Context: Cyber–physical systems present a challenge to testers, bringing complexity and
scale to safety-critical and collaborative environments. Digital twins enhance these systems …

Abstract Neural Operator Networks (ONets) represent a novel advancement in machine
learning algorithms, offering a robust and generalizable alternative for approximating partial …

Artificial intelligence (AI) and Machine learning (ML) are increasingly used for digital twin
development in energy and engineering systems, but these models must be fair, unbiased …

Smart cities, leveraging advanced data analytics, predictive models, and digital twin
techniques, offer a transformative model for sustainable urban development. Predictive …

Industry 4.0 targets the conversion of the traditional industries into intelligent ones through
technological revolution. This revolution is only possible through innovation, optimization …

Abstract The term Internet of Things (IoT) refers to a network that connects smart things with
sensors. Healthcare, transportation, and smart cities are some IoT applications. IoT …

In recent years, there has been growing interest in digital twin technology in both industry
and academia. This versatile technology has found applications across various industries …

The use of measured vibration data from structures has a long history of enabling the
development of methods for inference and monitoring. In particular, applications based on …

In this paper, we propose an abstract domain-neutral architecture for a cognitive digital twin
(CDT) and a software platform to develop such CDTs, including machine reasoning …

Digital twin (DT) technology, where digital representations are created for physical objects,
offers transformative capabilities in safety risk management, particularly in the risk …