Straits Salish Plant Stewardship in the 21st Century:Cultivating Co-management Relationships in BC

This research supports the T?Sou-ke Nation to re-establish connections with culturally important native plant species cultivated and stewarded by traditional T?Sou-ke peoples for food, medicine and technology and to store this information in database and maps. The product of this research will be accessed when T?Sou-ke consider both large, economic development projects proposed within their territory, and for plant harvesting opportunities (for food and commercial purposes) by their members.

Developing Cannabis resources for the 21st century

Over the past few years Cannabis has gone through a revolution with respect to its applications to both the medical and recreational markets. For legal reasons, much Cannabis genetics has been hap hazard but now with legalization scientific approaches can be used to develop useful Cannabis strains for the industry. In this proposal, we will develop two transformative programs to revolutionize Cannabis genetics. The first involves the development of a cheap fast method to identify Cannabis strains.

Methodology development for the non-destructive quality assessment of joints in polyethylene pipes based on ultrasound technology

The use of polyethylene (PE) plastic pipes for transporting gas and water has increased over the last few decades. The quality assessment and overall safety of the PE pipe networks have been of high priority for the distribution companies. The existing technology is somewhat complicated to use quickly and effectively by less experienced personnel. The proposed research study goal is to revise and evaluate the newest technological solutions for joint testing and propose a methodology that can address industry needs.

Personalized Wealth Management Advisor based on the Analysis of Times Series Related to Financial Transactions

The aim of this research project is to develop innovative tools that will help financial institutions deliver highly personalized services to their customers. We intend to use the most recent advances in statistical learning methods and machine learning algorithms mostly in deep learning, vector embeddings and autoencoders, to leverage the power of time series models by extracting high-level features from both assets and customers’ transactional data.

Using technology to measure, map and magnify the impact of due diligence programs in artisanal mining communities in Eastern D.R Congo

Ulula is a company that provides software and analytics to create responsible supply chains. In 2018, Timothy Makori, Ulula and the International Peace Information Service (IPIS), an independent research organization working on issues related to artisanal mining in Eastern Congo, undertook a baseline study assessing the social, economic and human rights impacts of initiatives promoting traceability and responsible artisanal mining in Eastern Congo.

Predicting Scleral Lens Rotation Based on Corneoscleral Toricity

Patients with corneal disease often require treatment with scleral lenses. Unlike regular soft contact lenses, these lenses are much larger and have a space between the cornea and the lens that is filled with fluid before lens application. These lenses are extremely useful in cases of extremely ocular dryness and in patients with irregular corneas. Adjusting these lenses to perfectly mold the surface of the eye is of the utmost importance to ensure that the patient is comfortable and sees well with their lenses.

Autonomous structure detection and inspection using unmanned aerial systems

In this project, a new method is developed to optimize the performance of an Unmanned Aerial Vehicle (UAV) for autonomous detection and on-the-job view-planning of infrastructure elements with the purpose of their accurate three-dimensional (3D) modeling. The existing view-planning approaches in the literature have mostly modeled non-complex or small-scale objects and have rarely been adapted to flying robots. In addition, the target object is often identified by human operators.

AI to predict emergency visits is an AI-based predictive analytics platform that goes beyond traditional claims-based risk scores to use all patient-related healthcare data to provide both clinicians and care managers with a full breadth of timely, transparent and accurate predictions of health outcomes. helps value-based providers confidently answer a variety of health-care questions like, which patients are most likely to be readmitted to the hospital? Or which of my patients would most benefit from establishing a relationship with a primary care provider?

Link predicting in court

The company Lexum is an undisputed leader in the development of information retrieval tools for the law - statutes, regulations and decisions of courts and tribunals. The project is to improve a new tool offer by the company. The tool is used to retrieve a list of legal subjects from a factual description. With that list extract, the tool provides a list of potential related document.

Low data drug modeling

The project aims to facilitate the research and development of new drugs by exploring Machine Learning methodology useful for both the generation of new molecules and the prediction of molecule properties. Doing so will involve training deep learning models on a large number of small, heterogeneous datasets, with the objective of transferring learned representations quickly when faced with a new drug-discovery or drug optimization objectives.