Predictive Models for the Manitoba Bio-Economy Atlas

The intern will develop a multi-year model of a biomass supply chain for Manitoba, which will comprise the back end for a web based Bio-Economy Atlas tool. The tool will create feasibility level assessments of the volume, consistency, variability, accessibility and logistics costs of the biofuel resource in Manitoba, including both conventional sources, such as agricultural residue, and unconventional sources, such as riparian biomass and cattails.

Developing a newly tunable Phase-Mask Interferometer for Fiber Bragg Grating inscription - Year two

Fiber Bragg gratings (FBGs) have attracted considerable interest in the past three decades as a key technology in different applications. The intention of this project is to develop a FBG writing technique based on a scanning tunable Phase-Mask Interferometer using different UV lasers. The project includes optimizing the tunability of the interferometer, and analyzing the specific problem situations encountered in the process in order to develop the interrogation methods of the proposed technique.

Non-intrusive assessment of vigilance in drivers based on eye movement and blinking

Due to lifestyle and work demands, chronic sleep deprivation is now experienced by many people, leading to increased drowsiness and fatigue which can have a negative influence on health, safety and work performance. Drowsiness, in particular, can influence fitness to drive and put people at significant risk. With this in mind and in response to increasing demand from market and public domains, Alcohol Countermeasure Systems (ACS) has launched innovative research into methods and technology for improving driver and vehicle safety.

Microgrid Protection Design Investigation using Real-Time Hardware-in-the-Loop

The electric power grid in Canada provides energy to the country. In order to provide more reliable power, to include more clean energy and to supply energy to remote Canadian communities, part of the power grid may be required to operate autonomously. At the distribution level, microgrids, which can be isolated from the main grid, are being deployed for this purpose. Protection schemes in microgrids are very different to those in conventional grids. This project deals with the design and deployment of microgrid protection schemes.

Computer Vision and Deep Learning for Moderating Visual Content

Two Hat Security is a company that develops next generation moderation tools for social networking apps. Since visual content (e.g. images, videos) is one of the most important types of data shared by social networking apps, an important problem for the company is to identify images/videos that are offensive or inappropriate. For example, certain images/videos might contain violence, nudity, or certain objects (knife, gun, bikini, etc.) that are considered offensive.

Integration of GNSS Precise Point Positioning and Inertial Sensing Technologies for Lane-Level Car Navigation

Present car navigation systems provide drivers with route guidance information relying mostly on Global Navigation Satellite Systems (GNSS). There is a growing demand at the present time to achieve decimeter-level accuracy for the purpose of accurate lane-level car navigation. This research aims at the development of reliable, accurate and continuous lane-level car navigation integrating the emerging GNSS precise point positioning (PPP) technology with motion sensors in land vehicles.

Developing Tools to Track Vocalizing Marine Mammals with Long Baseline Hydrophone Arrays

The scope of this project is to use acoustic data from long-baseline arrays of hydrophones to detect, locate, and track marine mammals based on their vocalization. Specifically, the project aims to assess methods and develop automated tracking algorithms that provide accurate results for individual signals, and a maximum of flexibility regarding the channel, array, and signal characteristics.

Application of Machine Learning Methods in Vancouver Island Supply Capability Determination

This project is a feasibility study of applying Machine Learning to Vancouver Island Load Supply Capability determination. The intern is expected to apply neural networks and other machine learning methods to train a transmission operation decision making model to determine the load supply capability of Vancouver Island. An operation scenario database covering equipment status and load information will be generated as the training data to the decision making model.

Creating a platform to collect / publish / analyze / control communication data streams

The NSERC Strategic Network for Smart Applications on Virtual Infrastructures is a five-year partnership between Canadian industry, universities, researchers, research and education  (R&E) networks, and high performance computing centres to investigate the design of future application platforms that will deliver software applications of greater capability and intelligence.

Control of HVDC Links in Synchronous and Asynchronous AC Grids using Wide Area Phase Angle Measurement

High Voltage DC Transmission (HVDC) is used for bulk power transfer over long distances. Manitoba Hydro’s HVDC system involves collection of AC power in the north where it is converted to DC and then transferred to southern Manitoba (approx 900km) through asynchronous HVDC links where it is converted back to AC to feed consumers. Asynchronous HVDC links can be used for improving electro-mechanical dynamics of the interconnected AC grids. This includes the functions of power swing damping, emulation of inertia and power-frequency droop.

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