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A Resilient Control Strategy for Cyber-Physical Systems Subject to Denial of Service Attacks:A Leader-Follower Set-Theoretic Approach

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1204-1214页

作者： Giuseppe Franzè Domenico Famularo Walter Lucia Francesco Tedesco DIMES department Universitàdella CalabriaVia Pietro Bucci 87036Italy ciise department Concordia UniversityMontrealQuebec H3G-1M8Canada IEEE

Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency,reliability and *** technologically costeffective,this makes them vulnerable to cyber-attacks with potentially catastrophic *** this end,we present a novel control architecture capable to deal with the distributed constrained regulation problem in the presence of time-delay attacks on the agents’communication *** basic idea consists of orchestrating the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed to isolate the attacked unit before it compromises the system *** on a multi-area power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial ofservice(DoS)attacks.

关键词： Denial-of-service(DoS)attacks distributed model predictive control leader-follower paradigm resilient control

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Effective Frameworks Based on Infinite Mixture Model for Real-World Applications

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Computers, Materials & Continua 2022年第7期72卷 1139-1156页

作者： Norah Saleh Alghamdi Sami Bourouis Nizar Bouguila department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia College of Computers and Information Technology Taif UniversityTaif21944Saudi Arabia The Concordia Institute for Information Systems Engineering(ciise) Concordia UniversityMontrealQC H3G 1T7Canada

Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security *** particular,recognizing human activities with accurate results have become a topic of high *** the current tools have reached remarkable successes,it is still a challenging problem due to various uncontrolled environments and *** this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some realworld *** particular,two nonparametric hierarchical Bayesian models based on Dirichlet process and Pitman-Yor process are *** models are then applied to address the problem of modelling grouped data where observations are organized into groups and these groups are statistically linked by sharing mixture *** choice of the Gamma mixtures is motivated by its flexibility for modelling heavy-tailed *** addition,deploying the Dirichlet process prior is justified by its advantage of automatically finding the right number of components and providing nice ***,a learning step via variational Bayesian setting is presented in a flexible *** priors over the parameters are selected appropriately and the posteriors are approximated effectively in a closed *** results based on a real-life applications that concerns texture classification and human actions recognition show the capabilities and effectiveness of the proposed framework.

关键词： Infinite Gamma mixture model variational Bayes hierarchical Dirichlet process Pitman-Yor process texture classification human action recognition

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