Projets novateurs réalisés

Examining the barriers and facilitators to trauma registry sustainability in the Global South

Injury is a leading cause of death and disability world-wide, however rates are especially high for low- and middle-income countries (LMICs). Trauma registries— databases that document information on the injured patient related to the injury event, demographics, process of care, and outcome— are commonly used in high-income countries and have proven extremely effective in reducing rates of death and disability through informing injury prevention and quality improvement programs. Their use in LMICs is less common due to the financial and human resource constraints of hospitals in many of these settings. In recent years, innovative strategies have been used to overcome some of these constraints. The purpose of this project is to examine both the barriers and strategies that facilitate trauma registry sustainability—with a specific focus on the use of m-health technologies—to create a resource toolkit that can be used to improve how trauma registries are implemented and operated in the global south.

Active Vision in Robotics for Optimal Mobile Camera Sensor Planning

Active vision or perception is one that can manipulate the viewpoint of the cameras in order to investigate the environment, and get better information from it. It mostly encourages the idea of moving a visual sensor to constrain interpretation of its environment. This research in active vision is concerned with determining the 3D pose and configuration for visual sensor, it plays an important role in by purposefully configuring and placing the visual sensor at several positions to observe a target, obtain the optimal quality of data as the input of objection detection and pose estimation technologies.

Rénovation urbaine et gentrification à Rio de Janeiro

Le présent projet porte sur l’action des mouvements sociaux luttant pour le droit au logement à et la ville à Rio de Janeiro, en particulier autour des enjeux de la gentrification, de la revitalisation urbaine et des évictions en tenant compte des dimensions territoriales du système d’éducation. Ce projet me permettra de connaître davantage la situation brésilienne autour des questions de logement et de sociologie urbaine, en particulier sur les enjeux de la gentrification. La question qui oriente notre projet est la suivante : comment se construit l’action des mouvements sociaux, luttant pour le droit au logement à et la ville à Rio de Janeiro, autour des enjeux de la gentrification, de la revitalisation urbaine et des évictions? Nos objectifs dans ce projet sont doubles. Dans un premier temps, nous souhaitons comprendre à la fois le phénomène de la gentrification à Rio de Janeiro et comment s’organise la lutte contre celle-ci pour y ressortir les liens avec le développement territorial et le système d’éducation. Dans un deuxième temps, et parce que nous travaillons sur ce sujet à Montréal au sein du Collectif de recherche et d’action sur l’habitat, nous cherchons à comparer ces phénomènes entre ces TO BE CON’T

Noise reduction, dereverberation and binary neural networks for improved automatic speech recognition

Technologies using vocal commands are very useful in situations where hands cannot be used (e.g. wearing gloves or in factory settings to operate complex machines). The performance of automatic speech recognition systems decreases significantly in the presence of noise or reverberation (i.e. echoes on objects and walls). This projects aims at improving the performance of our partner’s automatic speech to intent recognition (ASIR) system by reducing environmental noise and reverberation. We will reduce noise by separating speech signals from noise signals, exploiting their independence. We will also develop signal processing methods to reduce the reverberation that distorts speech signals in a room. Our partner’s system must function without any internet connection and must also minimise its energy consumption. For this purpose, we will develop binary neural networks for ASIR. The methods developed will be integrated into a single system that will be designed to be optimized globally.

Development of an Unmanned Glider for Autonomous Soaring

We will develop an algorithm for a small unmanned glider (a plane-shaped drone) to soar autonomously. Gliders gain energy from the atmosphere by flying in circles in streams of rising air, called thermals. This allows them to stay aloft for extended periods of time, in the range of several hours. Detecting thermals, as well as harvesting energy from them, with an automatic pilot, is the challenge that we are tackling in this work. We will write the program, as well as test it, both in a flight simulator and in the field (with a remote-controlled drone, flying autonomously). The partner organization builds glider-based autopilot solutions for the purpose of monitoring large and remote areas such as forests and fields, hence the need for a reliable thermalling flight controller.

Investigation of Bicycle Traffic Flow Parameters

Bicycle and pedestrian counts are important data for the planning and design of safe roads. However, installing pedestrian and bicycle counters across an entire city road network is not financially viable. Therefore, a good option is to estimate counts at the network scale, using knowledge from a handful of pedestrian and bicycle counters (strategically placed) and trip data from users who willingly share their position from their smartphones.
Eco-Counter, the partner organization, is a world leader is the development of automated pedestrian and cyclist counting systems. The company is expanding into data services and requires additional tools and methods to help their clients (transportation agencies) manage and visualize their data. This project will help Eco-Counter achieve this objective.

