Innovative Projects Realized

Détection et cartographie du nerprun bourdaine (Frangula alnus Mill.) par imagerie et données lidar acquises par drone

L’introduction d’espèces exotiques envahissantes (EEE) représente une problématique importante, potentiellement amplifiée par les changements climatiques qui favorisent l’implantation de ces espèces. L’envahissement des milieux forestiers par le nerprun bourdaine cause notamment des impacts négatifs sur la biodiversité et l’industrie forestière en limitant la croissance des arbres et en affectant la succession forestière. Les capacités de détection et d’intervention actuelles sont limitées principalement par la disponibilité de main-d’oeuvre et la superficie du territoire à couvrir. L’objectif de la recherche est de développer des approches cartographiques basées sur l’imagerie drone afin de fournir un outil de planification face au nerprun bourdaine qui puisse être généralisable sur le territoire québécois.

Biocompatible Smart Nanovectors for the chemoterapy treatment of prostate cancer

In developed countries cancer is the second most important cause of death. Since 1 in 4 Canadians will die of the disease and 1 in 8 men will be diagnosed with prostate cancer (PC), advanced chemotherapeutic treatments represent an important strategy to reduce cancer deaths without compromising a patients quality of life during and post-treatment. To this end, we will couple already established anticancer drugs (e.g. cisplatin) with innovative delivery strategies (so-called nanovectors) to more selectively deliver multiple anti-cancer drugs to cancer cells to trigger cell apoptosis and block tumor spreading. Biocompatible nanovectors labeled with a fluorescent marker will be coated with a peptide to direct the nanovector to the tumor. After loading the nanovectors with established platinum anticancer drugs, a research tool developed in Dr. Gailer’s lab (SEC-ICP-AES) will be used to determine the stability and the potential release of the platinum-drugs from the nanovector complex at physiological pH. Thereafter, the same research tool will be employed to observe the stability of those nanovector-platinum drug complexes in human blood plasma. Taken together, the proposed investigations are intended to significantly improve the targeted delivery of established anti-cancer drugs to the cancer target to develop more effective treatments against PC.

Ligand nanobeads to activate, identify and assay the insulin receptor complex on cultured macrophages

The protein hormones (ligands) that circulate in blood plasma and their receptors on the surface of cells are among the most important diagnostic and therapeutic molecules and are a key focus for the detection and treatment of diseases. Presenting the ligands on chromatography beads may permit the isolation of receptors by a modified form of affinity chromatography. The binding of the hormone insulin activates the insulin receptor on the cell surface which in turn leads to the recruitment of accessory enzymes or signalling proteins to the activated receptor complex that may be new drug targets. Finding new receptor specific drug targets is crucially important information that to date has eluded genetic, DNA/RNA or biotin-based technologies and may lead to new treatments for disease and is of great importance. Affinity chromatography won the Wolf prize for Pedro Cuatrecasas and Meir Wilchek in 1987. Electrospray won the Nobel Prize for John Fenn in 2002. Ion trap mass spectrometry won the Nobel prize for Wolfgang Paul in 1989. The combination of affinity chromatography, electrospray ionization and ion trap mass now permit the direct analysis of cell surface receptor complexes to reveal new drug targets. Here we propose a general solution for discovering the activated receptor complex from the cell surface to reveal the drug target proteins complexed with the receptor and test the effect of new molecular medicines termed silencing RNA, as well as traditional drugs, on the function of the receptors from live cells under the laser scanning confocal microscope.

An Investigation of Remote Healthcare Employees’ Job Demands and Resources, and their Effects on Worker Job Attitudes and Well-Being

The proposed research project will investigate the challenges facing Canadian healthcare workers who currently work either fully or partially from home – and examine the effect that these challenges have on their engagement, job satisfaction, well-being, and intentions to stay at versus leave their current job. To do this, our research interns will conduct interviews with employees who work fully or partially from home, to better understand the challenges they’ve faced – and what resources have helped them overcome those challenges. This project is intended to assist our partner organization in learning more about what resources they need to provide to their employees to maximize the organization’s engagement and retention goals as they transition to using at-home work arrangements long-term.

Foundations of Academic Success in Indigenous Children

This research aims to understand Indigenous children’s academic attitudes during the pivotal transition to off-reserve schooling after grade six. It uniquely acknowledges educators’ vital role as unconventional mental health providers within Indigenous communities. By exploring stereotypes and attitudes, it bridges the gap between academia and community mental health providers, recognizing education’s potential in addressing mental health traumas stemming from systems like the Canadian residential schools. This project will investigate the impact of forced transitions on Indigenous youth, addressing educational and mental health dynamics to enhance support for Indigenous communities in Canada.

