We propose a modified Susceptible-Infected-Susceptible (SIS) model to analyze the influence of the distributed infection rate on the epidemic spreading behavior in complex networks. Unlike the traditional SIS model, t...
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In order to improve the mobile services under the banner of the Internet of Things, we propose and design a new kind of Web-based method of media seamless migration. The method can ensure the media seamless migration ...
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Computer-supported collab.rative learning (CSCL) is an emerging branch of learning science concerned with studying how people can learn together with the help of computers. As an indispensable ingredient, computer med...
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A kind of SND-based algorithm for self-adapting network congestion control has been presented in this paper, which is for the complicated and integrated network environment that the Internet of Things (IOT) to face in...
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This paper presents a method of phase-shift control in two-beam laser interference lithography. In the method, a PZT actuator is used to push a mirror and introduce phase shifts in a He-Ne laser interference lithograp...
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Memory-based collab.rative filtering algorithms have been widely adopted in many popular recommender systems, however the rating data are very sparse, which affects prediction accuracy greatly. To solve this probl...
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Memory-based collab.rative filtering algorithms have been widely adopted in many popular recommender systems, however the rating data are very sparse, which affects prediction accuracy greatly. To solve this problem, we use expert opinions to improve prediction accuracy. Firstly, we propose a novel similarity measure in order to highlight users' background. Then, combining users' ratings with expert opinions, the prediction get a right balance in both expert professional opinions and similar users. Finally, since SVD-based collab.rative filtering algorithms shows good performance on the prevention of noise, we use it to smooth the prediction. Experiments of MovieLens have shown that our proposed method improves recommendation quality obviously.
Network coding is able to address output conflicts when fanout splitting is allowed for multicast switching. Hence, it successfully achieves a larger rate region than non-coding approaches in crossbar switches. Howeve...
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Network coding is able to address output conflicts when fanout splitting is allowed for multicast ***,it successfully achieves a larger rate region than non-coding approaches in crossbar ***,network coding requires la...
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Network coding is able to address output conflicts when fanout splitting is allowed for multicast ***,it successfully achieves a larger rate region than non-coding approaches in crossbar ***,network coding requires large coding buffers and a high computational cost on encoding and *** this paper,we propose a novel Online Network Coding framework called Online NC for multicast switches,which is adaptive to constrained ***,it enjoys a much lower decoding complexity by a Vandermonde matrix based approach,as compared to conven-tional randomized network coding Our approach realizes online coding with one coding algo-rithm that synchronizes buffering and ***,we significantly reduce requirements on buffer space,while also sustaining high *** confirm the superior advantages of our contributions using empirical studies.
With the development of high-speed railway, its security problem gained more and more attention. Noise data collected by sensors reflected the operation condition and was close related to the security of train. The ef...
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With the development of high-speed railway, its security problem gained more and more attention. Noise data collected by sensors reflected the operation condition and was close related to the security of train. The efficiency of processing data became significant due to the volume of data growing at an unprecedented rate. It was a challenge to process massive noise data effectively. A method for preprocessing massive noise data based on MapReduce was proposed by use of the idea of parallel computing. The experiments on Hadoop platform prove that the proposed method can improve the efficiency of preprocessing massive noise data.
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