Transparent and Trustworthy Deep Feature Learning for Cyber-Physical System Security

The latest artificial intelligence (AI) technologies have effectively leveraged the wealth of data from cyber-physical systems (CPSs) to automate intelligent decisions. However, for safety-critical CPS like smart grids and smart cities, the conversion of massive data into actionable information by the AI must be not only effective but also reliable.

Intelligent Cyber-Physical Situational Awareness for Smart Infrastructures

The availability of big data in smart infrastructures have become a strategical asset for operators to understand the situation of the infrastructure and monitor potential threats. However, most of the data still have not circulated beyond traditional corporation and technological boundaries, which have limited the visibility that could have been provided by the abundant data.

Data driven energy efficient base station sleep control for 5G systems

The objective of this project is to develop a software system which can optimally control the base station sleep states in 5G networks to save energy. The 5G wireless networks are required to be green and yield very low carbon dioxide emissions. Compared with that of 4G wireless networks, the power efficiency of 5G is expected to be increased to 100-fold. High energy efficiency is a critical requirement in 5G network design and operation.

Handheld Histories: Collecting, Modding, and Playing the Portable Platform

Thirty years after its landmark 1989 release, Nintendo?s Game Boy and its long line of successors continue to capture the imagination of thousands of players who harbor a nostalgic attraction to the technologies of their youth. Montreal-based Retro Modding has developed a profitable business modifying (or ?modding?) old video game handhelds and selling them alongside tools and parts for do-it-yourself projects. These alterations combine today?s expectations for consumer electronics (like backlights and rechargeable batteries) with the iconic form factors of early handhelds.

Improving hygrothermal modeling as design tools using field measurements to achieve durable and energy efficient wood structures

Computer-based simulation software, called hygrothermal modeling has become increasingly popular and useful to predict and evaluate heat, air, vapour, and water-related performance of buildings. This research project aims to improve such modelling for wood construction through validation using specifically measured property data and field/lab performance data. The goal is to make modelling a more reliable design tool and to subsequently improve the design and construction of both mass timber construction and light wood-frame construction.

Large-scale optimization algorithms for optical and fiber networks

Networks are moving towards being adaptive. This means that automation will be used to replace processes which are today highly manual. This project proposes a development of knowledge in the area of algorithms required to enable adaptive networks. The project will train two PhD students to understand optical networks and devise optimization algorithms in the areas of interest. In particular, the algorithms will be devised to be fast and near-optimal to enable their implementation in the network in accordance with operator’s goals of making the network near-optimal and adaptive.

Water, water everywhere!

“Traffic snarled due to a burst watermain near the Granville Aquaduct,” states News 1130.

Due to the estimated age of the infrastructure and pipe material, the City of Vancouver had slated the duct for replacement next year. A year too late for all those affected by today’s rupture.

In Canada, the replacement of pipes in poor and very poor conditions requires a total investment of about 25 billion dollars (Canadian Infrastructure Report Card 2016).

Electro-bioreactor (EBR) upgrading for high ammonium removal

The objective of this project is to build up an electro-biological system of high potential capacity for the removal of ammonium and phosphorus. Conventional biological treatment methods have limited capacity for removal of ammonia at higher concentrations. However, anammox bacteria have a high capacity to remove ammonium. The electro-biological treatment aims to enhance this capacity by electrically activating anammox bacteria on a fixed media.

Towards Automation of 3D Visualization & Analysis of Workspace Collisions on Construction Jobsites

Workspace Interferences/Collisions happen on construction jobsites when multiple resources (labor, equipment, material, etc.) don’t have enough space to coexist at the same time and will interfere with each other’s operations. These interferences affect performance, delaying the project, impacting cost, and may jeopardize the buildings’ integrity and people’s safety on site. Most of existing models simulate resources as being deterministic. However, the behavior of the crew interfering is more chaotic.

Automated Risk Identification in Modular and Offsite Construction

Modular and offsite construction, where a module of project or complete house is manufactured in a factory, requires a large upfront capital (working capital) investment in order to procure materials in advance of manufacturing and to deliver modules on time and on schedule. Thus, modular fabricators need to receive deposit and progress payment before the assembly process. In the eyes of a bank, a prefab house is “just materials”.