Projets novateurs réalisés

Examining the Effectiveness of Combined Rehabilitation and Botulinum Toxin Injection on Functional Improvement of the Upper Limb after Stroke

Through a pre-post design, I will examine the impact of UL rehabilitation followed by UL rehabilitation combined with BT on arm function. Patients with stroke and spasticity are unique; thus, the effect of BT is specific and it is difficult to compare groups of subjects. Using subjects as their own control is the most suitable way to determine the effect of an intervention. I will, therefore, conduct a study on a series of subjects before and after “UL rehabilitation.” Then, using the same subjects, I will do another before and after study, but this time using “BT combined with UL rehabilitation.” In order to increase the sensitivity and accuracy of my measurements, I will utilize kinematic analysis, an advanced measurement tool to complement the clinically based outcomes. This study is innovative and will contribute to the best practice in different rehabilitation disciplines by assisting with more advanced and…………………TBC

Antioxidant capacity and anti-inflammatory bowel diseases effect of hemp seeds grown in Canada

Hemp seed is a super fruit because its bioactive compounds have antioxidant, anti-inflammatory and antibacterial capabilities. Hemp seeds have the potential as a food therapy to reduce inflammatory bowel diseases (IBD). In this project, we will collect hemp seeds from 20 hemp cultivars grown in different provinces in Canada. Antioxidant capacities of hemp seeds will be determined by using different chemical assays. Selective hemp seeds of different levels of antioxidant capacities will be used to investigate the anti-IBD effect using both in vitro “gut-on-a-chip” platform and in vivo mouse model. This study can provide the insight to the medical significance of whole hemp seeds and demonstrate its innovative applications in the agri-food industry.

Rationality problems

Algebraic geometry is the study of algebraic varieties, geometric shapes that arise as solution sets to systems of polynomial equations. Algebraic geometry is a subject of central importance in contemporary mathematics, with multiple connections to other areas, such as number theory, combinatorics, representation theory, analysis, and theoretical physics. The simplest algebraic varieties are rational varieties. Informally speaking, these are varieties that admit a parametric presentation. A solid understanding of rational varieties is important both for theoretical purposes and for applications. The question of whether a specific variety is rational can be very difficult to answer. Questions of this type are called rationality problems. In this project I propose to try to answer questions in this area. Spending a semester at Universite Paris Sud, being mentored by Professor J.-L. Colliot-Thelene, and learning from some of the leading mathematicians in the field is an exceptional and unique opportunity.

Automatic Understanding of the Semantics of Source Code For IdentifyingSensitive Code Fragments

Source code is what programmers write as instructions to the computer to execute to complete a desired task. All operating systems and applications on a computer or a mobile device is a runnable version of a compiled source code. Experienced programmers can easily browse and understand source code in different programming languages because they have the necessary technical background that is not available for every-day users. Those experienced programmers can identify parts of source code that are of interest (e.g., can make the program run 10x faster if improved) or pose a threat (e.g., if reverse-engineered can expose cleints’ personal information). With billions of lines of code available within private companies or in public code repositories, it is not scalable to ask experienced programmers to identify these parts of code. This project targets finding a way to automatically detect such parts using machine learning.

La collaboration municipalité – économie sociale en Outaouais : études de cas et transfert d’apprentissages

La région de l’Outaouais possède un fort potentiel de développement dans le secteur de l’économie sociale. Les acteurs du développement en prennent de plus en plus conscience et plusieurs cas de partenariats entre des entreprises d’économie sociale (EÉS) et certaines municipalités de la région ont vu le jour afin de réaliser ce potentiel. Notre recherche vise donc à recenser, documenter et analyser certains de ces cas à différents degrés de partenariats avec des municipalités. Nous cherchons également à comprendre comment la nouvelle loi sur les gouvernements de proximité (loi 122) encadre les relations entre les entreprises de ce secteur et les municipalités. Nous sommes intéressés, notamment, aux formes de soutien et aux possibilités que la loi permet en ce sens. TO BE CONT’D

Changing Waters: Modeling Long-Term Fluxes of Phosphorus Under Changing Climate and Land Use in the North American Great Lakes Region

Participation in Mitacs Globalink will allow me to travel to Leipzig, Germany to pursue research at the Helmholtz-Centre for Environmental Research (UFZ). I will be working there as an undergraduate researcher within the Department of Computational Hydrosystems directly under Dr. Sabine Attinger. The aim of my project will be to learn and apply their mHM model (mesoscale Hydrologic Model). This is a unique, spatially explicit, distributed hydrologic model that uses grid cells as the primary unit and accounts for hydrologic fluxes from the hourly to the daily scale. This model will allow me to apply its framework to the Great Lakes region, which will be an expansion to my previous co-op term at the University of Waterloo, where I used the ELEMeNT model to predict trajectories for stream phosphorus loading into Lake Erie. Ultimately, this project will provide the opportunity to connect and combine two successful models in order to obtain a detailed and accurate depiction of the water quality and hydrology of watersheds contributing to the Great Lakes.

