Projets novateurs réalisés

Structural performance of novel sandwich panels under flexural, shear and axial loadings

Rising material costs, lack of quality control, labour shortages, challenging climates and significant on-site waste continue to be the challenges encountered by the Canadian construction industry. The collaboration between the research team and NEXII aims to develop the much-needed technical know-how for the new generation building panel products to address these challenges. This research concentrates on novel sandwich wall panels for use as the seismic force-resisting system (SFRS) of buildings with different archetypes, sizes, and connection systems. The seismic force modification factors are determined based on existing experimental test data and advanced dynamic analysis using finite element techniques.

Developing and enhancing clinical partner site management and training systems

Oncoustics is a startup, focused on AI-based diagnostics and point-of-care ultrasound. Data collection and clinical partner site management are critical operations for Oncoustics as they play a pivotal role in ensuring the accuracy and reliability of the ultrasound data collected. Clinical operation management and the resulting data collected are essential for conducting meaningful clinical research and for training our machine learning models for early detection of liver disease. This projects objective is to optimize and modify existing clinical site management systems for data collection through system assessment, development of site management plan, updating existing training systems and deployment of these updates to our clinics. As the company is growing, and its’ clinical partnerships are increasing, a scalable management system needs to be developed. Effective management of clinical partner sites helps to establish strong relationships with healthcare providers, fosters compliance with industry regulations, and ensures that operational challenges are identified and addressed promptly and improves our overall data collection and machine learning pipeline.

Preserving Cultural Heritage in Rural Nova Scotia

This project will result in an online site showcasing Festival Antigonish Summer Theatre’s archives. These archives include historic materials such as programs, promotional materials, promptbooks, and other theatrical ephemera. Festival Antigonish Summer Theatre is a bastion of rural Nova Scotia theatre. This digital archive will make these materials available to the community and to researchers: right now, these materials are only available on site in the basement of the Bauer theatre–and only a handful of people know what is there in the first place. The digital project will help showcase the important work of Festival Antigonish Summer Theatre, past and present, emphasizing the people who create arts culture in rural Nova Scotia. This project will benefit researchers in fields such as history by making previously unknown materials findable; will benefit the theatre by highlighting their work and bringing people to (and back to) their artistic home; and will benefit the community by reflecting our shared culture.

Pathways to resiliency; Understanding challenges and opportunities towards community youth engagement; a case study of rural Nova Scotia

Cumberland County is located in the Canadian province of Nova Scotia, close to the New Brunswick border. Cumberland County is made up of the Municipality of the County of Cumberland, two incorporated towns (Amherst and Oxford) and two Villages (Pugwash and River Hebert). According to Statistics Canada (2022) the population of Cumberland County, as of 2021, is 30,538, with the approximate size of the county being 4,248km2 (Department of Municipal Affairs and Housing, 2019/20). The proposed project is a collaboration between Mount Saint Vincent University researchers, the Municipality of the County of Cumberland, the Town of Amherst, and the Town of Oxford, in their mission to identify innovative solutions to engage youth in their communities. The partner organization will benefit by having a comprehensive report on how to improve the lives of youth in the area, and how to work to retain them. Furthermore, the partner organization will be presented with a list of recommendations. This will benefit the local community, economy, and more.

Efficient and Accurate Project Management Analysis Platform using Active and Few-Shot Learning Techniques for Advanced Insights and Predictions

This grant application, aims to develop an efficient and accurate project management analysis platform based on active and few-shot learning techniques. The main objective of our platform is to provide advanced insights and predictions related to project activities, teams, and budgets, using recent advancements in natural language processing (NLP), active and few-shot learning technologies. By automating most of the data science processes, our platform aims to reduce the need for manual data annotation, thereby minimizing human error and increasing the efficiency of the analysis. Our platform consists of two main subsystems: a log management and annotation subsystem and a model training and prediction subsystem. The log management and annotation subsystem will provide tools for efficiently managing and annotating project management logs, including NLP-based methods for automatically extracting relevant information from the logs. The model training and prediction subsystem will leverage active and few-shot learning techniques to train machine learning models that can predict project-related risks, identify over- or under- budgeting and data quality of project-related information. By combining these two subsystems, the platform will provide organizations with a powerful tool for making data-driven decisions and improving project management performance..

Invasive Plant Risk Mapping

Invasive species are one of the major threats to biodiversity in Canada and globally. It can be challenging to identify where and under which circumstances landscapes will be most susceptible versus resistant to invasive species, and not having this information can hamper conservation efforts. The objective of this Master’s project is to model and map current and future invasive plant species distributions and spread in Canada in relation to landscape connectivity and climate change. This will allow for the forecasting of the future burden of invasive plants to resident communities considering multiple facets of global change. The project’s results will be useful for determining where conservation actions should be targeted to sustain resilient landscapes.

