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

My project aims to understand cetacean habitat use in remote areas along Canada's coast. Using acoustic data from an array of permanently recording hydrophones, I am developing software to automatically detect, classify, and localize different species of whales that use the area .
The acoustic network is located deep in the Great Bear Rainforest in northern British Columbia in thus in important habitat for Northern Resident Killer Whales, humpback whales, and fin whales.

Design of an EV Charging Infrastructure: DC Grid for High Density Plug-in Electric Vehicle Charging and other DC Loads-Phase II

West 5 community in London, Ontario, will pursue high penetration of electric vehicles, and is exploring an innovative marketing program of including them with the sale of each new condominium unit. The primary objective of this project is to determine an economical approach to create an acceptable infrastructure for these electric vehicles that will be desired by the community. The study will evaluate how to improve the efficiency of using Solar Energy to charge vehicles? battery and for other DC loads in the London West 5 community.

SWAVE Ultrasound Elastography

Organ health is often tested today by biopsy, which involves placing a needle into the body and taking a small tissue sample for analysis in a lab. Researchers at the University of British Columbia invented a new technique to measure the health of tissue without a needle. This technique is called Shear Wave Absolute Vibro-Elastography (SWAVE) and it measures tissue elasticity by recording the small shear waves that result when tissue is vibrated with a loudspeaker-like device pressed against the skin.

Visual enhancement in normal and abnormal visual system

Vision loss related to malfunctioning of the brain have always been believed to be unrecoverable in adults. Novel treatments, however, have shown the opposite. Visual stimulation is a computer-based system which devised visual stimuli are presented to participants. Transcranial Magnetic Stimulation is a non-invasive technique to deliver an electric current to the brain. Both treatments have shown promising results on recovering vision in participants with amblyopia (lazy eye) and in the ones who lost it following a stroke. We will study the benefits of combining these two techniques.

Wind Turbine Power Curve Modelling for Reliable Power Prediction Using Isotonic Regression and Different Loss Functions

Electrical power generation based on wind energy has been one of the fastest growing renewable energy sources. An important area of research in wind energy is to find different ways to improve the power reliability of systems. Modeling wind turbine power curve using past data is often used as an efficient way to use empirical power curve instead of manufacturer company power curve.
As wind-power data are often so noisy, fitted wind turbine power curves could be very different from the theoretical ones that are provided by manufacturers.

An Efficient Data Analysis Pipeline

The proposed research project targets computational performance improvements of an data analysis pipeline. The project has a duration of four months and aims to achieve two objectives: (1) to properly characterize the performance of individual stages of the existing data analysis pipeline in terms of execution time, memory, and I/O, and (2) to improve the performance of individual stages where possible. The intern will use methods learnt and developed during the masters research and apply them to a real-world system at Acerta Analytics Solutions.

Dam Seepage Monitoring using Distributed Optical Fiber Sensing

The safe operation of a dam, such as Mactaquac, necessitates regular integrity monitoring over the structure lifespan. Optical fiber temperature sensing can provide seepage monitoring throughout a dam structure providing the operator with location specific seepage rates. Since the monitoring will be continuous over time and potentially operate over the lifespan of the dam operators can identify trends and evaluate repair effectiveness.

Anomaly Detection using GAN

The proposed research project targets anomaly detection of event data. The project has a duration of four months and aims to achieve two objectives: (1) to evaluate the effectiveness of a novel approach on GAN for real-world data, and (2) compare it to alternative methods. The intern will use existing research resources, and will apply them to real-world data provided by the partner, Acerta Analytics Solutions, Inc. to evaluate the different methods.

Securing IoT in Transportation Applications using Blockchain

The proposed solution will address IoT security challenges by using the blockchain technology to create feasible trust mechanisms. We will develop a solution by which exchanged information remains trusted and confidential to be handled efficiently at different places, and we will apply it to a smart transport use case.

High-Fidelity Data Converters for Medical Diagnostics

Diagnostic medical devices work by translating our vital signs, such as neuron electrical activity and brain waves, into digital data that can be manipulated by a computer. High-speed computer processing improves diagnoses by presenting the physician with a numeric or graphical readout of important features extracted from the signal. Often, the ability of computer programs to extract the most diagnostically-relevant information is limited by how well the device can recognize and ignore background electrical noise common in clinical environments.

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