AI’s applications in indoor localization

INLAN is pushing the boundaries of today’s asset-tracking solutions by innovating a highly scalable real-time asset-tracking technology. Implementation cost, tag cost, and system accuracy are the three primary parameters that need to be considered when evaluating an asset-tracking system. Obtaining high level of accuracy however, comes with several technological difficulties, among which the multipath effect is the most challenging one. In indoor environments, Radio Frequency (RF) signals bounce off different objects before arriving at a receiver. As a result, the received signals, are heavily distorted, making accurate localization in rich scattering environments an exceedingly more difficult task.
In this project, we want to investigate the possibility of using different AI algorithms to suppress the multipath effect and improve localization accuracy. Some of the possible approaches are:
1. Train a neural network to learn some of the key characteristics of an environment. This knowledge can then contribute to a modified signal processing approach on the receiver side and, subsequently, an improved localization accuracy.
2. A selected number of reference tags with known locations can be used to train the model. Reference tags can also be helpful to prevent the system from overfitting and to track the changes in time-variant environments.

Enhancing Grid Situational Awareness and Reliability with Advanced Analytics and High-Resolution Data

This project aims to develop tools that will actively monitor the electric grid and identify ways to resolve issues more quickly using detailed data from metering devices. By doing so, the project will assist utility companies in gaining an improved situational awareness of the power grid. The power grid has become increasingly complex due to the growing number of solar panels and electric vehicles connected to the distribution system. The outcomes of this project will contribute to better grid management, leading to enhanced reliability of power supply to customers. It will also allow more homes and businesses to generate their own electricity from renewable sources.

Développement d’un outil d’évaluation générique d’un système cadastrale, basée sur la norme ISO 19152:2012. Cas de la Colombie.

En Colombie, il existe un système cadastral composé de 5 différents cadastres, qui se chevauchent dans leurs compétences et leurs territoires. Il n’y a pas de lien entre les cartes produites pour les cadastres et le bureau de registre foncier. On constate de la confusion dans l’information. Ceci engendre une situation d’insécurité juridique de la propriété qui affecte la capacité de consolider et de rationaliser le marché des biens fonciers et immobiliers en Colombie. L’objectif général du projet de recherche est de développer une méthodologie permettant de poser un diagnostic sur les différents cadastres utilisés en Colombie. Un tel diagnostic est nécessaire afin de bien comprendre les forces et les faiblesses des cadastres colombiens et de formuler des recommandations pour en assurer l’amélioration, conformément aux modèles conceptuels reconnus à l’échelle internationale (entre autres le concept de Cadastre 2014 et la norme ISO-19152 : 2012).

Assessing Equity, Diversity, and Inclusion in a Not-For-Profit Organization

Equity, diversity, and inclusivity (EDI) initiatives can have a variety of benefits. However, the existing research focuses on how organizations can use recruitment and selection to promote EDI goals. When organizations cannot use recruitment and selection, how to enhance EDI is more ambiguous. The proposed research intends to increase our understanding of EDI in the Canadian chapters of the international coaching federation (ICF), a membership-based organization. The current project will achieve this by assessing diverse and minority group’s experiences and perceptions of the organization. We will create and administer surveys to the membership from the Canadian chapters. The goal of this internship is to provide (1) the ICF with a greater understanding of their membership and how they can enhance EDI, (2) a starting point for membership-based organizations to address and enhance EDI, and (3) a deeper understanding on how to enhance EDI through methods other than recruitment and selection.

Real-Time Proactive Road Safety Monitoring and Optimization

This study proposes a new signal optimization technique that can help reduce crashes at intersections. Using data from sensors installed at the intersections, vehicle trajectories can be used to identify near-misses that would provide insight into crash-risk. By quantifying the crash-risk using extreme value models, a crash-risk metric is derived that can be used to optimize signal timing. Recognizing that safety is a dynamic quantity which fluctuates over time, adjusting signal timing can effectively alter and reduce crash risk. A multi-objective optimization approach is thus taken by leveraging AI technologies, allowing for the crash risk to be reduced at a location in real-time alongside delay. As such, this proposal demonstrates a proactive approach to safety in a departure away from traditional reactive safety approaches.

Experimental Discovery of Computationally Predicted Metal–Organic Frameworks for Direct Air Capture

THIS IS A GENERIC TEXT PUT IN PLACE AS THERE WAS NO PROJECT OVERVIEW

Machine Learning Developer interns working within cross-functional teams to develop and commercialize AI-powered solutions in the Financial Services sector (1)

AltaML’s primary activities involve collaborating with traditional sectors to identify productivity and process challenges that can be addressed through applied AI. The previous cohort of interns worked on a marketing content generation use case, but for the upcoming term, students will be tasked with working on a chatbot for the Human Resource (HR) department, aiming to innovate and streamline internal processes while also enhancing employee engagement. In addition to this, interns will also explore the potential of utilizing Large Language Models (LLMs) to generate accurate yet secure financial reports. The challenge AltaML aims to solve is to support financial sectors to develop and deploy scalable generative AI models that follow responsible AI principles.

The anticipated social and economic benefits from the project include enhanced productivity, streamlined processes, and the successful deployment of ethical, responsible AI-enabled digital solutions. These solutions not only benefit AltaML’s clients but also contribute to the responsible advancement of generative AI in the financial sector. The project serves as a valuable opportunity for interns to gain hands-on experience in applying generative AI components and responsible AI principles within a real-world context, aligning with AltaML’s commitment to innovation and ethical AI practices.