Validating and improving Large Language Models for procedural tasks

Engineering organisations like Thales rely on large quantities of technical knowledge. When resolving a technical
problem, for example, users have to follow a multi-step procedure in which the steps are described with various
levels of detail, may not be up to date, or may not target the exact problem they are facing. Recent progress in
Large Language Models (LLM) showed capabilities for these models to reason over procedural knowledge but it
is still very difficult to evaluate if these models will be able to support users in executing complex, procedural tasks
in various scenarios. This project will address this research question by creating evaluation tasks for procedural
knowledge in order to test the performance of LLM, namely ChatGPT. These tasks are expected to form the
foundation of an API for LLMs applied to procedural knowledge, and will generate performance metrics that will
enable us to identify gaps in LLM abilities. These gaps will be addressed in a subsequent project.
7.3. Participant

Equal Access to an Education?: A Study on School Travel for Families Living with Childhood Disability

The project proposes to unpack the student transportation system through a comprehensive examination of legislative frameworks, in tandem with the lived school travel experiences of families living with childhood disability and school travel practitioners. The research aims are:(1) To understand how policy frameworks (e.g., international, federal, provincial, and municipal) shape school travel experiences for families living with childhood disability; (2) To demonstrate how disabled children and their families access and experience school travel; and (3) To identify tangible interventions to advance more equitable and inclusive school travel and education access for disabled students. To accomplish the latter, the following research question will serve as a guide: How does school travel materialize norms of able-bodiedness and able-mindedness (e.g., a preference for able-bodied, ‘neurotypical’ people)?

During their visit to Manchester, the intern will work closely with Dr. Cristina Temenos to analyze and interpret the data from the comprehensive content analysis of school travel policy, in addition to interviews with families/children living with disability and school travel practitioners. Dr. Temenos’ expertise in qualitative research methods, policy mobility and critical studies will be highly beneficial to this work.

Cell-specific mRNA design yielding highly efficient and safe gene editing in human epithelia

Gene therapies have the potential to help many patients with currently untreatable, severe, and life-threatening diseases. A certain type of gene therapy may even provide a cure for patients with genetic diseases. A key component of these gene therapies often is RNA. However, we are still lacking a good understanding of how RNA should ideally be designed and manufactured, especially when striving for an application beyond vaccination. Here, we are particularly interested in the lung as the target organ as several lung diseases would potentially benefit from an effective and safe gene therapy – many of them are poorly treatable to date.
Also, we currently do not know how RNA should be designed to exert especially powerful effects in specific cell types while maintaining good biocompatibility. Hence, in this project, we aim to understand the impact of RNA design and modifications when targeting the human lungs. We will generate a variety of RNA variants, assess the effect of these different structures on the efficacy and tolerability in the lungs, and develop criteria for other researchers how to effectively design safe and efficient RNA molecules for lung applications…

Indigenizing the Blue Economy

The project will pursue research that evaluates the potential benefits/ consequences of implementing eco-certification programs in Indigenous fisheries as an approach to improve the benefits Indigenous fish harvesters can obtain from their Treaty rights and/or commercial fisheries. In New Zealand, Maori scholars at theTe Kotahi and Ngai Tahu Research Centre are currently working with Maori fishers to understand how increased economic value from fisheries might be directed to Maori communities via certification and marketing. This internship will support this work, and also identify how initiatives underway in New Zealand can support Mi’kmaq and other First Nation’s development in Canada. The outcome of this partnership will assist the intern in developing a final research paper, as a requirement of the interns current masters degree at the home institution.

Adaptive Chaotic Map Selection to Reduce Overfitting in Artificial Neural Networks

Artificial neural networks (ANNs) have become a widely used machine learning tool in many different and broad fields of application. ANNs may be trained from training examples to perform various prediction or classification tasks. However, one of the problems exhibited by ANNs is that they typically overlearn the training examples and perform poorly on new inputs they haven’t been trained on. As a result, the ANN does not generalize well to novel data. The neuroscience field has shown some evidence that human cognition exhibits some form of chaotic behaviour. In our research, we use a mathematical tool called a chaotic strange attractor to generate chaotic sequences of values to inject into an ANN to reduce overfitting. While there are many different kinds of chaotic strange attractors, we propose a novel method of adaptively choosing a single or a subset of strange attractor(s), based on the nature of the training data, as well as on the nature of the distribution of possible solutions in the solution space. To assess the efficacy of our method, we propose to use three common data sets for training and testing and we propose to compare our method to the baseline ANN, dropout (DO)

Seeing the forest for the bees: pollinator and plant diversity across a chronosequence of harvest in managed boreal forests in Newfoundland, Canada.

This project aims to understand plant-pollinator relationships and species diversity in Corner Brook Pulp and Paper (Kruger) managed forests; and determine how these relationships may change under continued climate warming.