Mesonnier J.-S.,Banque de France 75001 Paris France |
Oxford Bulletin of Economics and Statistics | Year: 2017
We propose a simple approach to quantifying the macroeconomic effects of shocks to large banks' leverage. We first estimate a standard dynamic model of leverage targeting at the bank level and use it to derive an aggregate measure of the economic capital buffer of large US bank holding corporations. We then evaluate the response of key macro variables to a shock to this aggregate bank capital buffer using standard monetary VAR models. We find that shocks to the capital of large US banks explain a substantial share of the variance of credit to firms and real activity. © 2017 The Department of Economics, University of Oxford and John Wiley & Sons Ltd.
News Article | February 27, 2017
A protest at Ciudad Juarez, Chihuahua State, Mexico on February 26, 2017 against the proposed wall between the United States and Mexico (AFP Photo/HERIKA MARTINEZ) Montreal (AFP) - Built to keep out migrants, traffickers, or an enemy group, border walls have emerged as a one-size-fits-all response to the vulnerability felt by many societies in today's globalized world, says an expert on the phenomenon. Practically non-existent at the end of World War II, by the time the Berlin Wall fell in 1989 the number of border walls across the globe had risen to 11. That number has since jumped to 70, prompted by an increased sense of insecurity following the September 11, 2001 attacks in the United States and the 2011 Arab Spring, according to Elisabeth Vallet, director of the Observatory of Geopolitics at the University of Quebec in Montreal (UQAM). One third were intended to bring an end to a conflict, Vallet says, such as between north and south Cyprus, the two Koreas, and India and Pakistan. But in recent years "three distinct types of walls have appeared, including anti-migration walls -- the most common -- anti-trafficking walls and anti-terrorism walls," she told AFP. For Vallet, walls or fences are often used as a "turnkey response" to a sense of vulnerability felt when "migratory pressures are changing the nature of a society's identity, or exerting economic pressure." That is the case, she says, in Bulgaria, Greece or Hungary -- and most prominently in the United States where President Donald Trump's flagship campaign promise was to build a wall on the border with Mexico. Typically they represent "the divide between rich and poor, north and south," said Vallet, noting exceptions such as Saudi Arabia which has used walls to isolate itself from its neighbors. And in an electoral context, walls are typically linked to questions of "identity," used by demagogues to cast neighbors in a bad light -- and reinforce a sense of them and us. Vallet cites data from US border officials that shows that "walls deter and slow down people, but walls never keep them out." In some cases, there is evidence that moves to close borders can actually drive people who had not taken the decision to migrate to do so, she said, with walls fuelling the migration they are intended to curb. Meanwhile their dissuasive power is limited, she says, pointing at the depth of despair that drives migrants to undertake perilous migrations, with newborns in their arms, and exposing themselves to extreme personal danger. "Ninety percent of women will take a contraceptive, presuming not that they could be raped -- but that they will be." "A wall is extraordinarily expensive," she said -- money that could be better spent addressing the factors behind migrant movements. The cost of Trump's planned border wall, for instance, could reach $21.6 billion, according to a Department of Homeland Security estimate circulated by US media. Each kilometer of existing fencing between Mexico and the United States cost between one and eight million US dollars, Vallet noted. Closing off the whole border, as Trump has vowed to do, by adding more than 2,000 kilometers of wall in "desert areas where the land is privately-owned and will have to be expropriated, will push the cost up to US$21 million per kilometer." "If that money were invested in peace missions... or towards responding to the climate change that triggers food insecurity and migration," Vallet believes it would have the potential to change "the course of history." "You need to invest in peace missions, in security -- humanitarian corridors in Syria might have spared Hungary the need to build walls," she said.
