Mobile Network Carriers are experiencing unprecedented data traffic loads which are straining their existing infrastructure. They are thus interested in exploring research areas which focus on reducing this traffic load. The malicious traffic generated by malware on smartphones is of particular interest. My research focuses on the generation of a software system that marks traffic from smartphones to indicate the specific phone application which has generated the data flow.
The research project aims to develop an effective method that utilizes multiple features to improve mass spectrometry based peptide identification with database search approach. The project is a continuation to the student’s previous research on precursor charge state prediction, since predicted charge state is a novel feature and has a great potential to discriminate the correct and incorrect peptide identifications.
Metafor is developing a new class of IT system management solutions and as a part of this, Metafor wants a method to show differences between multiple deployed instances of an application. To implement this, Metafor requires an accurate and high-performance generalized tree differencing algorithm. Differencing algorithms are used for comparing different versions of a document or snapshots of data to find similarities and differences between them. And tree differencing algorithms perform differencing on hierarchical or treestructured data.
Traditional GPS RTK system requires at least two receivers one of which serves as base station with known coordinates. Assuming separation between base and rover receivers is not too long, for example 10 km, spatial correlations for GPS observation errors are pretty significant. Base station can be used to correct rover observations. As a result, 2 cm horizontal and 5 cm vertical positioning accuracy within less than 5 minutes initialization time is available at rover.
The research project will involve the development of features and techniques to aid people with communication disabilities through the use of consumer mobile devices (ex. smartphones) and tablet computers. Some of the major areas of interest include: location aware vocabularies, predictive sentence construction, and support for alternative input for people that also suffer from motor control problems. This work will directly benefit the partner organization by providing enhancements and breakthrough, cutting-edge, technology features to the MyVoice commercial product.
This project aims to assist a company in developing Discrete Event Simulation (DES) and Human Factors modeling (HFM) capabilities. Simultaneously the project aims to explore the impact of alternative engineering designs with a Human Factors (HF) focus. These two aims will help understand factors that affect the uptake and application of the DES and HFM in work system design. The participating company is Research In Motion (RIM), which is a well known Waterloo, Ontario based telecommunication company.
