Projets novateurs réalisés

Developing a Guidance List for repOrting Bibliom AnaLyses (GLOBAL)

A bibliometric analysis is a way to measure and analyze the impact and productivity of a person, organization, or field of study using the number and types of publications, citations, and other metrics. It can be used to identify patterns and trends in research, evaluate the performance of individual researchers or research groups, and identify areas of growth or decline in a field. The Guidance List for the repOrting of Bibliometric AnaLyses (GLOBAL) is a set of guidelines that will help researchers and authors report their bibliometric analyses in a consistent and transparent way. Over recent years, a large increase in the number of bibliometric analyses have been published, but little guidance is available on how to report it properly. This lack of guidelines is a problem, because it makes it difficult for others to understand, interpret, and critically assess the quality of the research. To address this issue, the intern and team propose to develop a set of guidelines through a process that involves reviewing existing literature and consulting with experts, then testing and refining the guidelines through surveys and a pilot study.

Enhanced & Editable Deep Fakes

Traditional Computer Generated Imagery (CGI) splits the process into separate stages: we model geometry; apply textures and define surface properties; animate motion; and apply lighting; before combining the elements when rendering imagery. Deep-learning methods such as Deep Fakes, or NeRF train a network to combine many of these steps into a single network, and are able to produce convincing results in this way. By combining these different aspects of image generation into a single unit, these networks also make it challenging for an artist to edit the properties of the network in an intuitive way. This is because the underlying representation, which is typically a latent vector, doesn’t have a simple connection with the high-level controls an artist expects. We wish to explore ways of giving our artists intuitive ways to control neural rendering. We also want to explore ways of enhancing our results by adding additional inputs to the process.

AI-driven Predictive Models and Consumer Insight for Trade Optimization Improvement

The proposed project is to develop AI strategies to provide precision marketing through consumer segmentation and recommender systems, as well as to promote events that shall meet various business goals for retailers and Unilever. Successful outcomes will feed into an On-Demand AI Engine aimed at improving consumer engagement and pricing strategy in the consumer packaged goods sector.

Prototype development for a system to generate on-road wind conditions within automotive wind tunnels

Wind tunnels are an important tool that are used for automotive performance testing. The focus of the research project is on the development of a system to be used in wind tunnels that can simulate gusts and sweeps that vehicles often experience while on the road. This is important since it can enhance vehicle testing capabilities for new vehicle designs with improved performance such as greater fuel or energy efficiency. The intern will research methods to cause gusts and sweeps events using aerodynamic surfaces and mechanical systems. Ultimately the goal is to design a build a prototype system and demonstrate gusts and sweep generation through measurement and analysis of effected air flows in the wind tunnel.

Towards AI Assisted Training Tool: Automated Identification of Calcifications in Optical Coherence Tomography Breast Tissue Images.

Breast cancer is the most common cancer (excluding non-melanoma skin cancer) in 109 countries including Canada. Approximately 70% of the breast cancer surgeries are breast-conserving lumpectomy procedures. Histopathology analysis typically require 2-4 days, resulting in the need for a second surgery if a margin is positive. Perimeter Medical is developing advanced Optical Coherence Tomography (OCT) imaging tools to visualize margins at the time of surgery. One of the keys needs is the training of medical professionals who would interpret images during surgery. Intern will contribute to development of an AI based solution that will have a click to reveal functionality to identify different features in OCT images. Intern will develop a binary classifier to identify calcifications which might be an early sign of cancer. Intern will learn various aspects of AI development from data labeling, curation to model building and optimization while Perimeter Medical accelerates the development of training tool.

Implementing Strategies for Community Engagement and Development

The work by the interns will help Oak Table to revamp and improve services delivered through several programs, improve communication, improve outreach, assist with the food preparation and assist with recovering from Covid-19 pandemic. These projects will assist Oak Table in recruiting additional volunteers and strengthening organizational capacity, specifically in regards to recreational, educational, and cultural programming needs as they move forward from the pandemic. These projects center around community building and engagement, and will help Oak Table to better fulfill its mission of providing support, hospitality, and advocacy in a safe and respectful community. This project will also run for 5 years. Each subsequent intern in 2024 and on will continue to build on the existing work to date and continue to support Oak Table by aiding in service delivery, improving service delivery and helping Oak Table continue to recover from Covid-19 and the significant volunteer loss.

Student Support for New Content for RaY Programs

Resource Assistance for Youth, RaY, is a street level non-profit organization that works with youth, ages 0-29, providing integrated programs and services. Their Hub Model is designed to provide everything street and marginalized youth need on their terms. This includes health supports, housing supports, mental health and addiction supports, basic needs, drop-in services, street outreach, employment and training, and cultural supports. Based on their personal experience and connections with youth, RaY has developed new and innovative programming such as an employment and training program that responds to the emerging needs of youth.
The Level Up! Education and Training program, provides education and training to youth between between 18-29, targeting youth that have a connection to Employment an Income Assistance (EIA) and/or CFS. The level up program has two streams. First, the Level Up! Launch Pad, a 9 week paid training program offered in an alternative classroom environment which focuses on building life skills. Second, the Level Up! Lift Up, a 7 week paid training program in a classroom atmosphere where you will gain skills for the desired job and how to keep the job.

