Innovative Projects Realized

Increasing real-time video streaming performance over Wi-Fi networks

This project focuses on improving the performance of the real-time video streaming over Wi-Fi networks, in which losing packets is a serious concern. State-of-the-art methods try to improve the robustness of AL-FEC mechanisms by providing unequal protection to the packets. But such approaches are complex and increase even more the delays. In contrast, the proposed research will study how to dynamically select the packet size and the period of AL-FEC redundant data (number of rows and columns in AL-FEC), crucial parameters for real-time applications. The research will study how to adjust the packet size dynamically based on estimated communication conditions (e.g. the number of packets received without error versus damaged ones, etc.) by using machine learning approaches. Appropriate selection of packet size will optimize the effective throughput as the network conditions change. TO BE CONT’D

Structural and Hygrothermal Performance of Masonry Walls with Large Cavities

A veneer wythe protects the indoor environment and other building components against adverse outdoor effects, such as rain and physical impacts. Veneer walls are connected to a structural substrate (e.g. wood frame or masonry units) by ties. These are usually made of steel and therefore high in thermal conductance. The ties penetrate the thermal insulation layer between the veneer and structural substrate and hence act as uniformly distributed point thermal bridges. In conventional thermal analysis, their presence is usually neglected. However, with the advent of newer energy codes that require larger cavities to accommodate thicker insulation layers and performance-based thermal analysis, the structural and thermal performance of the ties must be carefully assessed. To enhance the durability and sustainability of Canadian infrastructure it is necessary to develop a new tie system for large cavity walls, and test its performance with full-scale experimentation.

Feasibility Study to Determine the Application of Unmanned Aerial Vehicle for Aircraft Inspection

This project assesses the feasibility of using drones to inspect aircraft for surface damage and defects such cracks, fractures or dents. The intern will first carryout a comprehensive literature review and environmental scan of the existing technology. He will then assist in developing and conducting a series of physical tests to determine the best camera parameters, drone flight pattern, image format and proximity sensor performance. The results of these tests will be used to program a commercially available drone to carryout an automated image acquisition flight. The images will then be used to generate an accurate 3D model of the surface condition of the aircraft which will be automatically analyzed for defects.
The overall goal of the project is to develop drone-based aircraft inspection standards of practice which will improve defect detection, safety and inspection efficiency.

Automated Target Classification for Multi-Frequency Echosounders

The oceans cover the majority of our planet’s surface but much of their depths are still a mystery. Improvements in technology have allowed for the development of instruments on underwater platforms and autonomous gliders that are able to survey the world’s oceans. One instrument, called an AZFP (acoustic zooplankton fish profiler), emits high-frequency sonar pulses and listens for backscatter (reflections) to observe fish, zooplankton, suspended sediments, and other quantities in the water column. Backscatter data are complex and time consuming to process and interpret. This study seeks to use recent improvements in Machine Learning to automate the processing and interpretation of backscatter data to reduce the time and manual effort required. Some studies using Machine Learning have already been carried out, but these focused specifically on certain species of fish and plankton and ignore everything else. However, animals in the ocean are also affected by their environment. TO BE CONT’D

DESIGN OF A NOVEL HEAT EXCHANGER TEST RIG

Heat exchangers, used in building heating, ventilation and air conditioning (HVAC) systems to transfer heat from hot to cold fluids, are designed to operate under ideal conditions. However, in practice operating conditions may vary with ambient temperature or humidity. HVAC system efficiency can be improved significantly if fluid flow rates are adjusted in response to such changes. Armstrong Fluid Technology is a Canadian firm that has developed control systems to adjust the flow through building heat exchangers to maximize their efficiency. This project is being undertaken to develop a heat exchanger test rig and to use it to determine heat exchanger efficiency as a function of fluid temperatures and flow rates. The feedback control system will reduce the energy required for operating an HVAC system by approximately 30% and have a significant impact on Canada’s energy usage and greenhouse gas emissions.

Removal of Micropollutants from Wastewater by Immobilized Laccase on Hollow Silica Embedded Plastic Packing Reactor

Micropollutants can be found in almost all water bodies due to their recalcitrant character. As conventional treatment plants are not efficient for many recalcitrant pollutants, oxidative methods and physical treatment methods have been widely applied for treatment of wastewater.
Green enzyme-Laccase has high ability to transform many kinds of micropollutants, such as recalcitrant contaminants, into oxidized products that are less bioavailable or even harmless, as well as stable water-insoluble polymer derivatives. This project aims to promote laccase catalyzed treatment for removal of pharmaceuticals in pilot scale systems by using immobilized laccase on silica embedded packing by using partially purified laccase from P. Dryinus strain. Particularly, this project aims tor emove of pharmaceuticals from real wastewater and to evaluate the system durability and cost efficiency.