News Article | October 29, 2016
Seema Goel will be speaking at the upcoming University Art Association of Canada Conference this week at UQAM in Montreal. Her talk Data Dexterities is part of the session “Making Knowledge: Craft and the Digital” on Friday October 28th. In Data Dexterities she explores her own art/craft practise highlighting the use of digital technologies as a material to enhance touch, and play, and where the viewer’s awareness of the digital experience is integral to the success of the work. Data Dexterities: The project of shifting the digital experience beyond the binary is well underway. From simple yes/no response, Seema strives now to mimic the multiplicity available in human interaction. How does she, in craft, participate in this shift to engage the nuance and complexity of touch, materiality, and maker-user connection? How is craft language equally explored and accentuated through this effort? This presentation explores the contradictions and connections between touch and craft & digital interfaces through her own craft-based art practise. Bio: Seema Goel is a Canadian artist, writer, and curator. Her current work explores the manipulations and representations of the natural world resulting from human intervention. Using a wide range of media including taxidermy, projection, natural materials, and responsive technologies, she invites the viewer to engage these subjects through humour, touch, and participation. She has exhibited in North America and Europe and her writing has appeared in numerous literary publications, newspaper journals, and on radio and stage. Goel holds an MFA from the Rhode Island School of Design, an Associated Arts Diploma from the Ontario College of Art and Design, and a BSc. from McGill. She is also an alumna of the Harvard Summer Writing program, the Banff Centre Writing program, St. Peter’s Abbey, Fort San, and also managed to moonlight in the Brown Creative Writing program while a student at RISD. She is currently the STEAM coordinator and artist-in-residence in the faculty of Science at the University of Manitoba. For more information, please visit http://seemagoel.com/
News Article | December 15, 2016
Suicide is a serious public health problem in Canada, and it’s a sad reality that sometimes, people jump onto a subway track in an attempt to end their lives.According to researchers, artificial intelligence could help prevent suicides underground by helping to identify those who are at risk. Suicide crises are often temporary, according to the Canadian Association for Suicide Prevention, which provides a list of resources to those who need help. And subway attempts doesn’t always go as planned, said Brian Mishara, director of the Center for Research and Intervention on Suicide and Euthanasia at the Université du Québec à Montréal (UQAM). Oftentimes, he told me over the phone, people who attempt suicide by subway are left maimed and disfigured, and wind up in hospital, where they may only die after much protracted suffering. Read More: NASA's New Self-Learning AI Could Save First RespondersThis encouraged him and a group of students to watch CCTV video of 60 suicide attempts on the Montréal metro and identify behaviours that could indicate when an attempt is about to happen.“It’s really painful to watch someone display a lot of ambivalence before the attempt and then try to change their mind by squashing themselves down to the ground as the train’s approaching,” said Mishara. “That was the most difficult.”While some cities are approaching suicide prevention by building doors that only open when the train arrives—Toronto has also considered this—the cost can be prohibitive for older metro systems. Instead, Mishara thinks artificial intelligence can help by analyzing live CCTV footage and looking for the telltale signs of an attempt underway. “A human being can’t sit and watch 100 or more screens in real-time to try and see if there’s anyone at risk"“A human being can’t sit and watch 100 or more screens in real-time to try and see if there’s anyone at risk,” Mishara said. “The ideal situation would be to have automated, computerized monitoring where if certain patterns of behaviour are observed, the program could then immediately signal to someone in the control room or the driver to look at the video. The person can then make the judgement call.”Mishara considers his study, published on Wednesday in the journal BMC Public Health, a first step towards such a system. After analyzing videos of suicide attempts provided by the Société de transport de Montréal(STM), the city’s public transit agency, Mishara and his colleagues identified a set of behaviours that, together, can indicate an attempt is about to happen. These include pacing around the yellow line, placing an object on the platform, and appearing slouched and depressed. The idea would be to train software to identify these possible warning signs using pixel information from CCTV video feeds, a domain known as computer vision. Great strides have been made in computer vision thanks to a technique known as deep learning, although there’s a ton of work left to do in order to make it truly reliable in the real world. Still, universities and even Google have all proposed methods for computers to automatically, and accurately, evaluate human body poses. “A decision has not yet been made: we must evaluate before deciding on the recommendations,” STM spokesperson Amélie Regis wrote in an email, regarding whether or not the STM plans on implementing live CCTV monitoring with artificial intelligence. As Mishara said, this is just a first step. Get six of our favorite Motherboard stories every day by signing up for our newsletter.
Bergeron P.,Université de Sherbrooke |
Reale D.,UQAM |
Humphries M.M.,McGill University |
Garant D.,Université de Sherbrooke
Journal of Evolutionary Biology | Year: 2011
Mate selection for inbreeding avoidance is documented in several taxa. In mammals, most conclusive evidence comes from captive experiments that control for the availability of mates and for the level of genetic relatedness between mating partners. However, the importance of mate selection for inbreeding avoidance as a determinant of siring success in the wild has rarely been addressed. We followed the reproduction of a wild population of eastern chipmunks (Tamias striatus) during five breeding seasons between 2006 and 2009. Using molecular tools and parentage assignment methods, we found that multiple paternity (among polytocous litters) varied from 25% in an early-spring breeding season when less than a quarter of females in the population were reproductively active to 100% across three summer breeding seasons and one spring breeding season when more than 85% of females were reproductively active. Genetically related parents were common in this population and produced less heterozygous offspring. Furthermore, litters with multiple sires showed a higher average relatedness among partners than litters with only a single sire. In multiply sired litters, however, males that were more closely related to their partners sired fewer offspring. Our results corroborate findings from captive experiments and suggest that selection for inbreeding avoidance can be an important determinant of reproductive success in wild mammals. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.
