Evaluating Latency in Virtual Production Pipelines with Integrated Prediction Model for Motion Capture Data

Virtual Production (VP) is seeing a dramatic spike in interest and adaptation as the global film industry, particularly Hollywood, has been shutdown due to Covid-19. Virtual production is a broad term referring to a spectrum of computer-aided production and visualization filmmaking methods, and is also being used for broader applications from animation to industrial visualization. […]

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Sustainable Management of Abandoned, Lost, or Discarded Fishing Gear in British Columbia: Through the Lens of Local Stakeholders

A review of current literature will be used to develop an enhanced record of knowledge on the topic of lost fishing gear in British Columbia; specifically looking at the socio-economic and ecological impacts, regionally applicable case study solutions, best practice framework recommendations, and current policies on environmental management of marine debris in Canada. Results will […]

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Data Visualization of GIS Data at Scale

Access to private or leased land is currently not a simple problem. Landowners would like to know who is on their land, when, and for what purpose. Getting permissions from landowners is often not a straightforward task which often leads to obtaining permission being bypassed. Some landowners do not want hunters, but do not mind […]

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Can deep learning algorithms be trained to automate the classification of information held in historical and repeat photographs?

Repeat photography is a valuable tool for evaluating long-term ecological change. Historical photographs used for repeat photography often predate conventional remote sensing data by decades, and the oblique perspective of the photographs capture details of the landscape absent in nadir imagery. To date, most approaches to quantifying landscape change using repeat photography have involved manual […]

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A scenario-based modelling framework for projecting COVID-19 infections and deaths

The speed and extent of the COVID-19 pandemic has challenged our abilities, as forecasters, like never before. Early data on the disease’s epidemiology is limited, records of cases and infections are incomplete, and the dynamics and scientific understanding of the disease are changing daily. Scientists from around the world have been quick to respond by […]

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A Serious Approach to Sickness Prevention in Motion Base Simulators

Training personnel to operate machinery in the construction workplace requires a major devotion of time, resources, and safeguards. Recent methods involving virtual reality and motion base simulators have drastically enhanced the training process, but some users of these new methods report sickness and discomfort. This research aims to remedy this issue with a theoretical and […]

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Enhancement of an AI-driven space situational awareness platform for more robust predictions

As transportation to space becomes more accessible, space debris pose increasing risk to operational satellites. Objects orbiting the earth can have a detrimental effect on space travel and threaten the spacecraft and its personnel. These objects can be anything from active and passive satellites, orbital debris, space junk, asteroids and fragments from their disintegration and […]

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Predicting risk of unplanned hospital readmission within 30-days of discharge using machine learning approaches

Unplanned hospital readmissions are a preventable and costly outcome in the health care system. There are limited tools to estimate risk of readmission. The machine learning process offers an opportunity to develop a risk predictor to identify those at high risk of readmission upon discharge. OKAKI has an opportunity to diversify the commercial products it […]

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Optimizing Pretrained Clinical Embeddings for Automatic COVID-related ICD Coding

We are building a machine learning algorithm to be able to better understand the unstructured clinical notes that doctors write about patients. This will help hospitals and healthcare systems standardize and extract insights from these notes to make them more useful for determining how sick COVID patients are and how they are improving over time.

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Anion Exchange Membranes for use in Industrial Electrolysis Systems for Salt-Splitting

Salt splitting is a technology in which an electrochemical cell containing 2 membranes to transport positive and negative ions, is used to produce sulfuric acid and caustic soda from sodium sulfate, a compound found commonly from industrial brine streams. Salt splitting electrolysis is a sustainable solution for the expanding markets of acid and caustic recovery […]

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Development of an Oral Reovirus-Based Vaccination Platform for COVID-19

It is essential to develop a vaccine against SARS-CoV-2, the virus causing the global COVID-19 pandemic. The most efficient vaccines are built on attenuated live viruses, which can be engineered to display specific antigens and, once administered in humans, can safely induce an immune response and immunity to the disease of interest. Fast, reliable, and […]

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