7,655 research outputs found
Why Do Granular Materials Stiffen with Shear Rate? : Test of Novel Stress-Based Statistics
Peer reviewedPublisher PD
Normal frames for non-Riemannian connections
The principal properties of geodesic normal coordinates are the vanishing of
the connection components and first derivatives of the metric components at
some point. It is well-known that these hold only at points where the
connection has vanishing torsion and non-metricity. However, it is shown that
normal frames, possessing the essential features of normal coordinates, can
still be constructed when the connection is non-Riemannian.Comment: 4 pages, plain TeX. To appear in Class. Quantum Gra
Support Vector Machine classification of strong gravitational lenses
The imminent advent of very large-scale optical sky surveys, such as Euclid
and LSST, makes it important to find efficient ways of discovering rare objects
such as strong gravitational lens systems, where a background object is
multiply gravitationally imaged by a foreground mass. As well as finding the
lens systems, it is important to reject false positives due to intrinsic
structure in galaxies, and much work is in progress with machine learning
algorithms such as neural networks in order to achieve both these aims. We
present and discuss a Support Vector Machine (SVM) algorithm which makes use of
a Gabor filterbank in order to provide learning criteria for separation of
lenses and non-lenses, and demonstrate using blind challenges that under
certain circumstances it is a particularly efficient algorithm for rejecting
false positives. We compare the SVM engine with a large-scale human examination
of 100000 simulated lenses in a challenge dataset, and also apply the SVM
method to survey images from the Kilo-Degree Survey.Comment: Accepted by MNRA
Autocalibration with the Minimum Number of Cameras with Known Pixel Shape
In 3D reconstruction, the recovery of the calibration parameters of the
cameras is paramount since it provides metric information about the observed
scene, e.g., measures of angles and ratios of distances. Autocalibration
enables the estimation of the camera parameters without using a calibration
device, but by enforcing simple constraints on the camera parameters. In the
absence of information about the internal camera parameters such as the focal
length and the principal point, the knowledge of the camera pixel shape is
usually the only available constraint. Given a projective reconstruction of a
rigid scene, we address the problem of the autocalibration of a minimal set of
cameras with known pixel shape and otherwise arbitrarily varying intrinsic and
extrinsic parameters. We propose an algorithm that only requires 5 cameras (the
theoretical minimum), thus halving the number of cameras required by previous
algorithms based on the same constraint. To this purpose, we introduce as our
basic geometric tool the six-line conic variety (SLCV), consisting in the set
of planes intersecting six given lines of 3D space in points of a conic. We
show that the set of solutions of the Euclidean upgrading problem for three
cameras with known pixel shape can be parameterized in a computationally
efficient way. This parameterization is then used to solve autocalibration from
five or more cameras, reducing the three-dimensional search space to a
two-dimensional one. We provide experiments with real images showing the good
performance of the technique.Comment: 19 pages, 14 figures, 7 tables, J. Math. Imaging Vi
Transients in sheared granular matter
As dense granular materials are sheared, a shear band and an anisotropic
force network form. The approach to steady state behavior depends on the
history of the packing and the existing force and contact network. We present
experiments on shearing of dense granular matter in a 2D Couette geometry in
which we probe the history and evolution of shear bands by measuring particle
trajectories and stresses during transients. We find that when shearing is
stopped and restarted in the same direction, steady state behavior is
immediately reached, in agreement with the typical assumption that the system
is quasistatic. Although some relaxation of the force network is observed when
shearing is stopped, quasistatic behavior is maintained because the contact
network remains essentially unchanged. When the direction of shear is reversed,
a transient occurs in which stresses initially decrease, changes in the force
network reach further into the bulk, and particles far from the wheel become
more mobile. This occurs because the force network is fragile to changes
transverse to the force network established under previous shear; particles
must rearrange before becoming jammed again, thereby providing resistance to
shear in the reversed direction. The strong force network is reestablished
after displacing the shearing surface , where is the mean grain
diameter. Steady state velocity profiles are reached after a shear of . Particles immediately outside of the shear band move on average less than
1 diameter before becoming jammed again. We also examine particle rotation
during this transient and find that mean particle spin decreases during the
transient, which is related to the fact that grains are not interlocked as
strongly.Comment: 7 pages, 11 figures, accepted to Eur. Phys. J. E, revised version
based on referee suggestion
Self-Calibration of Cameras with Euclidean Image Plane in Case of Two Views and Known Relative Rotation Angle
The internal calibration of a pinhole camera is given by five parameters that
are combined into an upper-triangular calibration matrix. If the
skew parameter is zero and the aspect ratio is equal to one, then the camera is
said to have Euclidean image plane. In this paper, we propose a non-iterative
self-calibration algorithm for a camera with Euclidean image plane in case the
remaining three internal parameters --- the focal length and the principal
point coordinates --- are fixed but unknown. The algorithm requires a set of point correspondences in two views and also the measured relative
rotation angle between the views. We show that the problem generically has six
solutions (including complex ones).
