InteliRain Inc. has developed an effective sprinkler system producing excellent uniformity water distribution for regular or irregular areas but using 30% less water compared to most existing standard industry system. However, the performance of the InteliRain system deteriorates rapidly when it is tested in an open field with wind effect. In this project, the intern will develop a mathematical model and computational algorithm to simulate the InteliRain system for cases with wind effect.
A critical issue in the oil and gas industry is to quantify the composition of fluids flowing back from the hydraulic fracturing process. This quantification is usually carried out by a manual process (frequently via a visual test) to estimate the water and oil produced from a well flow back process. A sample of these onsite tests are sent to laboratories for chemical analysis. This process has been the status quo for decades. This approach is manual, prone to error, and does not lend itself to sophisticated real time analysis.
Machine learning is the concept where a computer can be trained to recognize data and predict future outcomes based on the trends that exist in the data. This method of analysis has not been used on engine data, specifically in-line oil. Oil is an engine’s lifeblood and a lot of data can be collected and engine health can be predicted based on these measurements. This project aims to deploy machine learning concepts in the area of engine failure prediction.
Diseases, there are a number of different serotypes that can cause infection. The vaccine is often targeted towards one or some of the serotypes. There is accumulating evidence that when serotype-specific vaccines are used, other non-vaccine serotypes may gain a competitive advantage and spread in larger magnitudes. This has raised the concern of serotype replacement when vaccination is used against a single or several serotypes of a disease. In other words, serotypes that not targeted by the vaccine are able to able to fill the ecological niche left open by the vaccine-targeted serotypes.
Harvesting energy from renewable resources, such as wind and ocean waves, is an important issue facing our world today. With the increase in carbon dioxide levels in the atmosphere, there is a need to move away from nonrenewable resources and to find new methods for capturing energy. Wind turbines operate most efficiently within a narrow band of wind speeds, outside of which the amount of electricity they produce plummets.
Acidification of fetal blood presents one of the greatest risks to the fetus during childbirth. Current monitoring technologies focusing on recording fetal heart rate are poor indicators of fetal stress levels, and provide minimal assistance in clinical decision-making. This is due to a lack of understanding about which features of fetal heart rate best represent blood acid levels.
Pratt & Whitney Canada (PWC) seeks to improve the monitoring of its machining process aiming to reduce cost and prevent the tools, workpieces and machine damages during the machining. To achieve this improvement, data mining and advanced artificial intelligence technique which called Logical Analysis of Data (LAD) is used. LAD has ability to identify conditions of tools and of determining which machining conditions can indicate the tool failure or degradation is happening, and which can be considered redundant.
FPInnovations has developed FPInterface, a software platform in which forest operations are simulated in order to estimate fibre supply costs, including harvesting and transportation. It currently has 7 sub-modules including MaxTour and FPAlloc. The goal of this project is to develop and validate optimization techniques in order to implement new sub-modules to FPInterface that will allow for more accurate scenario valuations.
Due to advances in low-power wireless communications, low-power analog and digital electronics, the development of low-cost and low-power sensor nodes that are small in size has received increasing attention. Sensor nodes have the ability to sense the environment nearby, perform simple computations and communicate in a small region. Although their capacities are limited, combining these small sensors in large numbers provides a new technological platform, called Wireless Sensor Networks (WSNs).