Comment on “Recent advances on solving the three-parameter infiltration equation” by Prabhata K. Swamee, Pushpa N. Rathie, Luan Carlos de S.M. Ozelim and André L.B. Cavalcante, Journal of Hydrology 509 (2014) 188-192
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This paper presents a remote sensing technique for calibrating hydrodynamics models, which is particularly useful when access to the riverbed for a direct measure of flow variables may be precluded. The proposed technique uses terrestrial photography and a ...
Optimization is important in science and engineering as a way of finding ”optimal” situations, designs or operating conditions. Optimization is typically performed on the basis of a mathematical model of the process under investigation. In practice, optimi ...
In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...
Approximation algorithms are a commonly used tool for designing efficient algorithmic solutions for intractable problems, at the expense of the quality of the output solution. A prominent technique for designing such algorithms is the use of Linear Program ...
The polynomial Hirsch conjecture states that the vertex-edge diameter of a d-dimensional polyhedron with n facets is bounded by a polynomial in d and n. For the special case where the polyhedron is defined as the set of points satisfying a system Ax ≤ b of ...
We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds ...
Institute of Electrical and Electronics Engineers2011
The effect of inflow waveform on the hemodynamics of a real-size idealized sidewall intracranial aneurysm (IA) model was investigated using particle imaging velocimetry (PIV). For this purpose, we implemented an error analysis based on several PIV measurem ...
In this work, we consider multitask learning problems where clusters of nodes are interested in estimating their own parameter vector. Cooperation among clusters is beneficial when the optimal models of adjacent clusters have a good number of similar entri ...
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolera ...
We propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models that are described in terms of differential equations either driven by random measures or with random coefficients. The CMLMC algorithm so ...
