Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

With the adoption of autonomous systems in higher levels of autonomy, large-scale,
complex and dynamic systems are becoming commonplace. Ensuring safe operation of …

Risk assessment must evolve for addressing the existing and future challenges, and
considering the new systems and innovations that have already arrived in our lives and that …

Probabilistic risk assessment (PRA) is a systematic process of examining how engineered
systems work to ensure safety. With the growth of the size of dynamic systems and the …

Modern Medical Information Systems very often comprise Medical Devices and governed by
regulations which require stringent Risk Management activities to be implemented to …

Current electricity pricing models take into account costs of generation, transmission,
emissions and a fixed cost of distribution based on time of day and type of primary source …

Dynamic probabilistic risk assessment (PRA) more explicitly treats timing issues and
stochastic elements of risk models. It extensively resorts to iterative simulations of accident …

While traditional probabilistic risk assessment (PRA) using event tree and fault tree is mainly
concerned with static uncertainties, dynamic PRA techniques address the timeline response …

There have been many advancements and developments in hazard and risk analysis
techniques over the past several decades. Since then, many researchers integrated various …

For a long time, research into integrated deterministic-probabilistic safety assessment has
been continuously conducted to point out and overcome the limitations of classical ET (event …