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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 ...
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 ...
In this paper, we present a pull-based dissemination protocol for efficient distribution of scalable video content in overlay peer-to-peer networks with mesh structures. The proposed protocol employs prioritized network coding, where the network coded pack ...
This work concerns the identification of the structure of a genetic network model from measurements of gene product concentrations and synthesis rates. In earlier work, for a wide family of network models, we developed a data preprocessing algorithm that i ...
We analyze the class of networks characterized by modular structure where a sequence of l Erdos-Renyi random networks of size N >> 1 with random average degrees is joined by links whose structure must remain immaterial. We find that traceroutes spanning th ...
We calculate learning rates when agents are informed through public and private observation of other agents' actions. We characterize the evolution of the distribution of posterior beliefs. If the private learning channel is present, convergence of the dis ...
Benford's law applies to a wide variety of natural and man-made datasets and it has been successfully applied to test the integrity of data and to detect possible fraud and anomalous results in economy, politics, and management studies. In this paper, we i ...
We consider a set of interacting phase oscillators, with a coupling between synchronized nodes adaptively reinforced, and the constraint of a limited resource for a node to establish connections with the other units of the network. We show that such a comp ...
Computational neuroscience is a branch of the neurosciences that attempts to elucidate the principles underlying the operation of neurons with the help of mathematical modeling. In contrast with a number of fields pursuing a tightly related goal, such as m ...
In this paper, we study the soundness amplification by repetition of cryptographic protocols. As a tool, we use the Chernoff Information. We specify the number of attempts or samples required to distinguish two distributions efficiently in various protocol ...