Information-based Public Transport Control Strategy Study Under Pandemic Situation

Health and safety are key concerns during the current public health crisis to individuals who rely on public transit. To lessen the risk of those individuals, the research aims to develop an information-based control strategy using real-time travel information as a meaningful non-pharmaceutical intervention strategy in the public transportation sector. To achieve this goal, the […]

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CONVERGENT CROSS MAPPING FOR DEMAND FORECASTING

The availability of inexspensive electricity in a constant and reliable fashion is critical to economic development and efficient resource consumption. To this end, accurate short term load forecasting (STLF) on an electrical grid enable the minimization of dispatch and running costs on the scale of seconds to a week. Models and approaches employed in STLF […]

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Achieving Circular Wastewater Management with Machine Learning

Effective wastewater treatment is essential to the health of the environment and municipal wastewater treatment plants in Canada are required to achieve specific effluent water quality goals to minimize the impact of human generated wastewater on the surrounding environment. Most wastewater treatment plants include a combination of physical, chemical, and biological unit processes and therefore […]

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Application of a DNN model for seismic performance prediction of structures retrofitted with steel dampers

The intensity and frequency of earthquakes in Korea have increased in the past few years. Thus, the need for seismic retrofit of many middle- or low-rise buildings has increased which were designed without seismic design provisions. Nonlinear time history analyses need to be performed for accurate seismic performance evaluation and for appropriate retrofit of structures. […]

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Multi agent reinforcement learning with multiple time scale on financial markets

I am working on reinforcement learning for finance based on deep mathematical knowledge and the host supervisor is working on financial engineering, reinforcement learning and Markov decision process. We will study deep reinforcement learning for stock market trading and for portfolio management. The goal is to find a practical deep reinforcement agent to manage stock […]

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Detection of malicious documents by extracting and interpreting macros in Microsoft Office files

Macros can greatly enhance the capabilities and convenience provided in documents. They also invite adversaries to include malicious code in lure documents, often used as initial access into a user’s environment. This project will extract and analyze macros and determine their indent and potential for malicious code execution. Reducing time to response through malicious code […]

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Real-time Automated Security Report Generation

In today’s world, organizations protect themselves and their customer’s data through the implementation of complex cybersecurity solutions composed of many different nodes, each generating constant streams of data. Building reports from this data through the calculation of various metrics can provide much needed visibility into the state of the environment. However, building such reports can […]

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Malicious/phishing Website Detection

Malicious websites in general, and phishing websites in particular, attempt to mimic legitimate websites to trick users into trusting them. The goal of the project is to develop algorithms for detecting these malicious websites in two contexts: • detecting if a site visited by a user is a malicious site • detecting malicious sites that […]

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Creating a comparison and alert methodology for managing the CCTX feed

Most collaborations and government departments share their threat data feed in Data Exchange. Inescapably, nowadays with increasing threat data, it is a challenge to extract a large amount of threat data and unify the format more quickly. And as more and more companies join in sharing, the redundancy of this duplicate data will increase dramatically. […]

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Development of a technique for radioactive source term detection and realtime analysis for low-level radioactive waste

Nuclear power currently provides approximately 50% of Ontario’s electricity. Operation of nuclear power plants produces a variety of radioactive waste. In particular, low-level radioactive waste makes up about 95% of total non-fuel waste volumes. To reduce volume, low-level materials must be sorted to determine if their radioactivity has sufficiently decayed and they can be safely […]

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Integrated Circuit Architectures for Photonic Computing

Photonic integrated circuits allow the computations required for artificial neural networks to be performed using light. By doing so, they obviate many of the challenges associated with electronic computers, paving the way to a new class of information processing hardware. Such hardware could help address the growing demand for machine learning and artificial intelligence in […]

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