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This article presents the Mobile Century field experiment, performed on February 8, 2008, to demonstrate the feasibility of a prototype location-based service: real-time traffic estimation using GPS data from cellular phones only. Mobile Century consisted of 100 vehicles carrying a GPS-equipped Nokia N95 cell phone driving loops on a 10-mile stretch of(More)
In this article, we investigate real-time estimation of flow state in open channels using the measurements obtained from Lagrangian sensors (drifters). One-dimensional Shallow Water Equations (SWE), also known as Saint-Venant equations, are used as the mathematical model for the flow. After linearizing and discretizing the PDEs using an explicit linear(More)
We present a state estimation method for twodimensional shallow water equations in rivers using Lagrangian drifter positions as measurements. The aim of this method is to compensate for the lack of knowledge of upstream and downstream boundary conditions in rivers that causes inaccuracy in the velocity field estimation by releasing drifters equipped with(More)
We present a method for assimilating Lagrangian sensor measurement data into a shallow water equation model. The underlying estimation problem (in which the dynamics of the system are represented by a system of partial differential equations) relies on the formulation of a minimisation of an error functional, which represents the mismatch between the(More)
INTRODUCTION To understand better the risk of tuberculosis transmission with increasing delay in tuberculosis treatment, we undertook a retrospective cohort study in Shenzhen, China. METHODS All pulmonary tuberculosis cases in the Shenzhen tuberculosis surveillance database from 1993-2010 were included. Sputum smear positivity and presence of pulmonary(More)
This article presents a method to estimate flow variables for an open channel network governed by the linearized Saint-Venant equations and subject to periodic forcing. The discharge at the upstream end of the system and the stage at the downstream end of the system are defined as the model inputs; the flow properties at selected internal locations, as well(More)
This article presents a method to estimate flow variables for an open channel network governed by first-order, linear hyperbolic partial differential equations and subjected to periodic forcing. The selected external boundary conditions of the system are defined as the model input; the flow properties at internal locations, as well as the other external(More)
An inverse modeling problem for systems of networked one dimensional shallow water equations subject to periodic forcing is investigated. The problem is described as a PDE-constrained optimization problem with the objective of minimizing the norm of the difference between the observed variables and model outputs. After linearizing and discretizing the(More)
A parameter identification problem for systems governed by first-order, linear hyperbolic partial differential equations subjected to periodic forcing is investigated. The problem is posed as a PDE constrained optimization problem with data of the problem given by the measured input and output variables at the boundary of the domain. By using the governing(More)
This article presents a data assimilation method in a tidal system, where data from both Lagrangian drifters and Eulerian flow sensors were fused to estimate water velocity. The system is modeled by first-order, hyperbolic partial differential equations subject to periodic forcing. The estimation problem can then be formulated as the minimization of the(More)