Innovative Projects Realized

Design and Seismic Performance of Steel CBFs: Advancing Standards through Canadian and European Code Comparison

This research project aims to investigate the seismic behaviour of steel concentrically braced frames (CBFs), a widely used seismic-resistant system in Canada and Europe. Previous experimental and numerical studies have identified several shortcomings regarding the seismic performance of steel CBFs. In response, this project seeks to propose new design guidelines within the framework of the Canadian and European seismic codes to improve the behaviour of steel CBFs under seismic loads, aiming to promote global ductile mechanisms and prevent drift and damage concentration under earthquakes. The project findings will contribute to advancing seismic design methods for steel-braced frame structures, improving current structural design practices, and strengthening the resilience of communities in seismic-prone areas. Such enhanced provisions are expected to potentially reduce structural damage and economic losses during major earthquakes and contribute to saving lives by ensuring safer structures. Additionally, the outcomes of this research will support the construction industry in achieving more cost-effective and optimised designs without compromising safety. The data generated in this project will also serve as a valuable resource for future research initiatives, further enlarging knowledge in the field of earthquake engineering and contributing to the state of the art of steel CBFs.

Les agressions sexuelles perpétrées à l’endroit de victimes inconnues

Ce projet a pour objectif d’examiner les facteurs influençant la mobilité géographique des délinquants sexuels, en vue de mieux comprendre leurs comportements de déplacement pour commettre des crimes. La majorité des recherches actuelles montrent que ces individus tendent à rester proches de leur domicile, mais des cas de déplacements plus longs restent peu explorés et pourraient révéler des dynamiques spécifiques. Nous allons analyser plusieurs milliers de cas en nous appuyant sur des critères comme le milieu de vie (urbain, semi-urbain, rural), les caractéristiques personnelles des délinquants, l’âge des victimes, et l’impact des déménagements ou autres points d’ancrage. En utilisant des outils de visualisation et d’analyse spatiale (comme Tableau et QGIS), nous pourrons modéliser les trajets criminels et identifier des modèles de déplacement. Cette étude vise à combler les lacunes des recherches précédentes, en prenant en compte des variables telles que la stabilité de la distance parcourue au fil du temps et la typologie des territoires de chasse. L’analyse spatio-temporelle approfondie, accompagnée de rapports visuels, contribuera à clarifier les différences entre les délinquants dits “locaux” et ceux qui voyagent loin, permettant ainsi de fournir des bases solides pour la prévention et l’élucidation des crimes non résolus.

Online Application to Support Training for Heart and Lung Sounds Assessment by Nursing Students and Health Care Professionals

This research project deals with the question of using multimedia computer applications for training Nursing students or professionals to identify heart and lung sounds as part of an overall health assessment session. The new design for this Nursing training application will support a wide array of mobile devices, by using novel technologies such as HTML5, CSS and JavaScript. We will also setup the foundations to assess whether the new application is as effective in helping Nursing students and trainees as our previous work. A matrix will be developed to assess the work taking into account such things as scalability, performance and reliability. The ground work for a future development study will also be created.

Implémentation de la Stimulation Électrique Fonctionnelle sur les membres supérieurs

Ce projet vise à améliorer la réadaptation des personnes atteintes de paralysies ou de troubles neuromusculaires affectant les bras, grâce à une technologie appelée stimulation électrique fonctionnelle (SEF). Cette technique utilise des impulsions électriques pour activer les muscles, permettant des mouvements que les patients ne peuvent pas réaliser seuls.

L’étude se concentre sur l’effet de la SEF sur la perception de l’effort pendant un exercice de pédalage à bras. Plus précisément, nous souhaitons déterminer si cet exercice est perçu comme moins fatigant avec la SEF comparé à l’exercice sans SEF.

La perception de l’effort joue un rôle clé dans l’engagement dans l’activité physique, essentielle pour la santé. Un effort trop intense peut décourager, en particulier chez ceux avec des limitations physiques, tandis qu’un effort modéré favorise la motivation. En facilitant l’exercice grâce à la SEF, on peut réduire l’effort perçu, rendant l’activité plus accessible.

Ces avancées pourraient avoir un impact significatif, rendant ces solutions accessibles à plus de personnes et entraînant des bénéfices pour la santé cardiovasculaire, musculaire et mentale, tout en améliorant la qualité de vie globale.

