Projets novateurs réalisés

Development of a helmet grading system based on linear and rotational acceleration

Helmets are currently tested and certified based on appropriate standards using a pass/fail criteria. All helmets that are available in the market have passed this standard testing. Unfortunately, the pass/fail threshold is well above known head injury threshold. Other than by comparing the price, consumers do not have a quantitative way to determine whether one helmet is better than another. In this project, a user-friendly helmet grading system will be developed for different types of helmet. The grading system takes into account different aspects of impact such as peak and duration of measured acceleration pulse. Shield-X Technology Inc. has been looking for such comprehensive helmet grading system to evaluate their products. The grading system will also help Shield-X with its product development and communications with the third party companies in regards to how well its technologies enhance helmet performanc

An Evaluation of the Reliability of Forensic Case Formulation in the Risk Assessment of Intimate Partner Violence

Intimate partner violence (IPV), also known as spousal assault and domestic violence, is the most common form of violence experienced by women worldwide. Fortunately, IPV risk assessment tools, training, and practices have improved immensely over the last 20 years. One of the areas that can still be improved is training those using violence risk assessments for evaluations to better understand the root causes of violence at the individual level. The process of determining root causes of violence is an advanced skill now considered necessary for the comprehensive assessment of violence risk and determining risk management strategies. This study will develop and test a training program to improve aspects of risk assessment training and increase the utility of the training process. Improving the training around the root causes of violence within risk assessment is one of the last frontiers to improving risk assessment practices and training and ultimately reducing the incidence of IPV.

Probabilistic Image Generation from Layout

Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object
layouts is still a difficult problem. Among the core challenges are the diversity of appearance a given object may possess and, as
a result, exponential set of images consistent with a specified layout. In this project, we propose to address these challenges by a
probabilistic generative model, which can generate a set of realistic images by giving the coarse spatial layout (bounding boxes +
object categories). To further increase the controllability of the image generation, attributes or textual description of each object in
the layout may also be provided. A probabilistic generative model will be designed to better model the uncertainty the target
image. It will compose distributions based on given information and decodes samples from these distributions into realistic
images. The expected outcomes include the source code of the proposed model, one research paper to be published at a top-tier
international conference or journal, and one patent of the proposed algorithm.

Design and Exploration of a General Purpose Stochastic Computing Processor

The rise of Internet of Things (IoT) with millions of edge devices created per year drives the need for computing platforms that have lower power, better fault tolerance and greater computing flexibility. With more and more novel applications and algorithms being rapidly deployed, the traditional approach of using custom hardware to achieve a low power budget will not scale. This project explores the design of an ultra low power, fault tolerant stochastic computing general purpose processor that satisfies the key metrics that IoT edge devices care about while being able to support the rapid shift in applications. Not only will the realization of a stochastic general purpose processor be able to maintain a low power envelope and be resilient through bit-flip errors, stochastic computing’s ability to provide progressive precision (i.e. compute results that start as a rough approximation and become more accurate over time) is often a desirable property for many of the applications in this space (e.g. machine learning).

Day and night location planning for general practitioners

Primary care plays a vital role in the health care system. Challenges in accessing primary care is a growing area of concern globally, with demonstrated negative patient and health system outcomes. Patient and physician preferences for both location and daytime/afterhours access differ. Determining the location of primary care practices that meet the needs of both patients and physicians is a complex optimization problem with multiple criteria.

The specific objectives of the project are to develop a framework to measure and evaluate how well primary care practices cover a population. This will be considered from the physician and patient perspectives and differentiated by daytime versus afterhours needs. Using this framework, we will develop an Operations Research model to recommend an optimal practice network.

The proposed research builds upon collaborations between Dalhousie University and KIT. This project will support applied case studies based on German and Nova Scotia primary care networks.

Optimal spatial movement strategies in foraging among free-ranging Japanese macaques (Macaca fuscata)

Choices allow us to navigate through physical space, to literally or figuratively problem-solve, to achieve goals. While this behavioural phenomenon is common across time and space for our human species, many other species make movement choices as well. The objective of my research is to assess how individual and social factors influence route choice decisions in foraging within a group of free-ranging Japanese macaques (Macaca fuscata). Specifically, I will explore how factors such as life-stage, sex, physical disability, and/or competition impact individual decision-making in a foraging experiment. This study promises to positively contribute to the gap in knowledge surrounding motivations underlying optimal route strategies adopted by Japanese macaques, as well as, providing insight into individual variation and compensatory behaviours adopted in foraging strategies.

Pharmacological properties of selective MT1 receptor partial agonists in an animal model of bipolar disorder.

