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关环法合成麝香酮的研究新进展 被引量:2
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作者 李建民 王晓琴 +1 位作者 解丽娟 张忠诚 《精细石油化工》 CAS CSCD 北大核心 2012年第2期81-84,共4页
从长链二元酸、有机金属催化剂介导的缩合反应、关环复分解反应和仿生合成4个方面,综述了2000年以来由关环法合成麝香酮的研究进展,评述了各类合成路线的优缺点,并对关环法合成麝香酮的研究进行了展望。
关键词 天然麝香 麝香酮 关环法 合成
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Deep learning-based intelligent management for sewage treatment plants 被引量:2
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作者 WAN Ke-yi DU Bo-xin +5 位作者 WANG Jian-hui GUO Zhi-wei FENG Dong GAO Xu SHEN Yu YU Ke-ping 《Journal of Central South University》 SCIE EI CAS CSCD 2022年第5期1537-1552,共16页
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
关键词 deep learning intelligent management sewage treatment plants grey relation algorithm gated recursive unit
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The Impact of Trade Facilitation on Economic Development: A Case of East African Community (EAC)
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作者 Robert Suphian 《Journal of Modern Accounting and Auditing》 2012年第11期1753-1762,共10页
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
关键词 trade facilitation customs environment trade flows
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Trusted Anomaly Detection with Context Dependency
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作者 彭新光 闫美凤 《Journal of Shanghai Jiaotong university(Science)》 EI 2006年第2期253-258,共6页
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
关键词 system security anomaly detection context dependency
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