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207 results on '"Xia, YunNi"'

201. Concept Drift Adaptive Physical Event Detection for Social Media Streams

Author

Suprem, Abhijit, Musaev, Aibek, Pu, Calton, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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202. Investigating Personally Identifiable Information Posted on Twitter Before and After Disasters

Author

Sheinidashtegol, Pezhman, Musaev, Aibek, Atkison, Travis, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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203. Maintaining Fog Trust Through Continuous Assessment

Author

Khattak, Hasan Ali, Imran, Muhammad, Abbas, Assad, Khan, Samee U., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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204. SMT-Based Modeling and Verification of Cloud Applications

Author

Zhang, Xiyue, Sun, Meng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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205. Study on the Coordination Degree Between FDI and Modern Service Industry Development in Shenzhen

Author

Zhu, Xiangbo, Ou, Guoliang, Wu, Gang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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206. Correction to: Study on the Coordination Degree Between FDI and Modern Service Industry Development in Shenzhen

Author

Zhu, Xiangbo, Ou, Guoliang, Wu, Gang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Xia, Yunni, editor, and Zhang, Liang-Jie, editor

Published
2019
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207. Reliability prediction of ontology-based service compositions using Petri net and time series models.

Author

Li J, Xia Y, and Luo X

Subjects
Computing Methodologies
Abstract

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy.

Published
2014
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