Fiber Bragg gratings (FBGs) have attracted considerable interest in the past three decades as a key technology in different applications. The intention of this project is to develop a FBG writing technique based on a scanning tunable Phase-Mask Interferometer using different UV lasers. The project includes optimizing the tunability of the interferometer, and analyzing the specific problem situations encountered in the process in order to develop the interrogation methods of the proposed technique.
Emerging applications such as interactive video conferencing, Voice over IP (VoIP) and cloud computing are required to achieve an end-to-end latency of less than 200 milliseconds. In many wireless networks, the round-trip time can alone reach this limit. Hence it is necessary to develop new delay-optimized networking protocols and delay-sensitive coding techniques in order to meet such stringent delay constraints. The proposed project will investigate both theoretical foundations and practical implementations to reduce delays in interactive communication scenarios.
Le projet porte sur le développement des algorithmes permettant de transporter d’une façon stable, par deux robots humanoïdes Nao, une table miniature dans un environnement encombré. Plusieurs étapes sont nécessaires pour arriver à ce résultat. En premier lieu, il est essentiel de compenser les perturbations causées par les oscillations latérales dues à la marche bipède. Puis, une planification de trajectoire de marche doit être effectuée afin de faire naviguer les robots dans l'environnement encombré.
The main objective of the proposed research project is to develop a new transient stability simulation method based on advanced computational and modeling techniques that is both fast and accurate. Transient stability studies are an important part of system planning and operation as they ensure that a system will maintain stable operation following severe disturbances. However, traditional simulation techniques were not designed for the size and complexity of modern power systems.
Many big data challenges are characterized not only by a very large volume of data that has to be processed but also by a high data production rate. In this project, new storage approaches for big data will be explored. Key point is the efficient use of modern hardware, especially modern storage technology such as SSDs. These new technologies have highly improved performance in comparison to traditional hardware. However, classical data structures and algorithms can not directly be applied due to the different characteristics of these devices.
Unlike centralized computing, which is typically performed in a single data-center, Cloud computing enables the computation to be spread across multiple geographically distributed data-centers which are abstracted as a single system by the Cloud management layer. This computational model enables disaster recovery (DR) by re-establishing the services provided by a data-center affected by the disaster in another healthy data-center capable of hosting the applications providing these services.
In this project, a methodology for controlling the distributed generation resources connected to the distribution system level will be developed. This control strategy will improve the efficiency and reliability of the operation by decreasing the losses, managing the assets, and increasing the system reliability. There are currently several feeders in the BC Hydro distribution system with considerable amount of distributed generation installed. This has caused voltage problems at the feeder level and also control issues at the substation level.
Disruptive antenna technologies are required to provide performance and fabrication advantages in developing broadband wireless application products in emerging upper microwave and millimeterwave radio bands. The internship will investigate the feasibility of applying Polymer-based Dielectric Resonator Antenna (PRA), technology developed at the University of Saskatchewan, to commercial antenna array applications
MixGenius works on automated musical production by real-time musical genre detection. High accuracy of genre detection for a variety of sub-genres is required for quality production and has yet to be achieved. The project involves researching available real-time high-accuracy musical genre detection methods and improving upon them, extracting each genre’s audio features, calibrating the algorithm with a database of songs of different genres, testing them with other songs of the same genres and repeating the process as needed to improve detection accuracy.