Automated CNC processing of complex and high-aspect-ratio microfluidic devices for biomedical applications

Disposable microfluidic devices, also known as labs-on-a-chip, made out of plastic materials have seen increasing applications in chemical and biomedical analysis. In most applications, microfluidic devices usually incorporate small channels and chambers for micro sized dimensions, using heights between a few hundred to a few micrometers. Currently, manufacturing processes have been established to create these sub-millimeter deep features. However, in other applications, higher (or deeper) features of a few millimeters may be needed.

Applied Machine Learning for Malware and Network Intrusion Detection

Wedge Networks is a leading cybersecurity solution provider in Canada. In this project, we aim to investigate the application of statistical machine learning and deep learning to cyber threat detection, aiming to detect both network intrusions and malware binaries transmitted in the network.

Enhancing Lateness Management in Cross-docking

Today's marketplace is moving faster than ever, and companies are challenged to distribute their products more quickly, efficiently and cost-effectively. This has led to the rise of cross-docking in the global supply chain to help keep pace with customer demand. Cross-docking refers to the practice of unloading goods or materials from an incoming vehicle (e.g., train car, truck, vessel container) and then loading them directly onto outbound vehicles with no storage in between.

Enhancing Lateness Management in Cross-docking

Today's marketplace is moving faster than ever, and companies are challenged to distribute their products more quickly, efficiently and cost-effectively. This has led to the rise of cross-docking in the global supply chain to help keep pace with customer demand. Cross-docking refers to the practice of unloading goods or materials from an incoming vehicle (e.g., train car, truck, vessel container) and then loading them directly onto outbound vehicles with no storage in between.

Prototype Behavior Based Integrity Verification (BBIV)

Web computing, in which the world-wide web is itself employed as a distributed computing platform, is entering a stage of rapid expansion with the advent of Open Web Platform so that programs that once worked only a native environment on desktop, tablets or phones can now work from within a browser itself. There is therefore a need for a new form of protection for apps.

End-User Understanding of Web Certificates - Year two

Users must decide which websites to trust and which to avoid. How can users know if a website is truly what it claims to be? This is a pivotal issue. When attackers can convince users to trust their sites, though phishing or other strategies, user security and privacy are easily compromised, malware can be downloaded, and infrastructure undermined.
Our plan is to conduct user studies to explore the understanding of browser-presented certificate information.

Automatic Casting from Videos Using Deep Convolutional Neural Networks

In automatic casting applications, the aim is to accurately recognise facial regions that correspond to a same actor appearing in a movie to produce described video. In particular, this project will focus on challenging tasks of capturing and modeling the facial trajectory for each person appearing in a movie in order to predict when/where the principal actors appear. This is a challenging task because recent movies are typically high quality and faces are often occluded and their appearance varies significantly according to pose, illumination, blur, etc.

NLP Techniques for Automated Entity Recognition

The primary goal of this project is to explore a variety of new and existing Natural Language Processing (NLP) techniques to improve the performance, and further the automation of, Knote’s text analysis software – specifically with entity recognition. Entity recognition is the process of identifying all groupings of words in a collection of documents that fall within that entity’s purview, such as proper names or chemical compounds.

Image Style Classification and Its Application on User Engagement

In this project, we will apply machine learning to perform image style classification. We will build a system that uses image style classification to increase user engagement in an eCommerce platform setting. We will study the effects of user preferences for particular image styles on their engagement with the platform.
Image style classification is the task of categorizing an image based on attributes such as composition style (e.g., minimal, geometric, etc.), atmosphere (hazy, sunny), or colour (pastel, bright).

Webpage customer persona discovery and push notification guidelines

Cellphones get notifications from different companies every day, but we do not know whether these notifications have a significant impact on customers’ behaviour. Knowing the impact of these notifications would provide useful insights to marketing strategists. Since user behaviour will determine the efficacy of push notifications, this project initially aims to build a behavioural model, which will group customers based on their web site navigation behaviour.

Pages