This work is a holistic automatic methodology for cloud resource management system, which is a corner stone to build any cloud system. Cloud players rely on this to reduce management effort and cloud running cost, by enabling dynamic service access to cloud clients with cheapest price for customer, and high revenue for cloud providers. Customer […]

Broadcast radio is changing from an analog medium based on frequency modulation (FM) to a full digital broadcast based on orthogonal frequency division multiplexing (OFDM). The high peak-to-average power ratio of the OFDM waveform requires different power amplifier topologies and a high degree of linearity. The research in this project analyzes current amplifier performance for […]

Automatic detection and classification of the Auditory Brainstem Responses (ABR) is used in newborn hearing screening. Improved detection algorithms will reduce test time, prevent infants with hearing loss from being missed while reducing the number of normal hearing babies referred to diagnostic testing. We have already improved the objectivity of ABR classification in neurological assessments […]

The main goal of this project is to develop a platform that helps to optimal design of a power converter for switch reluctance motors. The research will focus on multi-domain models and multi-objective optimization routines. Due to the high complexity of developing such a tool, the component models will include loss, thermal, and cost aspects, […]

Advances in Whole Slide Imaging (WSI) and Machine Learning (ML) open new opportunities to create innovative solutions in healthcare and in particular digital pathology to increase efficiencies, reduce cost and most importantly improve patient care. This project envisions the creation of new automated ML tools including the design of a custom Convolution Neural Network (CNN) […]

The ultimate objective of the project is to develop an AI-based framework addressing the forecasting needs of a typical fashion and apparel retailer. The project activities involve development of models predicting demand for particular fashion and apparel items in the context of different customer groups, as well as techniques for identifying fashion trends. The developed […]

Electrical heating of oil sands allows for production in situ in a mode similar to conventional liquid oil production. This avoids disturbing and redistributing the overburden and production sands. A further advantage of electrical heating is that the power consumption can be matched to the availability of sources such as wind power.

A solar wireless charger makes use of the power of the sun to charge your mobile phone. The benefit of this portable device is that it makes it possible to charge your phone outdoor or when someone does not have access to electricity right away. It also helps people in undeveloped countries where access to […]

Governments around the globe are pressing the automotive industry to reach lower emission and better efficiency with various specifications targets and regulations. With the increasing amount of electric vehicle models that are available and the higher demand on the market, major OEMs are looking for components to differentiate themselves and offer competitive solutions. As the […]

We will work with Alimentation Couche-Tard (ACT) to adapt retail practices to the post-pandemic world. Consumer behaviour has dramatically evolved due to the recent COVID-19 pandemic. Consumers are spending less time shopping and they aim to minimize physical contact. This shift in purchasing behaviour will generate unique data that may allow us to develop new […]

Automotive Open System Architecture (AUTOSAR) is a system-level standard used worldwide by automotive companies and suppliers to develop standardized software development frameworks for automobiles. The RTE software of AUTOSAR should be configured to develop an Electronic Control Unit (ECU). The manual and semiautomatic code creation phases of the software development process for the RTE is […]

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. Learning with deep neural networks has enjoyed huge empirical success in recent years across a wide variety of tasks. Lately many researchers in machine learning society have become interested in the generalization mystery: why do overparameterized DNN […]