Amblyopia is a common eye d isease caught by many children. For some reason, the traditional treating method is unsatisfactory and ineffective. By connecting home and hospital through Inte rnet, patients can receive...Amblyopia is a common eye d isease caught by many children. For some reason, the traditional treating method is unsatisfactory and ineffective. By connecting home and hospital through Inte rnet, patients can receive service of treatment designed for their own purpose. Thus the effectiveness of therapy is expected to have sigificent improvment. A n ew Internet based telemedicine system for amblyopia is put forward in this pape r with further discussions of its principles, framework and implementation method s.展开更多
Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network...Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network applications by optimized back-propagation (BP) neural network. Particle swarm optimization (PSO) algorithm was used to optimize the BP neural network. And in order to increase the identification performance, wavelet packet decomposition (WPD) was used to extract several hidden features from the time-frequency information of network traffic. The experimental results show that the average classification accuracy of various network applications can reach 97%. Moreover, this approach optimized by BP neural network takes 50% of the training time compared with the traditional neural network.展开更多
With the increasing popularity of the Internet and mobile Internet, the Virtual Community （VC） is becoming an important medium for person-to-person communication. To realise the potential of the VC, it is neces- sar...With the increasing popularity of the Internet and mobile Internet, the Virtual Community （VC） is becoming an important medium for person-to-person communication. To realise the potential of the VC, it is neces- sary to cultivate within it good group cohesion and vitality. Using empirical and experimental research methods, this study explores the ef- fect of users＇ trust in the VC Platform （VCP） on group cohesion and vitality and how brand and perceived privacy security can affect us- ers＇ trust in the VC. The research results indi- cate that the brand of the VCP can directly af- fect users＇ trust in the VC, and can also influe- nce it indirectly through users＇ perceived pri- vacy protection and perceived security protec- tion. Further, this study also confu＇ms that the performance of the VC （group cohesion and vitality） is significantly affected by users＇ trust in the VC. The results of this study can provide theoretical guidance for internet companies to maintain and enhance the value of VCs.展开更多
Exposing EFL （English as a Foreign Language） students to different varieties of English can be beneficial in numerous ways, but teachers may be unaware of how they can do this. This paper briefly explains the concep...Exposing EFL （English as a Foreign Language） students to different varieties of English can be beneficial in numerous ways, but teachers may be unaware of how they can do this. This paper briefly explains the concept of World Englishes, then describes one teacher＇s attempt to use the Internet to provide his students with examples of real English from around the world. Finally, it offers a selection of positive student responses to the experience.展开更多
Due to the rapid development,Internet has become the main field for brand building.Under this circumstance,the image of the brand is always consistent with the consumers' perception.Therefore,this study uses the m...Due to the rapid development,Internet has become the main field for brand building.Under this circumstance,the image of the brand is always consistent with the consumers' perception.Therefore,this study uses the method of text mining of search engine to explore the categories of brand archetype based on Brand Personality Theory from the perspective of Internet.The results find that 12 brand archetypes,including caregiver,sage,hero,innocent,dominator,creator,vitality,explorer,stylish woman,lover,cooperator,and vogue gentleman,have a high degree explanation.Deeper study uses case study to verify the reasonability and effectiveness of the classification standard.展开更多
In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicas...In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.展开更多
Interact traffic classification is vital to the areas of network operation and management. Traditional classification methods such as port mapping and payload analysis are becoming increasingly difficult as newly emer...Interact traffic classification is vital to the areas of network operation and management. Traditional classification methods such as port mapping and payload analysis are becoming increasingly difficult as newly emerged applications （e. g. Peer-to-Peer） using dynamic port numbers, masquerading techniques and encryption to avoid detection. This paper presents a machine learning （ML） based traffic classifica- tion scheme, which offers solutions to a variety of network activities and provides a platform of performance evaluation for the classifiers. The impact of dataset size, feature selection, number of application types and ML algorithm selection on classification performance is analyzed and demonstrated by the following experiments： （1） The genetic algorithm based feature selection can dramatically reduce the cost without diminishing classification accuracy. （2） The chosen ML algorithms can achieve high classification accuracy. Particularly, REPTree and C4.5 outperform the other ML algorithms when computational complexity and accuracy are both taken into account. （3） Larger dataset and fewer application types would result in better classification accuracy. Finally, early detection with only several initial packets is proposed for real-time network activity and it is proved to be feasible according to the preliminary results.展开更多
文摘Amblyopia is a common eye d isease caught by many children. For some reason, the traditional treating method is unsatisfactory and ineffective. By connecting home and hospital through Inte rnet, patients can receive service of treatment designed for their own purpose. Thus the effectiveness of therapy is expected to have sigificent improvment. A n ew Internet based telemedicine system for amblyopia is put forward in this pape r with further discussions of its principles, framework and implementation method s.
