Development of an annular array histotripsy transducer with co-registered ultrasound imaging

This project will focus on the design, fabrication and testing of an annular array-based histotripsy transducer that will improve the combined ultrasound imaging and therapy endoscopic device currently in development at Daxsonics. Histotripsy is a method of focusing high intensity ultrasound waves to liquify tissue and is a promising new method of accurately removing tumors with much less damage to surrounding tissue than current methods. This device will be part of a surgical suite for minimally invasive neurosurgery, enabling removal of tumors with extremely high precision.

Discovering causal variants controlling ripening period, phenolic content and softening during storage in apple (Malus domestica).

Apples are among Canada's most valuable fruit crops, and the improvement of apple varieties is crucial for the success of the industry. Breeding apples is expensive and time consuming, requiring decades of investment. A better understanding of the relationship between genetics and fruit traits will allow for more efficient breeding. Current apple breeding techniques make use of genetic markers, but these markers are of limited use.

Characterization of various insulation materials, coatings, and non-metallic membrane for corrosion under insulation performance

Corrosion under insulation (CUI) is among the major damage mechanisms acting in Oil & Gas processing plants and chemical industries that causes process leaks, and the failures of thermally insulated systems. The hydrocarbon leaks from CUI result in the increased carbon footprint and can even cause catastrophic fires. CUI triggers from inevitable moisture ingress in thermal insulation, and so need to be better understood and managed for cleaner and safer operation of process facilities.

Intelligent Autonomous Mobile Robots with Safe Navigation in Dynamic Environment

With the global pandemic effect, the market is experiencing a significant transformation, with robotics to adopt the roles of delivery vehicles and personal assistants. Atlantic Business Express is looking at bring the service robots to Canada, starting in Nova Scotia through working with Dalhousie University. The project is to develop intelligent path planner for mobile robots with safe navigation through obstacles in indoor dynamic environment. The interns will develop an intelligent motion planner as well as efficient collision and obstacle avoidance modules.

Automatic detection and classification of marine biogenic habitats, species, and substrates

Canada works towards designating 30% of our national waters as Marine Protected Area (MPA) by 2030. The need to collect baseline information and monitor such a huge territory, which is equivalent to the area covered by Alberta, Manitoba, New Brunswick, and Nova Scotia altogether, will be next to impossible without a paradigm shift in the way field observation data are processed. We propose a platform for automatic classification of bedrock and species for habitat classification, coastal monitoring, and resource assessments.

QUOREM: A data science platform for microbiology research

In the genomics era, microbiologists are collecting data at an accelerating pace. We have created a data science platform called QUOREM that significantly reduces the technical burden experienced by microbial ecologists associated with managing ever-increasing quantities of data. We believe that public and private research groups in Canada could benefit our platform, and the ability to provide commercial support and hosting services is key to driving adoption and growth. We hope to learn how to take the next steps to realizing this vision through Springboard Atlantic’s Lab2Market program.

Development of Signal processing techniques for blood sample transport

This research project involves the development of signal processing techniques in order to analyze the integrity of blood specimen during blood sample transport in hospitals using the pneumatic tube system.

Optimization of an Engineering Information Retrieval System using Topic Models and Knowledge Graphs

The oil and gas industry is in the top five largest sectors in the world in terms of dollar value, generating an estimated $3.32 trillion in revenue annually. It is estimated that 40-60% of workforce in the oil and gas industry will retire in the next five years, so preserving the knowledge stored in documents is an important objective. The industry partner (WESI -- Waterford Energy Services Inc.) has been developing a document management system to support this objective.

Detecting noise and artifact in CW ultrasound signal processing using machine learning and cloud-based tools

Continuous wave (CW) ultrasound systems are extremely sensitive to movement, noise, and artifacts of reflective tissues within the body that return doppler ultrasound signals to the receiver. In the application of CW ultrasound to clinical applications, classifying and handling noise/artifacts is essential for broad clinical adoption. A machine learning (ML) algorithm is commonly used for pattern recognition of large sets of data, such as physiological signals, and it has been used recently for biomedical applications.

Moment Connections to RHS Columns

The proposed research aims to demonstrate the performance of effective, non-proprietary moment connections for wide-flange (W-) beams to rectangular hollow section (RHS) columns in limited-ductility (Type LD) moment resisting frames (MRFs) that are easy and cost-effective to fabricate, handle, and erect. Two W-beam-to-RHS column moment connection prototypes will be developed and tested, in duplicate, at full-scale. It is anticipated that testing will demonstrate the W-beam-to-RHS column prototype connections conform with the Canadian steel design code.

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