Upgrading of heavy and high-contaminant Hydrofaction™ Oil, to fuels blendstock with the use of Catalytic Steam Cracking

The Project’s objective is to continue the upgrading work executed in the previous MITACS Converge project with a larger focus on more challenging biocrude oils such as heavy fractions, high viscosity, high nitrogen, high ash oils that are produced from feedstocks such as “feed gate residues” in the form of manures, biosludges and organics from municipal waste. The performance objective remains to optimize and scale up the upgrading of Hydrofaction™ Oil to blendstocks for transport fuels.

Precise-ITC Soft Decision forward error correction (FEC) for High-speed Optical Communications

Increased market demand for data and cloud computing is driving business for Precise-ITC corporation. As data bandwidth grows our customers are using advanced modulation techniques for fiber optic efficiency. Recovering the data from a modulated signal after signal impairment requires advance digital signal processing (DSP) algorithms that are able to adapt and cancel impairments in the network. Furthermore, forward error correction (FEC) could be used to improve error correction, enhance system reliability, and extend optical transmission distance.

An Efficient Data Analysis Pipeline

The proposed research project targets computational performance improvements of an data analysis pipeline. The project has a duration of four months and aims to achieve two objectives: (1) to properly characterize the performance of individual stages of the existing data analysis pipeline in terms of execution time, memory, and I/O, and (2) to improve the performance of individual stages where possible. The intern will use methods learnt and developed during the masters research and apply them to a real-world system at Acerta Analytics Solutions.

Anomaly Detection using GAN

The proposed research project targets anomaly detection of event data. The project has a duration of four months and aims to achieve two objectives: (1) to evaluate the effectiveness of a novel approach on GAN for real-world data, and (2) compare it to alternative methods. The intern will use existing research resources, and will apply them to real-world data provided by the partner, Acerta Analytics Solutions, Inc. to evaluate the different methods.

Upgrading of heavy and high-contaminant Hydrofaction™ Renewable Crude Oil, to transport fuel blendstock

The Project’s objective is to continue the upgrading work executed in the previous MITACS Converge project with a larger focus on more challenging biocrude oils such as heavy fractions, high viscosity, high nitrogen, high ash oils that are produced from feedstocks such as “feed gate residues” in the form of manures, biosludges and organics from municipal waste. The performance objective remains to optimize and scale up the upgrading of Hydrofaction™ Oil to blendstocks for transport fuels.

Securing IoT in Transportation Applications using Blockchain

The proposed solution will address IoT security challenges by using the blockchain technology to create feasible trust mechanisms. We will develop a solution by which exchanged information remains trusted and confidential to be handled efficiently at different places, and we will apply it to a smart transport use case.

Macroeconomic Models for Performance and Investigation Prediction

Corporations are under a lot of scrutiny, especially when they annually release their financial reports to the government. If a corporation makes a mistake, or if an employee submits fraudulent information, or if it appears that either is the case, then they risk being asked to amend the filing by the government, which will cause their share price to suffer and force them to painstakingly redo the report at great expense. Caseware will sell software that can analyze these reports and determine if an amendment request is likely.

Assessing trust of artificial intelligence technology in the context of workplace relations

The goal of the project is to gain insight into individuals’ reactions to an artificial intelligence (AI) product currently in development at Kiite. The product is designed to fulfill some of the role responsibilities typically occupied by a manager. Trust is an important factor in both leader-employee relationships and in user experiences with AI-based systems. Thus, the partnership with Kiite offers a novel research opportunity to contribute to an emerging area of research on when and why humans are liable to (dis)trust AI technology in the workplace.

Content Delivery Networks to the Home

CONTENT Delivery Networks (CDNs) are large distributed infrastructures of replica servers placed in strategic locations. They deliver content to end-users with reduced latency by replicating content on surrogate servers. However they face a major challenge when content is delivered to end-users accessing a same content in home settings: inefficient bandwidth usage in the access network. There are as many streams from the replica server as end-users accessing the same content.

High-Fidelity Data Converters for Medical Diagnostics

Diagnostic medical devices work by translating our vital signs, such as neuron electrical activity and brain waves, into digital data that can be manipulated by a computer. High-speed computer processing improves diagnoses by presenting the physician with a numeric or graphical readout of important features extracted from the signal. Often, the ability of computer programs to extract the most diagnostically-relevant information is limited by how well the device can recognize and ignore background electrical noise common in clinical environments.

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