Networked noncooperative games are investigated,where each player(or agent) plays with all other players in its neighborhood. Assume the evolution is based on the fact that each player uses its neighbors current infor...Networked noncooperative games are investigated,where each player(or agent) plays with all other players in its neighborhood. Assume the evolution is based on the fact that each player uses its neighbors current information to decide its next strategy. By using sub-neighborhood, the dynamics of the evolution is obtained. Then a method for calculating Nash equilibriums from mixed strategies of multi-players is proposed.The relationship between local Nash equilibriums based on individual neighborhoods and global Nash equilibriums of overall network is revealed. Then a technique is proposed to construct Nash equilibriums of an evolutionary game from its one step static Nash equilibriums. The basic tool of this approach is the semi-tensor product of matrices, which converts strategies into logical matrices and payoffs into pseudo-Boolean functions, then networked evolutionary games become discrete time dynamic systems.展开更多
The mainstream approaches to green networking are discussed first from the view of engineering,including resource consolidation,server virtualization,selective connectedness,and proportional computing.A brief introduc...The mainstream approaches to green networking are discussed first from the view of engineering,including resource consolidation,server virtualization,selective connectedness,and proportional computing.A brief introduction to network virtualization techniques is given then and a virtual node embedding approach is provided.Finally,three kinds of enhanced green networking schemes by network virtualization are proposed,that is enhancement to sever virtualization,resource consolidation and Adaptive Link Rate(ALR).Examples are included to show the virtue of network virtualization to green networking in terms of energy efficient communications.展开更多
The privacy protection of resource description framework （schema） （RDF（S） ） repository is an emerging topic in database security area. In this paper, entailment rules are investigated based on RDF（S） repositor...The privacy protection of resource description framework （schema） （RDF（S） ） repository is an emerging topic in database security area. In this paper, entailment rules are investigated based on RDF（S） repository firstly. Then, an idea that uses reasoning closure to judge whether the privacy disclosure caused by inference is existed is proposed. Furthermore, the definitions of impli- cation conditions and information measure of triple statements which gains data hiding algorithm with combining proposition logic reasoning theory are introduced. Meanwhile, a conversion method from conjunctive normal form to disjunctive normal form based minimal hitting sets of set cluster is aiso proposed. Finally, the experimental results show that our algorithm can prevent privacy disclosure of RDF（S） repository effectively.展开更多
The prevalence of long-tailed distributions in real-world data often results in classification models favoring the dominant classes,neglecting the less frequent ones.Current approaches address the issues in long-taile...The prevalence of long-tailed distributions in real-world data often results in classification models favoring the dominant classes,neglecting the less frequent ones.Current approaches address the issues in long-tailed image classification by rebalancing data,optimizing weights,and augmenting information.However,these methods often struggle to balance the performance between dominant and minority classes because of inadequate representation learning of the latter.To address these problems,we introduce descriptional words into images as cross-modal privileged information and propose a cross-modal enhanced method for long-tailed image classification,referred to as CMLTNet.CMLTNet improves the learning of intraclass similarity of tail-class representations by cross-modal alignment and captures the difference between the head and tail classes in semantic space by cross-modal inference.After fusing the above information,CMLTNet achieved an overall performance that was better than those of benchmark long-tailed and cross-modal learning methods on the long-tailed cross-modal datasets,NUS-WIDE and VireoFood-172.The effectiveness of the proposed modules was further studied through ablation experiments.In a case study of feature distribution,the proposed model was better in learning representations of tail classes,and in the experiments on model attention,CMLTNet has the potential to help learn some rare concepts in the tail class through mapping to the semantic space.展开更多
文摘Networked noncooperative games are investigated,where each player(or agent) plays with all other players in its neighborhood. Assume the evolution is based on the fact that each player uses its neighbors current information to decide its next strategy. By using sub-neighborhood, the dynamics of the evolution is obtained. Then a method for calculating Nash equilibriums from mixed strategies of multi-players is proposed.The relationship between local Nash equilibriums based on individual neighborhoods and global Nash equilibriums of overall network is revealed. Then a technique is proposed to construct Nash equilibriums of an evolutionary game from its one step static Nash equilibriums. The basic tool of this approach is the semi-tensor product of matrices, which converts strategies into logical matrices and payoffs into pseudo-Boolean functions, then networked evolutionary games become discrete time dynamic systems.
基金the National Natural Science Foundation of China，the PAPD Project of Jiangsu Higher Education Institutions，the National S&T Dedicated Mega-Project，the Qing Lan Project of Jiangsu Province of China，the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications),Ministry of Education
文摘The mainstream approaches to green networking are discussed first from the view of engineering,including resource consolidation,server virtualization,selective connectedness,and proportional computing.A brief introduction to network virtualization techniques is given then and a virtual node embedding approach is provided.Finally,three kinds of enhanced green networking schemes by network virtualization are proposed,that is enhancement to sever virtualization,resource consolidation and Adaptive Link Rate(ALR).Examples are included to show the virtue of network virtualization to green networking in terms of energy efficient communications.
基金Supported by the National Natural Science Foundation of China(61272511)
文摘The privacy protection of resource description framework （schema） （RDF（S） ） repository is an emerging topic in database security area. In this paper, entailment rules are investigated based on RDF（S） repository firstly. Then, an idea that uses reasoning closure to judge whether the privacy disclosure caused by inference is existed is proposed. Furthermore, the definitions of impli- cation conditions and information measure of triple statements which gains data hiding algorithm with combining proposition logic reasoning theory are introduced. Meanwhile, a conversion method from conjunctive normal form to disjunctive normal form based minimal hitting sets of set cluster is aiso proposed. Finally, the experimental results show that our algorithm can prevent privacy disclosure of RDF（S） repository effectively.
基金supported in part by the National Natural Science Foundation of China(62006141)the National Key R&D Program of China(2021YFC3300203)+1 种基金the Overseas Innovation Team Project of the“20 Regulations for New Universities”Funding Program of Jinan(2021GXRC073)the Excellent Youth Scholars Program of Shandong Province(2022HWYQ-048).
文摘The prevalence of long-tailed distributions in real-world data often results in classification models favoring the dominant classes,neglecting the less frequent ones.Current approaches address the issues in long-tailed image classification by rebalancing data,optimizing weights,and augmenting information.However,these methods often struggle to balance the performance between dominant and minority classes because of inadequate representation learning of the latter.To address these problems,we introduce descriptional words into images as cross-modal privileged information and propose a cross-modal enhanced method for long-tailed image classification,referred to as CMLTNet.CMLTNet improves the learning of intraclass similarity of tail-class representations by cross-modal alignment and captures the difference between the head and tail classes in semantic space by cross-modal inference.After fusing the above information,CMLTNet achieved an overall performance that was better than those of benchmark long-tailed and cross-modal learning methods on the long-tailed cross-modal datasets,NUS-WIDE and VireoFood-172.The effectiveness of the proposed modules was further studied through ablation experiments.In a case study of feature distribution,the proposed model was better in learning representations of tail classes,and in the experiments on model attention,CMLTNet has the potential to help learn some rare concepts in the tail class through mapping to the semantic space.
