Nowadays, huge amounts of data have been captured along with the day-to-day operation
of assets including railway systems. Hence, we have come to the era of big data. The …

We estimate and study the evolution of the dominant dimensionality of dynamical systems
with uncertainty governed by stochastic partial differential equations, within the context of …

In this paper, we quantify the dynamical causes and uncertainties of striking differences in
acoustic transmission data collected on the shelf and shelfbreak in the northeastern Taiwan …

Accurate and computationally efficient acoustic models are needed for varied marine
applications. In this paper, we focus our attention on forward models, which are essential to …

Robust informative acoustic predictions require precise knowledge of ocean physics,
bathymetry, seabed, and acoustic parameters. However, in realistic applications, this …

Onboard forecasting is challenging but essential for unmanned autonomous ocean
platforms. Due to the numerous operational constraints of these platforms, efficient adaptive …

This paper presents a comprehensive introduction and systematic derivation of the
evolutionary equations for absolute entropy H and relative entropy D, some of which exist …

The state of the ocean evolves and its dynamics involves transitions occurring at multiple
scales. For efficient and rapid interdisciplinary forecasting, ocean observing and prediction …

Parallel discrete event simulation (PDES) represents a class of codes that are challenging to
scale to large number of processors due to tight global timestamp-ordering and fine-grained …

To solve the problem of using information to control behavior for unmanned underwater
vehicle (UUV), this paper presents a situation awareness method on the basis of ontology …