Quantum Key Infrastructure

The research described in this project proposes a very realistic and Quantum Computing resilient key distribution networking protocol to enable highly secure and efficient information flow. On one hand, the protocol provides unconditional one-time-pad based encryption; on the other hand, it is based on information-theoretic concepts that can be cost-effectively implemented today to establish Quantum Key Infrastructure (QKI) that somewhat resembles already existing Public Key Infrastructure (PKI). The PKI to a large extent could be used to enable QKI.

Described Video and Language Detection on Audio-tracks Using Machine Learning

Bell Media receives content from different providers, including content it produces in-house. There are standards for tagging audio tracks with metadata however many facilities (including Bell) do not adhere to these standards. Currently Bell uses a manual approach to classify unlabeled audio tracks, which is inefficient, and time consuming for massive digital media that Bell has and receives. Bell is developing a single ingest pipeline to accelerate the labeling and processing of media files it receives.

Novel Portable Sensor to Reveal “Hidden” COVID-19 Infection

In Canada, as of April 21, only 569,878 people (~1.5% of the population) have been tested, with more than 38,413 positive COVID-19 cases identified; yet most people, including the asymptomatic COVID-19 cases, are not eligible for testing. Given that as many as 45% of all COVID-19 cases lack the known symptoms, or so-called asymptomatic cases, up to an estimated 17,000 cases could be asymptomatic and thus endangering public health. Moreover, these symptoms are not observed in the early stages of the disease, even in symptomatic cases.

Applying Machine Learning to Develop Meaningful Rail Condition Indices

Rail transit and freight rail properties apply rail grinding to maintain rail condition and ensure satisfactory performance of rail infrastructure systems. The proposed research investigates and applies a variety of computationally intelligent algorithms to establish useful relationships between rail corrugation, noise generation, and vibration. These relationships will support more timely and effective rail grinding interventions. The algorithms will process real-world rail corrugation, noise, and vibration data collected from three rail transit properties in North America.

Noninvasive blood glucose monitoring system by midinfrared spectroscopy

More than 400 million people are suffering from diabetes mellitus in the present world. Till date, there is no cure for diabetes; however, it can be controlled by regulating the sugar intake in blood. Hence, diabetic patients need to monitor their blood sugar level regularly for few times a day. The conventional techniques are invasive in nature and require drawing out blood by pricking fingertips which is a painful process and possess a risk of infection.

Developing a Multiphysics FEA Model of an Inductive Conductivity Sensor

The CTD is a rosette structure which is circular in shape and houses a number of elements. These elements include sensors, water sample bottles, ropes and cables to support the CTD structure. The sensors included in the CTD are not limited to conductivity, temperature and depth, but also include sensors to determine other physical properties. In this research, a model of the CTD sensor designed by RBR will be developed for the purpose of measuring conductivity and determine the nature of the water sample by calculating indirect parameters associated with it.

Development of bead-based detection of SARS-CoV-2 IgM/IgG in a multiplex POCT platform

COVID-19 is a highly infectious respiratory disease that is caused by the SARS-CoV-2 virus. RT-qPCR is a nucleic acid testing that is widely adapted to confirm the infection. Point-of-care IgM/IgG testing strips have been adopted in some countries for screening and surveillance. However, these antibody testing strips are restricted to a positive/negative testing result.

Ex-vivo Device for Screening the Efficacy of COVID-19 Vaccines and Producing Antibodies

COVID-19 has significantly impacted the health of the global population. Although timely detection and isolation are important, vaccination is probably more effective in fighting against COVID-19. Our proposed ex-vivo can help the validation of the COVID-19 vaccine and produce antibodies for COVID-19. The benefit to the Canadian community and the industry partner is palpable.

Ultrasound image analysis for identifying blood in an existing effusion in knee joint

Ultrasound, an inexpensive, accessible and portable device is gaining popularity in various disease diagnoses. In this project, we aim to analyze the ultrasound images generated for knee joint for diagnosing hemarthrosis (joint bleeding), a common clinical event in patients with severe hemophilia. We aim to analyze the images using machine learning and deep learning techniques.

Wireless charging based on capacitive-inductive resonance

This project is about a novel chip-based wireless power transfer system. Its integrated and flexible design eliminates the need for power cables for any DC device in homes, offices, parkades and power generating facilities. Unlike existing solutions, the system operates simultaneously with multi electricity requirement devices, has extended range, generates no heat, can transfer power through solid material, while increasing the effective utilization of harvested electricity. It does so at a lower cost per power density than its competitors.

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