In this project, the intern research team is proposing to research and develop a Decision Support System (DSS) based on current research in constraint-based optimization, dynamic scheduling and probabilistic modelling. The Ottawa Paramedic Services (OPS) can use this system in their command and control centre to improve its operation and as a result improve the lives of the residents of Ottawa. The system is supposed to handle the burden of the combinatorial complexity while the human operator makes high level, strategic and tactical decisions.
A High Dynamic Range display is a display that can reproduce a wider range of image intensities than typical displays - that is, a range more closely matching the capabilities of the human visual system. Specifically, BrightSide Technologies’ DR37-P display can produce an eye-squinting 4000 cd/m2 (as bright as a ceiling fluorescent light) or as dim as 0 cd/m2.
Data mining refers to non-trivial extraction of implicit, previously unknown, and potentially useful information from data. In this project, the intern will apply data mining techniques to agro-meteorological data provided by Manitoba Agriculture, Food and Rural Initiatives (MAFRI). Specifically, he plans to develop mathematical solutions to analyze both current and historic weather data as well as related information such as crop yields, soil inventories, and crop management practices.
This project is part of a larger research project which investigates the applicability of the peer-to-peer (P2P) computing paradigm in designing large-scale content distribution systems. To develop an efficient content distribution system, it is essential to understand the workload that will be distributed, the behavior of content consumers and the environment in which the system will operate.
This project aims at performance modelling of athletes and involves the collection of detailed data that affects rider performance in professional cycling. This data is utilized for assessment of training and performance and for supporting individual training schedules through modelling and profiling of individual athletes. The methodology is based on pattern discovery and recognition using Self Organizing Maps, an exploratory data analysis model of demonstrated success in automated monitoring tasks involving multiple parameters.
Behavioural detectors for intrusion detection require training in order to correctly characterize the operation of a service – protocol combination. Implicit in this is the assumption that the learning algorithm will scale to large datasets and provide simple solutions. This work will address both requirements under a Genetic Programming context through the use of a combined multi-objective, host-parasite model. It has already been demonstrated that both schemes are appropriate independently.
The objective of the project is to determine the impact of various game features on VLT game play. These features are based on the current strategies adopted by SPIELO for its North American market. This data will be collected from players in a real life setting, then analyzed, and used for player profiling and as an input for improving existing strategies and measure their effectiveness. The analyzed data, the derived player profiles and the inference from the study will be used in developing a software simulator of original gaming environment.
Currently, EMS paramedics record patient information such as history, medical assessment, and treatments rendered onsite with pen and paper. They then convert this information to a paper-based call report and hand it over to the hospital along with the patient. This method is time-consuming and error prone. It causes delay for data analysis and lengthens paramedic turn-around time. This project will produce a data collection tool based on the mobile IP infrastructure which will reduce clerical errors, improve data analysis and medical care.
Distributed Denial of Service (DDoS) attacks are widely regarded as a major threat to the Internet because of their ability to make a service unavailable and create a huge volume of unwanted traffic. Unwanted traffic control is one of the most important challenges of Bell Canada. Current countermeasures cannot assure higher quality of service under a tremendous increase in unwanted traffic.
This project is about content-based networks. In content-based networks, the decisions regarding the forwarding of data are done by inspecting the actual information contents. The forwarding process is guided by properties of the payload data. This is in contrast with traditional networks where forwarding is guided only by the destination addresses contained in packets.