Projets novateurs réalisés

Building on Assets and Strengthening Roots: A Netnography of Development, Implementation, and Effects of a Cross-Border, Online Biliteracy Curriculum

This innovative investigation into cross-border, online biliteracy curriculum is a timely response to Canada’s two major future challenge areas, namely, how to leverage emerging technologies to benefit Canadians and what knowledge to produce for Canada to thrive in an interconnected, evolving global landscape. Led by experienced researchers in the areas of cross-border literacy curriculum and online literacy learning programs, the current project seeks to develop and implement a cross-border, online biliteracy curriculum to build on the respective linguistic and cultural strengths of Heritage Language Learners in Canada and Chinese Mandarin Language Learners in China and create a social networking space for them to navigate multiple linguistic and cultural worlds. The project is also designed to investigate the effects of this asset-oriented biliteracy curriculum upon learners’ literacy and identity options (i.e., possibilities for learners to acquire receptive and expressive literacy skills and form notions of self in and through these literacies).

Preservation and Recovery of the Proteome: A Clue to Investigate Ancient and Archived Samples

Proteins make up a large part of every organism, comprising a significant portion of teeth, hair, bone, tissue, and horn. The composition of proteins is highly variable, and these differences cause the physical differences between, species, populations, and individuals and give rise to many of the pathologies that can affect organisms. Studying proteins and their differences can elucidate species identity, relationships between individuals, and characteristics of disease. Expanding this examination to include aged and ancient specimens can extend these investigations through time, giving insights into dynamic change and evolution. Understanding the effects of degradation on the quality and quantity of ancient samples is key to obtaining sufficient proteins. This study will compare and optimize various methods for the extraction and preparation of proteins for proteomic analysis of ancient bone, tissue, hair and blood residue through a range of ages. In addition to these ancient samples, archived biomedical specimens will also be analyzed. These biomedical specimens will also vary in age and manner of preservation. The proteomic analysis of the biomedical specimens could assist in understanding disease and its inheritance to be continued…

Étude computationnelle sur l’Interface solide-solide entre différents électrolytes solides pour le développement de nouvelles batteries Li-ion

Mon projet consiste à explorer l’interface entre électrode et électrolyte solide pour le développement des batteries lithium-ion tout solide en utilisant la DFT (chimie computationnelle). La batterie aux ions lithium est le système de stockage d’énergie le plus prometteur qui puisse être couplé aux énergies renouvelables. Néanmoins, la présence de solvants inflammables dans l’électrolyte liquide dans ces batteries n’est pas sécuritaire. Les électrolytes solides (ES) sont l’alternative la plus intéressante aux électrolytes liquides car ils sont très stables à haute température. Cependant, ils possèdent une conductivité trop basse du lithium et surtout de nombreux problèmes à l’interface avec la majorité des électrodes. J’ai l’intention d’utiliser la DFT pour simuler l’interface entre une électrode et un ES afin de trouver la cause de cette instabilité. Le calcul DFT est un outil indispensable qui va aussi me permettre de couvrir une large gamme de matériaux et de trouver le couple électrode/ES le plus stable possible à tester en batterie.

Mechanisms of the relationship between ageing and dementia.

As our population ages, the burden of dementia is growing. Alzheimer’s disease (AD) is the most common cause of dementia; currently we do not have any disease-modifying treatments for AD. There is motivation to better understand the mechanisms of AD development and expression to control the burden of disease.

Frailty is related to neuropathological features of AD (i.e. plaques and tangles) and clinical dementia. Frailty and AD-type dementia share many risk factors and clinical features. We aim to to understand the relationship between neuropathological changes in AD and dementia expression, by taking frailty into account.

To accomplish this, we will examine how the relationship between traditional AD neuropathology and cognition differs over levels of frailty, investigate whether combining neuropathological markers could improve our understanding of this relationship, and observe how cognition and frailty change over time in relation to each other and neuropathology.
This approach creates opportunity for new prevention and treatment of dementia.

Caractérisation du rôle de la protéine précoce immédiate 1 dans l’intégration chromosomique des herpèsvirus humains de type 6A/B

L’herpèsvirus humain 6B (HHV-6B), virus de la roséole, infecte près de 95% de la population avant l’âge de deux ans. Il est connu qu’HHV-6B intègre son matériel génétique aux télomères de la cellule qu’il infecte, régions des chromosomes qui contrôlent la durée de vie des cellules. Il est anticipé qu’une insertion d’HHV-6B à cet endroit affecterait la multiplication des cellules à long terme. Le mécanisme de l’intégration d’HHV-6B est à ce jour pas connu. HHV-6B possède une protéine, IE1, exprimée très tôt suite à son infection. Des études de notre laboratoire démontrent que lorsque IE1 est absente, HHV-6B s’intègre beaucoup moins, suggérant que cette protéine favorise l’insertion du virus dans les chromosomes humains. Ainsi, nous étudierons le rôle d’IE1 et son importance dans l’intégration chromosomique. Les résultats obtenus permettront d’avancer nos connaissances sur le rôle d’IE1 dans l’intégration chromosomique d’HHV-6B et, contribuera à l’avancement des conséquences biologiques et médicales rattachées.

