Innovative Projects Realized

Infrared imager

This project will develop the enabling technologies for next generation infrared sensors. Although infrared imaging was

historically developed for military applications, the biggest opportunities for growth are in commercial markets. Infrared

imaging is recognized as an important green technology because of its numerous applications in environmental

monitoring, thermography, process control, and inspection and maintenance of industrial equipment. Commercial vision

applications include surveillance, automotive and maritime safety, and fire?fighting. The proposed project represents an

important opportunity for Canada to contribute to these areas or growing importance. The main technical hurdles

addressed in this project include the development wafer?level vacuum packaging of microbolometers, low?temperature

3D?integration with electronics, cost?efficient deposition of high quality temperature sensitive thin film structures, and

optical efficiency. This project is in collaboration with Teledyne DALSA, developers of advanced imaging and semiconductor

technologies, with the Université de Sherbrooke and the École Polytechnique de Montréal.

Automatic weld seam positioning on sheet metal enclosures by semi-supervised deep learning

Deep learning in computer vision has set new standards in mobile and web-based applications. The power of learning-based computer vision has also tremendous potential in machine vision. Traditionally, machine vision in manufacturing employs analytic solutions often resulting in excellent accuracy but poor robustness. The goal of this project is to increase robustness of a vision-based measurement process in sheet metal manufacturing using deep learning. The ability to accommodate variations in manufacturing enables a manufacturer to provide customized solutions in a more time efficient and cost effective way. One of the major challenges in machine vision is the lack of appropriate large-size training data for supervised learning. This project will train a deep learning algorithm based on all kind of data including expert-labelled images, existing results of a machine vision algorithm and unlabeled images. The project is to provide an effective solution for the industrial partner and general research results.

Développement de surfaces aluminium superhydrophobes antibactériennes par procédés plasma

Les surfaces sont exposées au dépôt de divers type de bactéries présents dans leur environnement favorisant par la suite la contamination de la surface. Ceci défini un problème majeur dans divers domaines comme par exemple la diminution des rendements dans les industries agro-alimentaires, pharmaceutiques ce qui a contribué à l’augmentation des coûts de production. Les infections associées aux soins de santé (IAS) aussi sont causées par une grande variété de bactéries, de champignons et de virus pendant les traitements médicaux dans les milieux de soins de santé. Le traitement des IAS est devenu plus difficile et couteux compte tenu de l’augmentation de la résistance antimicrobienne via à vis des antibiotiques. En effet, plus de 50 % des IAS sont causées par des bactéries résistantes à au moins un type d’antibiotique.

De nombreuses méthodes ont été inventées pour faire face aux problèmes de l’adhésion des micro-organismes. Cependant ces méthodes sont souvent limitées dans leur application vu l’utilisation des agents nocive pour l’environnement et l’inefficacité d’application sur les grandes surfaces.

Une solution intéressante qui pourrait empêcher l’adhésion des bactéries, est de développer des surfaces superhydrophobes (non-mouillables) dans lesquels les agents antibactériens seront incorporés.

Accelerated detection and classification for surveillance applications

Object detection and classification for surveillance applications via deep neural networks have attracted a lot of interests in computer vision (CV) communities. Accurate and fast CV algorithms can alleviate intensive manual labour and reduce human errors due to fatigue and distraction. In detection problem, the aim is to determine bounding boxes which contain interested objects and classify the category of the detected object. Thus, the detection problem can be formulated as a regression problem to localize multiple objects within a frame. Due to very limited computational budgets on the edge devices, server-side solutions like YOLO and R-CNN are not suitable for embedded devices or high-throughput applications that scale to thousands of cameras. It is challenging to achieve real-time object detection performance while maintaining high accuracy. In this research proposal, we focus on reducing computation latency by developing models with a smaller number of trainable parameters to accelerate object detection and classification. First, we take the advantage of the depth separable convolution layer which has less model complexity. Second, we consider hierarchical processing units to localize multiple objects in one-time forward pass of the neural network.

Transfert d’expertises liées à l’étude de l’embryogénèse et de la valvulogénèse chez la souris.

Avant de débuter mon doctorat sur des modèles animaux de valvulopathies au sein de l’institut du thorax de Nantes, je souhaite partir 12 semaines à l’institut de cardiologie de Montréal afin de développer des compétences en termes de dissection embryonnaire et de caractérisation des embryons par méthode de double hybride. En effet, j’aurai l’occasion lors de ma thèse de travailler sur un modèle de rat de prolapsus valvulaire mitral. La pathologie est congénitale, néanmoins la dissection des embryons et des coussins valvulaires ainsi que leur étude est bien délicate et non maitrisée au sein de l’insititut du thorax de Nantes. De plus, le protocole de double hybride afin d’investiguer les acteurs du développement de pathologies valvulaires n’est pas développée à Nantes. La mise au point de ces protocoles est un processus long et coûteux. L’équipe avec laquelle je souhaite collaborer à Montréal disposera des embryons afin de développer ces protocoles de début Janvier 2020 à Mars 2020. Il est donc primordial pour moi de partir à la recherche de ces expertises afin de les développer sur Nantes à mon retour.

