Canadas coastal regions are an excellent source of marine renewable energy. These regions are also popular with marine mammals, providing good feeding opportunities. However little is known about how marine mammals will be affected by tidal energy developments. Concerns include the impacts of sound on animals ability to find food and navigate, the indirect effects of changes in prey distribution and abundance, and the direct impacts of collision with tidal energy structures in the water column.
AYO Smart Home is an integrator of new technologies to provide affordable and energy-efficient housing for First Nations communities across Canada. AYO manages the technology and supply chain to deliver Net-Zero houses consisting of efficient building envelopes, heat recovery systems, energy-efficient HVAC, LED lighting, mold-resistant materials, and smart home controllers.
Wesgar is a factory that produces metal sheets for its customers. After a product is ready, it will be delivered to the customer. The objective of this project is to improve the On Time Delivery. At Wesgar they have different machines in their production system. These machines are able to process different products based on the shape, size and material. Each product must pass some specific machines to be processed through the production plan. A schedule that determines which product must pass which machine at what time is required for the production system at Wesgar.
Different snowpack structures and weather conditions create distinct types of avalanche problems that require different risk mitigation practices. In North America, nine types of avalanche problems have been identified in the recently introduced Conceptual Model of Avalanche Hazard (CMAH). Avalanche Canada and Parks Canada forecasters have identified and assessed avalanche problems according to the CMAH daily since the winter 2009/10. This dataset provides a unique opportunity for examining the nature of avalanche hazard in western Canada.
Pintellect is Enterprise Social Software that gives employees access to the thoughts and ideas of the organizations influencers by encouraging them to share links to the internal files or external resources such as books, TED talks, podcasts, articles, etc. The objective for this project is to develop multiple algorithmic solutions for curated feed of content by department on the dashboard based on number of identified criteria.
Community hospitals in small towns or rural areas face challenges in delivering health care that will allow elderly members of their community to remain in the community that they helped to build. Using simulation modelling, this project will develop strategies for delivering complex continuing care in rural hospitals that is closely integrated with long-term care, residential care, and home care services. Small towns and rural communities have a tight-knit social fabric and the contributions that family support and community services provide to health care are important factors.
Over the past three decades, there have been drastic declines in voter turnout and traditional political participation across North America, particularly among younger demographics. As young people increasingly move away from institutionally-driven practices, political participation is no longer only defined by voting in elections, volunteering with civic associations and town hall meetings but increasingly manifests through civic media political engagement facilitated by digital tools.
We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are in the process of signing partnership agreements with retailers capable of collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems customized for the data-sets available to brick and mortar retailers.
Project is to import ten years of historical data on news events, public sentiment metrics and the price movement of S&P 500 related equities for study and analysis through the latest Data Mining and Machine Learning techniques. The goal is to uncover correlation and causality between events and price movement of global markets in multiple timeframes (three hours, daily, weekly, monthly and yearly). Specifically, the research would answer the question which features (metrics) generated from initial news and sentiment data have predictive power and which don't.
There are several platforms that allow users to share real time video with the public. However, these platforms lack the tools that would allow creative professionals to create artistic video compositions extemporaneously. Our prior research assessed the potential for artistic expression within live video broadcasting by developing and integrating new creative tools within the Generate platform, a mobile tool for dynamic artistic video compositions. Behavioral analysis provided the information to determine the effectiveness and relevance of video art in an online real time nature.