Projets novateurs réalisés

Rural Food Production with Passive Solar Greenhouses

This project will explore how a rural community’s focus on a local/regional food system can augment their economy and outline the feasibility for a passive solar greenhouse for food production in the northern, rural town of Athabasca, Alberta. Using a community economic development model, the project will incorporate resident input in determining design elements as well as business planning options, and working with Athabasca University’s Centre for Architecture, share a viable prototype for a sustainable social enterprise.

NutraForge Product development Acceleration

The proposed project focuses on developing advanced AI technologies to enhance the partner organization’s platform. The intern will work on integrating and optimizing AI-driven solutions, such as personalized nutrition analysis and professional-client data sharing, using tools like OpenAI’s models and Retrieval Augmented Generation (RAG). By strengthening the AI workflows, including speech recognition and data processing, the project will enable more accurate and scalable analysis. This development will benefit the organization by improving the platform’s ability to deliver personalized recommendations and insights, making it a more powerful tool for both users and professionals.

Develop a Reverse Recipe System using Sensory Data inputs and Machine Llearning to Create Gut-friendly Versions of Traditional Beverages

Kulture Rebellion a Canadian-based company is at the forefront of innovative fermentation technology, specializing in developing gut-friendly beverages. The main activities of Kulture Rebellion include researching and developing new fermentation techniques, producing gut-friendly beverages, and experimenting continuously to enhance the sensory profiles of their products. The primary innovation challenge Kulture Rebellion faces is developing a highly accurate and efficient reverse recipe system. This system needs to utilize sensory data inputs from traditional fermentation processes to create gut-friendly beverages that replicate the sensory experiences of traditional drinks (Yu Haukun et al., 2022). This challenge is complex because it involves continuously processing and analyzing vast amounts of sensory data and refining the algorithm for improved accuracy and adaptability.
In order to address this challenge the company wants to develop and refine a reverse recipe system using sensory data inputs and machine learning to create gut-friendly versions of traditional beverages. This system aims to accurately replicate the sensory profiles of traditional drinks while using pre-specified gut-friendly ingredients. The approach involves several phases to ensure the project’s success. Initially, the project will focus on scoping, legal paperwork, project planning, budgeting, intellectual property assignment, and obtaining stakeholder sign-off.

In the development phase, the WIMTACH-CEDA team will create a web portal to input measured fermentation parameters and collect data. The team will then integrate OpenAI to convert the AI model’s output data into human-readable sensory outputs. Additionally, the AI model, developed in a previous phase, will be optimized and deployed using the fermented data to predict sensory data. The portal will facilitate the collection data from fermentation trials conducted by Kulture Rebellion and used the data from the fermentation to optimize the AI model for the higher accuracy.

Enhancing atomic quantum memory through collective atomic behaviours

Quantum memories are key components in the development of a quantum network. Among their many uses, these memories will facilitate the synchronization of quantum signals at repeater nodes, which are a crucial technology for extending the long-distance reach of quantum communications. Quantum memories facilitate the transfer of quantum information from electromagnetic signals into matter-based quantum states through careful engineering and control of the light-matter interaction. This project will explore the preservation of true quantum information in an atomic quantum memory, beyond established proof-of-concept demonstrations with attenuated classical signals, by relying on expertise from both the home and host institutions in quantum optics and atomic physics. The project will develop the tools for an experimental demonstration proving the preservation of quantum correlations and entanglement in an Autler-Townes splitting atomic quantum memory. Additionally, the project will include theory work exploring how the atomic medium can be enhanced through many-body and multi-atom effects to improve the storage time and the preservation of quantum information.

Ground operations in the aviation industry

This research project aims to solve the problem of fragmented data in the aviation industry by developing a system that integrates and analyzes various data sources. The goal is to create dynamic dashboards that provide real-time insights into safety, compliance, and operational status for different users, such as airlines and ground service providers. The focus will be on ground handling operations, including fueling, de-icing, and passenger handling. By aggregating data, developing analytical systems with machine learning, and creating user-friendly dashboards, this project will help stakeholders make informed decisions, enhance operational efficiency, and uphold safety standards in the aviation industry.

The relationship between dark matter and peculiar velocities: Newtechniques and tests with numerical simulations

During this research I will contribute to our growing understanding of dark matter and dark energy by applying and extending the theoretical framework of simulation and modeling of how dark matter couples via gravity to induce measureable peculiar velocities. As a result of this work Dr. Lavaux and I hope to produce a large set of randomly generated universe simulations which can be used to confirm how peculiar velocities and the systematic and random errors associated with measuring them can depend upon the cosmology of the simulation. In working with both Dr. Lavaux, Dr. Jens Jasche, and I will also contribute to constructing a constrained simulation matching the 2M++ catalogue. I will also work with Dr. Lavaux in developing an alternative to maximum likelihood and minimum variance velocity reconstruction measures for cosmology surveys. These works will help understand gravity and constrain the formation history and composition of the universe.

An Exact Method for the Quadratic Knapsack Problem Through Binary Decision Diagram

This Mitacs Globalink project, part of a PhD thesis titled “Exact and Heuristic Methods for the Quadratic Knapsack Problem (QKP),” aims to develop new optimization techniques for solving the QKP, a problem with significant applications in industries like logistics, finance, and electronics. Building on prior successes, including a dynamic programming heuristic and an algorithm using Binary Decision Diagrams (BDDs), the project will focus on creating a branch-and-cut algorithm specifically for the QKP. This collaboration between experts from Université Laval, Université de Québec à Montréal, and Carnegie Mellon University integrates advanced BDD techniques with QKP models. The research outcomes are expected to contribute significantly to combinatorial optimization, with broad applications across various industries, enhancing global advancements in solving complex optimization challenges.

