10,311 research outputs found
Observational Prospects for Afterglows of Short Duration Gamma-ray Bursts
If the efficiency for producing -rays is the same in short duration
(\siml 2 s) Gamma-Ray Bursts (GRBs) as in long duration GRBs, then the
average kinetic energy of short GRBs must be times less than that of
long GRBs. Assuming further that the relativistic shocks in short and long
duration GRBs have similar parameters, we show that the afterglows of short
GRBs will be on average 10--40 times dimmer than those of long GRBs. We find
that the afterglow of a typical short GRB will be below the detection limit
(\siml 10 \microJy) of searches at radio frequencies. The afterglow would be
difficult to observe also in the optical, where we predict R \simg 23 a few
hours after the burst. The radio and optical afterglow would be even fainter if
short GRBs occur in a low-density medium, as expected in NS-NS and NS-BH merger
models. The best prospects for detecting short-GRB afterglows are with early
(\siml 1 day) observations in X-rays.Comment: 5 pages, 2 figures, submitted to ApJ lette
The Rapidly Fading Optical Afterglow of GRB 980519
GRB 980519 had the most rapidly fading of the well-documented GRB afterglows,
consistent with t^{-2.05 +/- 0.04} in BVRI as well as in X-rays during the two
days in which observations were made. We report VRI observations from the MDM
1.3m and WIYN 3.5m telescopes, and we synthesize an optical spectrum from all
of the available photometry. The optical spectrum alone is well fitted by a
power law of the form nu^{-1.20 +/- 0.25}, with some of the uncertainty due to
the significant Galactic reddening in this direction. The optical and X-ray
spectra together are adequately fitted by a single power law nu^{-1.05 +/-
0.10}. This combination of steep temporal decay and flat broad-band spectrum
places a severe strain on the simplest afterglow models involving spherical
blast waves in a homogeneous medium. Instead, the rapid observed temporal decay
is more consistent with models of expansion into a medium of density n(r)
proportional to r^{-2}, or with predictions of the evolution of a jet after it
slows down and spreads laterally. The jet model would relax the energy
requirements on some of the more extreme GRBs, of which GRB 980519 is likely to
be an example because of its large gamma-ray fluence and faint host galaxy.Comment: 13 pages, submitted to ApJ Letter
Registration of retinal images from Public Health by minimising an error between vessels using an affine model with radial distortions
In order to estimate a registration model of eye fundus images made of an
affinity and two radial distortions, we introduce an estimation criterion based
on an error between the vessels. In [1], we estimated this model by minimising
the error between characteristics points. In this paper, the detected vessels
are selected using the circle and ellipse equations of the overlap area
boundaries deduced from our model. Our method successfully registers 96 % of
the 271 pairs in a Public Health dataset acquired mostly with different
cameras. This is better than our previous method [1] and better than three
other state-of-the-art methods. On a publicly available dataset, ours still
better register the images than the reference method
A microgravity isolation mount
The design and preliminary testing of a system for isolating microgravity sensitive payloads from spacecraft vibrational and impulsive disturbances is discussed. The Microgravity Isolation Mount (MGIM) concept consists of a platform which floats almost freely within a limited volume inside the spacecraft, but which is constrained to follow the spacecraft in the long term by means of very weak springs. The springs are realized magnetically and form part of a six degree of freedom active magnetic suspension system. The latter operates without any physical contact between the spacecraft and the platform itself. Power and data transfer is also performed by contactless means. Specifications are given for the expected level of input disturbances and the tolerable level of platform acceleration. The structural configuration of the mount is discussed and the design of the principal elements, i.e., actuators, sensors, control loops and power/data transfer devices are described. Finally, the construction of a hardware model that is being used to verify the predicted performance of the MGIM is described
k-d Darts: Sampling by k-Dimensional Flat Searches
We formalize the notion of sampling a function using k-d darts. A k-d dart is
a set of independent, mutually orthogonal, k-dimensional subspaces called k-d
flats. Each dart has d choose k flats, aligned with the coordinate axes for
efficiency. We show that k-d darts are useful for exploring a function's
properties, such as estimating its integral, or finding an exemplar above a
threshold. We describe a recipe for converting an algorithm from point sampling
to k-d dart sampling, assuming the function can be evaluated along a k-d flat.
We demonstrate that k-d darts are more efficient than point-wise samples in
high dimensions, depending on the characteristics of the sampling domain: e.g.
the subregion of interest has small volume and evaluating the function along a
flat is not too expensive. We present three concrete applications using line
darts (1-d darts): relaxed maximal Poisson-disk sampling, high-quality
rasterization of depth-of-field blur, and estimation of the probability of
failure from a response surface for uncertainty quantification. In these
applications, line darts achieve the same fidelity output as point darts in
less time. We also demonstrate the accuracy of higher dimensional darts for a
volume estimation problem. For Poisson-disk sampling, we use significantly less
memory, enabling the generation of larger point clouds in higher dimensions.Comment: 19 pages 16 figure
Cross Pixel Optical Flow Similarity for Self-Supervised Learning
We propose a novel method for learning convolutional neural image
representations without manual supervision. We use motion cues in the form of
optical flow, to supervise representations of static images. The obvious
approach of training a network to predict flow from a single image can be
needlessly difficult due to intrinsic ambiguities in this prediction task. We
instead propose a much simpler learning goal: embed pixels such that the
similarity between their embeddings matches that between their optical flow
vectors. At test time, the learned deep network can be used without access to
video or flow information and transferred to tasks such as image
classification, detection, and segmentation. Our method, which significantly
simplifies previous attempts at using motion for self-supervision, achieves
state-of-the-art results in self-supervision using motion cues, competitive
results for self-supervision in general, and is overall state of the art in
self-supervised pretraining for semantic image segmentation, as demonstrated on
standard benchmarks
Objects that Sound
In this paper our objectives are, first, networks that can embed audio and
visual inputs into a common space that is suitable for cross-modal retrieval;
and second, a network that can localize the object that sounds in an image,
given the audio signal. We achieve both these objectives by training from
unlabelled video using only audio-visual correspondence (AVC) as the objective
function. This is a form of cross-modal self-supervision from video.
To this end, we design new network architectures that can be trained for
cross-modal retrieval and localizing the sound source in an image, by using the
AVC task. We make the following contributions: (i) show that audio and visual
embeddings can be learnt that enable both within-mode (e.g. audio-to-audio) and
between-mode retrieval; (ii) explore various architectures for the AVC task,
including those for the visual stream that ingest a single image, or multiple
images, or a single image and multi-frame optical flow; (iii) show that the
semantic object that sounds within an image can be localized (using only the
sound, no motion or flow information); and (iv) give a cautionary tale on how
to avoid undesirable shortcuts in the data preparation.Comment: Appears in: European Conference on Computer Vision (ECCV) 201
Alfalfa Cultivar Yield Test for South Dakota: 2000 Report
The South Dakota Alfalfa Cultivar Yield Test reports relative forage production characteristic for available cultivars at several locations in South Dakota. Cultivar are entered in the test by seed companies and public breeders at their own discretion. A list of cultivar and companies is in Table 8 at the end of this circula
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