Amorfix Life Sciences has had success producing highly specific antibodies, which can be used to diagnose disease. The company has recently gained access to an algorithm (ProMISTM) which allows to predict antibody targets on proteins in their diseased state, allowing development of very specific antibodies with diagnostic and therapeutic potential. The proposed project involves a comprehensive approach of identifying suitable protein targets involved in disease for the new algorithm by extensive database and market report mining.
The research project will be to develop a computational fluid dynamics (CFD) model of the Proceptor. The function of the Proceptor is to separate grease from contaminated water streams. The objective of this research is to study the separation process in greater details to reinforce and enhance the company’s understanding of the Proceptor design. Two commercial software products, Fluent and CFX, will be considered for building the model. The model will be validated using available experimental data.
In this project we proposed to use mathematical programming approaches to an optimization problem where a depot has to stop receiving orders from stores and fulfill the received orders using trucks. The depot can use different cut-off times to different stores and considering order arriving patterns and transportation efficiency. We will develop heuristic and exact algorithms to the optimization problem with an objective of maximizing the sum of orders processed in a day. The optimization is subject to varous contraints such as transportation capacity and delivery time window.
The focus of this project will be to model and optimize the scheduling of clinics at PMH-assigning clinics to clinic areas and clinic timeslots. The objective will be to improve the current schedule with respect to key performance metrics. These metrics will include clinic overtime, the equality of the distribution of demand on shared resources and the volume of patients which are able to take advantage of same day inter-clinic referrals.
The research project is to investigate a multi]factor multi]asset extension of the Hestonf93 stochastic volatility model for comprehensive Credit Value Adjustment calculation and Commodity Counterparty Credit Risk methodology. The extended model covers counterparty hazard rates correlated with the underlying and interest rates in order to model wrong]way exposure.
Currently, cellulosic ethanol production is laden with technical challenges, and as a result, not economically viable. The reason for this lies with the toughness of the plant feed material generally called biomass. Processing biomass to allow fermentation to ethanol often requires harsh operations such as extreme heat, pressure, acidity, or a combination of all three. This often leads to the formation of unwanted chemicals that are toxic to organisms that enable fermentation.
Intelligent visual surveillance refers to the use of context rich visual sensors, i.e. video cameras, for the purpose of surveillance. Surveillance systems can be deployed in diverse environments, such as airports, department stores, office buildings, home buildings, conference rooms, parking lots, and hotels for diverse purposes, such as ambient and personal security, information recording, and personal identification.
Surgical education has changed dramatically over the last 15 years as traditional “time served” approaches have given way to objective assessments of efficiency. These assessments are very resource intensive and require a greater level of training for the educators and evaluators. Furthermore they often do not provide timely, meaningful feedback to the trainees. To overcome these difficulties, the Surgical Skills Centre (SSC) at Mount Sinai Hospital is seeking to improve the efficiency of the assessment process and concurrently better integrate feedback into surgical education.
Problems associated with measuring scientific and technological advances make it difficult to determine the impact of R&D on scientific advancement, technical change and ultimately productivity and output. Our research uses new publication-based measures of technical and scientific change to: (1) quantify the importance of R&D and determine the strength of these relationships, (2) document differences between the US and Canada, as well as different regions (states, provinces and mega-regions), and (3) explore whether the variations are linked to regional productivity gaps.
In this project, we attempt to investigate the feasibility of using behavioral synthesis technology for large scale chip project. The project will be completed in Metabacus Inc, an Ontario startup company that develops and markets behavioral synthesis technology, which automatically converts software into chip designs. Although promising, one obstacle for the wide deployment of behavioral synthesis as the next generation chip design methodology is demonstrating the success of the technology on large-scale chip project.