Nouaouria N.,UQAM |
Applied Soft Computing Journal | Year: 2014
This paper describes a novel Particle Swarm Optimization (PSO)-based classification algorithm with improved capabilities in comparison to several alternatives. The algorithm uses a new particle-position update mechanism and a new way to handle mixed-attribute data based on particle position interpretation. The new position update mechanism combines particle confinement and dispersion for improved search space coverage, and the proposed interpretation mechanism uses the frequencies of non numerical attributes instead of integer mappings. As our experimental results have shown, this leads to better cost function evaluation in the description space and subsequently enhanced processing of mixed-attribute data by the PSO algorithm. Our experimental setup consisted of three large benchmark databases, and the obtained recognition accuracies were better than those obtained with well-known classifiers. © 2014 Elsevier B.V.
di Sciullo A.M.,UQAM
Communications in Computer and Information Science | Year: 2015
We consider the properties of an integrated competence-performance model where the grammar generates the asymmetrical relations underlying linguistic expressions and the parser recovers these asymmetries. This model relates Asymmetry Theory, which is a theory of the Language Faculty, and asymmetry-based parsing, which is a theory of language use. We discuss the derivation and parsing of morphological and syntactic argument structure dependencies under the world level and above in order to show that the grammar generates these dependencies and that the parser recovers them. The integrated competence-performance model is sensitive to the configurational and featural asymmetries underlying linguistic expressions and contributes to reduce the complexity. Lastly, we draw consequences for natural language understanding. © Springer International Publishing Switzerland 2015.
Communications in Mathematical Physics | Year: 2016
The Eisenstein functions (Formula presented.) are some generalized eigenfunctions of the Laplacian on manifolds with cusps. We give a version of Quantum Unique Ergodicity for them, for (Formula presented.) and (Formula presented.) with (Formula presented.). For the purpose of the proof, we build a semi-classical quantization procedure for finite volume manifolds with hyperbolic cusps, adapted to a geometrical class of symbols. We also prove an Egorov Lemma until Ehrenfest times on such manifolds. © 2016, Springer-Verlag Berlin Heidelberg.
Reyter D.,INRS - Institute National de la Recherche Scientifique |
Belanger D.,UQAM |
Roue L.,INRS - Institute National de la Recherche Scientifique
Journal of Hazardous Materials | Year: 2011
Ni, Cu, Cu90Ni10 and Cu70Ni30 were evaluated as cathode materials for the conversion of nitrate to nitrogen by a paired electrolysis process using an undivided flow-through electrolyzer. Firstly, corrosion measurements revealed that Ni and Cu70Ni30 electrodes have a much better corrosion resistance than Cu and Cu90Ni10 in the presence of chloride, nitrate and ammonia. Secondly, nitrate electroreduction experiments showed that the cupro-nickel electrodes are the most efficient for reducing nitrate to ammonia with a selectivity of 100%. Finally, paired electrolysis experiments confirmed the efficiency of Cu70Ni30 and Cu90Ni10 cathodes for the conversion of nitrate to nitrogen. During a typical electrolysis, the concentration of nitrate varied from 620ppm to less than 50ppm NO3- with an N2 selectivity of 100% and a mean energy consumption of 20kWh/kg NO3- (compared to ~35 and ~220kWh/kg NO3- with Cu and Ni cathodes, respectively). © 2011 Elsevier B.V.
Faghihi U.,UQAM |
Fournier-Viger P.,UQAM |
Knowledge-Based Systems | Year: 2012
To mimic human tutors and provide optimal training, a cognitive tutoring agent should be able to continuously learn from its interactions with learners. An important element that helps a tutor better understand learner's mistake is finding the causes of the learners' mistakes. In this paper, we explain how we have designed and integrated a causal learning mechanism in a cognitive agent named CELTS (Conscious Emotional Learning Tutoring System) that assists learners during learning activities. Unlike other works in cognitive agents that used Bayesian Networks to deal with causality, CELTS's causal learning mechanism is implemented using data mining algorithms that can be used with large amount of data. The integration of a causal learning mechanism within CELTS allows it to predict learners' mistakes. Experiments showed that the causal learning mechanism help CELTS improve learners' performance. © 2011 Published by Elsevier B.V.