The road network supports the mobility of people and goods, and is vital to the economy at both the national and municipal levels. As part of the preparation of their intervention plans and the monitoring of infrastructure compliance, Quebec municipalities need to capture and analyze data on their road network.
Caused by planktonic and biofilm drug-resistant bacteria on implants, periprosthetic joint infections (PJI) is one of the most devastating complication in orthopedics and is in line with forecasted rise in joint replacement. From the perspectives of patients, surgeons, hospitals, and health care system, PJI thus present a great unmet medical need, resulting in high morbidity, and even mortality, among affected patients. Therefore, clinicians would find invaluable a technology with a potential to manage PJI on implants.
Thales Canada develops control systems for avionics applications, which operate in harsh environments that may compromise the functionality of very high density chips. The company needs to develop a generic power interface for different avionics applications with a high level of criticality. However, such circuitry requires a lot of space on printed circuit boards when implemented as discrete components.
The aero-engine design process is highly iterative, multidisciplinary and complex in nature. The success of an engine depends on a carefully balanced design that best exploits the interactions between numerous traditional engineering disciplines such as aerodynamics and structures as well as lifecycle analysis of cost, manufacturability, serviceability and supportability. Pratt & Whitney Canada (P&WC) is the world leader in the design and manufacturing of small aero-engines.
The purpose of this project is to investigate self-adaptive forecasting and anomaly prediction algorithms based on deep neural networks (DNNs). DNNs present a compelling technology due to their wide-spread availability through open-source projects (e.g. TensorFlow, MXNet). However, usability of DNNs in scenarios outside of image, speech or text pattern recognition is mostly unproven. This project aims to reduce the knowledge gap that exists in the usage of DNNs in the context of pattern recognition with DNNs in network management and network equipment manufacturing.
Mecademic manufactures the smallest and most precise six-axis robot arm. The repeatability of this robot is better than 0.005 mm, but like any industrial robot, the robot’s accuracy is far worse. The only practical way of improving the robot’s accuracy is to calibrate each individual robot.
This project applies wide-bandgap (WBG) transistors to voltage level multiplier module (VLMM) topology in motor inverter applications. It is expected that this approach can yield the benefits of WBG motor inverters (high motor efficiency, fast control response, lower motor torque ripple, close to ideal sinusoidal motor current waveform, smaller filter size, lower cost filter, etc.) while leveraging the benefits of VLMM (lower component cost, high frequency switching only at low voltage, filter-less output signal) to yield a commercially viable highly-efficient pure-sine motor inverter.
Radio frequency integrated circuit power amplifiers (RFIC PAs) operating at microwave frequencies (e.g. 5 to 6 GHz) and at millimeter-wave (mm-wave) frequencies (e.g. 60 GHz) are electronic components used in the front-end modules (close to the antenna) of mobile communication equipment such as cellular handsets. Envelope detectors constitute a critical component in a newly proposed dynamic biasing technique for RFIC PAs based on positive envelope feedback, for power efficiency improvement and distortion reduction.