Impacts of living with the endangered Golden Langurs in the forested landscapes of Bhutan

The Golden Langur (Trachypithecus geei), a unique and venerated primate species endemic to the Eastern Himalayas, particularly Bhutan, confronts persistent challenges as a result of interactions with human populations (Thinley et al., 2019). Bhutan, well-known for its dedication to environmental preservation, presents a distinctive arena to explore the tolerance levels of local communities towards the damage caused by Golden Langurs. This study examines the extent of acceptance exhibited by the local people in Bhutan towards the negative effects of Golden Langurs. The primary research question for this internship is – What is the impact of golden langurs on farm incomes and what is the mechanism of crop protection adopted by farming communities? This internship is part of a larger project which aims to understand the tolerance level of people towards damage caused by golden langurs in the agroecosystem of Bhutan. This project will improve the understanding of human-wildlife conflicts especially in the context of an endangered species conservation and develop collaborative ethnography as a way to address concerns of community building and biodiversity conservation.

Generative AI as a service for Small Business

Small and medium-sized businesses (SMBs) face increasing pressure to remain competitive in a rapidly evolving digital landscape. Many SMBs face obstacles in adopting AI solutions due to limited resources and the complexity of available products, which are often too generalized to meet the specific needs or scale of smaller businesses [1]. Existing AI solutions are typically designed for larger enterprises and lack the customization required for the unique operational challenges of smaller businesses. As a result, these companies are unable to efficiently utilize their data—such as customer service logs, website analytics, and social media feedback—to drive informed decision-making and improve customer engagement. To address this problem, there is a need for a solution that enables SMBs to transform their unstructured data into a usable, interactive knowledge base, empowering them to make data-informed decisions and strengthen client relationships. This requires an approach that is both accessible for non-technical users and capable of processing complex data in a way that delivers relevant and meaningful insights.
WizeWerks, a consultancy specializing in AI solutions, is focused on empowering SMBs to access the benefits of generative AI without the need for extensive in-house expertise. As a solution to this this, WizeWerks wants to develop a white-label platform that SMBs can brand as their own which will allow them to offer an AI-powered support agent that interacts with their unstructured data and transform such data into an interactive knowledge base. The system will generate meaningful insights to help SMBs respond to customer inquiries, predict emerging trends, and make data-informed business decisions.

Kanin Energy-Heat Pump Feasibility Study

The project will consist of conducting a feasibility study and a preliminary design on the application of heat pumps for heavy industry to achieve decarbonization and economic objectives. Heat pumps can play a significant role in helping heavy industries achieve decarbonization by efficiently capturing and utilizing low-temperature waste heat, upgrading it to higher temperatures, and providing thermal energy for various industrial processes.

Scalable AI-as-a-Service (AIaas) Platform Development

This project focuses on building the core infrastructure for Farpoint’s new AI-as-a-Service (AlaaS) platform. Two interns will work with Farpoint engineers to create a robust and scalable system using Kubernetes for managing resources and efficiently distributing workload. The interns will also implement load balancing and network routing to ensure smooth handling of high user traffic and AI model requests. This new platform will allow Farpoint to reduce reliance on costly third-party providers, give them greater control and flexibility in deploying and managing AI models, and ultimately, strengthen their position as a cutting-edge provider of innovative AI solutions.

Data Collection and Model Development for Prosthetic Fitting using a Robotic Gait Simulator

ProsFit is a medical device manufacturing company that supports prosthetic clinic owners to radically improve productivity and user outcomes. Through innovation, ProsFit strives to provide limb wearers a choice of affordable, reliable and desirable prosthetic products and services. ProsFit has developed and is commercializing the solutions to provide improved mobility and quality of life to millions of amputees, at scale, and has attained significant professional usage (>700 amputees fitted worldwide). The proposed project will conduct collaborative research with the Centre for Intelligent Manufacturing (CIM) at Sheridan College with the aim to gather data for enhancing the comfort of prosthetic users with lower-limb amputations. The challenge is that a large dataset is required to improve provision services and outcomes. Through CIM, the project utilizes a 6-axis robot set-up developed at CIM that can mimic human movement patterns, allowing for thorough testing of how changes in variables affect force distribution and other data through our Robotic Gait Simulator (RGS). Long-term engagement between ProsFit and CIM is planned to develop this technology, and the proposed project will establish data collection capabilities on the robotic gait simulator, engage in data collection, and begin to build the model for prosthetic fitting with best outcomes.

