Enhancing Software Lifecycle Visibility and Traceability

Teams of specialized workers develop most software. For example, one team may specialize in the requirements that describe what the software is to do. Another team may specialize in producing the software itself. Yet another team may specialize in determining whether the software meets the desired requirements. Supporting communication between all these teams is challenging: each team is focusing on their part of the system, yet needs to have awareness of the work being performed by other teams.

Dolmen: Towards the programmatic assembly of large-scale distributed systems

Modern distributed applications are becoming increasing large and complex. They often bring together independently developed sub-systems (e.g., for storage, batch processing, streaming, application logic, logging, caching) into large, geo-distributed and heterogeneous architectures.

Stressless Gamification to Improve Workplace Health

Stress is a top workforce risk and according to a Towers-Watson 2013 survey, half of all employers identify improving the emotional and mental health of employees as their top priority for building health and productivity programs. The objective of this research is to improve StressWelliQ’s systems and product portfolio by creating gamified technology solutions and thereby improving the lives of Canadians. The creation and evaluation of this technology will allow StressWelliQ to create a more effective augmented stress management platform.

Social and Environmental Impact of Co-operatives

The intern will work with the project supervisors to develop an online tool to capture 15 key performance indicators (KPIs) that reflect social and environment performance of co-operatives in Canada. The intern will attend focus meeting with the supervisors in order to identify the co-operative participants’ requirements. The intern will complete a systems mock-up and detailed user requirements document that will be approved by CEARC. An online web-based system will be developed to gather submitted data, produce benchmarks and functionality to create on-demand reports.

A big data approach to schedule optimization

Workforce scheduling algorithms are used by businesses around the world, including hospitals, factories, and retail stores, to determine when and where employees should come to work. Usually, the needs of organizations change over time, but the scheduling algorithms used in these systems usually do not change. Kronos is an industry leader in scheduling software, and has access to a lot of data reflecting schedule changes in many organizations.

Photonic sensors for rapid and selective detection of bacteria in water

In recent years monitoring and protection of food and water resources became a priority of governments worldwide. Bio-hazards are potential threat for these resources thus need to be addressed both in industry and in academia. Therefore, developing an accurate, fast and cost effective technique for detection of pathogenic strains called for increased demand on the areas targeted by the fiber-optic systems.

Cloud-based RealTime Energy Monitoring with Wireless Sensors

Long-term monitoring and modeling energy consumption behaviors is a daunting task for decades. This project aims to achieve efficient energy consumption data collection and processing using wireless sensors and cloud platform together, focusing on large scale enterprises that consume large amount of energy, e.g., electricity, gas. By tackling the challenges through algorithm design and system integration, a prototype system will be delivered, which can effectively gather data from distributed sensors and efficiently analyze real time data on the cloud platform.

Aurora Lighting

The proposed project contributes to the development of a product for use in public spaces to provide LED lighting which is made interactive through sound responsiveness. This sound responsiveness is made possible through the use of modern micro-computers which can be programmed to use sounds in the environment to create different lighting effects. Unfortunately, this is a difficult task if the environments are noisy. It's a lot like trying to have a conversation during a loud party; a lot of information gets lost.

Automatic Image Filtering Using Deep Learning

Two Hat Security is a company that develops next generation moderation tools for social networking apps. Since images are of the most important data shared by social networking apps, an important problem for the company is to identify images that are unsafe or inappropriate. In particular, images containing certain objects (e.g. knife, gun, bikini, etc.) are considered unsafe. It is obviously not practical to manually sift through all the images to find the unsafe ones.

Expert Gestures for Multi-touch Interaction

Modern smartphones and tablets, and many notebook computers rely on multitouch interaction to augment keyboard and mouse input. Multi-touch gestures typically consists of taps and swipes - simple gestures that don't exploit the full range of technical and human capabilities. In earlier work, we determined that users are willing to learn expert-level gestures, but often find them difficult to discover and challenging to learn without formal training.

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