01534nas a2200205   4500008004100000245008200041210006900123260000900192300001400201490000700215520085300222653002301075653002201098653002401120653002201144100001201166700001501178700001801193856011701211       2013                        eng d00aResearch on an adaptive algorithm of service selection in pervasive computing0 aResearch on an adaptive algorithm of service selection in pervas  c2013  a482 - 4880 v113 aAn adaptive genetic algorithm of service selection in pervasive computing is presented in this paper. By means of matrix encoding, this algorithm carries out selection, crossover and mutation operations of genetic algorithm, with matrix as individual chromosome and matrix array as gene. Based on the elitism selection strategy and adaptive strategy, this algorithm replicates the optimal individual of every generation to the next generation, and adaptively adjusts crossover and mutation probabilities according to the fitness value of individual, which is aimed at protecting the individuals with high fitness and weeding out those with low fitness. Simulated comparison proves that this algorithm is of good convergence, which also shows more stable optimization ability, compared with ordinary genetic algorithm and random selection algorithm.10aAdaptive Algorithm10aElitism Selection10aPervasive computing10aService Selection1 aWei, L.1 aLanfei, Z.1 aJianqiang, D.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84892166746&partnerID=40&md5=ea96f5d6b9c178bdf71b3822a053afae01896nas a2200205   4500008004100000245008100041210006900122260000900191300001400200490000600214520116200220653003801382653002601420653002401446653005201470100001501522700002101537700001501558856011701573       2006                        eng d00aExpressing and interpreting user intention in pervasive service environments0 aExpressing and interpreting user intention in pervasive service   c2006  a102 - 1060 v43 aThe introduction of pervasive computing environments enforce new ways of human-machine-interaction. The welldefined interaction interfaces will make place for other, more intuitive ways of interaction. In a pervasive service environment, the system middleware should take care of capturing the users expression of an action intention, solving ambiguousness in this expression, and executing the final pervasive action This article introduces the Pervasive Service Action Query Language (PsaQL), a language to formalize the description of a user intention using composed pervasive services. It presents the next steps of intention treatment in a pervasive service environment: A mathematical model is given, which helps to express the algorithms performing translation of the user intention into an executable action. To implement such algorithms, a suitable object- oriented model representing actions is introduced. In the scope of PERSE, a pervasive service environment developed by our research group, general evaluation metrics for such algorithms are identified, a prototype has been developed and first benchmark results are presented in this article.10aAlgorithms in pervasive computing10aObject-oriented model10aPervasive computing10aPervasive Service Action Query Language (PsaQL)1 aBihler, P.1 aScuturici, V.-M.1 aBrunie, L.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-34547320698&partnerID=40&md5=47a322c63cbf87aec59acd1e5104f08d