Innovative Projects Realized

Assessing Equipment and Technologies for use in the Development of Dykelands and Upland in Atlantic Canada for Sustainable Agricultural Production

The research in this Master’s project is focused on documenting and analyzing the contemporary costs associated with maintaining and/or developing agricultural dykeland and the costs associated with the development of upland. It will also recognize the evolution of land development equipment and identify modern equipment and technologies appropriate to maximize agricultural potential on both dykeland and upland. Primary outcomes from this research will involve determining the financial cost of improving under-utilized dykeland and a return on investment using contemporary technology and innovative techniques versus traditional methods. This will involve researching, and potentially testing, cutting-edge technologies used in agriculture and dyke maintenance including, unmanned aerial vehicles (UAVs), structure from motion (SfM) software, remote sensing, topographical surveying, land development machinery and precision agriculture. These technologies will be subjected to a cost-benefit analysis to determine their efficacy in modern dykeland management.

Perioperative Opioid Usage Quality Improvement [CDTS-PDF1]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system. Such a system could risk-stratify children and adults before surgery, so that pre-habilitation and optimized analgesic combinations can be employed to reduce persistent post-procedural pain. Artificial intelligence-augmented systems will also give clinicians actionable feedback on their practice, so they can learn how to improve their care, reduce their patients’ risk further, and
help them to recover more quickly from their procedure.
Postdoctoral fellows will lead day-to-day project activities and spend significant time working with both our clinical sites (St. Paul’s Hospital and BC Children’s Hospital) as well as industry partners (Careteam and Xerus) who will benefit from their methods expertise, ability to collaborate with clinicians and academic researchers, design, implementation, and evaluation skills.

Perioperative Opioid Usage Quality Improvement [CDTS-PDF2]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system. Such a system could risk-stratify children and adults before surgery, so that pre-habilitation and optimized analgesic combinations can be employed to reduce persistent post-procedural pain. Artificial intelligence-augmented systems will also give clinicians actionable feedback on their practice, so they can learn how to improve their care, reduce their patients’ risk further, and
help them to recover more quickly from their procedure.
Postdoctoral fellows will lead day-to-day project activities and spend significant time working with both our clinical sites (St. Paul’s Hospital and BC Children’s Hospital) as well as industry partners (Careteam and Xerus) who will benefit from their methods expertise, ability to collaborate with clinicians and academic researchers, design, implementation, and evaluation skills.

Radar-based Real-Time Detection of Overdose Incidents in Small Public Spaces

This project aims to train machine learning models that use millimetre-wave radar data to non-invasively detect health incidents, such as overdoses in public bathroom stalls. The partner, Brave Technology Coop, has developed a small, wall-mounted, radar sensing unit on which we want to directly deploy real-time gesture detection software, an instance of cutting-edge “Edge AI.” The unit can then immediately notify a responder if it detects a target incident, which otherwise would not be detected until a passerby notices.

The project will improve Brave’s ability to accurately classify these incidents, thereby strengthening their ODetect sensor product. Additionally, it will investigate other health-related gestures that may diversify the product’s target market.

Development of Freshwater Forecasting System using the SWAT-MODFLOW total water budget model

We will design and build a software suite for producing 36-hour forecasts of water flow rates and turbidity (cloudiness) at any point along the channels of the Upper Yellowstone River Watershed (UYRW). This forecasting system will respond to real-time sources of information on weather and upstream sensor readings, and will be designed for continual updates (via automatic daily recalibrations) based on modern statistical techniques. This project will substantially modify an existing software package (SWAT-MODFLOW) by introducing: turbidity forecasting; a more realistic accounting of snow buildup in the mountains; a calibration system designed for real-time updates; and an easy-to-use interface for running simulations and plotting inputs/outputs. The partner organization will be able to use this software for scenario-planning, and to obtain more accurate estimates of watershed metrics – both historical and current — that are crucial to managing human water users (public and private), wildlife, and the environment.

Handheld intraoral ultrasound for assessment of tooth-periodontium complex

Correction of misaligned teeth requires orthodontic braces treatment. Cone-beam computed tomography (CBCT) has been routinely used in orthodontic diagnosis and treatment planning in recent years. Its three-dimensional capability to view images has a significant advantage over traditional 2D X-rays. However, CBCT typically delivers more radiation than conventional dental 2D X-rays. As children and adolescents are the most common individuals getting braces to correct misaligned teeth, they are increasingly susceptible to harmful effects of excessive radiation, due to rate of cellular growth and organ development, and longer life expectancies. This proposal suggests using ultrasound techniques to study tooth-gum tissue complex and validating the ultrasound results with CBCT. Ultrasound method is non-invasive, cost-effective, and free of ionizing radiation. If ultrasound is found to be a reliable tool in imaging the tooth-gum complex, children and adolescents will benefit immensely from the decreased radiation risks and reduced cancer rate. The project’s outcome will significantly advance the commercialization of DenSonics’ ultrasound technology.

