How can airports prepare for future public health disruptions? Experiences and lessons learned during the COVID-19 pandemic from a systemic perspective based on expert interviews

A copula-based model to describe the uncertainty of overtopping variables on mound breakwaters

Contingency Games for Multi-Agent Interaction

High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems

Distributed Adaptive Synchronization in Euler Lagrange Networks with Uncertain Interconnections

Uncertainty of thermosphere mass density observations derived from accelerometer and GNSS tracking data

Adaptive Prescribed Performance Asymptotic Tracking for High-Order Odd-Rational-Power Nonlinear Systems

Abstracting the Traffic of Nonlinear Event-Triggered Control Systems

Discrete-Time Fractional-Order Dynamical Networks Minimum-Energy State Estimation

Robustness Analysis of Platoon Control for Mixed Types of Vehicles

Promises of Deep Kernel Learning for Control Synthesis

Formal Abstraction of General Stochastic Systems via Noise Partitioning

Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods

From speculation to reality: Enhancing anticipatory ethics for emerging technologies (ATE) in practice

Synchromodal freight transport re-planning under service time uncertainty: An online model-assisted reinforcement learning

On the quantitative resilience assessment of complex engineered systems

Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback

Decision making under deep uncertainty for pandemic policy planning

Capturing the uncertainty about a sudden change in the properties of time series with confidence curves

Modeling Pedestrian Tactical and Operational Decisions Under Risk and Uncertainty: A Two-Layer Model Framework