New Directions – Training and Mentoring Improvements

The T.E.P Program within the organization of New Directions works with young woman, individuals involved within the criminal justice system and those who have been diagnosed with pre-natal exposure (FAS, FASD & ARND) between the ages of 12-17 who happen to be indigenous. Their goal is to offer empowerment of the individuals that they work with, through the means of introducing the girls within the program to their indigenous culture/ways, developing tools that allow them to engage in social environments and educate them on matters such as emotional well-being, sexuality and reproductive health issues. This, which happens to be all done as the mentor and participants develop an interpersonal relationship to understand one another in the different scenarios they find themselves in, that challenges these ordeals.

Data Farms’ Crop Monitoring Unit Design & Development

Data Farms is a precision agriculture internet of things (IoT) company using sensors to monitor crops in real-time. We help farmers use resources more efficiently, saving fuel and fertilizer costs, and optimize indoor and greenhouse environments to improve crop yield. Custom alerts allow farmers to react fast when conditions change to avoid crop loss and crop failure. This project will enable Data Farms to design and produce outdoor crop monitoring units for a proof of concept project, partnering with farmers in NL with the plan to expand to other markets in Canada. Canada’s harsh environment increases the risk of crop loss and crop failure. Real-time environmental and soil monitoring allows farmers to react fast when conditions change, and improve resilience in the changing climate.

Maria Edison – Strengthening International Canadian Trade Relations for Sourcing and Innovating Critical Technology and Advanced Manufacturing Processes through Market Research

The intern will conduct a multidisciplinary market research project on international critical technology and advanced manufacturing techniques, with the goal of identifying viable strategic partnerships for Canada. They will create documents, presentations, and brochures for various technologies to spread awareness of commercial opportunities and encourage sector growth in Canada. In partnership with the Cansbridge Fellowship (partner organization) and Dr. Brent McKnight (academic supervisor), they will identify viable strategic partnerships for Canada by considering commercial needs and alignment with Canadian policy goals. The academic supervisor will provide a breadth of knowledge on strategy and strategic partnerships, while the partner organization will provide mentorship and a global alumni network to support multidisciplinary research across industries. The direct benefit to the partner organization is achieving their mission of promoting global collaboration and attracting Canada’s global-minded youth to the program. This will be achieved through additional social media marketing and making the market research accessible to all.

Production of Sustainable Aviation Fuel and other renewable transport fuels via a modified Fischer-Tropsch Synthesis Technology

Sustainable aviation fuel (SAF) is a description increasingly used to refer to aviation turbine fuel (jet fuel) that is produced from renewable and sustainable resources. The use of SAF for commercial air transport holds the promise of reducing the fossil fuel footprint of this industry. However, in North America it is at present not legal to commercially operate an aircraft with 100% SAF. The purpose of this project is to produce fully formulated synthetic jet fuel in sufficient quantity for it to be submitted for qualification under ASTM D4054, which describes the standard practice for qualification and approval of new aviation turbine fuels and fuel additives. For this purpose, batches of kerosene must be produced and pre-qualified to the amount of 300 L (80 gal) that can be submitted for qualification under ASTM D4054 for tier 2 testing. Specifically, the fuel process must reflect the process description for which the fuel is qualified. Due to the importance of having 100% SAF qualified, this project leads investment in a demonstration scale facility. The conversion steps involved in the process include acid catalysis, metal catalysis, and bifunctional metal-and-acid catalysis. Separation will be by distillation.

Kerem Topal Ismail Oglou – Leveraging AI and Data Analytics to Minimize Waste Generation in the Fashion Industry and Drive Sustainability.

During the internship, the intern will focus on three primary objectives related to the commercialization of sustainable solutions for the fashion industry:

Conducting a comprehensive business market analysis on retail/consumer goods industry standards for demand forecasting.
Extracting, cleaning, categorizing, and analyzing historical sales data to drive insights into consumer purchasing behavior and seasonality.
Assisting the engineering team in creating and improving an AI model to predict better consumer demand and production volume needs.

The intern will combine their passion for data analytics, sustainability, and technical skills to research demand forecasting techniques, analyze the company’s data, and visualize patterns to identify increased or decreased demand periods. This analysis will help determine overproduction periods and estimate waste generation that could have been avoided with better forecasting.
The intern will also collaborate with the engineering team to improve an AI model that predicted consumer demand and required production volumes more accurately. This model will help the fashion company minimize overproduction, waste generation, and become more sustainable.
Throughout the internship, the intern will benefit from the guidance of their academic supervisor and the partner organization, gaining valuable experience and expanding their professional network. They will develop problem-solving, communication, and project management, enhancing their career prospects.