Experimental investigations on metabolic and transcriptomic profiling of Rhodococcus opacus cultivated on lignin stream

In recent years, lignin valorization has gained increasing attention in both academic and industrial sectors, hoping to achieve salient breakthroughs in lignin metabolism. Many studies have pointed to a promising approach using microorganisms particularly bacteria for lignin valorization through a bio-funneling approach, converting it into products of biotechnological interests. Thus, this project aims to contribute to advancements in the bioconversion of lignin stream (upstream and downstream), a highly abundant industrial by-product in both Canada and Brazil, which is currently burnt for heat and electricity production in the paper mills, posing significant environmental risks. This project will essentially focus on understanding the genetic and metabolic mechanisms involved in converting phenolics and lignin by Rhodococcus opacus, a bacteria capable of consuming aromatic compounds and producing lipids from this substrate.

We’re Only Human: Enhancing a Cultural Sensitivity Training Virtual Reality Prototype in Early-Stage Development

Objective: Draw on Researcher Expertise to Assist the Calgary Catholic Immigration Society (CCIS) in their Development of a Virtual Reality (VR) Cultural Sensitivity Training System

Background: Through informal testing with eight CCIS employees, a design concept introduced in the “Preconceptions” application that is a VR cultural sensitivity training program. It creates a digitally immersive environment that tracks people’s eye movements to reveal implicit biases (e.g. show how one looks longer at a visible minority in a retail store). Patterns are presented to reveal implicit attentional bias.

Current Inniative: CCIS needs support systematically gathering and interpreting high-quality information for the purpose of continued innovation, development, and deployment. As such, CCIS is partnering with a social scientist that has a strong research background in community-based research. Since the social scientist is an expert in qualitative and quantitative data, he will be able to support an intern in developing high-quality information gathering strategies that includes sampling a diverse group from various demographics. The partnership will provide maximally effective information for improving an innovative cultural sensitivity training product.
An intern will learn to facilitate the use of the application: preparing the VR setup to ensure all technical aspects are functioning correctly, guiding participants through the eye-tracking activities, and analyzing data to identify patterns ensure participants understand how to interpret their data and reflect on their biases. The supervised internal will design questionnaires and focus groups for collecting feedback focusing on the effectiveness of the application in achieving learning objectives.

Outputs: (1) High-quality experience in a community-university partnership that provides transferable skills for a student-intern. (2) High-quality information-gathering tools such as effective surveys and focus group guides that enable further development and refinement of the VR system. (3) Improved efficacy of an innovative application from participant feedback and technical observations distilled into recommendations.

Stage au Festival Akousma

Le projet vise à implémenter une culture de la médiation dans la programmation des activités de la société de diffusion Akousma afin de faire mieux connaître les musiques numériques immersives.

Différentes activités, actuellement en projet, pourront être mises en place auprès de publics néophytes afin de partager et rendre plus accessibles ces façons de faire de la musique. Ces activités pourront être présentées aussi bien à des publics jeunes, d’âge scolaire, qu’à des personnes âgées qui feront la découverte de ce type de musique mal connu.

De nouvelles technologies peuvent aujourd’hui permettre de présenter des concerts de type alternatif qui peuvent permettre à un public peu habitué à la salle de concert de découvrir un monde sonore nouveau ; on pense aux écouteurs à conduction osseuse, par exemple, qui peuvent être utilisés lors de « soundwalks » (ou excursions sonores) et aussi à des haut-parleurs sans fil qui peuvent être utilisés pour animer des places publics.

À la fin du stage, la société de diffusion de concerts aura en main les outils nécessaires pour incorporer ce volet d’activités de médiation à sa programmation régulière et elle pourra également partager son expertise en la matière auprès de ses partenaires qui occupent un créneau similaire. À terme, ce sont les musiques numériques en particulier, mais aussi les musiques nouvelles en général, qui bénéficieront de ces développements. La stagiaire aura acquis une expérience non-négligeable en organisation de concerts et d’autres activités, et elle aura pu mesurer l’impact de ses interventions sur les publics visés.

Digital Twins for City Challenges

The goal of the proposed project is to develop a Digital Twin of a city to enhance urban planning and emergency management. University of Calgary faculty members and students will work with the City of Calgary on developing a Digital Twin of the City of Calgary as well as an application prototype of this twin to evaluate its usefulness in supporting the overall goal. Digital Twin technology bridges between the physical and virtual world, enabling real-time data management, analytics, simulation and control.

Global GNSS Interference Detection and Impact Analysis for Aviation Safety

Global navigation satellite systems have significantly improved aeronautical navigation over the past decades, providing a safe and precise means of navigating airspace. Unfortunately, recent years have seen a worrying increase in GPS interference incidents in aviation, which is alarming because GPS is crucial for modern aviation navigation and safety. GPS interference, through jamming and spoofing, can lead to navigational errors, increased risk of accidents, and compromised air traffic control. IATA’s Global Aviation Data Management (GADM) team is preparing reports on GPS signal loss using data from the Flight Data Exchange (FDX) program to address this. They plan to extend their analysis globally using ADS-B data to identify safety issues. Various methods, including statistical analysis, software-defined radios, and machine learning algorithms, are being explored to detect GNSS jamming and spoofing. Long Short-Term Memory (LSTM) networks are particularly effective in modelling aircraft trajectories using ADS-B data because they can handle sequential data over long periods. This project aims to improve the detection of GNSS interference by applying advanced machine-learning techniques to global ADS-B data. The GADM team will provide a secure data-sharing environment, and ETS researchers will implement methodologies to detect interference patterns, enhancing aviation safety.