The motivation for this research comes from an overall need to improve the performance of high voltage module (HVM) and to reduce the size and its material costs while maintaining its efficient performance, with no partial discharge, arc or thermal issues. In particular, stable transient and steady state performances must be achieved for medical X-generators under wide load variation, ranging from 40-150 kV output voltage and 0.1-1000 mA output current to obtain defect free images. The desired HV module will combine the optimum cost-effective design with compactness.
In last few year, due to bad impression, single used plastics has received huge attention from scientist, environmentalist and attentive people from different part of the world. Since only a fraction of these plastics are recycled or repurposed, due to numerous reasons, municipal and industrial waste contain a large portion as plastics. As Canada is planning to put a ban on single used plastics by the end of 2021, putting an effort to replace these plastics with bio-based, compostable, and biodegradable plastics could be a potential solution.
TV Whitespace (TVWS) designates the inactive or unused space between TV channels actively used in UHF and VHF spectrum :470 MHz to 700 MHz. The TVWS band performs best in the most rural service areas. This is due to the characteristics of TVWS, and how it's shared with powerful analog TV stations Such TV transmitters can have up to hundreds of kilowatts of transmit power creating strong interference. Due to spectrum sharing with these powerful analog TV stations the reliability of wireless communications in TVWS is affected.
Lithium-sulfur batteries (LSBs) have ultra-high energy density (~2600 Wh kg-1) and have great potential as power sources for electric vehicles and portable electronics. However, they suffer from the problems of low practical ability and poor life span, which limit their wide application.
The electrification of the automobile industry is one of the main paths toward global decarbonization and a promising solution to address oil supply shortages and environmental pollution. However, the EV industry still faces critical challenges such as long charging time, low battery lifetime, and safety considerations, which restrict widespread adoption of EVs. In this project, we aim to develop a hybrid modeling framework to tackle these challenges.
We are working on active compression sleeves for treating edema, which is the swelling of tissues due to the build-up of excess fluids, impacting roughly 40% of individuals with chronic spinal cord injuries. The technology behind this active compression sleeve is air microfluidics and minifluidics. The goal is to deliver a product that increases the quality of life of its users.
Unsupervised machine learning has recently been introduced into the field of quantum many-body physics. A strategy based on generative models has been particularly successful in the data-driven learning of quantum states. In this proposal, we aim to adapt this technology to applications in quantum chemistry. The primary focus of this research will be on the reconstruction of molecular wavefunctions using data obtained from qubit-based quantum simulators, such as superconducting circuits or trapped ions.
Nanomaterials as carriers are very suitable for the delivery of chemotherapeutic drugs in cancer treatment. Because nanomaterials as a carrier platform have strong permeability and retention delay in the treatment of tumors, they can passively target tumor cells. Metal organic framework ?MOF ?is a kind of porous material with large pore size and high specific surface area, which can achieve drug encapsulation. We adjusted the size and morphology of MOF to obtain biocompatible materials with an average particle size of less than 200nm.
In AI safety, compliance ensures that a model adheres to operational specifications at runtime to avoid adverse events for the end user. This proposal looks at obtaining model compliance in two ways: (i) applying corrective measures to a non-compliant Machine Learning (ML) model and (ii) ensuring compliance throughout the model’s training process. We aim to achieve the first via removal of gradient information related to features involved in biasing the model.
There is a lack of “diversity” in Canada’s tech industry and this is what the research is based on. The lack of research considering racial diversity in the tech industry in Canada leaves a significant gap in understanding issues that would be critical in addressing such a lack of diversity. This research will explore how, to what extent, race is represented in Southwestern Ontario’s tech industry. In so doing, it will determine if, and if so, to what extent, there is there is a race equity pay gap.