Development of a tool for analysis of low-frequency oscillation modes in power systems signals

Power systems are subjected to randomly occurring normal and abnormal events that can trigger oscillatory response creating unsafe sustained fluctuations in power, voltages, currents and the frequency. Increasing integration of power electronics interfaced renewable generation contribute to new types of oscillations due to control interactions, sometimes supper imposed on classical electromechanical oscillations. Such oscillations can damage equipment and ultimately results in blackouts due to cascaded tripping if not controlled using appropriate remedial actions.

Improving GFlowNets for low data drug discovery

GFlowNets are generative networks that consider the generation process as a flow network. They are theoretically better at handling the difficult cases of sampling different modes of a distribution and when different sampling trajectories can yield the same final state. In this work, we hope to explore various improvements to GFlowNets to make them suitable alternatives for molecular generation and optimization in drug discovery. The research can expand the capabilities of chemists and could enable the discovery of new drugs faster and with less resources.

Evosep One LC optimization and absolute quantitation of proteins in human and mouse plasma using Multiple Reaction Monitoring and Parallel Reaction Monitoring-Mass Spectrometry

Proteins are sub-cellular molecules that provide important information of how well the body is functioning at a given time. Abnormal increase or decrease in the level of proteins can be indicative of the presence of a disease. Hence, developing tools to accurately measure protein levels in the human body is of utmost importance. Over the past few decades, a specialised instrument called the Mass Spectrometer (MS) has been used for this. The MS instrument can be used in a targeted and untargeted manner.

On-farm prediction of carcass traits in live beef cattle using new digitized and non-invasive technologies

Almost all commercially processed beef carcasses are graded based on their quality and yield. However, grading information is provided to the producers after slaughtering of animals, then feedlot operations do not take full advantage of this information to navigate their cattle finishing strategy. This project will develop a new non-invasive procedure using hand-held ultrasound tools and machine learning models to estimate carcass traits on-farm in live animals. The carcass traits, including marbling score and yield grade, will be predicted real-time without the need for manuall assessment.

Enhancing online mental wellness programming for older adults with heart failure

Mental distress is common among individuals with chronic heart failure. Online wellness programming is typically more heavily subscribed to by women rather than men. As part of a larger randomized controlled trial, this project aims to evaluate the distinct recruitment and engagement needs of men and women with heart failure with online mental wellness programming.

Automated carbohydrate counting and machine learning could improve glycemic control in youth living with type 1 diabetes

People with type 1 diabetes (T1D) treated with a basal bolus insulin regimen need to match their insulin bolus calculation with the estimated carbohydrate content of food to maintain glucose control. We want to provide them with a more flexible approach and give them the opportunity to quickly adapt mealtime insulin using automated carbohydrate counting technology.

Robust design, fabrication and characterization of slip-resistant micro and nanoreinforced polymeric shoe soles with surface patterning

Slips, trips, and falls are common causes of many injuries people experience inside or outside of their workplace each year all over the world. Using high-performance shoes can decrease slip falls. Winter and safety footwear should provide sufficient slip resistance on icy surfaces to overcome the slip hazard in frozen and contaminated environments. Developing high-performance anti-slip footwear is a priority and an open challenge and incorporation of reinforcing fillers and NPs are wise perspective for modifying the polymers used as soling materials.

Evacuations and Resilience Hubs: Preparing Edmonton and Canadian Cities for Extreme Events and Climate Change

This research project to enhance evacuation planning and resilience hub design in Edmonton will be completed through a partnership between the University of Alberta, Alberta Ecotrust Foundation, the City of Edmonton, and Mitacs. The graduate student interns will complete and guide research tasks related to data collection (e.g., survey and focus groups), data analysis, and research dissemination.

Assessment of Drag Force on Piles Subjected to Service Loads Adjacent to MSE Walls

A large portion of the infrastructures, including bridges in Manitoba, are constructed on problematic alluvial soils such as soft clays. One of the concerns related to the piled foundation bridges is downdrag which is a downward movement of the soil relative to the pile. Drag force is an additional axial force imposed on the pile due to downdrag. Underestimating this force may have detrimental impacts, including excessive settlement or even failure of structures.

Modular Multilevel Converters with Energy Storage – Design, Modeling, and Operation

Modern power systems wherein renewable resources such as solar and wind power are extensively used need to rely on some means for energy storage to address the intermittency of such resources. This proposal investigates a class of power electronic converters that are able to connect battery energy systems to the grid and provide multi-directional pathways for the flow of energy. Various models will be developed for these converters to facilitate their design, analysis, and computer simulations.