For an Autonomous Vehicle (AV) to make decisions and drive independently on urban streets, the problem at hand can be broken down into many phases, two of which are perception and prediction. Perception refers to the process of extracting valuable information from the environment using data collected by sensors such as LIDAR and camera. This includes detection of cars, ped estrians, lanes among many objects. Prediction refers to the process of tracking all the known objects and predicting the possible future actions so as to enable the autonomous vehicle to make informed decisions.
Electrocardiography or ECG is a technology that can be used to monitor the electrical activity of the heart over a long period of time. Such signals can be utilized for interpreting both the structure and function of the heart. Traditional ECG designs consist of several electrodes that need to be placed directly in contact with a patients skin. These metallic sensory electrodes are usually made into disc-like configuration and one of the major drawbacks is the inconsistency in signal recording due to poor skin contact from the non-flexible nature of the electrode design.
Thousands of chemical compounds are released into the environment as a result of human activity. While exposure to manufactured chemicals is concerning, the majority of such contaminants are not monitored by regulatory agencies and their environmental and human health impacts are unknown. The objective of this collaboration is to develop and evaluate state-of-the-art tools to identify chemical contaminants in our environment. Specifically, contaminant molecules will separated and detected using a technique called gas chromatography-atmospheric pressure ionization mass spectrometry.
The remote First Nations communities of Canada suffer from a dire lack of access to emergency response systems and services during times of crises. They lack access to life-saving services such as paramedics, 911 services, and search and rescue services due to their geographic isolation. This often puts them in grave danger and results in loss of lives.
This project will focus on furthering the development of a compact picosecond infrared laser (PIRL) system for use in surgical applications. This laser system, which represents a new paradigm for laser surgery, is unique in its ability to provide high-speed cutting of biological tissue without the collateral damage to surrounding tissues inherent in current surgical laser technologies. Furthermore, this laser allows for the possibility of real-time diagnostics, as molecular fragments of the ablated tissue are left intact and can be analyzed through mass spectrometry.
The objective of the project is to investigate how machine learning techniques can be used to detect anomalies in volumes of transactions. This requires the student to conduct a literature review about the topic as well as experimenting with a subset of selected machine learning techniques. The results from the research could help the partner organization in improving in place mechanisms used to detect anomalies in volume of transactions.
The partner is creating artificial intelligence which can help diagnose over 1,300 skin conditions with dermatologist-level accuracy. They are focused on building the functionality that is to be deployed through their app and web-interface that makes it possible to snap a photo, ask questions, and get an instant diagnosis. The partner is very focused on the project given its critical need as part of the overall system/solution. The main objective of the project is to enhance and finalize Triage’s diagnostic system to the point where it is ready to be launched.
Ultra-reliable and low latency communication is increasingly an important aspect of future wireless communications. Specifically, in the context of mission critical communications for large-scale networks of sensors and actuators in automated and/or remote-control applications, low-latency wireless communication with high level of determinism is a vital element. The key performance indicators for such use case are in sharp contrast to the current broadband communications, since latency and reliability are paramount but lower data rates can be tolerated.
Tracking the component configuration and modifications to aircraft within the commercial airline business presents a challenge for manufacturers such as Bombardier with currently available methods. This research problem is significant to the aerospace industry to construct efficient maintenance schedules for different aircraft and to properly evaluate system reliability for safety purposes. The objective of this research is to determine a new methodology for tracking and determining probable component configuration for commercial aircraft.
Pelmorex (owner of the brands The Weather Network and MeteoMedia) operates weather information services accessed by all Canadians on desktop computers, mobile apps and television. The mobile app is one of the most downloaded and used apps in the country, within both the Apple/Google ecosystems of smart phones/tablets. Continuous and accurate location data is collected from the apps in a privacy safe way, adhering to Canadian privacy commissioner guidelines and standards such as Pipeda, with no PII (personally identifiable information) being collected.