In sports timing systems,P2P communication is used at low frequency bandwidths(under 135 KHz) between tags and readers in the RFID field.However,in such cases,collisions tend to occur when a reader deals with multiple...In sports timing systems,P2P communication is used at low frequency bandwidths(under 135 KHz) between tags and readers in the RFID field.However,in such cases,collisions tend to occur when a reader deals with multiple RFID tags simultaneously.To overcome this issue,a sports timing system including a Multi Reader Controller(MRC)loaded with an advanced multiple reader algorithm and application was created and applied at large-scale citizens' marathon events.In these cases,a large number of people pass over the installed urethane type's antenna mat continually during a short period of time.This study verified the superiority of the improved algorithm and application through the on-thespot application of the multi reader algorithm and application program,which allows us to smoothly measure runners' times through multiaccess reading for rapid collision avoidance.展开更多
People's attitudes towards public events or products may change overtime,rather than staying on the same state.Understanding how sentiments change overtime is an interesting and important problem with many applica...People's attitudes towards public events or products may change overtime,rather than staying on the same state.Understanding how sentiments change overtime is an interesting and important problem with many applications.Given a certain public event or product,a user's sentiments expressed in microblog stream can be regarded as a vector.In this paper,we define a novel problem of sentiment evolution analysis,and develop a simple yet effective method to detect sentiment evolution in user-level for public events.We firstly propose a multidimensional sentiment model with hierarchical structure to model user's complicate sentiments.Based on this model,we use FP-growth tree algorithm to mine frequent sentiment patterns and perform sentiment evolution analysis by Kullback-Leibler divergence.Moreover,we develop an improve Affinity Propagation algorithm to detect why people change their sentiments.Experimental evaluations on real data sets show that sentiment evolution could be implemented effectively using our method proposed in this article.展开更多
文摘In sports timing systems,P2P communication is used at low frequency bandwidths(under 135 KHz) between tags and readers in the RFID field.However,in such cases,collisions tend to occur when a reader deals with multiple RFID tags simultaneously.To overcome this issue,a sports timing system including a Multi Reader Controller(MRC)loaded with an advanced multiple reader algorithm and application was created and applied at large-scale citizens' marathon events.In these cases,a large number of people pass over the installed urethane type's antenna mat continually during a short period of time.This study verified the superiority of the improved algorithm and application through the on-thespot application of the multi reader algorithm and application program,which allows us to smoothly measure runners' times through multiaccess reading for rapid collision avoidance.
基金ACKNOWLEDGEMENTS The authors would like to thank the reviewers for their detailed reviews and constructive comments, which have helped improve the quality of this paper. The research was supported in part by National Basic Research Program of China （973 Program, No. 2013CB329601, No. 2013CB329604）, National Natural Science Foundation of China （No.91124002, 61372191, 61472433, 61202362, 11301302）, and China Postdoctoral Science Foundation （2013M542560）. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
文摘People's attitudes towards public events or products may change overtime,rather than staying on the same state.Understanding how sentiments change overtime is an interesting and important problem with many applications.Given a certain public event or product,a user's sentiments expressed in microblog stream can be regarded as a vector.In this paper,we define a novel problem of sentiment evolution analysis,and develop a simple yet effective method to detect sentiment evolution in user-level for public events.We firstly propose a multidimensional sentiment model with hierarchical structure to model user's complicate sentiments.Based on this model,we use FP-growth tree algorithm to mine frequent sentiment patterns and perform sentiment evolution analysis by Kullback-Leibler divergence.Moreover,we develop an improve Affinity Propagation algorithm to detect why people change their sentiments.Experimental evaluations on real data sets show that sentiment evolution could be implemented effectively using our method proposed in this article.