Phase-field crystal modeling of the interplay between nanostructure changes and ion transport in lithium-ion battery electrodes

The focus of my research is modelling graphene-hBN (graphene-hexagonal-boron nitride), a novel two-dimensional ceramic with the ability to allow for the measurement of both plastic and elastic strain. Mixing graphene with hBN augments the properties of the ceramic by making it stronger and more versatile. When exposed to an elastic strain, the ceramic will exhibit higher conductivity, but under plastic strain, it loses conductivity. Due its exceptional chemical and thermal stability, graphene-hBN is considered a material of the future, sometimes called the “miracle material” due to its exceptional mechanical and electric properties. For example, it can be used in a wide range of applications from reinforcing structures such as alloys, steel and plastics, to, due its excellent electric properties, electronics (in particular sensors under biological and chemical conditions and in quantum dot devices).

Computational modeling offers a versatile approach to investigate the properties of this new promising material. In this study we develop a new model to study phase transformations and morphological changes in graphene-hBN. The so-called phase-field crystal (PFC) method is used as the basis. TO BE CON’T

Les microplastiques et contaminants associés dans l’estuaire et le golfe du Saint-Laurent : caractérisation environnementale, sociale et bioaccumulation ou dépuration chez les bivalves

Ce projet propose de définir les enjeux socio-environnementaux et socio-économiques reliés à la présence de microplastiques (MP) marins dans l’estuaire et le golfe du Saint-Laurent, une région hydrologique complexe sous-étudiée vis-à-vis cette problématique. Ceci permettra d’orienter les décisions visant à protéger l’environnement tout en soutenant les secteurs maritimes, notamment ceux reliés aux ressources marines commerciales. Ainsi, ce projet intersectoriel, multipartenaire et innovant a pour but d’étudier :
• L’abondance et la diversité des MP et de certains autres contaminants associés dans l’eau et chez deux espèces sentinelles de mollusques;
• La représentation sociale qu’ont les populations littorales à ce sujet.
Ce projet propose donc de déterminer les bases de cette problématique afin de soumettre, avec l’implication des communautés côtières, de nouveaux projets et des solutions intersectorielles pour mieux comprendre les effets environnementaux des MP et pérenniser l’industrie de la pêche, de l’aquaculture et de la transformation des produits marins au Québec

Application of Real-time Axis-based SLAM in Geotechnical Engineering

Mining operations evaluate tunnel stability by looking at orientations of exposed rock faces and extrapolating the underlying rock formation. The most widespread and traditional method for determining these characteristics involve hand measurements with static tools. This process is both time intensive and prone to error. Additionally, it may be dangerous to measure rock faces that are hard to reach. The goal of this project is to implement a novel algorithm that can quickly and automatically determine sets of parallel rock faces and their orientations. This research will help successfully develop the RockMass Mapper which will be the company’s flagship product and is scheduled to launch in early 2020. The mining economy contributes to nearly 20% of Canada’s GDP and RockMass’s solution will improve the overall impact the mining industry will have on Canada’s economy while also improving the working conditions of those involved.

An investigation of consensus and performance in distributed systems

Within a tiered or zoned architecture, new business constraints for regional data residency, imply a need for new architectural patterns. These constraints are not arbitrary: they arise directly from customers demand to ensure their confidential data stays within their defined borders unless required otherwise (e.g. data originating in the U.S. is intended for an E.U. entity). An architecturally clean approach is to negotiate the movement of data only at the persistence layer. The objective is to review the industry landscape for suitable replacements or to otherwise alter the existing design to facilitate the replication of data based on these requirements. Specific targets for consistency latency (with defined upper bounds) and parity performance for read and write rates must be met. Parity performance is measured via msg/s and is achieved if the modified/replacement system has at least the same performance profile (average, median, and 99% percentile) as the existing system.

Measurement of Surface Adhesion using Non-Contact Atomic Force Microscopy

Surface energy is a critical parameter in determining the frictional energy dissipation that occurs when two surfaces slide across each other. In this project, the influence of single atomic layers of lubricants will be placed on metallic surfaces and the impact on surface energy will be measured using non-contact atomic force microscopy. In previous studies conducted at the University of Calgary, it has been calculated that traditional methods of determining surface energy, such as through pull-off experiments and water contact angle experiments, will not provide the required accuracy and precision that is necessary to detect the change in surface energy that occurs when one atomic layer of lubricant is used, compared with two atomic layers of the lubricant. Through this collaboration, we expect to gain access to instruments that will be capable of measuring surface energy with the required precision and accuracy.

A General Approach to Interpret and Explain a Deep Neural Network Model

Deep neural networks have demonstrated state-of-the-art modeling accuracy on a wide range of real-life problems, with some cases surpassing human performance. Despite the promise of deep neural networks as an enabling technology for a large number of industries and fields, there are two particular key challenges in the design of deep neural networks in real-world, operational scenarios. First, the design of deep neural networks is a very time consuming process for a machine learning expert, and often results in complex, non-optimal deep neural networks. Secondly, many of the deep neural networks designed in recent years, while achieving high accuracy, are often very complex with high millions to billions of parameters, making such networks intractable for real-time scenarios on mobile device, IoT devices, and other embedded devices. TO BE CONT’D