Possible self-organizing dynamics for land-atmosphere interaction
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Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...
Measured meteorological time series are frequently used to obtain information 8 about climate dynamics. We use time series analysis and nonlinear system identification 9 methods in order to assess outdoor-environment bioclimatic conditions starting from th ...
Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...
Recent years have seen spectacular developments in the domain of nano-optics.
Alongside the well-known techniques of super-resolution microscopy progress
in nanofabrication has enabled important improvements in the fields
of optical imaging and spectros ...
In this work, we present an adaptive motion planning approach for impedance-controlled robots to modify their tasks based on human physical interactions. We use a class of parameterized time-independent dynamical systems for motion generation where the mod ...
Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...
When laminar shear flows in large wall-bounded domains transition to turbulence, the flow exhibits spatio-temporally chaotic dynamics. Despite its chaotic dynamics, the flow may self-organize into characteristic spatially periodic patterns of unknown origi ...
We study the dynamical process of congestion formation for large-scale urban networks by exploring a unique dataset of taxi movements in a megacity. We develop a dynamic model based on a reaction and a diffusion term that properly reproduces the cascade ph ...
This work is motivated by the identification of the land-atmosphere interactions as one of the key sources of uncertainty in climate change simulations. It documents new developments in related processes, namely, boundary layer/convection/clouds parameteri ...
In this work, we present an adaptive motion planning approach for impedance-controlled robots to modify their tasks based on human physical interactions. We use a class of parameterized time-independent dynamical systems for motion generation where the mod ...