NIRS is a popular secondary analytical method that is being used for non-destructive quantification of compounds and mixtures in the agriculture and agri-food sector. The study aims to estimate the starch content (amylose and amylopectin) in rice samples with NIRS. A dataset is being established by obtaining NIRS spectra (400 to 2500 nm, 0.5 nm resolution) on over 400 milled and ground rice samples. Iodine-binding and spectrophotometric techniques will be used for acquiring the ground-truth.
Skin-penetrating bone-anchored implants are used in a variety of applications to provide tremendous functional benefits to patients. Globally, the dental implant industry has been valued at 5.08 billion USD where implants are used for replacing single teeth, for larger prostheses, and for full dental arches. The success of these implants relies on a structural integration between the implant and the living bone. Evaluation of the integrity of the bone-implant interface is important to prescribe loading, to identify the risk of failure, and to monitor the long-term health of the implant.
Red Maple Trials (Ottawa, ON) created a facility for the research of allergy, in which patients can be exposed (challenged) to airborne allergens and symptoms can be monitored in a controlled manner. The primary clientele of Red Maple Trials are pharmaceutical companies testing allergy medications.
The main problem being addressed is the current lack of control and quality in the deposition of mixed mortar in the application of large-scale 3D printing. This is a significant issue because the properties of the mixes used depend heavily on the material ratios and mixing/pumping time. This means that slight variations can lead to blockages in the system or even collapse of the intended printed items.
Current 3D Concrete printing system use many different mix/pumping systems. Two system which are very popular are the MTEC Duo Mix 2000 Connect from MTEC, MAI®MULTIMIX-3D.
Durham Region is committed to responding to the climate emergency by embedding climate change considerations across all elements of Regional business. This research will involve an examination of the Region’s entire waste management system and develop a full life cycle analysis model for GHG emissions which can be used to identify opportunities and support strategies to reduce GHG emissions caused by waste management activities.
This project consists of three subprojects. In the first subproject, an ammonia-fueled a power generator will be developed and experimentally tested. Thus, the emission released from the generator such as CO2, NOX, and SOX, will be reduced substantially. The second subproject of the project is to investigate the ammonia economy starting from production to last use in various sectors. Evaluating a microgrid system and compatible electrical vehicle, and their economic benefits, advantages or disadvantages will be researched extensively.
Many aspects of healthcare are time consuming and error prone. Recently there has been great progress in using artificial intelligence to solve a number of problems. One of the best examples of this is image labelling using a type of neural network approach called deep learning. Recent research has shown that deep learning approaches can outperform expert human radiologists when diagnosing disease in chest x-rays, in some situations. In this project we use a large set of chest x-rays as a test bed and develop a new method for software based radiological diagnosis using deep learning models.
In order to accelerate the transition of our electricity system to renewable sources, it is important that buildings participate effectively as distributed generators. However, traditional integration methods for solar energy often add complexity to our electricity system. With the rapidly declining costs of battery systems, building-level microgrids are becoming a viable alternative allowing buildings to generate and use renewable energy locally rather than exporting to the grid, enhancing the resilience of energy supply and improving demand profiles.
The inspection process has been an inseparable part of manufacturing to measure dimensions such as diameter, flatness, roundness and straightness of the parts. Besides, on some machined surfaces, it is required to measure roughness and identify surface defects. For defect detection, companies are still relying on visual inspection, which is very slow and labor-intensive. To overcome all challenges, interferometry instruments are used to acquire 3D images. Still, once a surface is acquired, the position and size of defects have to be found, and sometimes defect has to be classified.
Lithium-sulfur (Li-S) batteries have been considered as one of the most promising candidates to meet the energy storage demand for electric vehicles due to their high theoretical energy density of 2600 Wh kg-1, low cost, natural abundance, environmental friendliness. State-of-the-art Li-S batteries, using liquid electrolytes, still have significant challenges in their safety and lifespan.