Pretrain, prompt, and transfer: Evolving digital twins for time-to-event analysis in cyber-physical systems
Cyber-physical systems (CPSs), eg, elevators and autonomous driving systems, are
progressively permeating our everyday lives. To ensure their safety, various analyses need …
progressively permeating our everyday lives. To ensure their safety, various analyses need …
Evolve the model universe of a system universe
Uncertain, unpredictable, real-time, and lifelong evolution causes operational failures in
intelligent software systems, leading to significant damages, safety and security hazards …
intelligent software systems, leading to significant damages, safety and security hazards …
MarMot: Metamorphic Runtime Monitoring of Autonomous Driving Systems
Autonomous Driving Systems (ADSs) are complex Cyber-Physical Systems (CPSs) that
must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural …
must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural …
Metamorphic runtime monitoring of autonomous driving systems
Autonomous Driving Systems (ADSs) are complex Cyber-Physical Systems (CPSs) that
must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural …
must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural …
Advancing data-driven sustainable design: A novel NEV form design approach in China's market
Z Wang, S Niu, C Fu, S Hu, L Huang - Journal of Cleaner Production, 2024 - Elsevier
As the concept of sustainable development spreads globally, New Energy Vehicles (NEVs)
have increasingly become a focal point in social and environmental agendas. In the form …
have increasingly become a focal point in social and environmental agendas. In the form …
Generating and detecting true ambiguity: a forgotten danger in DNN supervision testing
Abstract Deep Neural Networks (DNNs) are becoming a crucial component of modern
software systems, but they are prone to fail under conditions that are different from the ones …
software systems, but they are prone to fail under conditions that are different from the ones …
Baywatch: Leveraging bayesian neural networks for hardware fault tolerance and monitoring
J Hoefer, M Stammler, F Kreß, T Hotfilter… - … on Defect and Fault …, 2024 - ieeexplore.ieee.org
As Deep Neural Networks are increasingly being utilized in safety-critical domains,
assessing the uncertainty of the models during inference will be a crucial component in …
assessing the uncertainty of the models during inference will be a crucial component in …
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks
Recent decades have seen the rise of large-scale Deep Neural Networks (DNNs) to achieve
human-competitive performance in a variety of AI tasks. Often consisting of hundreds of …
human-competitive performance in a variety of AI tasks. Often consisting of hundreds of …
Applications of Certainty Scoring for Machine Learning Classification in Multi-modal Contexts
Quantitative characterizations and estimations of uncertainty are of fundamental importance
for machine learning classification, particularly in safety-critical settings such as the military …
for machine learning classification, particularly in safety-critical settings such as the military …