Human Thermoregulation and Technical Apparel

Nature of the work: This project will assess a novel lululemon clothing ensembles during transitions between differing environments.
Anticipated Outcomes: An optimization of the design of clothing ensembles for transitions between different environments is the anticipated outcome.
Relevance: The project will provide garments for Canadians to improve their health, safety and comfort during outdoor activities.

Software Framework for Smart Building Energy Audits

With more and more buildings being controlled by automation systems, one would expect their energy performance to be optimised. This is not the case however. Buildings can still go out of tune, and building operators can become overwhelmed by the alarms sounding from the automation systems, not knowing how to prioritize them. SES consulting is well poised to provide a “human in the loop” performance analysis service, leveraging their expert knowledge and the data from the building automation system.

Large Consumer-Generated Data Optimization and Prediction

The proposed research aims to target large-scale consumer-generated data to analyze, visualize, and make predictions out of. The data will be collected from the consumers to make assessments on their lifestyles, and will come in forms such as heart-rate variance, that is, being temporal data. Researchers with visual analytics background will apply new visualization techniques on the data in order to grasp the insights and improve the model to interpret the data. The research problem is to relate measures of stress, recovery and mindful activities to the data obtained.

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.

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