Antimicrobial Coatings Development

Copper-based antimicrobial coatings could play a significant role in reducing infections in hospitals and care facilities, reducing spoilage in consumer appliances, and reducing fouling on the hulls of ships. In this project, the development of copper-based coatings will be pursued for a wide variety of surfaces using paints and other advanced coating technologies. The chemical and physical properties of the coatings will be characterized and improved to minimize costs while maintaining effective killing of bacteria and fungi. With this information, the project partner will be able to continue advancing towards commercialization of a coatings industry for achieving the various antimicrobial goals.

Reducing Greenhouse Gas Emissions Through Calcium Looping CO2 Capture

Global warming and climate change have been increasingly attracting the attention of researchers and the public in the past few decades. It is believed in the scientific community that climate change is a direct effect of the increase of greenhouse gases (GHGs) in the atmosphere. Carbon capture and sequestration (CCS) is a promising solution for reduction of greenhouse gas emissions. One promising methodology for capturing CO2 is calcium looping (CaL). Lime (CaO) is a solid material that has the ability to capture CO2 to produce limestone (CaCO3) and a clean gas stream. The clean gas stream will then be released into the atmosphere with minimal environmental impact, and the limestone will be heated to high temperatures to produce pure CO2 and lime. Modeling the calcium looping process provides insight for industrialization of this process without the difficulties of experimental methods. Research will be conducted in an attempt to better understand calcium looping and overcome the challenges associated with this process.

Understanding the Rise of the Asian Multinational Corporations: Organizational Competence and Innovativeness in Business Culture

Asian multinational corporations (MNCs) have been a primary driver of the world region’s economic rise. Their emergence brings fresh air and new challenges to the global economic order. Key to their success is a distinct form of business culture and organizational strategy, which the existing scholarship has yet to address. This project aims to develop a theoretical model to understand and explain this critical infrastructural dimension of Asian MNCs. This understanding is crucial as the Canadian businesses continue to compete and collaborate with said firms at home and abroad. The project contributes to a wide range of ongoing initiatives of Canada-Asia engagement at the Cansbridge Fellowship Foundation. Through multi-site field research, we will add a new transnational, real-world perspective to the Cansbridge’s intellectual outlook. The project will also contribute raw data to the Cansbridge database on Asian MNCs’ organizational behavior and business cultures, which will be made available to the Canadian business community.

Real-time Modeling of Virtual Synchronous Generator Type VSC Converters for Power Supply to Offshore Platforms

The voltage source converter VSC mimicking the behavior of a synchronous machine provides many advantages for grid operation. This “virtual synchronous generator (VSG)” will be implemented as a real-time simulator model on the RTDS simulator and used to investigate several operating scenarios.
The VS G behaves like a synchronous machine, which is one of the most widely used components of the legacy power system, and so it is well understood. The VSG can provide inertia and damping to the network. Particularly when the ac system is weak, frequency oscillations can be minimized with this approach. Also the VSG is versatile- it can function in the grid-connected mode and also islanding mode without a controller structure change. The VSG can also achieve power sharing between different VSC without communication link.
Several operating scenarios will be simulated. First, one single VSC is connect to the grid. And then the simulated system will expand to two or more VSCs to investigate their parallel operation. Both normal steady state operation and abnormal fault conditions will be tested. Besides, the VSC with VSG controller will be investigated as a synchronous compensator to provide reactive power support to the LCC-HVDC station…

Development of New Chromophores for Soil Detection on Surgical Instruments (part 2)

Small surgical instruments can be used multiple times if cleaned properly after each surgery. At the end of the cleaning process, a visual inspection of each instrument is performed in order to detect any traces of soil such as blood, tissue or any other biological materials. However, the human eye is not a flawless sensor and soils that are not visible to the naked can be present. The objective of this project is to develop new chromophores that could bind selectively to biological materials and emit light in a specific region of the electromagnetic spectrum, allowing quantitative analysis of the soil in an ambient environment without the need for complex setups that are difficult to operate. This technology will give STERIS a significant edge over the competition as no other reliable method for quantitative analysis has been commercialized yet. The results obtained in the first phase of this project are highly encouranging, but improvement still need to be done to make these molecules even more water-sluble to ensure an organic solvent-free process.

Enhancements/Tools for an Intelligent Voice-Centric Application

For educational voice?centric applications on computer and electronic devices, the proposed project

aims to investigate methodologies and tools to support collaborative production environments. The

company is developing proprietary collaborative production methods to support high quality ondemand

content for mobile applications at a fraction of the cost of traditional models. A key research

question for this voice? and language?centric application is: what methods and tools should be used

to streamline the animation production process for animators collaborating on 2D animations using

shared characters and resources? The main area of investigation is build an integrated tool for lipsyncing

in a 2D character environment – something that currently does not exist to the level of

sophistication as being proposed. The research project will also investigate the development of a

speech engine specialized for educational mobile applications and specific collaborative production

environment. This applied research is strategic and beneficial to the partner organizataion for being

cost effective while increasing creativity and quality.

Automatic Verification of Comparators and Hash Functions

The implementation of data structures usually requires checking for certain mathematical properties such as equality. Those properties are usually implemented in methods that reason about the objects stored in these data structures. However, the implementation of such methods is fairly complex, and may exhibit software bugs that may not necessarily lead to program crashes. Therefore, it is often hard to reproduce such bugs. This project aims at developing an automatic method that verifies the correctness of the implementation of such methods, without the need to reproduce the bugs that may result from incorrect implementations. Our focus will be comparators and hash functions as prime examples of such methods that check for mathematical properties.