基金Project(2007CB311106) supported by National Key Basic Research Program of ChinaProject(NEUL20090101) supported by the Foundation of National Information Control Laboratory of China
文摘Internet traffic classification plays an important role in network management, and many approaches have been proposed to classify different kinds of internet traffics. A novel approach was proposed to classify network applications by optimized back-propagation (BP) neural network. Particle swarm optimization (PSO) algorithm was used to optimize the BP neural network. And in order to increase the identification performance, wavelet packet decomposition (WPD) was used to extract several hidden features from the time-frequency information of network traffic. The experimental results show that the average classification accuracy of various network applications can reach 97%. Moreover, this approach optimized by BP neural network takes 50% of the training time compared with the traditional neural network.
基金supported by the National Natural Science Foundation of China under Grants No.71201011,No.71301106,No.71103021the Ministry of Education in China under Grants No.13YJA630084,No.13YJC630034,No.20120005120001
文摘With the increasing popularity of the Internet and mobile Internet, the Virtual Community （VC） is becoming an important medium for person-to-person communication. To realise the potential of the VC, it is neces- sary to cultivate within it good group cohesion and vitality. Using empirical and experimental research methods, this study explores the ef- fect of users＇ trust in the VC Platform （VCP） on group cohesion and vitality and how brand and perceived privacy security can affect us- ers＇ trust in the VC. The research results indi- cate that the brand of the VCP can directly af- fect users＇ trust in the VC, and can also influe- nce it indirectly through users＇ perceived pri- vacy protection and perceived security protec- tion. Further, this study also confu＇ms that the performance of the VC （group cohesion and vitality） is significantly affected by users＇ trust in the VC. The results of this study can provide theoretical guidance for internet companies to maintain and enhance the value of VCs.
文摘Exposing EFL （English as a Foreign Language） students to different varieties of English can be beneficial in numerous ways, but teachers may be unaware of how they can do this. This paper briefly explains the concept of World Englishes, then describes one teacher＇s attempt to use the Internet to provide his students with examples of real English from around the world. Finally, it offers a selection of positive student responses to the experience.
基金supported by Project 71202155 of National Science Funds for Distinguished Young Scientists of China
文摘Due to the rapid development,Internet has become the main field for brand building.Under this circumstance,the image of the brand is always consistent with the consumers' perception.Therefore,this study uses the method of text mining of search engine to explore the categories of brand archetype based on Brand Personality Theory from the perspective of Internet.The results find that 12 brand archetypes,including caregiver,sage,hero,innocent,dominator,creator,vitality,explorer,stylish woman,lover,cooperator,and vogue gentleman,have a high degree explanation.Deeper study uses case study to verify the reasonability and effectiveness of the classification standard.
文摘In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.
基金Supported by the National High Technology Research and Development Programme of China (No. 2005AA121620, 2006AA01Z232)the Zhejiang Provincial Natural Science Foundation of China (No. Y1080935 )the Research Innovation Program for Graduate Students in Jiangsu Province (No. CX07B_ 110zF)
文摘Interact traffic classification is vital to the areas of network operation and management. Traditional classification methods such as port mapping and payload analysis are becoming increasingly difficult as newly emerged applications （e. g. Peer-to-Peer） using dynamic port numbers, masquerading techniques and encryption to avoid detection. This paper presents a machine learning （ML） based traffic classifica- tion scheme, which offers solutions to a variety of network activities and provides a platform of performance evaluation for the classifiers. The impact of dataset size, feature selection, number of application types and ML algorithm selection on classification performance is analyzed and demonstrated by the following experiments： （1） The genetic algorithm based feature selection can dramatically reduce the cost without diminishing classification accuracy. （2） The chosen ML algorithms can achieve high classification accuracy. Particularly, REPTree and C4.5 outperform the other ML algorithms when computational complexity and accuracy are both taken into account. （3） Larger dataset and fewer application types would result in better classification accuracy. Finally, early detection with only several initial packets is proposed for real-time network activity and it is proved to be feasible according to the preliminary results.
