Innovative Projects Realized

Development of artificial intelligence algorithms for microbiome-based classification of disease

The goal of this project is to help build artificial intelligence algorithms for the diagnosis of disease using data derived from the human microbiome. This project will be focused on implementing new statistical methods to reduce “noise” found in data from different sources, allowing for us to improve the training of artificial intelligence algorithms. Another focus of this project will be to implement new types of models that are better suited for microbiome data, allowing for more accurate predictions. With these improved models, Phyla (partner org) will be able to more accurately detect disease from the microbial profile of stool samples.

Analyse et implantation d’un système de suivi et évaluation de la performance dans une organisation canadienne de développement international

Comme toute entreprise, les organismes sans but lucratif (OSBL, OBNL ou ONG de leurs petits noms) tendent à croitre avec le temps et donc, à élargir leur offre de services et les projets du même coup. Cette expansion de l’organisme nécessite donc des changements au niveau de la gestion pour continuer leur bon travail tout en restant efficace. L’objectif principal de ce projet de recherche est donc de faire un bilan des pratiques en gestion de projet dans une organisation à but non lucratif et voir les pistes d’amélioration possibles pour ce qui a trait au suivi et contrôle des projets, pour ensuite leur fournir des outils concrets et adaptés à leur milieu. Cela leur permettrait, entre autres, de gérer plus efficacement plusieurs projets en même temps, ainsi que d’avoir une bonne vue d’ensemble des projets en cours en tout temps.

Investigating the Thermal Properties of the Moon with the I-SPI (Intelligent Sensing and Perception in Infrared) Imaging System

Water ice exists near the Moon’s poles due to the very cold temperatures caused by the limited exposure to direct sunlight in these regions. To understand the extent of water that exists on the Moon, we need to locate the areas where the temperatures are favourable for the preservation of water (less than -175°C/-280°F). To accomplish this, Mission Control has proposed an instrument, known as I-SPI (Intelligent Sensing and Perception in Infrared), to map the Moon’s temperature. I-SPI is currently in the research stage, and Mission Control requires the intern’s expertise to assist in the design and development of I-SPI for a future rover mission to the Moon. Specifically, the intern will lead a science investigation to evaluate the thermal properties of the Moon to support Mission Control in determining the temperature requirements needed to build I-SPI.

Ultrasonic and microwaves cannabis oil extraction methods for targeted nanomedicines delivery

Today’ssociety consumes chemicals daily in its food, in care products but also thecomposition of pharmaceutical drugs, research on methods of extracting cannabisoils and their therapeutic effects support and emphasizes-for the productionof more effective and beneficial drugs for health with fewer side effects,thanks to its virtues and antioxidant, anti-inflammatory and neuro-regulatorycapacities, capable of contributing to the stabilization /improvement of acertain syndrome (autoimmunity, psychiatric illnesses, viral pathologies). thenew microwave-assisted extraction processes and ultrasonic-assisted extractionnot only reduce the quantities of solvents used for extraction and energyconsumption, but are also ecological processes.

Moderating speech in private online spaces: A public consultation

How do ordinary people in Canada want to see their speech to be policed on private online platforms? Should government, platforms, both, or neither be setting more limits on online expression? Our consultation project will guide members of the public through a ranking of their core values, provide background information about the consequences and trade-offs to different standards and approaches to content moderation, and ask them to make decisions through a sample of fictionalized content moderation scenarios. The final product will teach us something about their general public moderation preferences when asked to choose between more complex options than a simplistic right to freedom of expression versus potential online harms dichotomy.

Student Web Portal

The proposed research project proposes to study how to best provide a student learning portal for children of age 8 to 13 years old. Such system requires to carefully reviewing the literature both in terms of designing for children, and in terms of interpreting the results of usability studies with children. Designing an effective student learning portal will demand of the intern to take into consideration what is attractive for this age group and how to make those students willing to spend some time online for their study. This includes looking at colors schemes, type of activities, type of motivations, etc. Another difficult task will be to extract valuable information from the children when testing the interface. For the partner company, this portal is a critical building block of their business: no company today can remain state of the art without providing online environment for their students.

Functional MRI in Neuroscience (In framework of IRTG 2150)

Pollination efficiencies of flower visitors of agricultural crops

Understanding Question Difficulty and Student Ability in Mathematics Assessments

Education software is abundant on the web, but few support the analysis of students’ performance and test difficulty over user-defined questions and learning objectives. The idea of this project is to create a computer program to provide educators with insights on student performance on assessment items and perceived and actual assessment item difficulty within fine-grained learning objectives. This tool also provides departments with key metrics to identify potential course delivery issues and compare students’ understanding of course material year over year. The software proposed here estimates item difficulty and student ability by building a mathematical model from student performance data on assessment question items. In addition, an interface is envisioned to help educators and students better understand model results based on fine-grained learning objectives.

Long COVID and cardiac function

Recent research has confirmed the lethal ‘acute’ effects of the COVID-19 virus on the heart, but there is a growing concern and increasing number of those individuals infected by the virus to remain ‘chronic’ as long-haulers, i.e., Long COVID. There are estimates that as many as 40-60% of individuals infected continue to experience symptoms for up to 12 weeks, and as many as 10-20% continue to experience symptoms longer than 12 weeks. Thus, the proposed research will investigate the effects on Long COVID on the heart using the LLA Recordis™ cardiac sensor and echocardiography. We have demonstrated previously that the LLA Recordis™ cardiac sensor can measure and record how the heart is contracting and relaxing with every heartbeat. The current research will help us to understand the long-term complications on the heart. This research will assist LLA Technologies Inc. to enter the global market to commercialize their cardiac sensor and become a leader in Canada and globally for cardiac diagnostics.

Detection and investigation of downtime causes

The use of machine learning and big data in production is still in its early stages as only a limited amount of data is used. This research aims to improve productivity by determining factors affecting downtime. Changeover’s time and performance rate improvement during production will be addressed considering not only equipment data and product data but also a variety of factors such as raw material consumption, environmental effect on material properties, production sequences and operators’ impact.
This project will include an evaluation of state-of-the-art techniques, the selection of data sources required for performance loss and changeover times analysis, the preprocessing of data, and the testing of different machine learning and big data techniques to identify the main factors impacting the downtime in production.

Integration of Electric Vehicles into the Power Distribution System

Electric vehicles (EVs) have become increasingly popular because of their high efficiency and sustainability. However, EVs represent an intensive electric load. Their penetration to the power system poses significant challenges to power distribution system operation and control, such as voltage drop and transformer overload. This study will evaluate the impact of EV penetration on Saskatchewan’s urban residential power distribution system and develop plans to cope with the EV load growth. Actual EV charging profiles will be analyzed to understand the characteristics of the EV charging. Individual and aggregated EV charging models based on Saskatchewan’s local situations will be developed. The impact of uncontrolled EV charging load on the voltage drop of 120/240V systems and 14.4 kV to 120/240V service transformers will be evaluated. Optimal EV load aggregation methods and smart charging algorithms will be developed to cope with the negative impact.