Preliminary data suggest a possible involvement of the melatonin MT1 but not MT2 receptor in the pathophysiology of bipolar disorder. The main objective of this short project is therefore to investigate at preclinical level whether the first selective MT1 receptor partial agonist to be synthesized (UCM871) can improve the bipolar symptomatology of the mice genetically modified for the Clock gene. This genetically modified mouse model is the one that today best represents the human bipolar pathology in mice. Furthermore, we will start to explore the possible neuronal mechanism of action of the novel drugs. For this purpose, we will use behavioral pharmacology tests that will allow us to evaluate the pharmacological effects of the novel drug on symptoms of mania measured as increased locomotor activity in the open field test. TO BE CONT’D

Using fractal analysis to determine if physical impairment in Japanese macaques (Macaca fuscata) reduces behavioural movement complexity

Free ranging and wild animals sometimes experience challenges of physical wellbeing and optimal movement ability, but assessing if they are stressed in these situations can prove difficult. My research will be focusing on a population of Japanese macaques on Awaji Island, Japan that are born with very high incidences of limb malformations that cause physical impairment. This circumstance provides a rare opportunity to observe behavioural responses to disabilities. Previous work suggests that disabled individuals in the population spend a similar amount of time engaged in locomotion compared to non-disabled individuals since they live within social groups. However, fully understanding and quantifying the costs of these disabilities remains a challenge. Fractal Analysis is a non-invasive method for quantifying subtle variations in the complexity of movement behaviour patterns and sequences. Using Fractal Analysis, I plan to test the hypothesis that impairment caused by congenital limb malformations will alter the complexity of movement behaviours for disabled monkeys under free-ranging conditions; either becoming more stereotypical or conversely more random in their behaviour patterns. This research will potentially reveal whether animals are experiencing subtle difficulties without disturbing them in their natural environments.

Variational integrator for the RSW equation on the sphere under local uncertainty

Numerical simulation is a cornerstone of modern science and industry, and is used in many facets of our everyday lives. While many of us are familiar with short-term weather forecasting, substantially more computational effort is dedicated to longer-term simulations of the Earth’s ocean and atmosphere, for climate and other reasons. In such simulations, certain properties of the physical system, such as conservation of mass and energy, are critical to achieving physical fidelity, and much research effort has been devoted to developing simulation algorithms that preserve these and other properties, known as variational or geometric numerical integrators. During my stay, I will work with Drs. Werner Bauer and Etienne Mémin on the development of a stochastic variational integrator on refined grids for the rotating shallow water equations on the sphere. TO BE CONT’D

Production d’un extrait riche en antioxydants à partir de la complémentarité et de la synergie des petits fruits par cryoconcentration et évaluation du potentiel antioxydant

L’objectif principal de ce projet est d’évaluer l’effet de la

cryoconcentration pour la production d’un extrait riche en molécules antioxydantes

à partir des petits fruits de la région du Lac-St-Jean. Ces études

auront permis d’ouvrir la voie à des projets industriels en vue de valoriser les

petits fruits produits de la région. Une analyse de la capacité anti-oxydante des

extraits permettrait de vérifier si l’activité des molécules bioactives est préservée

plus longtemps au cours de la cryoconcentration et l’entreposage. De plus, une

analyse portera sur l’étude de la stabilité des différents composés au cours de

réhydratation des extraits. Pour ces travaux, il serait intéressant, pour Opti-bleu,

de développer des nouveaux produits à haute teneur en antioxydant et de

pouvoir valider l’efficacité des extraits afin d’obtenir une homologation des

molécules bioactifs d’origine végétale auprès d’organismes tel que Santé

Canada.

Storm Shelters Resilient to Changing Canadian Climate

The recent tornado that hit the Ottawa-Gatineau region in September 2018 damaged hundreds of homes and many hydro poles/towers leaving more than 450K customers without power. In Canada, the average annual loss due to local events (i.e. thunderstorms, tornados and downbursts) is in the order of $200M. The number of these extreme local events has been increasing during the past three (3) decades due to climate change and is expected to continue increasing. The storm shelter industry in the United States has progressed in terms of addressing hurricane and tornado winds, but this is not the case in Canada. Most available shelters in the US are not designed to withstand the Canadian climate (i.e. extreme temperature variation), require heavy construction and/or costly transportation and are not multi-purpose. The proposed research project focuses on designing an affordable, easy-to-transport/install storm shelter suitable for local storms in Canada. The shelter is inspired by the “bunkie” concept. The design relies on conducting Computational Fluid Dynamic simulations to identify a potential shelter solution(s), which will be tested at Ryerson University’s wind tunnel for further validation and evaluation of the maximum wind speed the shelter can withstand.

Nano Processing Technique for Flexible Electronics

Conductive polymer nanocomposites have become increasingly popular due to the combined flexibility and low cost. The presence of a conductive filler network, which is reconfigurable by applied strain, can be used in sensors. The materials to be developed are ideal for the biomedical field and wearable electronics where flexible non-invasive devices can be worn outside the body to monitor vitals such as heartrate and movement. This research is to tailor the phase morphology, electrical conductivity, and the piezoresistivity of polymer nanocomposites. To fabricate the smart materials, thermoplastic polyurethane and high-density polyethylene are mixed with nanoparticles (e.g., carbon nanotubes or silver nanowires) using various nanostructuring techniques to ensure a reconfigurable conductive networks can developed in the polymer matrices, which can be porous or non-porous. This material could have a substantial impact on many industries such as smart electronics and textiles, which could see these sensors embedded in clothing and biomedical devices.