1,750 research outputs found
Non-linear Kalman filters for calibration in radio interferometry
We present a new calibration scheme based on a non-linear version of Kalman
filter that aims at estimating the physical terms appearing in the Radio
Interferometry Measurement Equation (RIME). We enrich the filter's structure
with a tunable data representation model, together with an augmented
measurement model for regularization. We show using simulations that it can
properly estimate the physical effects appearing in the RIME. We found that
this approach is particularly useful in the most extreme cases such as when
ionospheric and clock effects are simultaneously present. Combined with the
ability to provide prior knowledge on the expected structure of the physical
instrumental effects (expected physical state and dynamics), we obtain a fairly
cheap algorithm that we believe to be robust, especially in low signal-to-noise
regime. Potentially the use of filters and other similar methods can represent
an improvement for calibration in radio interferometry, under the condition
that the effects corrupting visibilities are understood and analytically
stable. Recursive algorithms are particularly well adapted for pre-calibration
and sky model estimate in a streaming way. This may be useful for the SKA-type
instruments that produce huge amounts of data that have to be calibrated before
being averaged
Radio interferometric gain calibration as a complex optimization problem
Recent developments in optimization theory have extended some traditional
algorithms for least-squares optimization of real-valued functions
(Gauss-Newton, Levenberg-Marquardt, etc.) into the domain of complex functions
of a complex variable. This employs a formalism called the Wirtinger
derivative, and derives a full-complex Jacobian counterpart to the conventional
real Jacobian. We apply these developments to the problem of radio
interferometric gain calibration, and show how the general complex Jacobian
formalism, when combined with conventional optimization approaches, yields a
whole new family of calibration algorithms, including those for the polarized
and direction-dependent gain regime. We further extend the Wirtinger calculus
to an operator-based matrix calculus for describing the polarized calibration
regime. Using approximate matrix inversion results in computationally efficient
implementations; we show that some recently proposed calibration algorithms
such as StefCal and peeling can be understood as special cases of this, and
place them in the context of the general formalism. Finally, we present an
implementation and some applied results of CohJones, another specialized
direction-dependent calibration algorithm derived from the formalism.Comment: 18 pages; 6 figures; accepted by MNRA
Quantitative Analysis of Saliency Models
Previous saliency detection research required the reader to evaluate
performance qualitatively, based on renderings of saliency maps on a few
shapes. This qualitative approach meant it was unclear which saliency models
were better, or how well they compared to human perception. This paper provides
a quantitative evaluation framework that addresses this issue. In the first
quantitative analysis of 3D computational saliency models, we evaluate four
computational saliency models and two baseline models against ground-truth
saliency collected in previous work.Comment: 10 page
Distributed texture-based terrain synthesis
Terrain synthesis is an important field of Computer Graphics that deals with the generation of 3D landscape models for use in virtual environments. The field has evolved to a stage where large and even infinite landscapes can be generated in realtime. However, user control of the generation process is still minimal, as well as the creation of virtual landscapes that mimic real terrain. This thesis investigates the use of texture synthesis techniques on real landscapes to improve realism and the use of sketch-based interfaces to enable intuitive user control
Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
In radio interferometry, observed visibilities are intrinsically sampled at
some interval in time and frequency. Modern interferometers are capable of
producing data at very high time and frequency resolution; practical limits on
storage and computation costs require that some form of data compression be
imposed. The traditional form of compression is a simple averaging of the
visibilities over coarser time and frequency bins. This has an undesired side
effect: the resulting averaged visibilities "decorrelate", and do so
differently depending on the baseline length and averaging interval. This
translates into a non-trivial signature in the image domain known as
"smearing", which manifests itself as an attenuation in amplitude towards
off-centre sources. With the increasing fields of view and/or longer baselines
employed in modern and future instruments, the trade-off between data rate and
smearing becomes increasingly unfavourable. In this work we investigate
alternative approaches to low-loss data compression. We show that averaging of
the visibility data can be treated as a form of convolution by a boxcar-like
window function, and that by employing alternative baseline-dependent window
functions a more optimal interferometer smearing response may be induced. In
particular, we show improved amplitude response over a chosen field of
interest, and better attenuation of sources outside the field of interest. The
main cost of this technique is a reduction in nominal sensitivity; we
investigate the smearing vs. sensitivity trade-off, and show that in certain
regimes a favourable compromise can be achieved. We show the application of
this technique to simulated data from the Karl G. Jansky Very Large Array (VLA)
and the European Very-long-baseline interferometry Network (EVN)
Model consent clauses for rare disease research
Background: Rare Disease research has seen tremendous advancements over the last decades, with the development of new technologies, various global collaborative efforts and improved data sharing. To maximize the impact of and to further build on these developments, there is a need for model consent clauses for rare diseases research, in order to improve data interoperability, to meet the informational needs of participants, and to ensure proper ethical and legal use of data sources and participants' overall protection.
Methods: A global Task Force was set up to develop model consent clauses specific to rare diseases research, that are comprehensive, harmonized, readily accessible, and internationally applicable, facilitating the recruitment and consent of rare disease research participants around the world. Existing consent forms and notices of consent were analyzed and classified under different consent themes, which were used as background to develop the model consent clauses.
Results: The IRDiRC-GA4GH MCC Task Force met in September 2018, to discuss and design model consent clauses. Based on analyzed consent forms, they listed generic core elements and designed the following rare disease research specific core elements; Rare Disease Research Introductory Clause, Familial Participation, Audio/Visual Imaging, Collecting, storing, sharing of rare disease data, Recontact for matching, Data Linkage, Return of Results to Family Members, Incapacity/Death, and Benefits.
Conclusion: The model consent clauses presented in this article have been drafted to highlight consent elements that bear in mind the trends in rare disease research, while providing a tool to help foster harmonization and collaborative efforts
Shading Curves: Vector-Based Drawing With Explicit Gradient Control
A challenge in vector graphics is to define primitives that offer flexible manipulation of colour gradients. We propose a new primitive, called a shading curve, that supports explicit and local gradient control. This is achieved by associating shading profiles to each side of the curve. These shading profiles, which can be manually manipulated, represent the colour gradient out from their associated curves. Such explicit and local gradient control is challenging to achieve via the diffusion curve process, introduced in 2008, because it offers only implicit control of the colour gradient. We resolve this problem by using subdivision surfaces that are constructed from shading curves and their shading profiles.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/cgf.1253
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