2012 Technology Industry Labour Study

The project is about analyzing the Technology Industry in British Columbia. The study helps predict the British Columbia (BC) technology labour market through quantitative and qualitative analysis of answered questionnaires from technology companies in BC. A report summarizing the findings will be submitted to Cindy Pearson, COO of BCTIA by the end of December. In […]

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Simulation and analysis of light scatter in head mounted display lens

Head-mounted display (HMD) lenses can include a high degree of scattering (ghosting) which reduces brightness and contrast, and is distracting to the user. This can directly impact the utility of the device, if for instance some of the display is illegible because of excess light scatter and blurring. In this research, we want to investigate […]

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Georeferencing oblique imagery for vegetation analysis

To responsibly manage forest resources in southwestern Alberta, it is important to understand the disturbance regimes they have experienced in the past, are experiencing now, and are likely to experience in the future. The Mountain Legacy Project has several thousand repeat photographs which show areas of the mountains and foothills of the Rockies a century […]

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Development and characterization of nano-emulsification and liposomal platforms (NEP and LIP) for hemp oil nanoencapsulation and transmucosal delivery

A novel technology for delivery of biologically active compounds found in hemp oil is being developed. This novel technology significantly reduces the health risks associated with traditional administration of Cannabis products (e.g., smoking and THC-related intoxication) The proposed project, in collaboration with a federally-licensed facility for cannabinoid analysis, Abattis Bioceuticals, engages into the development of […]

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Arsenic release from arsenic-bearing minerals

When waste rocks generated by mining activities are exposed to the air and water, various toxic elements may be released to receiving waters and soils. Arsenic (As) is known as one of the most toxic pollutants which can cause damage to the environment and human health. To implement effective source control, it is essential to […]

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Improving sustainability and operations in residential development and its relationship to community resilience

The purpose of this qualitative study is to investigate how productivity improvements in a local company could contribute to its municipality’s (community) sustainability goals, and, by extension, to local community resilience. I will be using an action research (AR) methodology to create positive change and productivity improvements in the case of a company as the […]

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Advancing Out-of-Band Network Measurement for Multi-Hop Sensor Networks

This collaborative project with Rimeware will investigate out-of-band measurement approaches that can passively monitor the network traffic and provide rich detailed network information, e.g., latency, loss, route path, etc. The goal is to build a programmable system for accurate, generic, and robust network measurement. It includes two sub projects. In the first sub-project, we will […]

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Mastering Muons at the Weizmann Institute of Science

The proposed research project while at the Weizmann Institute of Science will have the main goal of contributing to the upgrade of the ATLAS detector. The ATLAS experiment is a multipurpose particle detector at the world’s largest particle accelerator, the Large Hadron Collider (LHC). In particular, a very important part of the ATLAS detector, the […]

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Community Capital Pilot Project in the District of Sechelt

This project will test pilot the newly developed Community Capital Tool (CCT) in the District of Sechelt. The CCT has been designed to guide and evaluate municipal level community development initiatives and decisions through a sustainability lens. In Sechelt the CCT will be used to assess the community’s newly adopted Sustainability Action Plan to create […]

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Apply Deep Neural Network to Detect Malignant Lung Nodules in CT Scans

Lung cancer has a poor prognosis and a high incidence in low resource settings. Early detection of malignant nodules can enable prompt intervention and improve treatment outcomes. Despite the recognized benefits of early nodule detection, it is clinically and computational challenging. Convolutional neural network (CNN) is a type of machine learning that has been applied […]

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High-throughput phenotyping of plant health using machine learning and computer vision

Phenotyping is used to develop new strains of plants, understand plant-affecting diseases (phytopathology) and evaluate the effects of various substances on plants. A growing variety of sensors and sensor technology is used to gather data used for phenotyping, in a non-destructive manner, and this overall process of data acquisition and analysis is being automated, leading […]

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