Much of the world's high-quality data remains under lock in relational databases. Access is gained through relational query languages. This can suffice for people who are well versed in both SQL and in the schemas of databases. However, anyone who does not know SQL or who is not well versed in the schema is effectively locked out. Keyword search over relational databases was proposed a decade ago to offer an alternative way to query a database. While the general approach has merit, many refinements are needed, before it can be an effective product.
A novel transmitter architecture which presents more power efficiency than that of the transmitters being used currently in mobile communication base stations is proposed in this research project. The result of this research fills the gap between the theoretical idea behind this transmitter structure and its practical usage in cellular network base stations. This transmitter can operate over a wide frequency range and with different mobile communication signal standards very power efficiently while maintaining the quality of the transmitted signal.
InSAR is a technique used by radar-based remote sensing for applications such as tracking spatial displacement/deformation of an object on earth, e.g., building and a bridge, over time. The object analysis part of InSAR processing belongs to an offline processing chain that operates on very high resolution images consisting of huge volume of data. The processing chain consists of several independent or loosely coupled operating entities with different resources requirements. Often multiple products are required to enter the chain simultaneously and they share processing resources.
Disruptive antenna technologies are required to provide performance and fabrication advantages in developing multi-functional antenna array solutions that could provide various capabilities, including multi-band frequency operation and two dimensional electronic steering. The internship will investigate the technical feasibility of such multi-functional antenna arrays for commercial applications in the context of fabrication constraints.
B. Gosselin and Doric Lenses Inc. have developed the first low-cost wireless head mounted optogenetic device enabling simultaneous biopotential recording and optical stimulation in the brain of freely moving rodents. This project aims at providing such a wireless optogenetic headstage system with user programmable functions, so it can address the dual nature of brain biopotentials, and become an essential tool for innovative research.
Pulse oximeters are key devices to provide early information on the respiratory and circulatory systems. In addition to be bulky and cumbersome, most commercially available systems lack a wireless connection, which cause numerous inconveniences. This project aims at designing a new wireless ring pulse oximeter which will enable to measure transmitted and reflected light from several locations around the finger to increase the quality of signal and gain more flexibility while improving comfort and ease of use.
Remarkably, very little prior work exists in the narrowly defined area of electromagnetic modeling of rocks and minerals. It is admittedly a difficult problem that requires, by definition, a multidisciplinary team with representation from both the mining and minerals domain as well as the EM modeling and simulation domain. Such a collocation of resources and expertise is being brought together in this team: Dr.
The proposed project aims at the design and implementation of low complexity digital pre-distortion (DPD) algorithms for concurrent multiband wireless transmitters. The power amplifier (PA) is one of the major sources of power dissipation in wireless base stations. The DPD techniques enable the PA to operate in higher power levels where it has its highest efficiency. To address the ever increasing demand for higher data rates, the carrier aggregation techniques are being adopted by the current and upcoming wireless standards.
The research will entail modeling of diesel engine emissions to correlate with varying states of diesel engine operations so as to determine normal operating parameters. Using machine learning techniques, develop methods to analyze, alert and report on abnormal operating conditions when the vehicle is monitored in real time. The research will provide an important first step towards the development of a predictive maintenance system for underground mining equipment.
More than 25% of the fatal and injury car crashes are related to fatigue or drowsiness. This calls for the need for designing automated driver monitoring systems, which can continuously measure the drivers' vigilance level and alert them if their cognitive state is not safe for driving anymore. One of the most reliable solutions is to directly measure the electrical activities of the brain to monitor the driver's cognitive state. The proposed research aims to design a non-intrusive yet efficient monitoring system that uses electroencephalogram (EEG) signals.