The Bay of Quinte, a Z-shaped embayment at the northeastern end of Lake Ontario, represents a characteristic case, where scientific uncertainty underlies the current management efforts to integrate environmental concerns with socioeconomic values. The proposed project aims to develop a methodological tool that can be easily engaged with the policy practice of adaptive management and […]

This project explores how multilingual immigrant children aged 8–13 in Canadian ESL support programs acquire English vocabulary during their early years of settlement. Vocabulary development is crucial for academic success, yet many newcomer children face barriers that go beyond language exposure alone. The research investigates how cognitive factors, such as working memory and phonological processing, […]

Obstructive sleep apnea (OSA) is common in 10% of adults and is associated with increased cardiovascular morbidity and mortality. Furthermore, there is a 3-fold increase in OSA prevalence in fluid retaining patients such as those with heart failure. Evolving evidence suggests that fluid accumulation in the neck could narrow the upper airway (UA), increase its […]

This project aims to develop an AI-powered visual inspection system using image data from P&WC’s existing Computer Vision Inspection System (CVIS) to enhance aircraft engine assembly issue detection. By leveraging deep learning techniques, the proposed solution will address current limitations in accuracy and consistency, targeting a 100% visual detection rate for anomalies such as: part […]

Developing quantum-enhanced LiDAR requires a deep understanding of the water medium’s optical properties, which vary with environmental factors. To address this, an oceanic model was created to estimate system performance based on water’s scattering and absorption traits, though it currently simplifies these as identical. In the proposed project, this will be refined. System analysis is […]

Vision Extrusions Group LTD is a recognized leader in the building products industry. They produce a wide range of products (as shown in Figure 1) including windows, doors, decks, fences, etc. utilizing extruded polymeric profiles as a substitute for wood. In the proposed project, the following objectives have been set by the partner organization to […]

Biocovers are earthen structures built into landfills and other industrial facilities to collect and degrade greenhouse gas emissions from the site. They are widely considered one of the most effective ways to combat methane. In order to assess the performance of those biocovers, operators have to attend to the biocover regularly and use a flux […]

Optimization of an ergonomics program within a manufacturing facility. AI camera based system for postural injury risk identification will be utilized to improve productivity and quality of injury risk identification. The project will then continue to applying the RACE Recognize, Assess, Control, Evaluate model. Physical Demands Analysis and process and design solutions for risk reductions […]

Epilepsy is a debilitating neurological disorder affecting approximately 50 million people worldwide (World Health Organization). This project proposes to develop a SMART (Seizure Monitoring At the Right Time) Headset for these patients to monitor their brain signal and track their movements, heart rates and breathing patterns. This headset will have new types of sensors suitable […]

This project focuses on researching and developing an advanced coordination mechanism between our API layers and LLM infrastructure. The goal is to efficiently access and reason across both structured and unstructured data sources to improve customer’s decision-making processes. Success will be measured by the speed in which that data source can be identified, sourced, and […]

This project proposes a completely novel workflow to automate the detection and quantification of bioturbation (i.e., biological sediment mixing by infaunal organisms) in deep-ocean sediment cores using the proven capabilities of neural networks in complex image interpretation. The new technique will enable precise, objective, and efficient quantification and identification of bioturbation types caused by infaunal […]

This project proposes a scalable quantum-enhanced generative model for drug discovery, targeting the design of KRAS inhibitors through the integration of Neural Quantum States (NQS), Quantum Circuit Born Machines (QCBMs), and CUDA Quantum acceleration. By replacing traditional quantum circuits with adaptive NQS representations and extending QCBM capacity to 32 qubits, the framework enables more expressive […]