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It is common for biological networks to encounter situations where agents need to decide between multiple options, such as deciding between moving towards one food source or another or between moving towards a new hive or another. In previous works, we dev ...
The evaluation of avalanche release depth distributions represents a major challenge for hazard management. This paper presents a rigorous formalism in which these distributions are expressed through a coupling of mechanical and meteorological factors. Con ...
In this paper, we show how an underlying system’s state vector distribution can be determined in a distributed heterogeneous sensor network with reduced subspace observability at the individual nodes. The presented algorithm can generate the initial state ...
This thesis focuses on the decisional process of autonomous systems, and more particularly, on the way to take a decision when the time at disposal in order to assess the whole situation is shorter than necessary. Indeed, numerous systems propose solutions ...
daptive networks (AN) have been recently proposed to address distributed estimation problems [1]–[4]. Here we extend prior work to changing topologies and data-normalized algorithms. The resulting framework may also treat signals with general distributions ...
Many details about the flow of water in soils in a hillslope are unknowable given current technologies. One way of learning about the bulk effects of water velocity distributions on hillslopes is through the use of tracers. However, this paper will demonst ...
Nanoparticles are finding many research and industrial applications, yet their characterization remains a challenge. Their cores are often polydisperse and coated by a stabilizing shell that varies in size and composition. No single technique can character ...
In this paper, we investigate the construction of compromise estimators of location and scale, by averaging over several models selected among a specified large set of possible models. The weight given to each distribution is based on the profile likelihoo ...
We present Scanning Mobility CCN Analysis (SMCA) as a novel method for obtaining rapid measurements of size-resolved cloud condensation nuclei (CCN) distributions and activation kinetics. SMCA involves sampling the monodisperse outlet stream of a Different ...
The idea of stochastic sediment transport models emerged in the 1930s, notably with the doctoral work of Hans A. Einstein (1936). Einstein's seminal work gave impulse to several stochastic models, which usually led to thin-tailed or bounded distributions f ...
