Developing nature-based interlocking barriers for protection against climate change-induced erosion and flooding

The joint research's primary goal is to pursue the most optimized design and materials of new interlocking barriers to prevent coastal erosion and reduce flooding, which are growing concerns of coastal communities like Newfoundland and Labrador. The research results will support investors and industry to have access to a cost-effective and efficient barrier to protect their natural resources and cultural heritage in a sustainable way.

A Community-Focused Pilot Project to Control the Impact of the Invasive Green Crab on the Native Lobster Population in Fortune Bay

This is a community focused two-year pilot project which brings together community leaders, the public, Memorial University, and Government Researchers to control the impact Green Crab have on the lobster and the environment in Fortune Bay.

A Community Needs Assessment of Fetal Alcohol Spectrum Disorder in Newfoundland and Labrador

Fetal alcohol spectrum disorder (FASD) is a lifelong disorder caused by prenatal exposure to alcohol that impairs cognitive, behavioural, social, and emotional development. It is the leading preventable developmental disability in Canada, impacting an estimated four percent of the general population, with higher rates among certain vulnerable groups. Newfoundland and Labrador has the highest rates of heavy drinking in Canada, which elevates the concern associated with this issue and the need for research into FASD in the province.

Modeling pipeline-soil interaction in dense sand using nonlocal Mohr-Coulomb model in a Coupled Eulerian-Lagrangian finite-element code

Pipelines are extremely important for the transportation of oil and gas. Buried pipelines can move in a relatively large distance under special scenarios, e.g. slope failure. Meanwhile, the surrounding soils are subjected to a large deformation. This project aims to develop a computer modeling technique to analyze the large-deformation behavior of soil and its impact on the pipeline. The result will be compared with a previous physical test so that the reliability of this new technique can be evaluated.

A mobile soil-flushing and enhanced oxidation (MSFEOP) system for the remediation of petroleum brownfields

Petroleum contamination in soil and groundwater caused by the leakage of underground storage tank is one of the most frequently occurred incidents in North America. The cost of remediation can be significantly increased if the contamination was not treated in time or the site is far away from the waste management facility. a mobile soil-flushing and enhanced oxidation (MSFEOP) system is therefore developing for an accessible and affordable options for site remediation.

Biosurfactant Production from Seafood Processing Waste

This project aims at developing an innovative technology through the utilization of fish waste as substrates for biosurfactant production. Through the proposed approach, fish waste will be recovered into fishery peptone and being used as a nutrient substrate for the synthesis of biosurfactant products with promising market values. The outcomes of this project will directly provide the fishery industry a new model of fish waste reuse and management by "turning waste into valuable products". It will also help reduce waste discharge and protect the environment.

Application of machine learning techniques to control surface quality of as-printed wire arc additive manufactured components

Nowadays, the wire arc additive manufacturing is making its path toward providing benefits to aerospace, defense, and oil and gas sectors, ascribed to the process capacity to fabricate components with minimum waste of material and lead time. However, the main challenges associated with the WAAM that have hindered the wide-spread application of the technology include the irregular and random quality of the WAAM fabricated surfaces.

Sensor Rank and Selection to Determine the Best Sensor to Increase the Efficiency of a Garbage Disposal Service.

In this modern world one of the biggest problems we face is waste control. As the population grows, so too does the waste being produced by humans. Our company is proposing to add a sensor to commercial garbage bins to detect when bins are full and thus trigger waste collection. This project will aim to identify the best sensor to use in a commercial garbage bin and will propose adding network technology to create a “smart” system. Sensor framework design and selection will be researched by this undergraduate team.

Optimizing a food wastage stream at the consumer level of the Food Supply Chain through Machine Learning and the Internet-of-Things.

Across the world, one-third of all the food produced yearly—¬¬¬worth $400 billion—is wasted (Bharucha,2017). This project aims to research and develop the accuracy of a machine learning algorithm in order to assess its efficiency in reducing food wastage and making restaurants more profitable.

The effect of the MyoStorm heated vibration ball on pain andperformance with an examination of underlying mechanisms

Foam rollers are popular devices used for training and rehabilitation and have been extensively investigated in the literature. Research has shown that foam rollers can increase range of motion, alleviate myofascial and muscle pain with no impairments and in some cases improvements in
subsequent muscular performance. Vibrating rollers have also been introduced but there are few studies investigating their effectiveness. Heat is an ubiquitous treatment modality used in therapy to increase blood flow and accelerate recovery.

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