Enhancement of technology and computer science has helped researchers in multiple fields and industries, from health care to automotive industry. Smoking is one of the habits that could harm humans dramatically. Lung cancer, heart attack is just some of the diseases that come with smoking. A large number of people strive to quit smoking each year by various methods, but not all of them are successful. In this research, we try to study what are the reasons that tempt people who quit smoking to smoke again.
The main objective of this project is using deep learning algorithm to enhance the current state of the art tooth wear monitoring system used in mining shovels. Unlike the current approach, the proposed deep learning method operates by building a model from input images in order to make data-driven predictions. We use deep learning approach to identify the pixels that belong to the teeth-line in each video frame taken by camera located on the mining device.
Merging different sub-companies into TELUS caused some of customer records to be repeated through the merged data-set. Algorithms are needed to determine the duplicate records. Currently a deterministic algorithm is being used in TELUS. In this project, we will investigate if machine learning can help to detect duplicates. Solving this problem has several parts. We have to preprocess the data and select some features from the TELUS records that help us in our model. A probabilistic model should be selected, implemented and tuned.
High definition acquisition devices have been commonly used in video capture. Millions of videos are recorded and stored daily. Due to the rapidly growing volume, effectively searching and matching the desired video clips from archives has become increasingly challenging. It may need days and weeks to locate the target information, such as suspected criminals, traffic violated vehicles, or accidental fall in care homes. While Google engine is designed for web searching, we propose to build a framework for efficient video searching.
In this project, we will establish biomarkers that objectively reflect the severity of injury, measure its progression, and predict neurologic outcome after acute spinal cord injury (SCI). This will be accomplished by comprehensively analyzing blood and spinal fluid samples from acute SCI patients. In addition, we will conduct a parallel experimental study in a large animal model of SCI with a similar analysis of blood and spinal fluid samples.
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.
The objective of this project is to develop methodologies for automatically generating responses in a natural language to converse with humans. Responses directly generated from the question-answer database are inflexible and cannot meet users' needs. On one hand, the responses should take into account the previous utterances that can keep a conversation more active. On the other hand, the responses should be appropriate for the emotions conveyed in a conversation that can make a conversion more user-friendly.
Sensing technologies require the deployment and maintenance of complex and large infrastructures. This research proposal is focused on peoples activity recognition technologies though existing WiFi infrastructures. The information gathered by this technology can be applied to different industries like home automation, security, etc. In the future, this technology will powered applications in the home automation industry as the one described next. Mary comes home and leaves her cellphone on the couch. As the system recognizes her, no alarm is activated.
The continuum of HIV care is highly complex. It includes prevention, testing, patient care, treatment, and support services. This project will help Providence Health Care utilise its limited resources to provide the best treatment and care for people living with HIV in Vancouver. Care for HIV patients includes antiretroviral therapy, treatment of co-morbidities, monitoring clinical markers of disease progression (CD4 count and viral load), and support services to ensure treatment adherence and retention in care.
Extensive research has been conducted for the computational analysis of mass spectrometry based proteomics data, however most of the traditional computational approaches take the assumption that the acquired spectra are generated from the fragmentation of a single precursor and the peptide is simply a linear sequence of amino acid residues. This ubiquitous assumption is impeding the utility of those computational approaches, especially when handling those non-canonical tandem mass spectra.