The algorithm has been implemented and tested both on synthetic data and on
publicly available real dataset. The experiments demonstrate that the method is
correct, numerically stable and robust.Comment: 13 pages, 7 eps-figure
Program for transfer research and impact studies
Research activities conducted under the Program for Transfer Research and Impact Studies (TRIS) during 1972 included: (1) preparation of 10,196 TSP requests for TRIS application analysis; (2) interviews with over 500 individuals concerning the technical, economic, and social impacts of NASA-generated technology; (3) preparation of 38 new technology transfer example files and 101 new transfer cases; and (4) maintenance of a technology transfer library containing more than 2,900 titles. Six different modes of technology utilization are used to illustrate the pervasiveness of the transfer and diffusion of aerospace innovations. These modes also provide a basis for distinguishing the unique characteristics of the NASA Technology Utilization Program. An examination is reported of the ways in which NASA-generated technology is contributing to beneficial social change in five major areas of human concern: health, environment, safety, transportation, and communication
Collaboration and teamwork: immersion and presence in an online learning environment
In the world of OTIS, an online Internet School for occupational therapists, students from four European countries were encouraged to work collaboratively through problem-based learning by interacting with each other in a virtual semi-immersive environment. This paper describes, often in their own words, the experience of European occupational therapy students working together across national and cultural boundaries. Collaboration and teamwork were facilitated exclusively through an online environment, since the students never met each other physically during the OTIS pilot course. The aim of the paper is to explore the observations that here was little interaction between students from different tutorial groups and virtual teamwork developed in each of the cross-cultural tutorial groups. Synchronous data from the students was captured during tutorial sessions and peer-booked meetings and analysed using the qualitative constructs of âimmersionâ, âpresenceâ and âreflection in learningâ. The findings indicate that âimmersionâ was experienced only to a certain extent. However, both âpresenceâ and shared presence were found by the students, within their tutorial groups, to help collaboration and teamwork. Other evidence suggests that communities of interest were established. Further study is proposed to support group work in an online learning environment. It is possible to conclude that collaborative systems can be designed, which encourage students to build trust and teamwork in a cross cultural online learning environment.</p
A PCA-based automated finder for galaxy-scale strong lenses
We present an algorithm using Principal Component Analysis (PCA) to subtract
galaxies from imaging data, and also two algorithms to find strong,
galaxy-scale gravitational lenses in the resulting residual image. The combined
method is optimized to find full or partial Einstein rings. Starting from a
pre-selection of potential massive galaxies, we first perform a PCA to build a
set of basis vectors. The galaxy images are reconstructed using the PCA basis
and subtracted from the data. We then filter the residual image with two
different methods. The first uses a curvelet (curved wavelets) filter of the
residual images to enhance any curved/ring feature. The resulting image is
transformed in polar coordinates, centered on the lens galaxy center. In these
coordinates, a ring is turned into a line, allowing us to detect very faint
rings by taking advantage of the integrated signal-to-noise in the ring (a line
in polar coordinates). The second way of analysing the PCA-subtracted images
identifies structures in the residual images and assesses whether they are
lensed images according to their orientation, multiplicity and elongation. We
apply the two methods to a sample of simulated Einstein rings, as they would be
observed with the ESA Euclid satellite in the VIS band. The polar coordinates
transform allows us to reach a completeness of 90% and a purity of 86%, as soon
as the signal-to-noise integrated in the ring is higher than 30, and almost
independent of the size of the Einstein ring. Finally, we show with real data
that our PCA-based galaxy subtraction scheme performs better than traditional
subtraction based on model fitting to the data. Our algorithm can be developed
and improved further using machine learning and dictionary learning methods,
which would extend the capabilities of the method to more complex and diverse
galaxy shapes
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