Maximizing Intrinsic Learning in an App-Based Approach to Language Learning

This research is focused on optimizing the language learning that occurs when students are allowed to practice English by conversing with native English speakers via a smartphone app, specifically Goji. Learning is best when the student maximizes the density of their practice, returning to practice often. This research will focus on the characteristics of the native English speaking “mentors” such as their personality, intelligence, and even physical appearance. We will assess the extent to which various characteristics predict how often a student chooses to practice and, through practice, the success level they achieve.
Our findings will be useful in terms of informing the mentor characteristics most relevant to student success. This will allow a more informed hiring process and, ultimately, a better learning experience for students.

Mobile Field Analytics Integration

VeriGrain is in the agricultural automated sampling and data management business. By providing representative sampling of the harvested grain provides the grain characteristics for maximum profit, helps to determine the risk of spoilage and helps farmers eliminate downgraded and rejected loads of grain at the terminal. Currently the samples are taken at the farm and are sent off for lab analysis to determine the quality and characteristics of the grain. However, advancements in technology through spectral analysis provide the opportunity to move some of the lab analysis out to the field. This spectral analysis allows for the determination of moisture content, protein analysis, disease analysis to take place quickly in the field to allow the farmer to make informed decisions with each load of grain they are harvesting. This project will seek to integrate aspects of spectral analysis into the sampling and data management aspects of the VeriGrain system.

A Feasibility Study on the Development of Oshawa Hydrogen Economy Hub

This project aims to investigate the establishment of a hydrogen hub in the Pickering and Oshawa region to reduce emissions from fossil fuels. Transportation sector is one of the major air pollution sources in Canada. Produced hydrogen will be used in vehicles operated with fuel cell that will be produced by GM and Hyundai. Fuel cells do not emit NOx, SO2, CO2 compared to conventional fossil fuels. Within the scope of this study, the proposed system will be investigated thermodynamically to optimize hydrogen production. In conclusion, this project aims to reduce air pollutants from fossil fuels, as well as to create new business opportunities, and to establish an economic hub based on hydrogen in Oshawa and its surrounding area.

Application of Actigate Targeted Performance Technology for the Treatment of Wheat Rust

Fungal rust infection of wheat is an ongoing problem in Canada and use of commercial fungicides is increasing while the problem of fungicidal resistance is also arising. This project aims to develop optimized fungicidal treatments for fungal rust infection of wheat. The issue of inefficient penetration of commercial fungicides will be addressed by applying a specific technology to enhance delivery of the active ingredient to target fungal pathogens thereby reducing the dose of fungicidal application. The mechanism of action of the resulting fungicidal formulations will also be explored. Decreasing the dose of synthetic chemical active ingredients will reduce their impact on the health of non-target organisms and provide benefits to the environment, while reducing costs for producers.

Investigating the performance of ultra-thin graphene oxide films for natural gas dehydration

The main goal of this project is to identify the key performance parameters of the membrane and collect some data on the membrane performance. To achieve this goal the intern needs to first develop a testing system to evaluate the dehydration performance of the membrane. After building the test system the intern will utilize the system to check the performance of a wide range of membranes and select which ones work best as well as factors that would impact the membrane performance. Then the test system will be brought to natural gas plant to verify the performance. Evercloak will supervise the intern and support out of lab research activities on their premise. Evercloak will benefit as the results of this project will inform key decisions within their technology development roadmap in addition to talent acquisition/training.

Follow up of horses treated with stem cells at eQcell Inc.

For over 10 years, eQcell Inc. has been treating horses with stem cells. In order to efficiently direct future research, a full picture of the efficacy of past treatments is necessary. This project will follow up with all clients across 8 clinics to collect an up-to-date snapshot of previously treated horses’ health and progression or regression from the time of treatment. These data will help generate hypotheses and narrow the research focus of the company to where stem cells may be best applied. This work fits within the overall vision of eQcell to develop novel treatment strategies for various equine diseases and conditions that will ultimately lead to a reduction in the number of Ontario horses affected by disease, reduce the number lost training days due to serious conditions resulting in a net positive impact on the Canadian and global equine industry.