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1. Information dynamics in the network of cyber-physical systems

   Wang, Yan (May 2020, Proceedings of 13th International Symposium on Tools and Methods of Competitive Engineering (TMCE2020))

   null (Ed.)

   Cyber-physical systems (CPS) are physical devices with highly integrated functionalities of sensing, computing, communication, and control. The levels of intelligence and functions that CPS can perform heavily rely on their intense collaboration and information sharing through networks. In this paper, the information propagation within CPS networks is studied. Information dynamics models are proposed to characterize the evolution of information processing capabilities of CPS nodes in networks. The models are based on a mesoscale probabilistic graph model, where the sensing and computing functions of CPS nodes are captured as the probabilities of correct predictions, whereas the communication functions are represented as the probabilities of mutual influences between nodes. In the proposed copula dynamics model, the information dependency among individuals is represented with joint prediction probabilities and estimated from copulas of extremal probabilities. In the proposed functional interdependency model, the correlations between prediction capabilities are captured with their functional relationships. A data-driven approach is taken to train the parameters of the information dynamics models with data from simulations. The information dynamics models are demonstrated with a simulator of CPS networks. 

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2. Topology-informed information dynamics modeling in cyber–physical–social system networks

   https://doi.org/10.1017/S0890060421000159  

   Wang, Yan (July 2021, Artificial Intelligence for Engineering Design, Analysis and Manufacturing)

   null (Ed.)

   Cyber–physical–social systems (CPSS) are physical devices that are embedded in human society and possess highly integrated functionalities of sensing, computing, communication, and control. CPSS rely on their intense collaboration and information sharing through networks to be functioning. In this paper, topology-informed network information dynamics models are proposed to characterize the evolution of information processing capabilities of CPSS nodes in networks. The models are based on a mesoscale probabilistic graph model, where the sensing and computing capabilities of the nodes are captured as the probabilities of correct predictions. A topology-informed vector autoregression model and a latent variable vector autoregression model are proposed to model the correlations between prediction capabilities of nodes as linear functional relationships. A hybrid Gaussian process regression model is also developed to capture both the nonlinear spatial and temporal correlations between nodes. The new information dynamics models are demonstrated and tested with a simulator of CPSS networks. The results show that the topological information of networks can improve the efficiency in constructing the time series models. The network topology also has influences on the prediction capabilities of CPSS. 

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3. Design of Trustworthy Cyber-Physical-Social Systems With Discrete Bayesian Optimization

   https://doi.org/10.1115/DETC2020-22661  

   Wang, Yan (August 2020, Proceedings of ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE2020))

   null (Ed.)

   Cyber-physical-social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently a trust quantification method was proposed to measure trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. In this paper, the applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. A Bayesian optimization method is developed to perform trust based CPSS network design, where the most trustworthy network with respect to a reference node can be selected to collaborate and share information with. 

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4. Design of Trustworthy Cyber–Physical–Social Systems With Discrete Bayesian Optimization

   https://doi.org/10.1115/1.4049532  

   Wang, Yan (July 2021, Journal of Mechanical Design)

   null (Ed.)

   Abstract Cyber–physical–social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus, one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently, a trust quantification method was proposed to measure the trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. The CPSS network architecture can be optimized by choosing a subnet such that the trust metrics are maximized. The combinatorial network optimization problem, however, is computationally challenging. Most of the available global optimization algorithms for solving such problems are heuristic methods. In this paper, a surrogate-based discrete Bayesian optimization method is developed to perform network design, where the most trustworthy CPSS network with respect to a reference node is formed to collaborate and share information with. The applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. 

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5. A Reference Architecture of Human Cyber-Physical Systems – Part I: Fundamental Concepts

   https://doi.org/10.1145/3622879  

   Damm, Werner; Hess, David; Schweda, Mark; Sztipanovits, Janos; Bengler, Klaus; Biebl, Bianca; Fränzle, Martin; Hagemann, Willem; Held, Moritz; Ihme, Klas; et al (January 2024, ACM Transactions on Cyber-Physical Systems)

   We propose a reference architecture of safety-critical or industry-critical human cyber-physical systems (CPSs) capable of expressing essential classes of system-level interactions between CPS and humans relevant for the societal acceptance of such systems. To reach this quality gate, the expressivity of the model must go beyond classical viewpoints such as operational, functional, and architectural views and views used for safety and security analysis. The model does so by incorporating elements of such systems for mutual introspections in situational awareness, capabilities, and intentions to enable a synergetic, trusted relation in the interaction of humans and CPSs, which we see as a prerequisite for their societal acceptance. The reference architecture is represented as a metamodel incorporating conceptual and behavioral semantic aspects. We illustrate the key concepts of the metamodel with examples from cooperative autonomous driving, the operating room of the future, cockpit-tower interaction, and crisis management. 

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