Implementation of Tensor Neural Networks

Tensor networks are a quantum inspired technique that provide useful mechanisms for solving hard problems, usually in the realm of quantum mechanics and many-body systems, through the manipulation and operation of tensors. The main challenge underlying this project is the productionalization of a quantum-inspired deep learning algorithm which currently exists as a proof of concept (POC). That POC was specifically built for a single user’s needs, applied to the fair pricing of financial derivatives.

Understanding and characterizing flux noise in D-Wave's superconducting circuit stack

While quantum computers in theory can solve problems exponentially faster than conventional computers, in practise they are quite challenging to build. One of the main problems facing the technology used by D-Wave, IBM, and google is the presence of flux noise. The current project aims to understand the origin of flux noise in D-Wave's superconductor-based quantum hardware. We will measure noise using two different kinds of experiments and we will apply our recently developed theory to model our results in terms of interacting magnetic impurities on top of the wires.

Predicting Perfect Matches Between Organizations

Successful partnerships between non-profit organizations and funders are fundamental for organizations’ abilities to concentrate on their mission, and for founders to see their philanthropic investments align with their values and make real impacts. Matching founders and organizations has traditionally been done informally through personal connections, networks, and expensive prospecting software and databases. Just like a dating app for philanthropic organizations, Orgmatch matches funders and non-profits together based on attribute-based representations.

Turkey Vulture Migration, Ecology, and Health in the Pacific Northwest

This project is examining the movements (migratory and local), status, and health of the Turkey Vulture in the Pacific Northwest, with a particular focus on Vancouver Island. This is at the northwestern edge of their relatively recent (and continuing) apparent range expansion and population growth locally. Through a process of trapping, tagging, monitoring, and observing vultures, we aim to learn about various aspects of their life history. These aspects include their local movements, foraging, and breeding habits/habitats, including details of nest sites and roosts.

Navigation Platform with Enhanced Telemetry and Visualization, using Augmented Reality on a Hybrid 2D/Holographic 3D Display System

The research project is focused on prototyping and testing a series of new visualization features as part of a marine navigation product currently under development at the partner organization. These features include the use of a depth-sensing cameras and 3D holographic displays.

Evaluate the Long-term effectiveness of a Family-based Childhood Obesity Management Program

Generation Health (GH) is a family-based intervention targeting families of children who are off the healthy weight trajectory. The GH is a 10-week program offered across BC where children and their families meet once a week online. Parents will be provided with healthy lifestyle content and will engage in discussions on how to engage in health behaviours, and children will participate in physical activities aiming to enhance their motor skills. Families will also have access to a web portal with content and suggestions of activities to be completed.

AI-powered Management of Specialty Crops

The conventional management manner of specialty crops is mainly based on intensive human labor which leads to low efficiency and high cost of crop production. Precision viticulture and autonomous management is a recent and significant step forward from traditional viticulture that is powered by technological advances in artificial intelligence and engineering. In this project, we will propose novel AI-powered management schemes for the management of specialty crops to remove its dependence on intensive human labor.

Evaluation of mechanical performance and in-situ health monitoring using destructive and non-destructive testing of cellulosic fiber reinforced cement composites

Today, construction activities have resulted in the depletion of vast amounts of non-renewable resources that cause climate change which is one of the most pressing environmental challenges of our day. The construction industry is a major source of greenhouse gas emissions globally. Sustainable construction is now mainstream, necessitating the investigation of environmentally friendly construction materials like cellulosic fibers. One of the potential applications of cellulose fibers is in development of cement-based composites.

Modelling land-based mitigation technologies (LMTs) with ALCES Flow: A participatory modelling platform for landscape simulation and ecosystem carbon emission analyses

Wildfire incurs major environmental and economic losses in many areas of the world. Although climate change is playing an important role in changing fire frequency and magnitude, human management strategies can play an arguably comparable role. Managers must choose from a range of strategies to ensure viability of forest stands, but research supporting efficacy of different approaches is not always available. In Venezuela, forests regions are threatened by wildfires originating in adjacent Savannas.

Decision-making for Sustainable Buildings

To contribute to society’s decarbonization goals, the Architecture, Engineering, and Construction (AEC) industry must rapidly transition to low-carbon buildings. Low carbon construction materials and other building technologies are contributing to this decarbonization, but the rate of change for this transition remains low.

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