3,572 research outputs found
Public Libraries: techno trends and collective memory
By public library I mean here a library providing some kind of universal access to its assets, one whose readership isn’t exclusively tied and restricted to a particular organization – including the generally called public libraries, but also many specialized libraries, such as the academic of the open kind. Despite all efforts, public libraries continue to face strong barriers to their participation in the information society. Participants of the World Meeting on the Future of the ISIS Software recognized that “the ISIS Software Family has a unique technological concept and developmental mission to cope with Information Storage and Retrieval Systems (ISRS), particularly for developing countries where the technology is widely known and used; that the ISIS Software Family has now fully embraced the Free and Open Source Software approach and the support of UNICODE structures to be fully open and multilingual” (Rio Declaration 2008), restating thus the persistent relevance of this software family.
OSS (Coar 2006) is defined as software whose source code is freely available, therefore allowing for free inspection and/or utilization, i.e., it is available for study and use by everyone without any payment or any other barrier to access. the lack of technical skill in libraries, a situation that libraries share with much of the public and cultural sectors. The study of OSS ILS, and of the their adaptation to the needs of specific public libraries may be the solution to this. Library Management Systems) that enhances digital archive interoperability between a diverse range of libraries
Nonlinear Stability of Riemann Ellipsoids with Symmetric Configurations
We apply geometric techniques to obtain the necessary and sufficient
conditions on the existence and nonlinear stability of self-gravitating Riemann
ellipsoids having at least two equal axes
Bose-Einstein condensates in deformed traps
Treballs Finals de Grau de FĂsica, Facultat de FĂsica, Universitat de Barcelona, Any: 2015, Tutor: Bruno Juliá-DĂazIn this degree thesis we study the properties of a Bose-Einstein condensate confined in both isotropic and anisotropic traps using a mean-field description in terms of the Gross-Pitaevskii equation and modified Gross-Pitaevskii equation. We also study the many particle limit and compare it with the Thomas-Fermi limits. Finally we study the aspect ratio of the system and see how it changes for the noninteracting limit and the strong repulsive limit
A Framework for Fast Image Deconvolution with Incomplete Observations
In image deconvolution problems, the diagonalization of the underlying
operators by means of the FFT usually yields very large speedups. When there
are incomplete observations (e.g., in the case of unknown boundaries), standard
deconvolution techniques normally involve non-diagonalizable operators,
resulting in rather slow methods, or, otherwise, use inexact convolution
models, resulting in the occurrence of artifacts in the enhanced images. In
this paper, we propose a new deconvolution framework for images with incomplete
observations that allows us to work with diagonalized convolution operators,
and therefore is very fast. We iteratively alternate the estimation of the
unknown pixels and of the deconvolved image, using, e.g., an FFT-based
deconvolution method. This framework is an efficient, high-quality alternative
to existing methods of dealing with the image boundaries, such as edge
tapering. It can be used with any fast deconvolution method. We give an example
in which a state-of-the-art method that assumes periodic boundary conditions is
extended, through the use of this framework, to unknown boundary conditions.
Furthermore, we propose a specific implementation of this framework, based on
the alternating direction method of multipliers (ADMM). We provide a proof of
convergence for the resulting algorithm, which can be seen as a "partial" ADMM,
in which not all variables are dualized. We report experimental comparisons
with other primal-dual methods, where the proposed one performed at the level
of the state of the art. Four different kinds of applications were tested in
the experiments: deconvolution, deconvolution with inpainting, superresolution,
and demosaicing, all with unknown boundaries.Comment: IEEE Trans. Image Process., to be published. 15 pages, 11 figures.
MATLAB code available at
https://github.com/alfaiate/DeconvolutionIncompleteOb
A convex formulation for hyperspectral image superresolution via subspace-based regularization
Hyperspectral remote sensing images (HSIs) usually have high spectral
resolution and low spatial resolution. Conversely, multispectral images (MSIs)
usually have low spectral and high spatial resolutions. The problem of
inferring images which combine the high spectral and high spatial resolutions
of HSIs and MSIs, respectively, is a data fusion problem that has been the
focus of recent active research due to the increasing availability of HSIs and
MSIs retrieved from the same geographical area.
We formulate this problem as the minimization of a convex objective function
containing two quadratic data-fitting terms and an edge-preserving regularizer.
The data-fitting terms account for blur, different resolutions, and additive
noise. The regularizer, a form of vector Total Variation, promotes
piecewise-smooth solutions with discontinuities aligned across the
hyperspectral bands.
The downsampling operator accounting for the different spatial resolutions,
the non-quadratic and non-smooth nature of the regularizer, and the very large
size of the HSI to be estimated lead to a hard optimization problem. We deal
with these difficulties by exploiting the fact that HSIs generally "live" in a
low-dimensional subspace and by tailoring the Split Augmented Lagrangian
Shrinkage Algorithm (SALSA), which is an instance of the Alternating Direction
Method of Multipliers (ADMM), to this optimization problem, by means of a
convenient variable splitting. The spatial blur and the spectral linear
operators linked, respectively, with the HSI and MSI acquisition processes are
also estimated, and we obtain an effective algorithm that outperforms the
state-of-the-art, as illustrated in a series of experiments with simulated and
real-life data.Comment: IEEE Trans. Geosci. Remote Sens., to be publishe
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