Soil organic matter stability in two typical agroforestry systems in central Alberta, Canada

Having more stable soil organic matter (SOM) in a land use systems means that less CO2 maybe emitted per unit area of land when the land is subject to an increasing temperature (global warming). The objectives of the project are two-fold: 1) to analyze short-term biological SOM stability in hedgerow and shelterbelt agroforestry systems, and 2) to characterize the SOM in these same samples using thermal analysis techniques during ramped combustion. We predict that the SOM in the forested area should be more thermally stable than that in the herbland, while it is less stable in the surface than in the subsurface layer. We also predict that the SOM in the hedgerow system may be less easily decomposed than that in the shelterbelt system. The expected output will give us insight into the carbon stability difference in different agroforestry systems as well as under different land covers. TO BE CONT’D

Longitudinal Weak Labeling for Lung Cancer Prognosis and Treatment Response Prediction

This project aims at evaluating whether recent results in deep learning models, trained to exploit weak labels (Hwang, 2016) can serve to extract meaningful lesion localizations from image-level labels, either from individual scans or given a (longitudinal) sequence thereof. To this end, we will scale up existing models that have been shown to work on 2D images to a 3D context, studying labeling performance as the dataset size grows. If successful, this work will assert the usefulness of DCNNs to provide a general modeling framework to integrate imaging with other clinical patient data into a predictive system that could help support clinical decisions and ultimately improve patient care.
TO BE CONT’D

Retirement Income and Wealth Management Analytics

The Research Group at CANNEX (formerly known as the QWeMA Group) develops solutions for the financial and insurance industry of North America. Our analytics play an important role in determining the value proposition of investment products. Our solutions help the financial community and public through their financial advisors to be able to make informed decisions.
We work at the intersection of finance, mathematics, actuarial science, and computer science. Our main objective of the proposed internship is to use our knowledge of mathematics, optimization, financial modeling, and statistics to discover new investment strategies for retirement as well as address ongoing challenges and difficulties in the industry. Interns will receive an opportunity to put their knowledge to solve a real world problem.

Stateful Intrusion Detection using Algebraic State-Transition Diagrams

Increasingly, cyber threats evolve targeting companies, industries and governments. As defense systems are strengthening, threat actors developed new tactics, strategies and techniques to break down security perimeters. Generally, the security of the perimeters are enforced by multiples intrusion prevention and detection tools responsible to provide proactive insights, real-time insights and operational insights for the detection, prevention and mitigation of eventual threatening activities on the monitored system. The performance of such tools depends of the different criteria including detection technique, state awareness, usage frequency and structure. Tools like Snort offer a real-time detection based on rules (or signatures) to detect threatening behaviours from its knowledge base. Snort signatures are expressed in a low-level language that limits the expression of more complex attacks such as advanced persistent threats, distributed and multi-step attacks. They offer basic options for dynamic or stateful analysis, which is necessary to detect aforementioned attacks. TO BE CONt’D

Intelligent Vision Based Navigation Systems

Utilizing geomatics sensors such as laser scanners, GNSS, Inertial Navigation Systems (INS), and photogrammetry cameras to provide mobile mapping solutions has been studied and utilized extensively in the past three decades. The data fusion between high-end mobile mapping systems such as laser scanning and imagery-based systems, and low-cost camera systems are still a fertile field in digital transformation. The anticipated outcome of this project is a software development kit (SDK) that enables data fusion between high-end mobile mapping systems and low-cost camera systems. This SDK will provide multidimensional digital infrastructure information for use in vision-based navigation (VBN) systems. The research could have significant impacts on the fields of LCMM, VBN for indoor navigation/mapping, and self-driving car navigation.

A Care Management Use Case: Correlation Detection between Dental Claiming Patterns and Overall Cost of Care by Participant

Green Shield Canada (GSC) is going to achieve the capability of data analytics in order to make data-driven decisions in various care management use case scenarios. One of these use cases is to detect specific patterns and associations between dental hygiene and health care costs of the individuals covered by them, predict points of intervention and deliver operational recommendations for its own organization as well as other related ones, such as the patients, health professionals and policy makers, in the form of cost-benefits analysis and other required prescriptions. For this purpose, we use their big datasets including claimants’ information, apply data mining and machine learning methods to find hidden patterns and correlations, predict individuals’ costs related to this specific use case in the future, and provide useful recommendations to GSC.

Detection of Fights in Crowd Video

Detection of fights and anomalous behavior of individuals in a crowd is a common problem in computer vision. Some tools that currently exist rely on optical flow of tracked features is a sequence of video frames. These motion algorithms are sensitive to independently moving objects in the frame. What constitutes an “anomaly” is context (eg. location) specific, thereby adding to the complexity. We aim to expand on existing work to create a baseline algorithm which can be used in a general use case, while in parallel investigate the state of the art; and if time permits, tune the algorithm to a specific use case