Projets novateurs réalisés

Accelerate development of new technologies and applications for advanced water treatment

Global population growth, urbanization and changing climate patterns have increased the demand for potable water, wastewater reuse and value recovery from wastewater, and treatment of industrial process water. Population growth also results in increased demand for the shipping of goods by ocean freight, with the associated risk of the transport of unwanted marine life from one location to another by the discharge of ballast water. Also, the increasing sophistication of food and drug production requires a corresponding development of fluid protection technologies to prevent contamination by undesirable microbes. Consequently, there is increased demand for improved technologies that can provide sustainable treatment of water and wastewaters, protection of the water supply, and development of new fluid treatment methods. This research project will develop knowledge and technologies to allow the development of new Trojan Technologies products in these three areas. Treatment technologies to harvest energy from wastewater, treat ballast water with ultraviolet light and filtration to treat invasive species, and remove harmful bacteria from liquid foods and drug fluids, are examples of proposed outcomes of this project.

Using machine learning to investigate sympathetic activation of the autonomic nervous system during treatment of mild traumatic brain injury, chronic pain and post-traumatic stress disorder

The goal of the proposed research project is to further our understanding and clinical management of Canadian Forces service members and Veterans suffering from a complex medical triad of traumatic brain injury, chronic pain, and post-traumatic stress disorder. Over half of rehabilitation patients experience one or more of these complex medical conditions, often associated with intractable symptoms which do not respond to traditional treatment options, and impairing their ability to function effectively at work and in the community. Using a Computer Assisted Rehabilitation Environment (CAREN) this research will collect and consolidate a series of non-invasive whole-body biological measurements from patients during immersive therapy sessions in the CAREN Virtual Reality facility. High-performance computing and machine learning will be used to develop and deploy real-time estimators of sympathetic neural activation of the autonomic nervous system (SAANS). TO BE CONT’D

Non-Contact Laser-Based Vibration Sensor

The discipline of Vibrometery is wide and has many applications, vibrations are present in any mechanical system that involves moving components. So far, the main method to measure these vibrations has been the traditional accelerometer sensor, although it has its limitations and challenges.
Laser Doppler Vibrometers (LDV) were developed in order to address some of these limitations and they offer a non-contact measurement of vibrations by leveraging the Doppler shift effect. Although LDV offers superior accuracy and the benefits of non-contact measurement, this technology has been historically very expensive and not practical for rugged industrial applications.
In this project, we propose to develop an alternative sensor to LDV by utilizing the propriety technology developed by the partner company in the field of RF/photonics. The idea is to design a sensor without the expensive opto-mechanical assembly that is required by LDV. This will enable the industrial partners to commercialize this technology and develop a series of product lines for the global Vibrometery market.

Magnetorheological Fluid Actuators for various industries

Exonetik designs, develops and manufactures magnetorheological (MR) actuator systems that enable novel functionalities to satisfy unmet customer needs. In collaboration with Exonetik engineers, interns will participate in the design, development and testing of customized magnetorheological actuators for three specific applications in the automotive, manufacturing and health sectors. The expected results of these subprojects will be prototypes that will be tested to demonstrate the added value that the technology can provide.

Building Resilience into Canadian Housing

Resilience is toughness, or the ability to function and bounce back after a traumatic event. In this Mitacs research project, the focus is on housing, and resilience results from features that protect Canadian lives and property from natural disasters. One of the ways that governments ensure the safety of Canadians is through The Canada Model Building Code. The insurance industry is also committed to protecting lives and property by contributing advice about resilience in Building Code Review Committees. However, simple resilience measures advocated by the insurance industry are not being adopted in the Code. The current research aims to understand why, and to shed light on the housing industry and its involvement in code revision.

A study of owner perceptions of health and longevity in dogs and cats fed meat- or plant-based diets.

Plant-based diets have been introduced to the companion animal nutrition market, though little evidence exists to support or refute the nutritional sufficiency of plant-based diets for cats and dogs, or the impacts these diets may have on the health and wellbeing of the animals they are fed to. The proposed study aims to question pet owners regarding their perceptions of their pets’ health and longevity, with a specific comparison of plant-based and conventional diets. This will be achieved through a survey made available to pet owners with questions regarding pet health and nutrition. The partner organization will benefit from a greater understanding of their clients’ pets and pet health, improving their ability to provide appropriate nutrition to these animals.

Modeling and design improvement of a novel energy conversionprocess

The industrial partner has developed a novel system to convert low-grade heat into electricity.

