Highlights
Proposed automatic COVID screening (ACoS) system for detection of infected patients.
Random image augmentation is applied to incorporate the variability in the images.
Applied hierarchical (two phase) classification to segregate three classes.
Majority vote based classifier ensemble is used to combine model’s prediction.
Proposed method show promising potential to detect nCOVID-19 infected patients.
A combination of recent observational results has given rise to what is currently known as the dark energy problem. Although several possible candidates have been extensively discussed in the literature to date the nature of this dark energy component is not well understood at present. In this paper we investigate some cosmological implications of another dark energy candidate: an exotic fluid known as the Chaplygin gas, which is characterized by an equation of state p = −A/ρ, where A is a positive constant. By assuming a flat scenario driven by non-relativistic matter plus a Chaplygin gas dark energy we study the influence of such a component on the statistical properties of gravitational lenses. A comparison between the predicted age of the universe and the latest age estimates of globular clusters is also included and the results briefly discussed. In general, we find that the behavior of this class of models may be interpreted as an intermediary case between the standard and ΛCDM scenarios.
Linearly coasting cosmology is comfortably concordant with a host of cosmological observations. It is surprisingly an excellent fit to SNe Ia observations and constraints arising from age of old quasars. In this article we highlight the overall viability of an open linear coasting cosmological model. The model is consistent with the latest SNe Ia "gold" sample and accommodates a very old high-redshift quasar, which the standard cold-dark model fails to do.
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