2,409 research outputs found
Nowhere people: making the invisible, visible
This context statement presents a critical examination of my work as a documentary photographer, focusing on the long-term project Nowhere People (2005-2016). It reveals as well the impact statelessness has on individuals and communities around the world. Given the interdisciplinary nature of this topic, the statement will employ methods of auto-ethnography as well as theories of state, human rights, memory and identity in order to illustrate the significance of the visual in articulating the lives of stateless populations.
This statement attempts to connect my own experience and journey of working in the field of documentary photography with the growing discussion and debate related to the state, human rights, nationality and the rights of non-citizens. I will demonstrate how this portfolio of public works presents a multidimensional portrait of this issue in a way that contributes to filling in substantial evidence gaps in the context of human rights by making the various elements of this invisible condition, visible. In addition, I will survey photography’s capacity to translate deficiencies inherent within human rights and international law and examine its role in challenging contemporary definitions of citizenship and identity.
I will discuss how I have navigated my work and the project Nowhere People through debates related to subjectivity, agency, representation, spectatorship and the interconnectedness between photographer, subject and viewer. I will also detail the pragmatic decisions I have made relating to the authorship and dissemination of the work to various audiences in relation to the tectonic shift in the access to information and use of the image within this shifting paradigm of visual culture
Residual Minimizing Model Interpolation for Parameterized Nonlinear Dynamical Systems
We present a method for approximating the solution of a parameterized,
nonlinear dynamical system using an affine combination of solutions computed at
other points in the input parameter space. The coefficients of the affine
combination are computed with a nonlinear least squares procedure that
minimizes the residual of the governing equations. The approximation properties
of this residual minimizing scheme are comparable to existing reduced basis and
POD-Galerkin model reduction methods, but its implementation requires only
independent evaluations of the nonlinear forcing function. It is particularly
appropriate when one wishes to approximate the states at a few points in time
without time marching from the initial conditions. We prove some interesting
characteristics of the scheme including an interpolatory property, and we
present heuristics for mitigating the effects of the ill-conditioning and
reducing the overall cost of the method. We apply the method to representative
numerical examples from kinetics - a three state system with one parameter
controlling the stiffness - and conductive heat transfer - a nonlinear
parabolic PDE with a random field model for the thermal conductivity.Comment: 28 pages, 8 figures, 2 table
Discovering an active subspace in a single-diode solar cell model
Predictions from science and engineering models depend on the values of the
model's input parameters. As the number of parameters increases, algorithmic
parameter studies like optimization or uncertainty quantification require many
more model evaluations. One way to combat this curse of dimensionality is to
seek an alternative parameterization with fewer variables that produces
comparable predictions. The active subspace is a low-dimensional linear
subspace defined by important directions in the model's input space; input
perturbations along these directions change the model's prediction more, on
average, than perturbations orthogonal to the important directions. We describe
a method for checking if a model admits an exploitable active subspace, and we
apply this method to a single-diode solar cell model with five input
parameters. We find that the maximum power of the solar cell has a dominant
one-dimensional active subspace, which enables us to perform thorough parameter
studies in one dimension instead of five
Factorizing the Stochastic Galerkin System
Recent work has explored solver strategies for the linear system of equations
arising from a spectral Galerkin approximation of the solution of PDEs with
parameterized (or stochastic) inputs. We consider the related problem of a
matrix equation whose matrix and right hand side depend on a set of parameters
(e.g. a PDE with stochastic inputs semidiscretized in space) and examine the
linear system arising from a similar Galerkin approximation of the solution. We
derive a useful factorization of this system of equations, which yields bounds
on the eigenvalues, clues to preconditioning, and a flexible implementation
method for a wide array of problems. We complement this analysis with (i) a
numerical study of preconditioners on a standard elliptic PDE test problem and
(ii) a fluids application using existing CFD codes; the MATLAB codes used in
the numerical studies are available online.Comment: 13 pages, 4 figures, 2 table
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