It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily ...It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily volumes of sewage.The generation of sewage is the result of multiple factors from the whole social system.Characterized by strong process abstraction ability,data mining techniques have been viewed as promising prediction methods to realize intelligent STP management.However,existing data mining-based methods for this purpose just focus on a single factor such as an economical or meteorological factor and ignore their collaborative effects.To address this challenge,a deep learning-based intelligent management mechanism for STPs is proposed,to predict business volume.Specifically,the grey relation algorithm(GRA) and gated recursive unit network(GRU) are combined into a prediction model(GRAGRU).The GRA is utilized to select the factors that have a significant impact on the sewage business volume,and the GRU is set up to output the prediction results.We conducted a large number of experiments to verify the efficiency of the proposed GRA-GRU model.展开更多
This study examined the impact of trade facilitation on economic development, particularly the impact of customs environment on trade flows over the period from 1995 to 2010. Five countries of the East African Communi...This study examined the impact of trade facilitation on economic development, particularly the impact of customs environment on trade flows over the period from 1995 to 2010. Five countries of the East African Community (EAC), namely, Tanzania, Kenya, Uganda, Rwanda, and Burundi, are involved. The study employs a gravity model for estimating bilateral trade flows between the EAC partner states. The ordinary least square (OLS) technique is adopted and applied for the regression analysis by using the Stata 10.0 software. Results suggest that, the customs environment of the importer is significant and possesses a strongly positive impact on East African trade flows. Results also find that the customs environment of the exporter is insignificant, even though it shows a negative relationship with the East African trade flows, hence a negative determinant. East African countries have to improve their customs environment, especially when undertaking an importation, in order to boost the overall trade flow in the block. They should also improve other trade facilitation indicators, such as port efficiency, regulatory environment, and infrastructure. The aid for trade, in terms of technical and financial assistance, should also be enhanced for the development of infrastructure, including roads, railways, ports, bridges, and border posts.展开更多
Anomaly detection of privileged processes is one of the most important means to safeguard the host and system security. The key problem for improving detection performance is to identify local behavior of the short se...Anomaly detection of privileged processes is one of the most important means to safeguard the host and system security. The key problem for improving detection performance is to identify local behavior of the short sequences in traces of system calls accurately. An alternative modeling method was proposed based on the typical pattern matching of short sequences, which builds upon the concepts of short sequences with context dependency and the specially designed aggregation algorithm. The experimental results indicate that the modeling method considering the context dependency improves clearly the sensitive decision threshold as compared with the previous modeling method.展开更多
基金Project(KJZD-M202000801) supported by the Major Project of Chongqing Municipal Education Commission,ChinaProject(2016YFE0205600) supported by the National Key Research&Development Program of China+1 种基金Project(CXQT19023) supported by the Chongqing University Innovation Group Project,ChinaProjects(KFJJ2018069,1853061,1856033) supported by the Key Platform Opening Project of Chongqing Technology and Business University,China。
文摘It is generally believed that intelligent management for sewage treatment plants(STPs) is essential to the sustainable engineering of future smart cities.The core of management lies in the precise prediction of daily volumes of sewage.The generation of sewage is the result of multiple factors from the whole social system.Characterized by strong process abstraction ability,data mining techniques have been viewed as promising prediction methods to realize intelligent STP management.However,existing data mining-based methods for this purpose just focus on a single factor such as an economical or meteorological factor and ignore their collaborative effects.To address this challenge,a deep learning-based intelligent management mechanism for STPs is proposed,to predict business volume.Specifically,the grey relation algorithm(GRA) and gated recursive unit network(GRU) are combined into a prediction model(GRAGRU).The GRA is utilized to select the factors that have a significant impact on the sewage business volume,and the GRU is set up to output the prediction results.We conducted a large number of experiments to verify the efficiency of the proposed GRA-GRU model.
文摘This study examined the impact of trade facilitation on economic development, particularly the impact of customs environment on trade flows over the period from 1995 to 2010. Five countries of the East African Community (EAC), namely, Tanzania, Kenya, Uganda, Rwanda, and Burundi, are involved. The study employs a gravity model for estimating bilateral trade flows between the EAC partner states. The ordinary least square (OLS) technique is adopted and applied for the regression analysis by using the Stata 10.0 software. Results suggest that, the customs environment of the importer is significant and possesses a strongly positive impact on East African trade flows. Results also find that the customs environment of the exporter is insignificant, even though it shows a negative relationship with the East African trade flows, hence a negative determinant. East African countries have to improve their customs environment, especially when undertaking an importation, in order to boost the overall trade flow in the block. They should also improve other trade facilitation indicators, such as port efficiency, regulatory environment, and infrastructure. The aid for trade, in terms of technical and financial assistance, should also be enhanced for the development of infrastructure, including roads, railways, ports, bridges, and border posts.
文摘Anomaly detection of privileged processes is one of the most important means to safeguard the host and system security. The key problem for improving detection performance is to identify local behavior of the short sequences in traces of system calls accurately. An alternative modeling method was proposed based on the typical pattern matching of short sequences, which builds upon the concepts of short sequences with context dependency and the specially designed aggregation algorithm. The experimental results indicate that the modeling method considering the context dependency improves clearly the sensitive decision threshold as compared with the previous modeling method.