Using machine learning to investigate sympathetic activation of the autonomic nervous system during treatment of mild traumatic brain injury, chronic pain and post-traumatic stress disorder

The goal of the proposed research project is to further our understanding and clinical management of Canadian Forces service members and Veterans suffering from a complex medical triad of traumatic brain injury, chronic pain, and post-traumatic stress disorder. Over half of rehabilitation patients experience one or more of these complex medical conditions, often associated with intractable symptoms which do not respond to traditional treatment options, and impairing their ability to function effectively at work and in the community.

A Framework for Assessing Regulations and Initiatives with Goals and Watson Analytics

Regulations are introduced to ensure the well-being, safety, and other societal needs of citizens and organizations. Yet, regulators often have difficulties assessing the performance of their regulations, and whether regulatory initiatives actually improve compliance. This project’s main objective is to investigate the suitability of a framework combining a standardized goal modeling notation with an existing cloud-based analytics and visualization tool (IBM Watson Analytics) for assessing compliance to regulations as well as the efficiency and effectiveness of regulatory initiatives.

A set membership filtering approach to low-complexity state estimation from PMU measurements

The widespread use of phasor measurement units (PMUs) in power-grids can greatly enhance state-estimation (SE) by making use of accurate, GPS time-stamped synchronous phasor measurements. Unlike conventional SCADA measurements which are reported every 4 seconds, synchro-phasor measurements are typically available as frequently as 30-60 measurements per second. While the availability of more measurements can provide accurate state estimates in real-time, the sheer amount of data can overwhelm the computational capabilities of most data processing systems.

Modeling and Dynamic Performance Assessment of a Battery Energy Storage Systems

Bulk storage of energy is a relatively new concept in many power systems. Among various energy storage media, batteries have shown great promise as a suitable option for use in power systems. Integrating a battery energy storage system in a power grid is not a trivial task and requires extensive studies to ensure that the system is able to respond satisfactorily to its surrounding’s variable conditions and deliver what is expected of it.

Maintenance Recommendation - Downtime Adaptive Learning

Time Series is a sequence of records and observations ordered in time. For instance, feedback from a sensor with timestamps can be considered a time series set. Studying Time Series can help with the predicting and understanding of a system and its behaviour. It can also be used to control the mechanism. In the past, data was expensive, and more challenging to process. Fortunately, today there are many sensors and servers which collect and report thousands of measurements. Internet of Things (IoT) produces large amounts of data.

Development of computationally efficient models for modular multilevel converters with integrated battery energy storage systems

The research project aims to develop new computer models for accurate representation of battery energy storage systems that are used in modern power systems. In particular state-of-the-art modular multi-level converters with integrated dc-dc converters will be considered. The models to be developed will provide high levels of accuracy and feature low computational intensity so that study of battery systems that are integrated into the grid using advanced converter systems becomes feasible on present-day computing systems.

The importance and multi-dimensional approach of marketing strategy in the data security industry

As a customer you expect your personal and sensitive data to be kept safe in the company’s storage and to be handled confidentially. But that is exactly among others one of the biggest challenge for businesses nowadays. Therefore, they need the best partner in IT and data protection by their side. Data security and protection solutions are offered by several software companies to address the issue. But how can businesses find the best suitable solution? That is when marketing strategy of the software companies comes into play.

Eye Gazing Enabled Driving Behavior Monitoring and Prediction

Automobiles have become one of the necessities of modern life, but also introduced numerous traffic accidents that threaten drivers and other road users. Most state-of-the-art safety systems are passively triggered, reacting to dangerous road conditions or driving behaviors only after they happen and are observed, which greatly limits the last chances for collision avoidances. Timely tracking and predicting the driving behaviors calls for a more direct interface beyond the traditional steering wheel/brake/gas pedal.

NOVA (Network Optimized Video Analytics)

Project NOVA will build on the University of Ottawa and Ciena’s advanced analytics capabilities to allow networks around the world to understand where video flows run over their network.  This will allow the network operators to improve video Qualify of Experience for their end customers, more quickly and cost effectively fix video impacting network problems, plan their networks to better support video, and provide greater customer service awareness of end customer over the top video quality. Ciena anticipates this capability will propel it into be the world leader in network video analytic

Intelligent Vision Based Navigation Systems

Utilizing geomatics sensors such as laser scanners, GNSS, Inertial Navigation Systems (INS), and photogrammetry cameras to provide mobile mapping solutions has been studied and utilized extensively in the past three decades. The data fusion between high-end mobile mapping systems such as laser scanning and imagery-based systems, and low-cost camera systems are still a fertile field in digital transformation. The anticipated outcome of this project is a software development kit (SDK) that enables data fusion between high-end mobile mapping systems and low-cost camera systems.

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