Community Prosperity Hub & Non-Profit Data Collaboration

The Greater Fredericton Social Innovation (GFSI) team and its partners have developed an open-access data repository called the Community Prosperity Hub, launched in 2023. This Hub is still in development but to-date it serves as a powerful tool for nonprofits in the Greater Fredericton area by making socioeconomic data accessible through user-friendly visualizations, summaries, and resources. These tools help organizations understand their impact, improve service delivery, and secure sustainable funding. Aligned with the 17 United Nations Sustainable Development Goals (SDGs), the Hub positions GFSI as a leader in community-level data initiatives.

The Hub has already reached over 300 stakeholders, including United Nations representatives, demonstrating its potential for broader use and adaptability. To further develop this platform, GFSI seeks to engage a computer science graduate to incorporate additional social determinants of health and link each Hub with Canadian funding sources.

GFSI is also advancing social inclusion initiatives by supporting the City of Fredericton’s Anti-racism Task Force recommendations. This includes developing the Canadian Atlas of Social Inclusion—an online tool for reporting incidents of racism—as well as the Fredericton Venues application, which enhances access to community spaces. These efforts showcase GFSI’s commitment to fostering an inclusive and data-driven community.

Conception et développement d’outils automatisées pourcaractériser, modéliser et quantifier la morphologie dessystèmes ostéo-articulaires en trois dimensions à l’aide deplusieurs vues radiographiques

Les problèmes de douleur chronique reliés à des troubles musculosquelettiques affectent une grande partie de la population et les coûts directs (visite médicale, traitements, médicaments) et indirects (absentéisme au travail, productivité réduite) sur le système de santé sont extrêmement élevés. Pour améliorer le diagnostic, la planification chirurgicale et le suivi des pathologies de la colonne vertébrale, de la hanche et du genou, il est essentiel de considérer et de visualiser les articulations et les paramètres cliniques qui leurs sont associés en trois dimensions. Ce projet vise à concevoir, développer et transférer des outils informatisés innovateurs afin d’améliorer et d’enrichir les plateformes d’imagerie d’EOS Imaging et de Global Imaging On Line, notamment dans le but d’optimiser la reconstruction 3D, l’analyse morphologique 3D des os et assurer une prise en charge personnalisée des patients

Integration of Inflation Signal in Picton Mahoney’s Asset Allocation Models

Picton Mahoney Asset Management (“PMAM”) was founded in 2004 to provide unique investment solutions to institutional, retail and high net worth investors in Canada and around the world.

The Multi-Strategy Team at PMAM uses economic cycle models to determine asset allocation preferences across time during different macroeconomic regimes. We have recently incorporated an additional inflation signal to our cycle models which requires more work to integrate into the asset allocation process. We have identified other ends uses, including our 40/30/30 marketing campaign and our new Wealth Management unit. We also require automation of reports that will alert the multi-strategy fund managers of any new signals that would necessitate a change in asset allocation.

University of Toronto’s Master of Mathematical Finance (MMF) students bring highly marketable and specific skill sets that can support PMAM’s analysts and portfolio managers within the Multi-Strategy and Macroeconomic Research Teams. Their Matlab, Python and SQL programing skills will move our projects forward by allowing us to update and automate our existing cycle models that make asset allocation decisions.
These skills will also allow us to expand the models to new use cases within the firm, including the new Wealth Management unit. MMF students have basic knowledge of key concepts such as Portfolio Construction, Asset Allocation, Factor Investing and the Global Macro investing environment. This allows MMF grads to be quickly integrated, making an immediate impact. They can also design, generate and automate reports related to the operation and monitoring of Multi-Asset and Multi- Strategy portfolios.
Providing MMF students with the opportunity to integrate their academic studies with hands-on experience at PMAM allows us to support the intern’s journey from academia to industry, while benefitting from their intellectually curious mindset, their ability to think differently, and their aspirations provide unique investment solutions to Canadian and global investors.