Improving Powder Performance by Development and Optimization of Industrial Lubricants and Mixing Technology for Powder Metallurgy

Ideal flow, high-volume Powder Metallurgy (PM) manufacturing can achieve uniform, consistent filling of die cavities, leading to high productivity, low rejection rates, improved part integrity and consistent part dimensions. The type and amount of lubricant, size and shape of lubricant particles, mixing parameters and certain environmental conditions all significantly influence the flow characteristics and apparent […]

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Improving Powder Performance by Development and Optimization of Industrial Lubricants and Mixing Technology for Powder Metallurgy – Year two

Ideal flow, high-volume Powder Metallurgy (PM) manufacturing can achieve uniform, consistent filling of die cavities, leading to high productivity, low rejection rates, improved part integrity and consistent part dimensions. The type and amount of lubricant, size and shape of lubricant particles, mixing parameters and certain environmental conditions all significantly influence the flow characteristics and apparent […]

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Computational and experimental characterization of mechanical performance of cross laminated timber (CLT)

Cross-laminated timber (CLT) is an engineered wood panel typically consisting of multiple layers of glued timber stacked in a cross-ply layup. Timber shows a strong anisotropic mechanical behavior due to its microstructure. With a cross lamination, the CLT possesses superior dimensional stability, strength and rigidity, in comparison to traditional wood products. In Canada, CLT is […]

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Using Deep Learning for Auto-tuning of High Performance GPU Applications

Graphics Processing Units (GPUs) are increasingly used to accelerate applications and to reduce their energy use. GPUs are particularly attractive for mobile platforms, where battery life is important. However, GPUs are hard to use, requiring developers to apply optimizations to their code to realize the performance and energy benefits of GPUs–a tedious and error prone […]

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Using Deep Learning to Auto-tune GPU Application

The fellowship mainly investigates an analysis of the state-of-the-art approaches, design and implementation of cutting-edge deep neural network models to be used on a mobile platform. It explored ways to optimize the deployment of these machine-learning models for prediction tasks on the mobile devices which requires energy efficiency and accuracy.

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Toward an Understanding of Beautiful Feather Cover in Laying Hens

Feather pecking (FP) in egg-laying hens, where individuals peck repetitively and excessively at other birds to pull out and eat their feathers, is a challenge for the industry with large economic and welfare implications. High prevalence of FP is reported (60-80%) and this is associated with mortality rates of up to 20-40%, which translates to […]

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Improving Metallic Yield in a Steel Rolling Plant through Optimization

The objective of this project is to use optimization to improve metallic yield (the percentage of raw material that ends up as usable product) in an ArcelorMittal Steel Rolling Plant. The metallic yield of the rolling operations depends upon the length of billets from which the final product is manufactured. Ideally, a single customer order […]

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STUDY OF INDIAN AND UKRAINIAN LEGAL FRAMEWORKS REGULATING BIOFERTILIZERS AND BIOCONTROL AGENTS IN REFERENCE TO CANADIAN MICROBIAL PRODUCTS – Year two

This research aims at primarily analysing the legal frameworks regulating biofertilizers and biopesticides (also known as ‘biologicals’) in India and Ukraine. After studying and analysing the legal frameworks, and barriers in registration procedures for R&D, trial, transfer, trade, transport and storage of new molecules and microbial strains of agro-biologicals, a draft of alternative regulations will […]

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STUDY OF INDIAN AND UKRAINIAN LEGAL FRAMEWORKS REGULATING BIOFERTILIZERS AND BIOCONTROL AGENTS IN REFERENCE TO CANADIAN MICROBIAL PRODUCTS

Unsustainable application of chemical fertilizers and pesticides has steadily declined food productivity the world over. Hence, agricultural practices need to evolve to sustainably meet the growing global demand for food without irreversibly damaging the world’s natural resources. Biofertilizers and biopesticides hold the potential to maintain agricultural productivity, while safeguarding agroecosystems and microclimates. While development/consumption of […]

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Process optimization for extraction of compounds from natural sources

The proposed research project aims to optimize the conditions for Carbon dioxide eXpanded Liquid Extraction (CXLE) which uses liquefied Carbon Dioxide (CO2) and ethanol as co-solvents for extraction of compounds from natural sources. Design alterations will be implemented to a Supercritical Fluid Extraction (SFE) unit at the partner organization (BioFoodTech) to perform CXLE and further […]

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Process optimization for extraction of compounds from natural sources – Year Two

Various methods have been developed to extract compounds from fruits, vegetables, and seeds. Subcritical and supercritical extractions are the most promising techniques with high output qualities and high cost efficiencies. Running the systems at different pressures and temperatures, the essential bi-product can be extracted from the natural compounds matrix. In addition to their effectiveness, the […]

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