Innovative Projects Realized

Learning based MPC for tissue manipulation

Robot-assisted surgery (RAS) has revolutionized surgical procedures, offering advantages over traditional methods. Currently, surgeons control robots for tasks like suturing and organ resection, leading to physical strain while the robot helps at the lower level by scalling down the movement and reducing hand tremor. These tasks are intricate and demand high dexterity and skill, leading to physical and cognitive strain for surgeons when performed manually. Automating these tasks presents an opportunity to improve surgical outcomes, mitigate human error, and reduce strain on surgeons.
Various control algorithms, including model-based (e.g., model predictive control) and model-free (e.g., reinforcement learning) approaches, have been developed. Model based control ensures sfety and stability however, their relience on accurate model of the system poses challanges in dynamic surgical settings. Model-free, specifically RL based control offeres adaptability by learning form the environemnt, however they requiers extensive interaction with the environemnt posing problems of safety and stability specifically during the initial phases.
To overcome these limitation we have porposed an (event-triggered) learning MPC for automating tissue manipulation. The proposed control uses accumulated error to trigger the Gaussian process and update the tissue model, thus adapting to changing dynamics online, while ensuring the safety and stability by imposing constraints.

Implementation of Analysis Algorithms Into Precision Feeding Application

This project is to continue to implement data analysis algorithms for real time analysis of precision feeding data provided by a novel custom poultry precision feeding system. In addition if time allows work on some computer vision algorithms to detect the presence of a bird in a feeding station.

Animal Health Technology Internship

With the DVM shortage, our registered veterinary technologist’s are stepping in to fill in areas where they are able to decrease some of the burden for our veterinarians. This is unique and puts our technologists in new roles than they may have not traditionally been in. We are in a time of innovation and change in the veterinary industry here in Alberta. Our technologists will have an increased expectation of client interaction, while also providing excellent nursing care. Communication and educating our clients and working within a team have never been so important. The communication and education can and should happen in our marketing also which is a new approach for our business.

Our project is to increase the utilization of registered veterinary technologists in offering wellness services to our clients. The project will utilize the NAIT AHT Co-Op student in our marketing of this innovative service, development and improvement of standard operating procedures/training for our team and a review of client feedback following the innovation to our product (wellness service delivery) and marketing strategy

Development of Deep Learning Techniques for Predicting Dynamic Responses of Local Elements in Complex Structural Systems

In our proposed project, we aim to predict the behavior of large structures like buildings and bridges and key devices upon the large structures in response to natural hazard such as earthquakes. By combining cutting-edge deep learning techniques with the multi-fidelity concept, we’re developing a deep learning model that can predict the response time histories of not only the large-scale structure but also key devices upon the structures under various seismic loads. Furthermore, utilizing hybrid simulation equipment available at the University of Toronto, this model will be refined and validated through experimental setups that mirror real-world conditions, enhancing its accuracy and reliability. This research, a collaborative effort between University of Toronto and Seoul National University, not only pushes the boundaries of engineering and artificial intelligence but also holds promise for making our communities safer and more resilient. The expected outcome is a significant advancement in structural engineering that benefits both institutions by enhancing their research capabilities and contributing to a safer, more predictable future in facing natural disasters.

Business strategy – Europassport

EuroPassport aims to strategically position itself in the market with the introduction of a new SaaS platform to disrupt the legal immigration industry. This project focuses on comprehensive research and analysis to understand market dynamics, customer needs, and competitive landscapes.

Indigenous contestation of natural resources in the Lacandon rainforest in Chiapas Mexico

The main objective of this research project is to develop a better understanding of the ongoing struggle over natural resources in the Lacandon forest, a region that includes the Montes Azules and Lacantun Biosphere Reserves. The Lacandon forest is a resource rich area known for its fertile soil, sub-soil and huge potential for ecotourism. Yet, the five different indigenous groups inhabiting the region do not have equal access to these resources. In order to better understand the inequality experienced by the inhabitants of the Montes Azules and Lacantún biosphere reserves, this research project is designed to analyze: (1) the history of the founding and management of these reserves; (2) the conservation policy promoted by Mexican environmental authorities in the Lacandon forest; (3) the different political, social and cultural factors that have contributed to restrict access to economic resources and to aggravate the conditions of inequality of the populations in the biosphere reserves; and (4) the counterproductive effects engendered by Mexican environmental policy in the biosphere reserves.

