Dynacon Inc. is a company that specializes in applying automation and robotics technology to the microbiology industry. Their complete robotics control systems automate the repetitive and time consuming process of sample handling and labelling, which were previously performed by lab technicians. The current project aims to enhance the reliability and overall value of the robotics system by developing intelligent imaging and vision algorithms to aid in the automation process.
This research intends to acquire a better understanding of driver behaviour, fuel consumption and the greenhouse gas emissions associated with the operation of ski resort fleet. Twenty‐six light and medium duty vehicles at ski resorts will be equipped with an onboard logging device that records electronic engine data (i.e.: idle time, distance travelled, highest speed, fuel efficiency, fuel cost, hard braking and acceleration thresholds) over an 8 month period.
Munich Reinsurance Company (Munich Re) is the largest life reinsurer in the Canadian marketplace. Proper risk assessment at Munich Re is vital in order to assure that Canadian policyholders receive their promised coverage. This assessment includes measuring and monitoring the mortality risk of its life related business. The goal of this project is to improve the models Munich Re uses to model mortality risk. Measuring mortality risk assists Munich Re in determining the capital it should hold for its life related business.
In the project, three interns will work intensively with Philip Beesley Architect Inc. on designing and implementing kinetic architectural envelopes. The envelopes will be presented as sculptural installations and as a dynamic shading system for the Canadian North House entry to the 2009 Solar Decathlon. Parametric modeling of components will be used to explore the conceptual possibilities for the project and establish design alternatives. Solar power and wireless communication technologies will be developed, building on the open source Arduino platform.
In order to bebug a system, one requires information from both offline and run time slates of the system. In more cases the information required to trace a problem does not correspond to the information available from the output provided by the system. Thus, additional probes must be inserted in order to achieve the required information. Herein lays the problem since the probing could perturb the system leading to side effects known as Heisenbugs. One major reason for the occurrence of these bugs is due to lack of information a developer has on the effect of probing.
This Mitacs-Accelerate internship has to do with studying the Emergency Department (ED) operations at the Grand River Hospital. In May of 2008, the provincial government announced funding for a number of hospitals to help them reduce ED wait times. The focus of the internship is an in‐depth study of the ED, and a detailed analysis of all information, patient, staff and equipment flows.
The goal of this project with Agfa Healthcare, a provider of diagnostic imaging and healthcare IT solutions, is to develop mathematical models for (i) assessment and (ii) improvement of compressed medical images. The rapidly increasing volume of data generated by new imaging modalities (eg CT scanner, MRI) necessitates the use of lossy compression techniques to decrease the cost of storage and improve the efficiency of transmission over networks. Increasing the degree of compression of an image, however leads to decreasing fidelity.
The project with Dynacon Inc., a company applying automation and robotic technology to microbiology industry, aims to design control software that drives an automated specimen processing robotic system. This robotic system automates the processes of handling and labelling biological specimen containers. It is used to increase the productivity of microbiology laboratories and quality of their results. This robotic system controller handles hundreds of specimen containers in a single run.
Risk management is a topic of great current importance to financial firms. In this project, the intern will undertake research with a small investment firm to develop more efficient risk management techniques. He will assemble a new database that is relevant to the firm’s existing and potential investment strategies. This database will be used to develop models of underlying risk factors, which will be used in the development of innovative risk management tools to assist the company with controlling its risk exposures.
Understanding the likelihood and trends in the occurrence and severity of natural disasters is an intricate part of insurance risk analytics. In today’s marketplace, the task of quantifying such risks is handled by vendors of catastrophe modeling tools. Due to proprietary, the vendors do not disclose the scientific and technical at sufficient detail for the users (insurance companies) to understand the modeling output thoroughly, such as sensitivity to assumptions, difference among different models, etc.