This work focuses on generation a framework to employ a set of 3D coordinates, as the input dataset to the model, and generate the 3D heat map based on the 3D shape. The generated 3D heatmap aims to define the most probable areas for fault categories on the 3D surface. To develop such a system, the 3D shape is printed and the 3D coordinates of simulated faults are recorded using a tool tracker. Then, a machine learning platform is employed to use the 3D fault datasets as the input and produce the probabilities of different fault categories on the given location.

Air-core dry-type electrical reactors are integrated into power system infrastructures to limit current and regulate voltage in transmission lines. These reactors, are designed and built to facilitate customer specific requirements using an elementary noise prediction model, which was developed almost 30 years ago. With increasingly stricter noise emission guidelines set by the environmental regulatory bodies, the need to better predict and meet specific noise requirements has become more important to the design and manufacturing of the reactors.

Many office and institutional buildings use concrete masonry walls as their loadbearing elements. They are required to withstand loads coming from their roof structures and also caused by wind and seismic events. This research project will determine the suitability of such masonry walls when subjected to these loads. Further, this project will research to improve the performance of these walls by introducing various new structural and construction details. The goal of this research will be accomplished through experimental and computer modeling techniques.

Cyber-physical systems or Industrial Internet of Things (IIoT) applications are more advanced than commercial IoT devices/applications mainly because of the prevalence of connected sensors and embedded systems in the industrial world. The objective of this project is to develop and package a low range, low power (LoRa Technology) remote asset monitoring and control system for “remote fixed utility” IIoT applications.

The goal of this project is to provide evidence of validity for two newly developed measures of quality of life; one for hidradenitis suppurativa (HS) and one for acne. Both HS and acne negatively impact quality of life; however, to date, there are no disease-specific, patient-centered quality of life measures. The results of this project will provide healthcare professionals with tools to assess the impact of these conditions and their treatments (HS and acne) on patients’ quality of life.

The Canadian government has increased its focus on regulating wastewater to the environment. The advent of new regulations has resulted in many municipalities requiring substantial upgrades to minimize release of nutrients promoting eutrophic water bodies. Traditional wastewater treatment technologies are in some cases cost prohibitive. Bishop Water Technologies (BWT) provides an ecofriendly and cost-effective technology for treating Canadian wastewater (municipal and industrial) while removing nutrients to rivers and lakes.

Harmful algal blooms (HABs) in the western basin of Lake Erie are detrimental to the ecosystem, reducing water quality and affecting drinking water for people in the region. Severe HABs in Lake Erie in the 1960s and 1970s resulted in the Great Lakes Water Quality Agreement in 1972. Since then, water quality has greatly improved; however in the 1990s, Lake Erie saw the blooms return. This has been attributed to factors such as zebra mussels’ bio-transforming nutrients, climate change, shifts in the form of phosphorus and lake sediment as an internal loading source.

The goal of the study is to research, test and compare imaging, diagnostic, and quantitative assessment capabilities of the high-frequency ultrasound (HFU) technology and the optical coherent tomography (OCT) for dental applications. A set of samples (possibly hard and soft tissues) will be specifically prepared by the research team from the host university and then imaged, and analyzed in order to determine anatomical features and possible diseases conditions. A newly developed scanning acoustic microscope as well as a prototype of a dental ultrasonic system will be used in this study.

Assistive Technology (AT) allows children with Specific Learning Disabilities (LDs) to adequately access school curriculum. There is a paucity of literature addressing perception of use and training for teachers to support use. Studies suggest that children with AT like their devices and find them useful. The proposed study will examine the ages of children provided AT devices, the types of AT hardware and software being used by children with various learning limitations in a school environment, and children’s perception of their AT devices.

This research aims at improving the accuracy of a 3D-vision tracking system. The physical set-up consists of a tool to be tracked, such as a drill, with one or more planar patterns attached to it and a set of cameras. This set consists of one to four camera clusters, where each cluster has one or more cameras. The current tracking system consists of several modules, including one for the calibration of the cameras (intrinsic and extrinsic), and another one for the calculation of the 3D coordinates of an unknown physical point, the tip of the tool.