We present the Toast++ open-source software environment for solving the forward and inverse problems in diffuse optical tomography (DOT). The software suite consists of a set of libraries to simulate near-infrared light propagation in highly scattering media with complex boundaries and heterogeneous internal parameter distribution, based on a finite-element solver. Steady-state, time- and frequ...

In this paper a forward solver software for the time domain and the CW domain based on the Born approximation for simulating the effect of small localized fluorophores embedded in a non-fluorescent biological tissue is proposed. The fluorescence emission is treated with a mathematical model that describes the migration of photons from the source to the fluorophore and of emitted fluorescent pho...

This paper presents a robust and accurate way to solve steady-state linear transport (radiative transfer) equations numerically. Our main objective is to address the inverse transport problem, in which the optical parameters of a domain of interest are reconstructed from measurements performed at the domain’s boundary. This inverse problem has important applications in medical and geophysical i...

In this paper, we describe the accuracy control and performance enhancement of linear solvers for the Integrated Water Flow Model (IWFM). This model is used by the State of California Department of Water Resources to assess the impact of climate change on water resources and the analysis of different conjunctive use scenarios across California. IWFM simulates groundwater, surface water and surf...

In response to the call for solvers by the CPAI’05 solver competition organizing committee, we implemented a constraint solver, called Mosar, using action rules (AR) in B-Prolog [3] particularly for this competition. The problem format used in the competition is very different from those used by practical solvers. For example, constraints are extensional numeric relations not implicit relations...

We present a multi-frontal hierarchically semi-separable solver to perform forward modeling of the 3D Helmholtz acoustic problem. Our frequency-domain solver combines two efficient approaches. First, it uses an optimal 27-point finite-difference scheme to decrease numerical dispersion and reduce required discretization of the model in terms of points per wavelength from 15 to about 4. Second, i...

in this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. in this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. to tackle the problem efficiently and effectively, an effici...

Hybrid dynamic systems combine continuous and discrete behavior. Often, computational approaches approximate behavior of an analytic solution, for example, numerical integration to approximate differential equation behavior. The accuracy and computational efficiency of the integration usually depend on the complexity of the method and its implicated approximation errors, especially when repeate...

Non-differentiable and constrained optimization play a key role in machine learning, signal and image processing, communications, and beyond. For highdimensional minimization problems involving large datasets or many unknowns, the forward-backward splitting method (also known as the proximal gradient method) provides a simple, yet practical solver. Despite its apparent simplicity, the performan...