Titlebook: Cyber Physical Systems. Model-Based Design; 9th International Wo Roger Chamberlain,Martin Edin Grimheden,Walid Taha Conference proceedings

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https://doi.org/10.1007/978-1-4757-3839-1g reasoning. In this paper, we propose an investigation on how to systematically derive and formally prove such timing models. Our approach is exemplified on a simple, accumulator-based processor called Lipsi.

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https://doi.org/10.1007/978-94-015-3375-1ntinuously accessible test pool with full feature support of the used microcontroller platform. The paper presents the architecture and the detailed implementation of the pool, and we provide an evaluation of its success based on usage statistics and student feedback.

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A Modular SystemC RTOS Model for Uncertainty Analysisutational platform. Hence these systems have to satisfy real-time constraints and support real-time communication. The design and verification of these systems is very complex, full formal verification is not always possible and the run-time verification is the only feasible path to follow. In this

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Multicore Models of Communication for Cyber-Physical Systemssuch as artificial intelligence and machine learning, call for ever-increasing processing power. However, for real-time systems, we need to prove statically that this processing demand can be performed within strict deadlines..This paper explores a time-predictable multicore architecture for those d

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Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Handes capable of grabbing varying objects and execute them timely as intended by the user. Current approaches often rely on physiological signal inputs such as Electromyography (EMG) signal from residual limb muscles to infer the intended motion. However, limited signal quality, user diversity and high

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