Since the adoption of the North American Free Trade Agreement (NAFTA) signed on January 1st 1994, the amount of truck freight moved between Canada, U.S. and Mexico has increased considerably. However, the transportation of goods has still have some gaps that need to be settled such as loss of merchandise and delay in delivery time. The reason of these gaps is due to the involvement of several participants in the transportation loop. The delivery of products from the manufacturers to the retailers is done through asset based carriers (55%) and owner operators (45%).
Ensuring data security in large data repositories is a challenging task as the volume and the nature of the data to secure constantly evolves. Large repositories are mostly composed of documents expressed in natural language and as a result they are a rich source of information. Given the importance of personal data protection, this proposal explores new methods to mine networks of communications between users and detect improper dissemination of sensitive information.
Estimating poses of three dimensional (3D) objects is of great importance to many high level tasks such as robotic manipulation, scene interpretation and augmented reality. Detecting poorly textured objects and estimating their 3D pose is still a challenging problem. The objective and expected result of this research is to develop a systematic and applicable approach that could detect poorly textured 3D object pose. The proposed method is using state-of-the art deep learning in computer vision.
The worldwide data explosion would emphasize on importance of knowledge discovery from massive, heterogeneous, and dynamic volumes of information (Big Data). Similar to other industrial organizations, Credit union industry deals with massive amounts of structured (e.g. customer demographics and transactional data) and unstructured (e.g. email, social media data, comments) data which they have not utilised well to be able to proactively offer their products and services according to their customer needs.
With childhood obesity and inactivity on the rise at an alarming rate, many government, education, and health agencies are promoting the development of physical literacy to combat this epidemic. The concept of childhood physical literacy refers to the development of fundamental movement skills that permit a child to move confidently and with control, in a wide range of physical activities. Wearable technologies have been quickly gaining in popularity, with devices and apps that can track fitness, sleep patterns, mood and even air quality.
REP is an athlete development platform for building better, and healthier athletes. Inside the REP platform are computer algorithms that can see how people move, and the accurately estimate how they are moving in three dimensions. The REP platform can then compare models of how you move, to models of how experts move. This comparison gives us rich information that people can use to improve their form. However, generating the expert models is quite hard, and its not always easy to understand how to actually compare users and experts.
Prior doing any type of construction that causes soil disturbance (digging, trenching, etc.), it is imperative to acknowledge which infrastructures such as water ducts, sewerage, electricity cables are buried. The GPR approach is recognized as performing to obtain the location and depth of underground objects but it shows some drawbacks. The proposal is to improve field survey and spatial data integration of GPR investigations by providing interoperate web and GIS capabilities available on portable device as smartphone or tablet.
IOT technology is a brand new, and rapidly growing field. Currently, there are no best practices published in the design of real-time, dynamic network displays. Our project focuses on developing and testing new business processes, user personas, and design-guidelines associated with these types of displays in a real-world environment. The findings from this work will not only inform future software development at Distrix, but also aims to offer meaningful contributions to the methodology literature in information visualization and human computer interaction.
This project focuses finding solution for acquiring super resolution image from objects submerged in turbid media. The project group will look at various environments including high pressure / high temperature test setups.
Radars are being used more and more in critical sites such as airports, military bases and borders for surveillance of huge areas to detect unwanted intrusions. Determination of the type of each target is essential for such systems to identify the nature of the intrusion and avoid false and nuisance alarms. This thesis is focused on the design of automatic target classification systems based on analysis of real radar data from different sites and environments.