337 research outputs found
An a posteriori error analysis of a mixed finite element Galerkin approximation to second order linear parabolic problems
In this article, a posteriori error estimates are derived for a mixed finite element Galerkin approximation to second order linear parabolic initial and boundary value problems. Using mixed elliptic reconstruction method, a posteriori error estimates in and -norms with optimal order of convergence for the solution as well as its flux are proved for the semidiscrete scheme. Finally, based on backward Euler method, a completely discrete scheme is analyzed and a posteriori bounds are derived, which improves earlier results on a posteriori estimates for mixed parabolic problems
Theoretical studies of the atomic transitions in boron-like ions: Mg VIII, Si X and S XII
In this paper, we have carried out the calculations of the weighted
oscillator strengths and the transition probabilities for a few low-lying
transitions of boron-like ions: Mg VIII, Si X and S XII which are
astrophysically important, particularly, in the atmospheres of the solar
corona. We have employed an all-order relativistic many-body theory called the
relativistic coupled-cluster theory to calculate very precisely these atomic
quantities of astrophysical interest. We have reported for the first time the
transition probabilities for some forbidden transitions which are unavailable
in the literature; either theoretically or experimentally. We also discuss the
physical effects associated with these transitions. Our data can be used for
the identification of spectral lines arising from the coronal atmospheres of
Sun and Sun-like stars having an extended corona.Comment: 8 pages, 4 table
Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries
With advanced image journaling tools, one can easily alter the semantic
meaning of an image by exploiting certain manipulation techniques such as
copy-clone, object splicing, and removal, which mislead the viewers. In
contrast, the identification of these manipulations becomes a very challenging
task as manipulated regions are not visually apparent. This paper proposes a
high-confidence manipulation localization architecture which utilizes
resampling features, Long-Short Term Memory (LSTM) cells, and encoder-decoder
network to segment out manipulated regions from non-manipulated ones.
Resampling features are used to capture artifacts like JPEG quality loss,
upsampling, downsampling, rotation, and shearing. The proposed network exploits
larger receptive fields (spatial maps) and frequency domain correlation to
analyze the discriminative characteristics between manipulated and
non-manipulated regions by incorporating encoder and LSTM network. Finally,
decoder network learns the mapping from low-resolution feature maps to
pixel-wise predictions for image tamper localization. With predicted mask
provided by final layer (softmax) of the proposed architecture, end-to-end
training is performed to learn the network parameters through back-propagation
using ground-truth masks. Furthermore, a large image splicing dataset is
introduced to guide the training process. The proposed method is capable of
localizing image manipulations at pixel level with high precision, which is
demonstrated through rigorous experimentation on three diverse datasets
Relativistic general-order coupled-cluster method for high-precision calculations: Application to Al+ atomic clock
We report the implementation of a general-order relativistic coupled-cluster
method for performing high-precision calculations of atomic and molecular
properties. As a first application, the static dipole polarizabilities of the
ground and first excited states of Al+ have been determined to precisely
estimate the uncertainty associated with the BBR shift of its clock frequency
measurement. The obtained relative BBR shift is -3.66+-0.44 for the 3s^2
^1S_0^0 --> 3s3p ^3P_0^0 transition in Al+ in contrast to the value obtained in
the latest clock frequency measurement, -9+-3 [Phys. Rev. Lett. 104, 070802
(2010)]. The method developed in the present work can be employed to study a
variety of subtle effects such as fundamental symmetry violations in atoms.Comment: 4 pages, 3 tables, submitte
Border Security using Raspberry Pi
Border Security is one of the major concerns for any country. Issues like political and economic instability in neighboring countries and border distribution demand a good border management and security system. The terrorist attacks that have been taking place over several years have increased the need of an improvised and high level security system. Hence, border infiltration monitoring and prevention is a system built to provide security at the borders. The device is based on the concepts of image capturing, cloud, and wireless data communication. Image processing concepts of noise removal, RGB to gray conversion, background subtraction and histogram of oriented gradients (HOG) are used to detect intrusion. Cloud is used to store the images of the intruder and retrieval at a farther place. Wireless data communication is used to send alert messages from the primary base station to the secondary base station. Further reactions are taken by handling manual robot for fire focusing to the enemy object by targeting and shooting and moving the robot towards enemy with robot detecting metals along its path for safety checking of any bomb present along its way
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