47 research outputs found
Modal analysis of gravitational instabilities in nearly Keplerian, counter-rotating collisionless discs
We present a modal analysis of instabilities of counter-rotating,
self-gravitating collisionless stellar discs, using the recently introduced
modified WKB formulation of spiral density waves for collisionless systems
(Gulati \& Saini). The discs are assumed to be axisymmetric and in coplanar
orbits around a massive object at the common center of the discs. The mass in
both discs is assumed to be much smaller than the mass of the central object.
For each disc, the disc particles are assumed to be in near circular orbits.
The two discs are coupled to each other gravitationally. The perturbed dynamics
of the discs evolves on the order of the precession time scale of the discs,
which is much longer than the Keplerian time scale. We present results for the
azimuthal wave number and , for the full range of disc mass ratio
between the prograde and retrograde discs. The eigenspectra are in general
complex, therefore all eigenmodes are unstable. Eigenfunctions are radially
more compact for as compared to . Pattern speed of eigenmodes is
always prograde with respect to the more massive disc. The growth rate of
unstable modes increases with increasing mass fraction in the retrograde disc,
and decreases with ; therefore instability is likely to play the
dominant role in the dynamics of such systems.Comment: 24 pages, 8 figures, 1 tabl
Slow pressure modes in thin accretion discs
Thin accretion discs around massive compact objects can support slow pressure
modes of oscillations in the linear regime that have azimuthal wavenumber
. We consider finite, flat discs composed of barotropic fluid for various
surface density profiles and demonstrate--through WKB analysis and numerical
solution of the eigenvalue problem--that these modes are stable and have
spatial scales comparable to the size of the disc. We show that the eigenvalue
equation can be mapped to a Schr\"odinger-like equation. Analysis of this
equation shows that all eigenmodes have discrete spectra. We find that all the
models we have considered support negative frequency eigenmodes; however, the
positive eigenfrequency modes are only present in power law discs, albeit for
physically uninteresting values of the power law index and barotropic
index .Comment: 9 pages, 7 figures, 1 table, accepted in MNRAS for pulicatio
Change Detection from Remotely Sensed Images Based on Stationary Wavelet Transform
The major issue of concern in change detection process is the accuracy of the algorithm to recover changed and unchanged pixels. The fusion rules presented in the existing methods could not integrate the features accurately which results in more number of false alarms and speckle noise in the output image. This paper proposes an algorithm which fuses two multi-temporal images through proposed set of fusion rules in stationary wavelet transform. In the first step, the source images obtained from log ratio and mean ratio operators are decomposed into three high frequency sub-bands and one low frequency sub-band by stationary wavelet transform. Then, proposed fusion rules for low and high frequency sub-bands are applied on the coefficient maps to get the fused wavelet coefficients map. The fused image is recovered by applying the inverse stationary wavelet transform (ISWT) on the fused coefficient map. Finally, the changed and unchanged areas are classified using Fuzzy c means clustering. The performance of the algorithm is calculated in terms of percentage correct classification (PCC), overall error (OE) and Kappa coefficient (Kc). The qualitative and quantitative results prove that the proposed method offers least error, highest accuracy and Kappa value as compare to its preexistences
Enhance GPS Accuracy via Integration of Artificial Intelligence
GPS has improved navigation and location-based services, its precision is still affected by things like weather and building materials. The purpose of this research was to investigate the feasibility of using AI methods to enhance GPS precision. This research proves that GPS accuracy has increased significantly, making it suitable for use in increasingly important fields including driverless vehicles, precision agriculture, geospatial mapping, and more. These results highlight the revolutionary potential of incorporating AI to improve the accuracy and reliability of GPS technology, ushering in a new era of navigation and location-based applications. In this study, authors introduce an Artificial Intelligence technique, to increase the precision of GPS receivers. Interoperability of Sensors Mostly made out of a Three-Axis Accelerometer Once GPS signal is lost with any cause, this change in delta latitude and delta longitude will be computed by our trained artificial neural network, and then, based on this interpolation, artificial neural network calculates latitude and longitude. The 3-axis gyroscope is part of an inertial measurement unit (IMU) that is used in conjunction with AI to predict navigation parameters when GPS loses communication with a satellite
Congestion Aware WSN-IoT-Application Layer Protocols for Healthcare Services
In the healthcare industry, WSN-IoT networks can be used to gather patient data for statistical purposes. IoT-based application-level protocols do not take into account these facts while forwarding the data to the gateway or server, which may degrade the network performance if the data was collected from a patient with ordinary/critical health issues and the route was busy or congested. In this paper, we'll look at the performance of two application layer protocols (i.e. CoAP and MQTT) within the constraints of a scalable network by integrating a congestion-aware scheme with them
MATHCAD Geometrie Benutzerhandbuch
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