Learning enabled components (LECs), while critical for decision making i...
Cyber-physical systems (CPS) like autonomous vehicles, that utilize lear...
In a cyber-physical system such as an autonomous vehicle (AV), machine
l...
Out-of-distribution (OOD) detection, i.e., finding test samples derived ...
Duckiebots are low-cost mobile robots that are widely used in the fields...
When machine learning (ML) models are supplied with data outside their
t...
In an edge-cloud system, mobile devices can offload their computation
in...
Deep Neural Networks are actively being used in the design of autonomous...
Uncertainties in machine learning are a significant roadblock for its
ap...
Highly complex deep learning models are increasingly integrated into mod...
Machine learning (ML) is actively finding its way into modern cyber-phys...
This paper considers the problem of decentralized monitoring of a class ...
The recent advancement of information and communication technology makes...
In the fields of co-simulation and component-based modelling, designers
...
In this paper we present a novel model checking approach to finite-time
...
The Internet of Things (IoT) will be a main data generation infrastructu...
Artificial Intelligence (AI) and Internet of Things (IoT) applications a...
Maintaining peer-to-peer connectivity with low energy overhead is a key
...
With rapid advancements in the Internet of Things (IoT) paradigm, electr...
Recent technological advances have fostered the development of complex
i...
With the growing scale of Cyber-Physical Systems (CPSs), it is challengi...
This demonstration presents a framework for building a resilient
Cyber-P...
Industrial cyber-infrastructure is normally a multilayered architecture....
As the industrial cyber-infrastructure become increasingly important to
...
Orchestrated collaborative effort of physical and cyber components to sa...
Scheduling of constrained deadline sporadic task systems on multiprocess...
Mixed-criticality real-time scheduling has been developed to improve res...
In this paper we consider the problem of mixed-criticality (MC) scheduli...
Systems in many safety-critical application domains are subject to
certi...
Mixed-Criticality (MC) systems consolidate multiple functionalities with...
Strategies that artificially tighten high-criticality task deadlines in
...
Many existing studies on mixed-criticality (MC) scheduling assume that
l...
Different scheduling algorithms for mixed criticality systems have been
...
Digital twin is a virtual replica of a real-world object that lives
simu...
Industrial process control systems are time-critical systems where relia...
Machine learning (ML) techniques are increasingly applied to decision-ma...
We consider the flow network model to solve the multiprocessor real-time...
Recent studies exploited external periodic synchronous signals to synchr...