differed significantly among the four seasons,and the greatest biomass occurred at the depth of 2.0 m in winter.The abundance of all seasonal samples in non-metric multidimensional scaling was clustered as one group at L-site and three groups at H-site.The environmental factors were more likely to be related to the variation of fouling assemblages.Furthermore,it also suggests that in tropical seas the integrated adaptability would qualify a species for dominating a fouling assemblage despite its short life cycle,rather than the usually assumed only species with long life span.This study reveals the complexity and characteristic dynamics of macrofaunal fouling assemblages in the tropical habitats,and the results would provide valuable knowledge for biodiversity and antifouling research.
基金National Natural Science Foundation of China(No.61862038)Lanzhou Talent Innovation and Entrepreneurship Technology Plan Project(No.2019-RC-14)Foundation of a Hundred Youth Talents Training Program of Lanzhou Jiaotong University。
文摘The imbalance of energy consumption in wireless sensor networks(WSNs)easily results in the“hot spot”problem that the sensor nodes in a particular area die due to fast energy consumption.In order to solve the“hot spot”problem in WSNs,we propose an unequal clustering routing algorithm based on genetic algorithm(UCR-GA).In the cluster head election phase,the fitness function is constructed based on the residual energy,density and distance between nodes and base station,and the appropriate node is selected as the cluster head.In the data transmission phase,the cluster head selects single-hop or multi-hop communication mode according to the distance to the base station.After we comprehensively consider the residual energy of the cluster head and its communication energy consumption with the base station,an appropriate relay node is selected.The designed protocal is simulated under energy homogeneous and energy heterogeneity conditions,and the results show that the proposed routing protocal can effectively balance energy consumption,prolong the life cycle of network,and is appicable to heterogeneous networks.
文摘The failure modes and effects analysis （FMEA） is widely applied in manufacturing industries in various phases of the product life cycle to evaluate the system, its design and processes for failures that can occur. The FMEA team often demonstrates different opinions and these different types of opinions are very difficult to incorporate into the FMEA by the traditional risk priority number model. In this paper, for each of the Occurrence, Severity and Detectivity parameters a fuzzy set is defined and the opinion of each FMEA team members is considered. These opinions are considered simultaneously with weights that are given to each individual based on their skills and experience levels. In addition, the opinion of the costumer is considered for each of the FMEA parameters. Then, the Risk Priority Numbers （RPN） is calculated using a Multi Input Single Output （MISO） fuzzy expert system. The proposed model is applied for prioritizing the failures of Peugeot 206 Engine assembly line in IKCo （Iran Khodro Company）.
