The strong tidal currents that make in-stream tidal energy possible, are also challenging to work in since they are also very turbulent. As the flow passes over the rough bottom and shoreline variations, eddies are generated over a wide range of scales. These eddies (i.e. turbulence) create fluctuating forces on tidal turbine blades and their […]

Machine learning can be used to predict employee events around retention, promotion or movement. This project explores how to generate better predictions by exploring correlations and exploiting them through features that increase predictive strength. Furthermore, the project explores how to reliably fine-tune the predictive model to a particular data set in the presence of interdependence […]

Social media and other real-time messaging applications represent valuable sources of real-time information that remain untapped by many service operators. The project is aimed at developing methodology for detecting suspicious and/or abnormal real-time events from textual live data feeds, based on predictive and/or anomaly detection algorithms applied to time series and text features. TRT Canada […]

This project aims to address the race bias of face recognition technology by developing new face feature sets and building the suggested models based on an equal number of images from varied-race photos using appropriate deep learning algorithms. This research seeks to deliver industry partner IRIS with guidelines for a developed prototype that facilitates the […]

Product documentation is an important information tool connecting any business to its end-users and customers. Comprehensive product documentation will likely result in positive evaluation of the products by the customers and may influence their future purchasing decisions. Many studies show product documentation remains an essential element of any new product even for modern electronic devices […]

In today’s competitive market, customer service has become essential to any company willing to expand and increase its business. Companies cannot afford to fall short of consumer expectations. With the recent progress in Artificial Intelligence (AI) and the impressive results in different industrial areas, companies are adopting AI techniques for customer service. Most of the […]

Data centers are now growing and expanding massively. They are large scale and heterogeneous. In addition, they rely more and more on emerging technologies such as Software Defined Networking (SDN) and Network Functions Virtualization (NFV) with “network softwarization” as their key feature. Moreover, they are now being augmented with edge data centers rooted in concepts […]

The rapid development of technology and its ubiquitous integration with modern society has clarified for business and technology leaders the need for ethical conversations about the role technology can and should play in our lives. By interviewing primary stakeholders in the technology sector and putting their ideas in conversation with literature about the role of […]

The measurement of toxins, such as arsenic, mercury, cadmium, lead and chromium for example, in food, beverages, environmental samples, waters, etc. must be carried out to verify that there is no danger. This requires analyses of numerous samples each day using instruments that can measure the small amounts that may be present. This research involves […]

The project concerns big data analysis and management for food testing industries by using Machine learning technique. Any food product before and during its distribution to the market must go through an extensive safety and quality tests at food testing laboratories. During this process, various microbiology and analytical chemistry tests will be performed on food […]

Across industries, many engineering documents and drawings have accumulated over the past few decades. However, they are mostly archived in paper or rudimentary electronic form (typically in an image or PDF format), rendering information retrieval highly inconvenient. As such, a lot of valuable engineering data have been left unutilized or at very least, difficult to […]

The explosion of popularity of deep learning owes a lot to the success of convolutional neural networks, widely used in diverse fields including computer vision and natural language processing. Recently, the group equivariant convolutional neural network (G-CNN) was introduced, where equivariance of symmetries inherent in the data set is built in the architecture of the […]