However, the system needs to be studied further through scientific research to help with

optimizing the product development, component design, and overall system performance for

commercialization. In the proposed research project, the intern will use computational

modeling to understand the fundamental thermodynamic processes, for the design

optimization of the individual component and the entire system. The simulations will also be

conducted to study the scalability of the system to target different markets. The intern will use

the simulations results to design and improve prototypes for the technology demonstration,

and will conduct the performance testing of the demo unit to generate the benchmark data for

marketing and commercialization of this novel technology.

LE PLUMITIF ACCESSIBLE

La présente demande concerne le chantier de recherche sur le « plumitif accessible » lequel s’inscrit dans l’axe Connaissance et conscience du droit du projet ADAJ (Accès au droit et à la justice) financé par le Conseil de recherche en sciences humaines (CRSH) en partenariat. En effet comprendre le contenu des plumitifs est un défi important. Au Québec, toute personne peut obtenir accès aux plumitifs relatifs à une instance civile ou criminelle. Il s’agit d’informations à caractère public. L’information disponible dans les plumitifs est aride et fragmentaire. Encore aujourd’hui, les plumitifs sont essentiellement consultés par des professionnels du droit, des personnes travaillant à l’administration de la justice ou des personnes faisant de la vérification d’antécédents judiciaires. TO BE CONT’D

2017 Neighbourhood Small Grants Program Evaluation

The 2017 Neighbourhood Small Grants Program Evaluation will deepen understanding of grassroots grant making through an analysis of program outcomes and participant feedback from the Vancouver Foundation’s 2017 Neighbourhood Small Grants (NSG) program. Using data collected by the Vancouver Foundation, the project intern will produce a report that highlights the outcomes, opportunities, challenges, and lessons learned from the program activities of the 2017 granting year of the NSG. The report will also compare the findings of the survey responses with similar academic research on community and neighbourhood development. Additionally, there will be a special focus on the impact and challenges of NSG projects incorporating arts and culture. This research will be publically available, supporting Vancouver Foundations’ ongoing delivery of the NSG program, and building capacity for other municipalities and institutions to design and implement grassroots grant making programs in their communities.

Talent Migration for Innovation & Growth: Case of Israel

This project examines how technology firms in Tel Aviv and Haifa, Israel attract and retain migrants with skills in science, technology, engineering, and mathematics (STEM). Israel strongly depends on its innovative technology firms; however, there is a growing awareness that Israel’s economy and innovativeness could lose momentum due to job shortages in the STEM sector. By conducting research on how sub-state entities, clusters, and technology firms navigate and influence a relatively rigid migration policy in Israel, this project seeks to gain insight into ‘best practices’ and hurdles in international talent mobility in Israel with the goal of providing actionable policy recommendations to better enhance high-skilled migration policies. TO BE CONT’D

Théorie PAC-Bayésienne pour l’apprentissage de réseaux de neurones profonds

De nos jours, l’analyse des données est au coeur de plusieurs nouvelles technologies, surtout avec l’arrivée de l’ère du « big data » et l’essor du « deep learning ». En effet, les réseaux de neurones profonds appliqués à des données massives révolutionnent certains domaines comme la vision, le traitement de la langue naturelle et la bioinformatique. Cependant, la compréhension théorique des performances de ces méthodes ne parvient pas encore à expliquer leurs accomplissements empiriques. Le présent projet vise à exploiter la théorie PAC-Bayésienne afin de mieux comprendre d’un point de vue théorique l’apprentissage profond. Le PAC-Bayes permet d’obtenir des garanties statistiques pour des algorithmes d’apprentissage automatique pouvant être exploitées durant le processus d’apprentissage. Ainsi, le développement d’outils théoriques permettra de faciliter l’exploitation des réseaux de neurones profonds et de guider les développements futurs dans ce domaine.

Commande non linéaire d’un robot parallèle à câbles dédié à la réadaptation des membres inférieurs

L’utilisation de systèmes robotiques en réadaptation médicale présente un certain nombre d’avantages par rapport à la thérapie traditionnelle, tels qu’une bonne répétabilité de mouvement, une assistance contrôlable avec précision pendant les mouvements et des mesures de performance quantifiables. Récemment, une nouvelle classe de systèmes robotiques, appelés robots parallèles à câbles, a été introduite dans le domaine de la réadaptation médicale. Dans de tels mécanismes, l’effecteur est entraîné directement par des câbles au lieu de liaisons rigides. L’étape la plus difficile et cruciale dans le développement des robots à câbles est la mise en œuvre d’un algorithme de commande qui rend le dispositif utile.
L’objectif de ce projet est de concevoir un contrôleur non linéaire pour le suivi de trajectoire d’un robot parallèle à câbles dédié à la réadaptation des membres inférieurs humains. TO BE CONT’D