Personalized ad targeting is one of the most important features to ensure a successful advertising campaign---e.g., F-150 ford pickup trucks are best shown to construction workers than teenage girls. Another important aspect of ad personalization is frequency capping the ads. For example, showing the same ad 100 times to 1 user will result in not having any budget left over for others, and this can make or break an advertising campaign.
Addictive Mobility is a leading (Big Data) online advertising company in Canada. They use real-time bidding (RTB) platform for online display advertising in mobile devices, where multiple companies compete to show a certain Ad to a specific user at a certain time. The goal is to optimize the system such that they minimize the cost over the campaign period but also send targeted ads to maximize return on investment such as number of clicks or purchases.
Addictive Mobility is a leading online advertising company in Canada. The success of ad campaigns drives the majority of the company revenue. Exploring advanced machine-learning techniques to efficiently control an ad's performance is crucial to the company strategy. The objective of the proposed project is to optimize the real-time bidding system in the sense that delivery has been carried out in real-time and within a time-interval of 100 ms.
The ultimate aim of this project is to design and develop methods and tools for classifying attributes of books such as genre, style, tone, and likelihood of being popular. Towards this end we will make use of various information types available on books and users of the Kobo catalog, including the text, meta-data associated with the text, and user features associated with readers of the text. This is a large undertaking.
How to define user requirements accurately and design user interface appropriately have been a very active research area concerned with human-computer interaction and graphic design. Because of the scale and the complexity of three-dimensional (3D) animation software, making correct design decisions becomes tougher. Houdini is a 3D animation software as well as the main product of Side Effects. Using 3D animation software is always very challenge for users. It requires longer learning curves as well as interdisciplinary knowledge.
The project aims to build a 3D object detection system by using a number of images from multiple cameras. The system will train on instances of objects to detect other instances of the same object. This means that if, for example, we want to detect a sphere, we will make the system learn how a sphere looks like by giving some example images. Now when the system encounters a new object which looks similar to the example images, the system will detect the new object to be a sphere. Similarly the system will train for detection of more complex objects.
Based on the evaluation of modelled soil vapour concentrations it is common for soil contaminants of concern (i.e., volatile contaminants) to pose a potential health risk to receptors via the soil-to-indoor air vapour migration pathway. However, it is understood that the approach used to model vapour concentrations in indoor air, though acceptable to the Ontario Ministry of the Environment, is highly conservative based on the assumptions related to the maximum soil concentrations and potential for natural attenuation of soil vapours.
Newly available technologies for 3D fabrication — notably hobbyist 3D printers — are widening the user base for 3D design software. Autodesk, currently the industry leader in 3D design software, is broadening the scope of their activities, seeking to reach amateur users and to encourage their use of Autodesk software solutions. One of the most difficult aspects of 3D design for fabrication is that the resultant 3D models do not just need to be aesthetically pleasing, they also need to be able to be produced using specific fabrication technologies.
Society uses thousands of chemicals and the potential risks to humans and the environment for the vast majority of these chemicals are largely unknown. It is not feasible to measure all of the chemicals and there are substantial data gaps; therefore, models are required to screen and evaluate chemicals for potential exposures and risks to humans and the environment and to address data gaps. ARC Arnot Research & Consulting develops models for screening-level exposure and risk assessment. There is a need to test these models.