147 research outputs found
Robustness of Planar Fourier Capture Arrays to Colour Changes and Lost Pixels
Planar Fourier capture arrays (PFCAs) are optical sensors built entirely in
standard microchip manufacturing flows. PFCAs are composed of ensembles of
angle sensitive pixels (ASPs) that each report a single coefficient of the
Fourier transform of the far-away scene. Here we characterize the performance
of PFCAs under the following three non-optimal conditions. First, we show that
PFCAs can operate while sensing light of a wavelength other than the design
point. Second, if only a randomly-selected subset of 10% of the ASPs are
functional, we can nonetheless reconstruct the entire far-away scene using
compressed sensing. Third, if the wavelength of the imaged light is unknown, it
can be inferred by demanding self-consistency of the outputs.Comment: 15 pages including cover page, 12 figures, associated with the 9th
International Conference on Position Sensitive Detector
The Tychonoff uniqueness theorem for the G-heat equation
In this paper, we obtain the Tychonoff uniqueness theorem for the G-heat
equation
An output-sensitive algorithm for the minimization of 2-dimensional String Covers
String covers are a powerful tool for analyzing the quasi-periodicity of
1-dimensional data and find applications in automata theory, computational
biology, coding and the analysis of transactional data. A \emph{cover} of a
string is a string for which every letter of lies within some
occurrence of . String covers have been generalized in many ways, leading to
\emph{k-covers}, \emph{-covers}, \emph{approximate covers} and were
studied in different contexts such as \emph{indeterminate strings}.
In this paper we generalize string covers to the context of 2-dimensional
data, such as images. We show how they can be used for the extraction of
textures from images and identification of primitive cells in lattice data.
This has interesting applications in image compression, procedural terrain
generation and crystallography
Non-Spinning Black Holes in Alternative Theories of Gravity
We study two large classes of alternative theories, modifying the action
through algebraic, quadratic curvature invariants coupled to scalar fields. We
find one class that admits solutions that solve the vacuum Einstein equations
and another that does not. In the latter, we find a deformation to the
Schwarzschild metric that solves the modified field equations in the small
coupling approximation. We calculate the event horizon shift, the innermost
stable circular orbit shift, and corrections to gravitational waves, mapping
them to the parametrized post-Einsteinian framework.Comment: 7 pages, submitted to PR
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The use of the Kalman filter in the automated segmentation of EIT lung images
In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging
Spatial Proximity and Similarity of the Epigenetic State of Genome Domains
Recent studies demonstrate that the organization of the chromatin within the nuclear space might play a crucial role in the regulation of gene expression. The ongoing progress in determination of the 3D structure of the nuclear chromatin allows one to study correlations between spatial proximity of genome domains and their epigenetic state. We combined the data on three-dimensional architecture of the whole human genome with results of high-throughput studies of the chromatin functional state and observed that fragments of different chromosomes that are spatially close tend to have similar patterns of histone modifications, methylation state, DNAse sensitivity, expression level, and chromatin states in general. Moreover, clustering of genome regions by spatial proximity produced compact clusters characterized by the high level of histone modifications and DNAse sensitivity and low methylation level, and loose clusters with the opposite characteristics. We also associated the spatial proximity data with previously detected chimeric transcripts and the results of RNA-seq experiments and observed that the frequency of formation of chimeric transcripts from fragments of two different chromosomes is higher among spatially proximal genome domains. A fair fraction of these chimeric transcripts seems to arise post-transcriptionally via trans-splicing
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells
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