Improving usage pattern quality by comparing different sequential pattern mining methods and the effect of considering additional user information

Frequent usage patterns generated can provide valuable information for several applications such as platform restructuring and recommendation. In this project, we aim to compare different practical methods, and to investigate the effect of user identity and user intention information on them. To that end, a technique and a framework need to be developed, in which frequent patterns are composed of more refined analysis result instead of simple frequent sequences of basic operations over all users’ behavior.

Developing Prediction Models on London Stock Exchange (LSE) Equitiesand Indicies using Microsoft Azure Machine Learning and Data Mining

I am to import ten year’s worth of amassed historical data on news events, price movement of equities and public sentiment metrics to Microsoft Azure platform for study and analysis through the latest Data Mining techniques with an Economics point of view to uncover the hidden correlation and casualty between events and price movement of global markets in multiple timeframes (three hours, daily, weekly, monthly and yearly).

Energy Harvesting and Power Management Techniques for Hybrid Powered Wearable Devices

Bigmotion Inc. was created to develop wearable health monitoring sensors and service the ‘at-home’ care segment of the elder care market. This project involves studying of existing literature and development of novel solutions for
power management and energy harvesting for the product including tracking and fall detection systems using hybridpower.

High Efficiency PFC Rectifier using Wide Band Gap Power Device

The energy-hungry telecomm industry is in need of power supplies with ever-increasing efficiencies to conserve energy and reduce carbon footprint. In collaboration with the industry partner, the proposed research project aims at developing a power factor correction (PFC) system, an essential component in a telecomm power supply, for achieving efficiency of 99% or above. The project will make use of emerging power semiconductors with superior characteristics to build a PFC circuit using one of the most promising circuit structures.

Generating Insight for Continuing Care through Exploration of RAI-MDS Data with Data Analytics and Computational Mode

The Resident Assessment Instrument Minimum Data Set (RAI-MDS) is used by health authorities for collecting information about individuals in continuing care facilities. Collected quarterly, RAI-MDS records contain more than 500 data elements, including cognition, psychosocial well-being, health conditions, communication, physical function, and activity patterns. Because of this it has great potential for providing an incomparable quantitative view on the lives of the oldest and most vulnerable Canadians.

Atmospheric Acid Emissions, Climate Change, and Coastal Salmon Stream Ecosystems in British Columbia - Year Two

Atmospheric acid emissions are increasing in north coastal British Columbia from increased metallurgical smelting, marine fossil fuel transport, and development of liquefied natural gas. Acid deposition can cause episodic acidification of streams when acidic compounds are flushed into streams after snowmelt and precipitation events over hours to weeks. Many salmon-bearing coastal streams are likely sensitive to episodic acidification, but these events are poorly quantified in western Canada.

Hydrogen Storage in Two-Dimensional Layered Nanomaterials: Characterization - Year Two

In this project, we will develop solid-state hydrogen storage materials for the potential applications of fuel cell electric vehicles. Based on the most cutting-edge achievements in related fields, two categories of two-dimensional layered nanomaterials are proposed. Their hydrogen storage capabilities will be elaborated by in-depth characterization of material structure and hydrogen storage properties.

Investigations in real-time spinal magnetometry using magnetoencephalography (MEG) for therapeutic biofeedback

Oscillatory neuronal activity can be quantified to help diagnose states of health and disease in the brain. These activities change on a fast time scale of milliseconds, which can only be captured by direct measurement of the brain’s electromagnetic activity. This is accomplished utilizing MEG and EEG technology, which can measure non-invasively these fast changes on the scalp surface. Moreover, using MEG, these signals can be observed within the brain volume through a localization process.

Hydrogen Storage in Two-Dimensional Layered Nanomaterials: Synthesis - Year Two

The objective of the proposed research is to investigate novel solid-state materials that have potential for hydrogen storage applications in fuel cell electric vehicles. Of interest are materials that can store hydrogen at ambient conditions and low pressures, have high gravimetric and volumetric hydrogen capacities, and can be safely packed into a hydrogen storage tank for automotive use. The research will focus on assessing the feasibility of threedimensional structures consisting of two-dimensional layered nanomaterials such as graphene as viable media to store hydrogen.

Quantitative assessment of risks involved in mechanized skiing in Canada

Helicopter and snowcat skiing in the backcountry involves different hazards such as avalanches, tree wells or helicopter incidents, which can result in serious injuries or even death. While the risk associated with avalanche involvements is well understood, no systematic analyses have been conducted on the other risks.

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