University of Victoria

About: University of Victoria is a education organization based out in Victoria, British Columbia, Canada. It is known for research contribution in the topics: Population & Galaxy. The organization has 14994 authors who have published 41051 publications receiving 1447972 citations. The organization is also known as: Victoria College.

The Pareto law of incomes—an explanation and an extension

Abstract: A stochastic model for the generation of observed income distributions is used to provide an explanation for the Pareto law of incomes. Analysis of the model also yields a prediction of Paretian (power law) behaviour in the lower tail of the distribution and this is shown to occur in a number of empirical distributions. A tractable four-parameter distribution is derived, and shown to fit extremely well to a number of different empirical income distributions.

Detecting opinion spams and fake news using text classification

Abstract: *Correspondence Traore, Issa, ECE Department, University of Victoria, Victoria, BC, Canada. Email: itraore@ece.uvic.ca In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike. Furthermore, the problem of fake news has gained attention in 2016, especially in the aftermath of the last U.S. presidential elections. Fake reviews and fake news are a closely related phenomenon as both consist of writing and spreading false information or beliefs. The opinion spam problem was formulated for the first time a few years ago, but it has quickly become a growing research area due to the abundance of user-generated content. It is now easy for anyone to either write fake reviews or write fake news on the web. The biggest challenge is the lack of an efficient way to tell the difference between a real review and a fake one; even humans are often unable to tell the difference. In this paper, we introduce a new n-gram model to detect automatically fake contents with a particular focus on fake reviews and fake news. We study and compare 2 different features extraction techniques and 6 machine learning classification techniques. Experimental evaluation using existing public datasets and a newly introduced fake news dataset indicate very encouraging and improved performances compared to the state-of-the-art methods.

The distribution of satellite galaxies: the great pancake

Abstract: The 11 known satellite galaxies within 250 kpc of the Milky Way lie close to a great circle on the sky. We use high-resolution N-body simulations of galactic dark matter haloes to test if this remarkable property can be understood within the context of the cold dark matter (CDM) cosmology. We construct halo merger trees from the simulations and use a semi-analytic model to follow the formation of satellite galaxies. We find that in all six of our simulations, the 11 brightest satellites are indeed distributed along thin, disc-like structures analogous to that traced by the satellites of the Milky Way. This is in sharp contrast to the overall distributions of dark matter in the halo and of subhaloes within it, which, although triaxial, are not highly aspherical. We find that the spatial distribution of satellites is significantly different from that of the most massive subhaloes but is similar to that of the subset of subhaloes that had the most massive progenitors at earlier times. The elongated disc-like structure delineated by the satellites has its long axis aligned with the major axis of the dark matter halo. We interpret our results as reflecting the preferential infall of satellites along the spines of a few filaments of the cosmic web.

Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton–proton collision data

Abstract: This paper presents the performance of the ATLAS muon reconstruction during the LHC run with pp collisions at root s = 7-8 TeV in 2011-2012, focusing mainly on data collected in 2012. Measurements ...

The quasar outflow contribution to agn feedback: vlt measurements of sdss j0318-0600*

Abstract: We present high spectral resolution Very Large Telescope observations of the broad absorption line quasar SDSS J0318 – 0600. This high-quality data set allows us to extract accurate ionic column densities and determine an electron number density of ne = 103.3±0.2 cm–3 for the main outflow absorption component. The heavily reddened spectrum of SDSS J0318-0600 requires purely silicate dust with a reddening curve characteristic of predominately large grains, from which we estimate the bolometric luminosity. We carry out photoionization modeling to determine the total column density, ionization parameter, and distance of the gas and find that the photoionization models suggest abundances greater than solar. Due to the uncertainty in the location of the dust extinction, we arrive at two viable distances for the main ouflow component from the central source, 6 and 17 kpc, where we consider the 6 kpc location as somewhat more physically plausible. Assuming the canonical global covering of 20% for the outflow and a distance of 6 kpc, our analysis yields a mass flux of 120 M ☉ yr–1 and a kinetic luminosity that is ~0.1% of the bolometric luminosity of the object. Should the dust be part of the outflow, then these values are ~4× larger. The large mass flux and kinetic luminosity make this outflow a significant contributor to active galactic nucleus feedback processes.