WP 1.1.8 – Metro Reach Silicon Photonic Integrated Transceiver

Driven by cloud based applications and services, there are substantial worldwide research and commercialization efforts that are being directed toward improving the capacity of intra- and inter-data center networks. Intra-data center networks operate in the O-band (1260-1360 nm) over distances ranging from 0.5 m to 20 km, and inter-data center networks operate in the C-band (1530-1565 nm) over distances ranging from 20 km to 160 km. While these two systems share similar constraints in terms of power consumption, footprint, and cost of the employed optical transceivers, they are distinct because of the differing operating wavelengths (e.g., the dispersive properties of fibers in the C-band). Enabled by original silicon photonic circuit designs and innovative packaging, the proposed research will address key challenges in data center networks, namely increasing the capacity whilst decreasing the power consumption, size, and cost of optical transceivers deployed in these networks.

Fault detection and severity assessment for gearboxes

The gearbox is a classical mechanical unit and has been widely used in modern power transmission systems. Fault detection and severity assessment of gearboxes prior to their failure can prevent the sudden failure of gearboxes, as well as enable condition-based maintenance and thus reduce maintenance costs. However, the fault detection and severity assessment are challenging when the gearbox operates under time-varying rotational speed (TVRS) conditions. Unlike the constant speed condition, the condition monitoring data, e.g., vibration, becomes non-stationary due to amplitude and frequency modulations induced from TVRS. Conventional signal processing and analysis tools are no longer applicable. Advanced signal analytic algorithms are in demand. This project aims at proposing an advanced statistical time series model to globally represent the gearbox vibration signal under TVRS. Fault detection and severity assessment objectives are subsequently achieved. The hypothesis is that the time series model-based method will have an improved fault detection rate and severity assessment accuracy compared with existing methods. The result of this project will fundamentally benefit the safety, maintenance and operation of power transmission systems.

Data Analysis and Consolidation for Aircraft Parts Manufacturing

Avcorp Industries provides the world’s leading aircraft manufacturers with supply chain solutions and repair support. Yield optimization, predictive maintenance, and equipment calibration are needs that are widespread throughout the manufacturing industry. The root cause of failures in product testing is often difficult to determine particularly when the failure signals are sparse relative to the available background data. Compounding the problem, the process must meet a variety of specifications for multiple customers simultaneously. This project aims to create a digital twin of the metal finishing line to leverage predictive analytics to analyze data (chemical, temperature, voltage) captured from the process line and provide new insights for an optimized manufacturing process. Leveraging the research capabilities in data analytics at Simon Fraser University, and partnership with D-Wave and SolidStateAI, Avcorp will move manufacturing fault detection processes from reactive to predictive-based. TO BE CONT’D

Compressed Supersymmetric Spectra at the Large Hadron Collider (LHC)

With the discovery of the Higgs boson, the Standard Model (SM) is complete. Experimental results, even precision tests involving higher order perturbative quantum chromodynamics (QCD) calculations, appear to confirm SM results. However, SM cannot be the final theory, and the quest for physics beyond the SM is very much alive. Of the beyond the SM scenarios, supersymmetry (SUSY) appears to be the most popular. Unfortunately, no signals of any new model, and in particular of supersymmetry, have been observed at the Large Hadron Collider (LHC). Given that no supersymmetry signals have been observed at the LHC, and the fact that constrained theories which can explain dark matter predict no visible signals at the LHC, it would appear useful to study extended versions of minimal supersymmetric standard model (MSSM). Supersymmetric secluded U(1)’ model with 3 additional scalars and neutralinos, in addition to the usual supersymmetric U(1)’ model spectrum gives rise to many more possibilities for compressed spectrum. That is, charginos, neutralinos and sleptons and sneutrinos would be light and close by, while the rest of the particles would be heavy. TO BE CON’T

Machine-Learning-Based Artistic Photo Manipulation and Stylization on Mobile Devices

Recent advances in using machine learning for object recognition and image manipulation have resulted in a new and emerging market for mobile applications that use machine learning for creating a variety of new artistic expressions. This research will develop a framework for performing machine-learning-based photo and video manipulation on mobile devices with the goal of integrating it with the Generate Toolkit. This proposal follows previous MITACS internships between the same partners and further extends our objectives. In the previous iterations of this project, we developed a fast, on-device style transfer library for both iOS and Android systems and started developing a user-interface to train machine learning models for style transfer, facilitating the exploration of the parameter space of the models within a computer-assisted creativity paradigm. Our main objectives for this internship term involves three tasks. TO BE CONT’D

Brain Imaging Biomarkers Type 2 Diabetes and Stroke

Adult onset diabetes, or type 2 diabetes, is becoming more common in Canada and across

the world. And it is a risk factor for stroke. For example, silent strokes lesions are common in

adults with type 2 diabetes. Despite this knowledge, we do not have a very good

understanding as to how type 2 diabetes affects the brain. We are proposing 2 internships

that will make use of magnetic resonance imaging to specifically address type 2 diabetes

effects in the brain. And we are also proposing new software tools that can be used to look at

brain connections, which is applicable to studying type 2 diabetes and stroke. Intern 1 will

focus on grey matter structure and blood vessels in the brain. Intern 2 will focus on grey

matter connections in the brain. Both internships involve developing software that will

facilitate clinical translation. In so doing we will foster collaboration between the intership site

(Baycrest) and the academic site (Sunnybrook)…….TBC