iClinic-HF is one of the specialized modules that is operating in the 12 heart failure (HF) clinics across British Columbia. The major challenge that these clinics face are the limitations and constraints in resources with regards to the staff and funding operating under constraints of a universal healthcare system environment. Further limitations of an effective […]

This project is examining the movements (migratory and local), status, and health of the Turkey Vulture in the Pacific Northwest, with a particular focus on Vancouver Island. This is at the northwestern edge of their relatively recent (and continuing) apparent range expansion and population growth locally. Through a process of trapping, tagging, monitoring, and observing […]

Earth elevation data is an important tool that helps scientists predict how rivers will respond to large floods and increased inputs of rocks and sand. Recent technological advances in elevation data collection are very effective for dry land, but much less effective for the wetted parts of the river. This causes gaps in the elevation […]

Regular expressions can be thought of as a mini programming language that has a general pattern notation that allows you to search texts for occurrences of string patterns. Recently, a prototype compiler for regular expressions was introduced that provided a 5x or better performance advantage over its closest competitors. The prototype implemented a novel new […]

Grapes will be exposed to volatiles from plants to investigate if the sensory profile of wine made from those grapes can be improved. The volatiles from forest fire smoke can get into grapes and negatively affect the sensory profile of wines, which is referred to as smoke taint. Grapes are most susceptible to smoke taint […]

Tyson Media Inc. (TMI) is an award-winning Television Production company based out of Vancouver, British Columbia. producing content for Netflix, Amazon Video, OutTV, and Discovery Channel, among others. An integral part (and key challenge) of the industry is the development of innovative and new programming concepts/shows. Together with Capilano University, TMI will recruit students to […]

The long-term effects of climate change and outbreaks of mountain pine beetle (MPB) on forests in western Canada are not well understood. In this project, we will develop quantitative models to assess the impacts of climate change and forest resilience on MPB outbreaks and persistence in forests. These models will be informed by the MPB […]

The material properties of thermoplastic polymer composite parts manufactured by the fused filament fabrication additive manufacturing process are highly dependent on the thermal history. A good understanding of the heat transfer in fused filament fabrication is crucial for an accurate stress prediction and subsequently for repetitive, high-quality printing. A numerical simulation to model the thermal […]

Finite Difference Time Domain (FDTD) simulations allow researchers to model complex devices and systems based on integrated micro/nano structures. The electrodynamic behaviour predicted by FDTD simulations match very well with the real physical systems, which significantly accelerates the development of novel devices. However, there are limitations in existing FDTD techniques to model metal nanoparticles on […]

To design and produce better materials for construction and manufacturing, as well as discover new and improved drugs, scientists need to be able to predict properties of molecules or crystalline solids – ideally, before they are made in the lab. At the atomic level, these properties are governed by quantum mechanics, which makes the prediction […]

Climate change is one of the greatest threats to human health in the 21st century, with approximately one in four worldwide, attributable to environmental factors (1). Ironically, healthcare itself is responsible for 5% of annual global greenhouse gas (GHG) emissions, equivalent to airplane travel (2). Within healthcare, kidney care services have substantial environmental impacts compared […]

There is a growing need to develop new crop protection products that are more effective against fungal disease and mitigate pathogen resistance. The fungicide product development process is time consuming and expensive and there is a great opportunity to reduce costs and time by using machine learning. In this project, an existing deep learning algorithm […]