Embedded Low Power Signal Processing for Passive Acoustic Monitoring

This project will attempt to explore the solution space around a number of key issues related to passive underwater acoustic monitoring. Namely the mitigation of acoustic flow noise in turbulent environments, digital compression techniques for underwater acoustic data and the implementation of real time signal processing algorithms related to the detection of marine mammals on ultra low power processors.

Terahertz Time Domain System to Characterize Performance of Terahertz Quantum Cascade Laser Sources

In this project, we plan to address the specific application and problem that TeTechS Inc is facing at this stage of its product development of photoconductive antennas, which is using its photoconductive antennas for characterizing performance of quantum cascade lasers (QCL) in time-domain measurement setup by demonstrating the capability of its proprietary terahertz sensor technology to be used by researchers in University to characterize QCL and in industry for building terahertz spectrometers with high signal and bandwidth.

Capacity Planning and Optimization of WiMAX for Smart Grid, Part 2

Smart grid (SG) aims at modernizing the current power grid which can better manage the electricity through the grid and react to the system faults quicker. To realize this goal, many sensors are attached to different points of the power grid infrastructure. These sensors collect data and can be used for controlling, protecting, and monitoring the status of the grid by receiving comands from the utility control center. Hence, a two-way communication infrastructure seen to be required for smart grid realization.

Textile Sensor Development for an EMG muscle activity monitoring system

GestureLogic is building a product that optimizes athletic performance. The product is a wearable sensory network that monitors muscle activity. The goal of this research is to take this inherently complex muscle data that is acquired by the sensory network and translate it to useful biometrics for the consumer with the help of intelligent algorithms. The algorithms will help intuitively visualize important metrics such as strength of muscle contractions, heart rate and fatigue. The benefit to the partner organization is twofold.

Development of a system for the automatic recognition and classification of normal and abnormal cells in human blood samples

Automation of medical diagnosis/detection process is very important in terms of enhancing diagnostic accuracy, increasing throughput, reducing cost, and training new staff. Our current goal is to go from the proof of concept stage (automatic recognition and classification of human blood images) to a complete working optimized prototype and to start testing it in an actual clinical lab environment with help from CLS. The prototype design will take into account user friendliness, high throughput, robustness, integration with existing lab work flow and reasonable cost.

Anti-islanding detection for renewable energy systems in distribution system

Integration of renewable energy systems into grid is an effective solution to the electric energy shortage and environmental pollution. A number of technical challenges may arise with increased grid-connected renewable energy systems. One of the most important issues is how to achieve the islanding protection. Many anti-islanding detection methods have been reported for single renewable energy systems in the last decades. In practice, however, the multi-unit systems are distributed in different feeders. Consequently, all of the existing methods might fail in this case.

Virtualized Wireless Access in the Green Sustainable Telcommunication Cloud System

This project is primarily focused on virtualizing wireless access network so that multiple operators can share the same physical resources while being able to stay isolated from each other. The basic idea is to allow wireless access points from different operators form a single virtual access point that efficiently manages its available resources. The goal is to exploit the advantages that can be obtained from virtualizing the air interface (i.e., spectrum sharing), protocol virtualization and flow-based virtualization.

Development of spectroscopic imaging technology for grain quality inspection

Fusarium fungi infestation causes Canadian grain producers a loss of almost $1 billion dollars per year. Fusarium fungi produce toxins, e.g., deoxynivalenol (DON) which cause toxic effects in animals and possibly humans. We will develop a portable hand-held hyperspectral imaging device to detect, in the field, Fusarium infestation in grains. We will also evaluate the applicability of spectroscopic Optical Coherence Tomography to accurately and quickly determine DON level in grains with high sensitivity (1 ppm to 10 ppm).

HVDC “Superline” for improved angular stabilityof AC-DC system

High Voltage DC Transmission (HVDC) is used for bulk power transfer over long distances. Manitoba Hydro system involves collection of AC power in the north where it is converted to DC and then transferred to southern Manitoba (approx 900km) where it is converted back to AC to feed consumers. Recently the problems of inter area oscillations have been reported in the system. Manitoba Hydro uses feedback signals such as frequency from the converter stations as control input to modulate power through HVDC links to damp these oscillations.

Calibration, Characterization and Optimization of Microwave Imaging System for Grain Monitoring

Microwave Imaging (MWI) is an emerging modality where the goal is to estimate the electrical properties of an object-of-interest. This is done by transmitting a microwave signal into the OI and collecting measurements outside the OI. The measurements are inputs to an optimization algorithm that solves for the unknown electrical properties. It has been proven using computational techniques that the proposed modality can be successfully adapted for monitoring moisture content inside grain bins.

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