A global semantics matching and QoS-awareness service selection are proposed when aimed at a web services composition process.Both QoS-aware matching and global semantic matching are considered during the global match...A global semantics matching and QoS-awareness service selection are proposed when aimed at a web services composition process.Both QoS-aware matching and global semantic matching are considered during the global matching.When there are demands for global semantic matching and QoS of service composition,a concrete service set which meets the demands is selected for the whole service composition process and an optimal solution is also achieved.A QoS model is built and the corresponding evaluation method is given for the matching of the service composition process.Based on them,a genetic algorithm is proposed to achieve the maximal global semantic matching degree and fulfill the QoS requirements for the whole service composition process.Experimental results and analysis show that the algorithm is feasible and effective for semantics and QoS-aware service matching.展开更多
The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only...The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only with robot's vision.By imitating spatial cognizing mechanism of human,the robot constantly received the information of artificial labels at cognitive-guide points in a wide range of structured environment to achieve the perception of the environment and robot navigation.The immune network algorithm was used to form the environmental awareness mechanism with "distributed representation".The color recognition and SIFT feature matching algorithm were fused to achieve the memory and cognition of scenario tag.Then the cognition-guide-action based cognizing semantic map was built.Along with the continuously abundant map,the robot did no longer need to rely on the artificial label,and it could plan path and navigate freely.Experimental results show that the artificial label designed in this work can improve the cognitive ability of the robot,navigate the robot in the case of semi-unknown environment,and build the cognizing semantic map favorably.展开更多
基金Specialized Research Fund for the Doctoral Program of Higher Education(No.20050288015)Innovation Funds of Nanjing University of Science and Technology
文摘A global semantics matching and QoS-awareness service selection are proposed when aimed at a web services composition process.Both QoS-aware matching and global semantic matching are considered during the global matching.When there are demands for global semantic matching and QoS of service composition,a concrete service set which meets the demands is selected for the whole service composition process and an optimal solution is also achieved.A QoS model is built and the corresponding evaluation method is given for the matching of the service composition process.Based on them,a genetic algorithm is proposed to achieve the maximal global semantic matching degree and fulfill the QoS requirements for the whole service composition process.Experimental results and analysis show that the algorithm is feasible and effective for semantics and QoS-aware service matching.
基金Projects(61203330,61104009,61075092)supported by the National Natural Science Foundation of ChinaProject(2013M540546)supported by China Postdoctoral Science Foundation+2 种基金Projects(ZR2012FM031,ZR2011FM011,ZR2010FM007)supported by Shandong Provincal Nature Science Foundation,ChinaProjects(2011JC017,2012TS078)supported by Independent Innovation Foundation of Shandong University,ChinaProject(201203058)supported by Shandong Provincal Postdoctoral Innovation Foundation,China
文摘The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only with robot's vision.By imitating spatial cognizing mechanism of human,the robot constantly received the information of artificial labels at cognitive-guide points in a wide range of structured environment to achieve the perception of the environment and robot navigation.The immune network algorithm was used to form the environmental awareness mechanism with "distributed representation".The color recognition and SIFT feature matching algorithm were fused to achieve the memory and cognition of scenario tag.Then the cognition-guide-action based cognizing semantic map was built.Along with the continuously abundant map,the robot did no longer need to rely on the artificial label,and it could plan path and navigate freely.Experimental results show that the artificial label designed in this work can improve the cognitive ability of the robot,navigate the robot in the case of semi-unknown environment,and build the cognizing semantic map favorably.
