This project aims to conduct a comprehensive review of existing power line (PL) data processing procedure used in practice and to design and develop the new automatic workflow by integrating state-of-the-art algorithms with current data processing chain. This leads to the establishment of an innovative framework on automatic PL feature detection and reconstruction from LiDAR data. It will also result in a functional software module that can be demonstrated in a GUI and can be pluggable to other existing software packages. The expected benefit to the partner can be summarized as: (a) Efficiency-time and cost effective maintenance of PLs are possible by introducing automatic methods in a PL scene classification and modeling. (b) Accuracy – the proposed technique ensures that more accurate clearance quantity which threaten PL system sis determined. (c) Productivity – the new technique is expected to enhance the updating process of a geospatial database related to main features in PL corridor area. 

Glioblastoma (GBM) is the most common and aggressive form of brain cancers and is the second most common cancer in children only behind leukemia. Conventional therapy consists primarily of surgery, radiation, and chemotherapy, and while these approaches have slightly improved the length of patient survival, there remains no cure for this disease. With the emerging understanding of biology in the process of cancer development, identification of therapeutic targets are being elucidated that will allow more targeted and effective treatment of the disease. This approach is especially important in pediatric brain cancer where conventional therapies may result in damage to the brain causing long-term neurocognitive deficits. We have identified one such target, a protein called the Y-box binding protein (YB-1) that is expressed in adult and pediatric GBM. In those cancer cells it promotes tumor cell growth and also drug resistance making it an attractive target for drug therapy. This project delves into a deeper understanding of how YB-1 controls drug resistance through its partnership with another protein, BMI-1, with the aim of increasing therapeutic efficacy. 

The web browser is arguably the most security-critical component in our information infrastructure. Banking, social networking, shopping, navigation, and card payments – almost any activity you can imagine now takes place within a browser window. HTML5 is a potential candidate for changing our experience on the web and its sale on devices is forecasted to top one billion in 2013. Hence, at Irdeto, HTML5 and its implementation on different platforms is seen as a profitable business. On the other hand, HTML5 introduces new set of security vulnerabilities that cannot be easily addressed by existing security technologies. The main objectives of this research project are to identify and understand HTML5 security problems, investigate key security areas and develop possible security solutions. This project is meant to help Irdeto have a better position on HTML5 security and maintain its first rank in the online market business. 

The purpose of this research is to reveal the factors that motivate firms to participate in voluntary energy programs, with reference to the Building Owners and Managers Association (BOMA) of Toronto Conservation and Demand Management (CDM) Program. The program directed incentive funds to reduce electricity demand in large Toronto commercial buildings and provided a $60 million subsidy for building owners and tenants to conduct energy conservation projects. The study will examine whether the subsidy was the primary motivator in a company's participation, or whether there were other underlying influences, such as public recognition/publicity, competitive advantages; to strengthen a company’s environmental practices; or to improve stakeholder relations. The results will aid Hydro One in determining the strengths and weaknesses of this particular energy program and may offer solutions in the improvement of current or existing voluntary CDM programs.