Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age c...Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.展开更多
In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment ch...In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment changes,the certain policy does not suit any more.Thereby,the policy-based management should also have similar "natural selection" process.Useful policy will be retained,and policies which have lost their effectiveness are eliminated.A policy optimization method based on evolutionary learning was proposed.For different shooting times,the priority of policy with high shooting times is improved,while policy with a low rate has lower priority,and long-term no shooting policy will be dormant.Thus the strategy for the survival of the fittest is realized,and the degree of self-learning in policy management is improved.展开更多
Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied t...Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied the Artificial Neural Networks （ANN） to estimate the water quality index on the Dong Nai River flowing through Dong Nai and Binh Duong provinces. The information and data including 10 water quality parameters of the Dong Nai River at 23 monitoring stations were collected during the recorded time period from 2010 to 2014 to build water quality prediction models. The results of the study demonstrated that the Water Quality Index （WQI） forecasted with GRNN was very significant and had high correlation coefficient （R2 = 0.974 and p = 0.0） compared to the real values of the WQI. Moreover, the ANN models provided better predicted values than the multiple regression models did.展开更多
In this paper, we conduct research on the enterprise management and the related employee incentive mechanism under the environment of enterprise social networks. As the sharp change in the environment, the enterprise ...In this paper, we conduct research on the enterprise management and the related employee incentive mechanism under the environment of enterprise social networks. As the sharp change in the environment, the enterprise how to win the competitive advantage for a long time which caused many strategic management thinking, to promote the new development of the theory of the strategic management. Our designed mechanism will enhance the management activities and promote the general value of the employees which has significant meanings.展开更多
At elevated temperature regimes and abundant precipitation, mobilization and accretion of weathered iron oxides are promoted especially in a reduced environments in the tropics. This may lead to the formation of plint...At elevated temperature regimes and abundant precipitation, mobilization and accretion of weathered iron oxides are promoted especially in a reduced environments in the tropics. This may lead to the formation of plinthite, which hardens irreversibly upon repeated wetting and drying to form petroplinthite. The need for this review stems from the seemingly dearth of information on the subject and a need to clarify different terms used in describing plinthite. We review various research works on plinthite and its associated pedogenic forms in the tropics. Furthermore, we proffer recommendations as to the most appropriate land use management practices that could help minimise the environmental and agronomic problems associated with plinthite and its related pedogenic forms. Parent material, temperature, seasonality and geomorphology are critical factors that influence soil water regime which in turn affect the pedogenesis of plinthite. Soil pH and mineralogy are additional factors that could also promote plinthite formation. Fossil plinthic soils are potential proxies for palaeoenvironmental reconstruction. Measures used in the management of plinthic soils include mechanically breaking the hardpans and the use of organic and inorganic amendments to modify the structure and chemistry of the soils. Avoidance of practices that would predispose soils to erosion would also prevent plinthization. We call for the relinquishment of the term ＂[aterite＂ which is a generM term for all forms of iron oxide-enriched earthy materials as used for plinthite. Plinthic horizon should also be incorporated into the United States Department of Agriculture Soil Taxonomy in view of its growing importance in soils.展开更多
基金supported by the National Key Technology R&D Program under Grant No. 2012BAH18B05
文摘Internet traffic classification plays an important role in network management. Many approaches have been proposed to clas-sify different categories of Internet traffic. However, these approaches have specific us-age contexts that restrict their ability when they are applied in the current network envi-ronment. For example, the port based ap-proach cannot identify network applications with dynamic ports; the deep packet inspec-tion approach is invalid for encrypted network applications; and the statistical based approach is time-onsuming. In this paper, a novel tech-nique is proposed to classify different catego-ries of network applications. The port based, deep packet inspection based and statistical based approaches are integrated as a multi-stage classifier. The experimental results demonstrate that this approach has high rec-ognition rate which is up to 98% and good performance of real-time for traffic identifica-tion.
基金National Natural Science Foundation of China(No.60534020)Cultivation Fund of the Key Scientific and Technical Innovation Project from Ministry of Education of China(No.706024)International Science Cooperation Foundation of Shanghai,China(No.061307041)
文摘In order to achieve an intelligent and automated self-management network,dynamic policy configuration and selection are needed.A certain policy only suits to a certain network environment.If the network environment changes,the certain policy does not suit any more.Thereby,the policy-based management should also have similar "natural selection" process.Useful policy will be retained,and policies which have lost their effectiveness are eliminated.A policy optimization method based on evolutionary learning was proposed.For different shooting times,the priority of policy with high shooting times is improved,while policy with a low rate has lower priority,and long-term no shooting policy will be dormant.Thus the strategy for the survival of the fittest is realized,and the degree of self-learning in policy management is improved.
文摘Recent trends in environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water quality. In this case study, the authors applied the Artificial Neural Networks （ANN） to estimate the water quality index on the Dong Nai River flowing through Dong Nai and Binh Duong provinces. The information and data including 10 water quality parameters of the Dong Nai River at 23 monitoring stations were collected during the recorded time period from 2010 to 2014 to build water quality prediction models. The results of the study demonstrated that the Water Quality Index （WQI） forecasted with GRNN was very significant and had high correlation coefficient （R2 = 0.974 and p = 0.0） compared to the real values of the WQI. Moreover, the ANN models provided better predicted values than the multiple regression models did.
文摘In this paper, we conduct research on the enterprise management and the related employee incentive mechanism under the environment of enterprise social networks. As the sharp change in the environment, the enterprise how to win the competitive advantage for a long time which caused many strategic management thinking, to promote the new development of the theory of the strategic management. Our designed mechanism will enhance the management activities and promote the general value of the employees which has significant meanings.
文摘At elevated temperature regimes and abundant precipitation, mobilization and accretion of weathered iron oxides are promoted especially in a reduced environments in the tropics. This may lead to the formation of plinthite, which hardens irreversibly upon repeated wetting and drying to form petroplinthite. The need for this review stems from the seemingly dearth of information on the subject and a need to clarify different terms used in describing plinthite. We review various research works on plinthite and its associated pedogenic forms in the tropics. Furthermore, we proffer recommendations as to the most appropriate land use management practices that could help minimise the environmental and agronomic problems associated with plinthite and its related pedogenic forms. Parent material, temperature, seasonality and geomorphology are critical factors that influence soil water regime which in turn affect the pedogenesis of plinthite. Soil pH and mineralogy are additional factors that could also promote plinthite formation. Fossil plinthic soils are potential proxies for palaeoenvironmental reconstruction. Measures used in the management of plinthic soils include mechanically breaking the hardpans and the use of organic and inorganic amendments to modify the structure and chemistry of the soils. Avoidance of practices that would predispose soils to erosion would also prevent plinthization. We call for the relinquishment of the term ＂[aterite＂ which is a generM term for all forms of iron oxide-enriched earthy materials as used for plinthite. Plinthic horizon should also be incorporated into the United States Department of Agriculture Soil Taxonomy in view of its growing importance in soils.
