The project is concerned with delivering a real-world joint perception prediction and tracking system that outperforms the current system implemented in the Uber ATG software stack. This will be achieved by implementing a production version of a state-of-the-art academic paper developed by the research team, testing it against real world scenarios, and then modifying the neural network, inputs, architecture, and operations to obtain better within system results.
Artificial Intelligence is powered by data. In general, the predictive power of AI improves with higher data abundance and higher data quality. However, real-world datasets vary greatly in quality and quantity. In drug design, like many other tasks, there is an abundance of low quality data and scarcity of high quality data. This project will be developing new computational approaches to balance data quality and quantity to make the most out of all available information.
With the rise in electronic health records, we are seeing more reports of clinician job dissatisfaction that is attributed to the amount of data entry work they are now required to do. Therefore, there is a lot of interest to use a speech recognition system to reduce the burden clinicians have by automating the documentation process as it passively listens during clinical visits. However, while many companies and research groups are devoted to construct such a system, there has not been any evaluation on the practicality and usability of this approach.
Cellulose nanocrystals (CNC), a form of cellulose, shows a lot of promise in the development of sustainable materials thanks to its unique properties such as high performance, large surface area, is readily available, renewable, and biodegradable. Early methods to synthesize CNC have not been very successful. In order to isolate CNC, to make them ready for fast production of industry needs, these challenges need to be resolved by chemical modifications.
Active vision or perception is one that can manipulate the viewpoint of the cameras in order to investigate the environment, and get better information from it. It mostly encourages the idea of moving a visual sensor to constrain interpretation of its environment.
Substitution of existing diesel buses by zero-emission propulsion technologies (electric batteries and hydrogen fuel cell) in vehicles – specifically public transit fleets – can play an instrumental role in realizing Canada's obligation towards green house gas emission reduction. It is imperative to enable transit agencies to assess the capabilities of existing technology variants in meeting the demands of existing operations to achieve successful, long-term integration while maintaining commercially viability.
Urbanization continues to drive the land conversion from natural areas to urban uses dominated by impermeable surfaces. This conversion has direct and indirect impacts on ecosystem services that are critical for a sustainable and resilient ecosystem as well as human wellbeing. Habitat removal and fragmentation accelerate biodiversity loss in urban landscapes. Additionally, climate change exacerbates these impacts even further. Hence, green infrastructure is also becoming more common in urban landscapes to offset negative urbanization impacts.
Heat exchangers, used in building heating, ventilation and air conditioning (HVAC) systems to transfer heat from hot to cold fluids, are designed to operate under ideal conditions. However, in practice operating conditions may vary with ambient temperature or humidity. HVAC system efficiency can be improved significantly if fluid flow rates are adjusted in response to such changes. Armstrong Fluid Technology is a Canadian firm that has developed control systems to adjust the flow through building heat exchangers to maximize their efficiency.
SOTI Inc. is a Canadian company providing control and management for mobile devices. Insight Agent is a product made by SOTI to help collect various battery specifications such as battery level, voltage, current and other metrics from mobile devices. This research project aims to use a machine learning and neural networks framework to predict the state-of-health for batteries in mobile devices. The intern will use the metrics collected by SOTI Insight Agent to derive formulas to calculate the key performance indicators (KPIs) of the battery system.
Urinary tract infections caused by indwelling catheters (CAUTIs) employed for the treatment of urinary flow are very common. Almost 100 million of these devices are sold on an annual basis with around 25% of these being marketed in the USA. In addition to the cost of catheters and their insertion, hospital treatment of CAUITs runs into the hundreds of millions of dollars every year.