Innovative Projects Realized

Carbon Footprints of Agriculture Production in Atlantic Canada

The proposed research investigates an opportunity of monitor, measure, and model the role of carbon sequestration and emission of carbon dioxide from agricultural soils of Atlantic Canada. Precision agricultural practices will be designed to promote sustainable agriculture in Atlantic Canada.

Data-driven Assessment of Suicide Risk for Treatment Seeking Population

As part of this proposal the intern will be working with DME to develop and examine the viability of data-driven point-of-care system for the assessment of suicide risk. DME is a Canadian start-up company in the business of developing cloud-based point-of-care monitoring systems for the management of psychiatric illnesses. DME has developed algorithms to diagnose and predict optimal treatment for major depression disorder and schizophrenia, and has been allowed patents describing its technology in Canada, the USA, and Australia. If found acceptable the algorithms

Breeding and migratory habitat use in Eastern Whip-poor-will in relation to forest management

Understanding how managed and harvested forests can still provide high-quality habitat for forest birds is key to ensuring both productive forestry operations and sustainable bird populations. We propose to use GPS-tracking technology to study how the Eastern Whip-poor-will (Antrostomus vociferus) uses habitat on its Canadian breeding grounds, during migration, and on the wintering grounds. The Whip-poor-will is designated as Threatened in Canada, and the forestry industry is expected to manage operations to protect Whip-poor-will and its habitat. Forest harvest can maintain the mosaic of open spaces and closed forests that Whip-poor-wills prefer, but detailed information about how these birds use the managed landscape is lacking. The GPS data will allow us to determine timing of use, home range sizes, and how breeding site selection connects to habitat use across the annual cycle. Our results will provide information for more nuanced protection of Whip-poor-will habitat while facilitating productive forestry operations.

Geometric Control Methodology for Modular Residential Construction Systems

As the use of modular construction grows as a favorable affordable housing solution, there is a need to determine which parts of the building are most critical to manufacture with a high degree of precision. Producing a whole building to the same level of precision as an automotive or aerospace assembly for instance, is costly, inefficient and waste of resources (if the goal is to ensure the building functions properly and can be assembled without issues). This project develops an overall strategy for addressing level of precision and optimal geometric control. Part of this is a novel tool to provide stakeholders with feedback on acceptable manufacturing precision during manufacturing. This project will help modular fabricators improve their profit margins, translating into lower overall costs for the industry. This is especially important for not-for-profit stakeholders (like the client in this project) in their ability to provide affordable housing solutions.

Designing an urban analytics prototype for the measurement of temporary public space projects

Our parks, public spaces and their activations can catalyze neighborhoods to build connections and create stronger communities. However, it is often challenging to measure the impact and value of these projects, at a neighbourhood level.
This project looks to develop a deeper understanding of the impact of public space initiatives, focusing on the short and long-term impact and value of permanent and temporary installations and how they impact communities.
The final result will be an urban analytics prototype to better capture data, visualize the data and draw insights of the possible impacts of public space projects, at a community level.
This project will assist those working in the built environment to understand the community level impact of installations in public spaces through the compilation urban data to better plan, develop and deliver projects.

Improving Efficiency and Robustness of Model-based Reinforcement Learning

Model-based reinforcement learning allows AI systems to learn and use predictive models of their environments to plan ahead, achieving tasks more efficiently. The proposed project aims to (i) develop methods for identifying when an uncertain and/or flawed model can be relied on to make plans, and when it cannot, and (ii) implement a method which allows an AI system to explore its environment exactly when exploration will be most useful for improving its model-based predictions and plans. Such methods for using models robustly, efficiently, and adaptively are promising for real-world applications of reinforcement learning which require systems to achieve tasks with limited data.

Siemens next generation land-based gas turbine engine combustors: Characterization and development of a newly-designed injection system

.Siemens Canada develops land-based gas turbine engines that are used for power generation. These engines burn natural gas and produce combustion pollutants such as carbon monoxide and nitrogen oxides. Reducing emission of these pollutants addition of low carbon fuel, such as hydrogen, to natural gas. However, addition of hydrogen leads to occurrence of combustion instabilities which are of safety concern for gas turbine operation. Through numerical simulations, Siemens has recently developed a fuel injection system that is believed to modify the combustion architecture inside the gas turbine engines such that allow for reducing the emissions from these engines while the possibility of combustion instability occurrence is minimized. The proposed project will experimentally assess the performance of this newly-developed Siemens fuel/air injection system. The experiments will be performed in collaboration with the National Research Council of Canada’s gas turbine laboratory research staff, UBC interns, and Siemens research engineers.

Développement d’un procédé industriel pour la production et l’utilisation d’un bioingrédientà base de bactéries lactiques pour la conservation à long terme des produits marins

Le développement de nouveaux produits antimicrobiens d’origine naturelle susceptibles de réduire

l’incidence des bactéries pathogènes et d’altération dans les aliments prêts-à-consommer et de

prolonger leur durée de vie, demeure une urgence dans le secteur agroalimentaire.

Dans le cadre de ce projet, on se propose de développer un procédé industriel pour la production et

la stabilisation à grande échelle de bio-ingrédients à base de C. divergens M35 et d’évaluer à l’échelle

industrielle le potentiel antimicrobien de ce bio-ingrédient comme alternative aux additifs chimiques

pour la bio-conservation à long terme des produits marins prêts-à-consommer.

Mitigation of product degradation in anesthetic gas capture

This project will assist a company with the commercialization of a system that captures anesthetic gases from hospital air emissions, to reduce their environmental impact and global warming effects. A working system is already developed, but under some conditions the anesthetic gases break down to form a hazardous hydrofluoric acid material. This acid is undesirable and can cause damage to the system equipment over time. This research will identify the root causes and mechanisms for this acid formation. This information will help the company to make changes such that the acid is not produced in the future, and successful commercialization can continue.

Cognitive and Physical Demands of Using Ergonomic Spinner Knobs

Howell ventures, located in Fredericton, is a leading company in North America for designing and producing driving aids. Driving aids, such as “remote spinner knobs” enable individuals who have physical limitations (due to structural, traumatic, or pathological reasons) who want to maintain their independence by driving their vehicles. The purpose of the study is to identify a remote spinner knob design that reduces cognitive and physical demands while driving.

Development of Strategy and Implementation Plan to Introduce AI based RainGrid’s Disruptive Digital Stormwater Smartgrid Technology in North American Markets in an era of Global Climate Change

The goal of this project is to develop a detailed strategic analysis and market/finance/commercialization strategy identifying gaps/barriers, opportunities/resources and benefits of developing the Ai/IoT digital “Stormwater Smartgrid” technology and its concomitant implementation business model for North American market.
This research project in collaboration with McMaster University will help RainGrid to facilitate the commercialization of the existing prototypes and to establish RainGrid as a global player in the rapidly emerging market for smart city, digital water technologies and associated business models in an era of global Climate Change.

Quantification and Improvement of Juvenile American Eel Passage Through Fishways and Wetland Water Control Infrastructure.

The American Eel is a species of significant ecological, social and commercial value and a species of conservation concern in part due to reduced habitat connectivity to both freshwater habitat as juveniles, commonly known as glass eels or elvers. During the proposed research period the intern will work to quantify passage of elvers through existing infrastructure that is representative of the majority of infrastructure within Ducks Unlimited projects within Atlantic Canada. This knowledge will permit DUC to quantify the ability of elvers to access freshwater habitat inside its projects and work to develop widely applicable solutions to increase elver passage. This will enhance the populations of eels within DUC projects and enhance the productivity long term viability of DUC wetland projects.