Transitional REM Sleep Brain Connectomes and Seizure Susceptibility

Seizures are rare while dreaming in rapid eye movement (REM) sleep. New research, however, suggests seizures may rebound during unstable REM sleep. This may be due to brain wiring (“connectivity”) since a highly connected brain is more prone to seizures, and connectivity changes from wakefulness to sleep. Brainwave tracings (“EEG”) can generate connectivity maps (“connectomes”) but adequate connectome resolution requires many EEG electrodes (“high density EEG”). This study uses high density EEG to examine brain connectomes and seizure susceptibility in unstable REM sleep.

Development of multiple algorithmic solutions to aid in making platform for delivering unique and reliable insights on Employee Engagement for organizations

Pintellect is Enterprise Social Software that gives employees access to the thoughts and ideas of the organization’s influencers by encouraging them to share links to the internal files or external resources such as books, TED talks, podcasts, articles, etc. The objective for this project is to develop multiple algorithmic solutions for curated feed of content by department on the dashboard based on number of identified criteria.

Malicious Traffic Predictive Indicators in Content Delivery Networks: a Big Data Analytics Approach

Content Delivery Networks (CDNs) represent the up-to-date standard to transfer data through on-growing Internet. They are designed to manage traffic streams to avoid network problems. Despite the fact that CDNs attempt to satisfy security requirements (authentication, data privacy and integrity), they face rising innovative threats, observable in the cyber-space. The main objective of this project is to design, implement and test new methods to detect and prevent maliciousness in CDNs. We aim at building an alternative solution to classical Web Application Firewalls (WAFs).

Recurrent Deep Architectures for Modeling Time Series Data

Deep learning is currently the dominant machine learning technique as a result of state of the art performance in vision (Russakovsky, et al., 2015), speech (Amodei, et al., 2015) and natural language processing (Vinyals et al., 2015). The improvement in performance of these models is attributed to the availability of large datasets for training the models as well as software & hardware improvements that help accelerate the training process. Recurrent Neural Networks (RNNs) are one of the most powerful and popular frameworks for modeling sequential data such as speech and text.

Intelligent Residential Energy Management Utility Controller

To research, design, and develop a network communication and control modules that integrate any residential HAVC control system with a utility energy management user interface. Developed signal modulation scheme will be implemented on development testing board. Device will network with all utilities for gas, water, and electricity.

Study of the Catalytic Effect of MFD on CuFeS2 Leaching

Bio-heap-leaching is a hydrometallurgical process used to process low grade chalcopyrite ore as the cost of alternative routes of processing and refining are not economically viable. The limitation however of the heap leaching process is the long time it takes to leach the metal and the low total recovery that can be achieved. As heap leaching being a large scale atmospheric leaching process, neither temperature nor pressure can be changed.

Statistical and Physiological Beat Modelling of Seismocardiogram Signal

"Seismocardiogram (SCG) is a signal that is captured by placing an accelerometer on the human chest. This signal captures very important timing information such as opening and closing of the heart valves. In addition to these timing information, the non-invasive nature of this signal makes it an attractive solution for remote monitoring of patients with heart conditions.
The morphology of SCG signal changes depending on different types of heart conditions and diseases. A mathematical model represents the morphology of a signal in terms of certain parameters.

Oil and lipid improvements in field pea to develop a non-traditional oilseedcrop

It has been noted in recent studies that provided an increase in the lipid content of the field pea (Pisum Sativum L.) through genetic manipulation, it can be used as a viable commercial alternative to conventional oilseed crops, which include canola and soybean. Genetic transformants with high lipid content can be created in the McGill University laboratories but its commercial viability needs to be tested with an industry partner.

Utilization of Supersolidus Liquid Phase Sintering (SLPS) in Metal Injection Molding (MIM) for Superalloys in aerospace applications

Powder metallurgy uses metal powders to produce parts of varying complexity. The processes can generally be divided in two big steps. The first is to form the powder into the required shape. This is generally done by pressing or molding the powder. The second step is to consolidate the powder into a solid piece of metal. This is done by heating the formed powder just below its melting temperature. At this point the metal particles will slowly coalesce into a uniform metal structure.

Controlling microbial processes in fracing fluids

Unconventional gas reservoirs are a great energy resource in the province of BC and Alberta and thus for Canada in general. Extracting this resource is not as straight forward as conventional gas reservoirs and requires hydraulic fracturing, also known as fracing or fracking, which has recently become a controversial topic in the public eye. This research project will examine water and fluids used in and returning from frac operations with respect to its geochemistry and bacterial populations.

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