Understanding robot locomotion characteristics and planning in heterogeneous multi-robot coverage

To be safe and efficient, autonomous robots will need to consider and understand one another when performing their respective tasks. Communication and joint planning between robots might not be possible due to the number of robots, adversarial behaviors, or the lack of common protocol.
In this project, we start by tackling this large issue at a small scale by focusing on a specific situation: multi-robot coverage with heterogeneous robots. We consider a team of robots that have to be deployed to cover a large scale environment. Each robot has different locomotion characteristics but they all share a common objective: for the team to cover the whole area as efficiently as possible.
The idea of this work is for each robot to use visual information to gather a semantic understanding of other robots’ characteristics and of the environment. TO BE CONT’D

Combining cortical stimulation and ‘mirrored’ visual feedback to enhance recovery of upper-limb: a pilot study.

Stroke is one of the most prevalent neurological conditions worldwide, especially among the elderly.

Motor impairment is one of the main disabilities associated with stroke. The ability of training and

physical activity to restore motor function after neural injury has long been appreciated. Nevertheless,

even with intensive task-specific training and physical activity, 15–30% of patients with stroke are

permanently disabled. As a result,research aiming to develop novel therapies that enhance

neuroplasticity is currently being conducted to allow rehabilitation of these patients. A promising

approach is modulation of cortical excitability using non-invasive brain stimulation techniques. These

techniques may instantaneously induce plastic changes within the cortical network of sensorimotor

areas, thereby improving motor function of the affected hand after stroke. Our work attempts to

elucidate whether repetitive administration of inhibitory non-invasive brain stimulation of the

unaffected hemisphere in sub-acute stroke over several days combined with sensorimotor

behavioural training using optical left-right reversing prisms could result in an enhanced effectiveness.

The primary objective is………….TBC

The Development of Phonological Awareness in Vietnamese Children

Vietnamese is widely spoken by over 90 million people in Vietnam and around the world. The proposed project will be the first to study phonological awareness (PA) and reading outcomes in Vietnamese-speaking children. Phonological awareness is the ability to explicitly and/or implicitly manipulate small meaningful units of speech. Many studies with English-speaking children have found PA to be a strong predictor of reading ability. The proposed project aims to measure the growth of PA skills in Vietnamese-speaking children from kindergarten through second grade, and to identify relationships between PA skills and reading outcomes. Results from the analyses will contribute to the existing knowledge base about PA. In the future, the findings will help to identify Vietnamese-learning children who are at risk for reading difficulties and inform effective instructional strategies. Finally, the applicant will develop research skills relevant to clinical practice in her future career as a speech-language pathologist.

Extending artificial intelligence in the operating room

Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. However, those detections should be interpretable, or more actionable in order to be audited or reviewed. This project applies various ‘explainable AI’ (XAI) technologies, which will allow us to evaluate the impact of solutions, which generalizes across the healthcare syste

Enhancing steady state processing of plant based ingredients for the food industry

In partnership with KeyLeaf (KL), Saskatchewan Polytechnic (SP) is developing a system for the bioprocessing industry that will interface through a mobile app, collect data on a NoSQL database, and use analytics to mine it for new insights into all processing aspects. The Engage phase of the project will commence in tandem with a MITACS grant of the same scope, involving building the database (DB) and user interface, determining how to best structure the data for analysis, designing the analytic algorithms, then testing the system and prepping for the next phase. This will produce a faster bioprocessing system for KL capable of identifying areas in its own processes that can be improved, thus increasing product quality. SP will benefit from knowledge exchange with KL and plant-based ingredient processing techniques will be fine-tuned.

Pelletization of Forest Wildfire Fuels in Western Canada

Forests in British Columbia have significant areas that need to be managed to limit the danger of fire and disease. Under current management approaches, there are few cost-effective options available to areas that are not already regularly harvested. A holistic analysis of pelletization of these materials could show that the sale of wood pellets, as well as the reduction in fire suppression and forest management costs and the increase in tax base would generate a net profit to the province and the businesses associated with the management.