The aim of the project is to predict future customer demand for repeat-buying items based on available customer purchase records. However, the purchase history for a single customer may not be sufficient to base predictions on. Also, some purchase records might be missing due to sales events at competitorsâ locations. Thus, treating each customer as a replicant of the average customer and averaging inter-purchase times to predict future demand will likely be an inadequate approach.
The proposed project is a characterization study on chitin nanowhisker nanocomposites. Chitin nanowhiskers are derived from chitin, a naturally occurring biopolymer found in arthropod exoskeletons, and offer great potential for reinforcement and property enhancement once blended with typical engineering plastic matrices. Compared to traditional inorganic fillers such as carbon nanotubes and graphene, chitin nanowhiskers are biocompatible and biodegradable, exhibiting comparable property improvements with none of the downsides of the inorganic materials (i.e. biohazardous, toxic).
Epilepsy affects an estimated 50 million people worldwide. These people can experience unexpected seizures that makes it risky for them to engage in everyday activities like driving and walking. A portable wireless neuromonitoring headset prototype that is worn on the head has been developed by Avertus Inc. to address this issue. The headset is designed to read brain waves, and, through a wireless connection to a cell phone, warn the wearer that the device has measured brain activity characteristic with an oncoming seizure.
Perimeter Medical Imaging (PMI) has developed an investigational imaging device to aid in achieving clear margins during surgical oncology procedures. This project will employ PMIâs device to image multiple types of human tissues, which have been previously removed during elective or medical procedures. This study will correlate the images obtained using PMIâs device with the true microscopic structure of the tissue, as confirmed by a pathologist.
The aim of the internship is for the intern to take up the challenge of detecting and removing noise from brain signals that are recorded using electroencephalogram (EEG). The noise that is of interest in the project is mainly caused by the subject chewing and walking. These noises are found to have caused the inability to have a high accuracy in performing seizure detection using EEG. Machine learning-based approaches are to be taken in the attempt to characterize these noises and subsequently eliminate it from the recorded brain signal.
Poor diet is one of the factors associated with obesity and overweight, which may increase the risk for chronic diseases such as diabetes, heart disease and cancer. Two ways to improve the diets at the population level are to 1) establish public health initiatives (e.g.
The aim of this project is to research and develop a new DICOM modality for the optical coherence tomography images obtained by Perimeterâs Optical Tissue Imaging (OTISTM) device. Following the creation of a suitable modality, a novel solution for transfer to and integration with the PACS servers utilized by current Perimeter customers will also be developed. The device currently allows for local storage and review of obtained data, with images only ever transferred onto different servers by Perimeter staff.
Low impact development (LID) technologies are increasingly part of the urban landscape for Canadian municipalities. Bioretention planters, also known as rain gardens, are an LID technology that infiltrates and filters runoff at the source. Though design guidance exists, there is little data available on the long term performance of LID technologies, such as bioretention systems. This study aims to contribute to the literature of field studies on the long term performance of bioretention systems, in terms of the hydrologic performance and maintenance needs.
A critical challenge today in neuro-surgery is the determination of tumor boundaries intraoperatively. There are means of doing this using high-resolution MRI machines, however, these can be prohibitively costly. Optical coherence tomography (OCT) offers a promising, cheaper, label-free alternative. However, the basic models used for clinical, real-time OCT limit its usefulness and depth of focus. This work will develop a type of image reconstruction that includes digital focusing and anisotropic properties.
Currently available diagnostic imaging tools, such as chest radiography and computed tomography, are inadequate for assessing the lungs of preterm neonates. There is considerable interest in using magnetic resonance imaging (MRI) to monitor lung development in neonates longitudinally, since it is a non-invasive and non-ionizing imaging modality. MRI can potentially detect complications at an early stage and improve outcomes by monitoring the effectiveness of therapy, however, images typically suffer from poor signal and organ motion.