Technical Process Technician & Data Management Assistant

??Bryan & Company LLP is a local Edmonton law firm (approx. 100 full-time employees) founded in 1928. Early in 2023, the Company welcomed a new IT Manager who is tasked with developing the technology roadmap for the next strategic planning cycle that will bring the Company to its centennial in 2028. ?Bryan is also in the midst of evaluating our technology needs and is contemplating a single, more all-encompassing technology solution. In preparation for this, we will need to clearly document all of our internal processes. ?In 2024, Bryan & Company will commence an upgrade of our document management system; this change includes moving to a cloud-based solution and the new technology will be integrated with Microsoft Outlook.

Port of Halifax – Aquatic Ecosystems Literature Review

The Halifax Port Authority (HPA) is launching a study that will examine aquatic ecosystems in the Halifax Harbour. This work will support HPA in better understanding local ecosystems that have the potential to be affected by port operations and thus determine the port’s zones of influence. This research study will help to establish benchmarks for aquatic ecosystem presence, health, diversity, vulnerability/resilience, and fecundity, in the Halifax Harbour and will support HPA in developing an approach to minimizing the potential impacts of the marine transportation sector within the port’s zones of influence. By gaining a better understanding of aquatic ecosystems in the Halifax Harbour, HPA can begin to prioritize efforts to minimize potential impacts.

Predicting Material Properties from Electronic Band Structures: Integrating Machine Learning with Computational Modeling Techniques

The project involves the development of a machine learning model which can predict targeted properties of materials from their band structure. Computational modeling methods, such as ab initio (quantum chemistry) calculations, Density Functional Theory and Molecular Dynamics, enable us to calculate properties of materials from their crystalline structure. The band structure is a representation of how the electrons are distributed in the material and how they behave. This is linked to many properties of the material, such that visualizing the band structure can elucidate the underlying electronic properties of materials. However, establishing such a correlation is far from trivial and necessitates extensive and intensive calculations. We envision that machine learning could bridge easily computed band structures with electronic properties of interest, namely total magnetization, piezoelectric and dielectric constants.

Life Cycle Assessment of Flame Retardant Textile used in the Production of Occupational Safety Clothing: A Case Study of the Personal Protective Equipment Industrytudy of the

The project is on Life Cycle Assessment (LCA) of Flame Retardant Textile used for the Production of Occupational Safety Clothing with focus on the Personal Protective Equipment (PPE) Industry, and the results of the research will provide data for the partner company to be able to provide information and guidance at different steps in the manufacturing and garment’s life cycle that will help decision-makers better understand how to make meaningful steps towards more sustainable decisions in this industry.

Designing visualization and analytical tools for citizen- and data- driven research in agroecology

To respond to the lack of digital tools for small-scale farmers, our team has been developing Litefarm (https://www.litefarm.org), a free and open source multifunctional web app which can be used by farmers to enter data for farm management, obtaining organic certification, and participatory assessment of agroecological outputs. Launched in 2020, LiteFarm is now the world’s first community-led, not-for-profit, digital platform joining farmers and scientists, and is being piloted independently by over 2500 farmers in more than 110 countries.The intern will join our team to develop a data dashboard for researchers and Litefarm users, while contributing to the development of specific statistical and mathematical methods to model green house gas emissions.

CityHive/REACH-Cities

CityHive is a Metro Vancouver-based non-profit organization on a mission to transform the way that young people are engaged in shaping their cities: in city planning, decision-making processes and urban sustainability issues. This project will support CityHive to complete a comprehensive evaluation on CityHive’s programs and youth engagement impact, including their CityShapers in Schools, Urban ReVision, Youth Climate Innovation Lab and other programs. The output of this project will be used to better inform the design and development of CityHive’s future civic education and climate action programs and provide greater direction for CityHive’s new Strategic Plan.