Examining backcountry recreationists’ understanding and use of the avalanche danger scale: insights from qualitative interviews and responses to an online survey

Danger scales use a combination of colours, words, and severity levels to efficiently communicate basic hazard information to a target audience. Avalanche warning services around the world use a colour-coded, five-level danger scale to communicate the severity of snow avalanche conditions to recreational backcountry users. While past research has primarily focused on helping forecasters produce accurate danger levels, there has been relatively little research on recreationists’ comprehension and use of danger ratings.

Designing and developing a real-time medical data transfer system for space health usage

In recent years there has been a rapid increase in companies providing rocket launch services for private space travel (SpaceX, Blue Origin and Virgin Galactic to name a few). Access to space by private citizens means that companies will need to collect health information from the private astronauts as well monitor their health while in space. This information will have to be transmitted from space to the ground in a secure manner so that individual health information remains private.

Deciphering the catalyst-ionomer interface in fuel cells: Molecular dynamics simulations of local transport properties

Polymer electrolyte fuel cells are a key technology in the race against climate challenge, and while commercial applications are increasingly common, challenges remain in cost, performance, and durability. Most of the issues that prevent full commercialization affect the catalyst layer, the region where the power-generating electrochemical reactions take place, like the oxygen reduction reaction. This layer consists of platinum nanoparticles supported on a carbon material and covered by an ion conducting polymer.

Improving avalanche forecasts in data-sparse areas with physical snowpack modelling - Year two

Assessing dangerous avalanche conditions requires a reliable stream of weather and snowpack data, which can be difficult and expensive to collect in many remote areas of Canada. Snowpack conditions can be simulated in these areas by coupling weather forecast models with physical snowpack models, however, this method has had limited adoption by avalanche forecasters.

Project Yellow Cricket: Fantasy hockey data analysis and pattern recognition

Officepools.com is a flagship product of GSL Group, acquired in 1999. The site is an online fantasy sports platform offering various sporting and entertainment events to choose from, such as football and golf, but primarily specializing in the National Hockey League (NHL).
Officepools.com has a userbase of around six hundred and fifty thousand people, with the majority of users being male aged 30 to 50 years and located in Canada.

Radon: Building a BC Based Response - Year two

Radon is a cancer-causing radioactive gas produced by the natural decay of uranium in rocks and soils. Radon can enter buildings and reach high levels in indoor air (Khan and Gomes, 2017). It is the second-leading cause of lung cancer (after smoking). killing approximating 3200 Canadians a year (Chen et al. 2012). High radon concentrations can be easily remedied, and doing so is a cost effective way to prolong life and reduce death from disease (Gaskin, et. al. 2018). However, Canada’s legal rights and remedies to respond to radon in Canada are largely inadequate (Dunn and Cooper, 2015).

Data Science: From Principle to Practice

Data science is an interdisciplinary field that combines statistics, computer science, and domain knowledge. The rise of data science has fundamentally changed how people solve problems in all kinds of industries. To fill the talent gap, SFU professional master’s program (PMP) was launched in 2014. In this Mitacs cluster project, SFU PMP will collaborate with multiple industrial partners to investigate innovative solutions to address various data science challenges in data management, model development, and application & product

Creating a machine learning model to predict activity in playgrounds across North America

Biba is a company that creates interactive experiences for families on playgrounds and provides data for playground owners. This research project explores how can we leverage third party data sources and machine learning to confidently determine how many people are in a playground at a given time and how long they spent there. This kind of information is critical for park and playground stakeholders, and if we can solve this problem, Biba would be the first company to be able to produce an industry metric of this kind.

Incorporating fish movement and sensitive benthic habitat in the ecosystem approach to fishery management of Canada’s sablefish fishery

British Columbia’s sablefish fishery is among the most highly valuable fisheries in Canada. In the early 1990s, mainland inlets were closed to commercial fishing because young sablefish were thought to grow in these protected areas before moving to the offshore areas where the fishery operates; we will look at movement patterns of sablefish within BC to understand the net contribution of these inlet sablefish to the offshore fishery to aid fishery managers.

A Community-Based Participatory Action Research Project to Examine How People Who Use Drugs are Represented in Anti-Stigma Campaigns and How Anti-Stigma Work Can be Made More Inclusive

Through a review of existing anti-stigma campaigns targeting stigma towards people who use drugs (PWUD) and a series of focus groups conducted with marginalized PWUD, this community-based research project will explore how anti-stigma campaigns can be made more inclusive of all PWUD, especially those most severely impacted by stigma.

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