Informing Indigenous Marine Protection in Gitga’at Territory

Marine protected areas (MPAs) are a popular strategy for ocean conservation in Canada and several
options are available to pursue this type of protection. However, the current federal and provincial processes for
MPA development involve engagement in lengthy multi-stakeholder processes that can overwhelm local
communities and their conservation objectives. An alternative strategy is the establishment of MPAs led by
individuals or organizations in a community.

Sustainability planning and performance assessment in Maple Ridge, BC

The Centre for Sustainable Development at Simon Fraser University has been a leader in sustainable development theory and practice, in Canada and internationally, since 1989. The Centre stimulates sustainable development research and study in BC and elsewhere; collects and provides information about sustainable development; carries out sustainable development projects in partnership with communities and agencies, and facilitates effective use of university resources in responding to requests for assistance on sustainable development problems.

Optical determination of membrane defects and correlation with fuel cell performance and durability - Year two

There is a strong push toward producing fuel cells on a commercial scale. This means a greater focus on production speed and yields with a need to understand the unintended features that arise from larger-scale manufacturing processes. This project requires the set up of state-of-the-art, camera-vision, defect detection equipment to find and collect observed membrane features. These features will then be catalogued and tested to determine their impact on membrane durability and whether they affect later processing steps.

Development of Ex-situ Mechanical Durability Tools and Thermo-mechanical Design Curves for Fuel Cell Membranes - Year two

Hydrogen powered polymer electrolyte membrane fuel cells (PEMFCs) are a clean energy technology that generates electricity without harmful emissions at the point of use. Current R&D efforts mainly target to commercialize PEMFCs through cost reduction and durability enhancement. The lifetime of PEMFC is limited by the degradation and failure of the polymer electrolyte membrane (PEM). The proposed research project addresses the mechanical degradation mechanism, a key factor reducing the lifetime of PEMs, by developing in-house ex-situ mechanical durability evaluation tools.

Effects of various compounds on central nervous system neurons as potential therapeutics against epilepsy

Xenon has developed isoform selective blockers of the sodium channels that are expressed in CNS neurons with the intent of developing them for therapeutic use, especially epilepsy. The primary goal of this research project is to determine the activity of compounds on CNS neurons. Until now, all characterization has been done with heterologously expressed channels. Until recently, a major impediment to such studies is the heterogenous nature of CNS neurons, so that a large number of studies need to be conducted for a complete characterization.

The design and evaluation of a wearable technology as an effective tool for promoting early childhood physical literacy development

With childhood obesity and inactivity on the rise at an alarming rate, many government, education, and health agencies are promoting the development of physical literacy to combat this “epidemic.” The concept of childhood physical literacy refers to the development of fundamental movement skills that permit a child to move confidently and with control, in a wide range of physical activities. Wearable technologies have been quickly gaining in popularity, with devices and apps that can track fitness, sleep patterns, mood and even air quality.

Investigating nanostructured local data storage and off-grid powering for the adaptive corrosion protection system

During the proposed internships, smart-grid integrated adaptive corrosion protection system (ACPS) will be developed as a stand-alone unit to provide optimum corrosion protection along with the nanostructured local data storage and off-grid powering. This will allow the continuous monitoring of the corrosion status of the metal infrastructures (e.g. transmission towers) along with the power-grid monitoring data. The proposed system can be directly monitored from the centralized control-room.

Applying Deep Learning to Optimize 3D Pose Estimation from Monocular Video

REP is an athlete development platform for building better, and healthier athletes. Inside the REP platform are computer algorithms that can “see” how people move, and the accurately estimate how they are moving in three dimensions. The REP platform can then compare models of how you move, to models of how experts move. This comparison gives us rich information that people can use to improve their form. However, generating the expert models is quite hard, and it’s not always easy to understand how to actually compare users and experts.

Perpetual Nomads: an exploration of indigenous narratives and imagery through contemporary and experimental mediums

The goal of the Perpetual Nomads project is to make illustration depicting many indigenous and environmental issues through traditional art media and digital media. The team will be exploring the viability of creating Mixed Reality interactive experiences to increase the awareness, empathy, egalitarianism and environmental concern in users through these illustrated narratives. Since people use new technologies and traditional arts for expressing themselves in so many ways, its crucial for youth to be exposed to powerful ideas relating to consciousness, sustainability and connectivity.

Predicting Building Energy Consumption Using Machine Learning Methods: a Comparison

The aim of this project is to predict building energy consumption for next days. Firstly, we will collect several data such as weather data, time data, and historical energy consumption of the building. We will analyze the collected data to recognize the usage patterns of the building, for instance, the low and the high electricity consumption of building. After data analysis, we will apply several machine learning models to predict energy consumption of building, and finally all models will be compared to choose the outperform method.

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