Frequent usage patterns generated can provide valuable information for several applications such as platform restructuring and recommendation. In this project, we aim to compare different practical methods, and to investigate the effect of user identity and user intention information on them. To that end, a technique and a framework need to be developed, in which frequent patterns are composed of more refined analysis result instead of simple frequent sequences of basic operations over all users behavior.
I am to import ten years worth of amassed historical data on news events, price movement of equities and public sentiment metrics to Microsoft Azure platform for study and analysis through the latest Data Mining techniques with an Economics point of view to uncover the hidden correlation and casualty between events and price movement of global markets in multiple timeframes (three hours, daily, weekly, monthly and yearly).
As manufacturing and resource-based industries face growing challenges, Canadas future increasingly depends on advances in and sustainability of knowledge organizations. Knowledge-based workers comprise a growing proportion of the workforce today. More often than not, they work in the context of large-scale expert networks, spanning across different disciplines and organizations. They rely on software technologies for their discipline-specific activities, the coordination of their activities, and their communication with each other.
Teams of specialized workers develop most software. For example, one team may specialize in the requirements that describe what the software is to do. Another team may specialize in producing the software itself. Yet another team may specialize in determining whether the software meets the desired requirements.
In modern large data centers hundreds of thousands of VMs run simultaneously on thousands of physical computing nodes and networking nodes with different security policies. A centralized security architecture based on managing all their security policies in a few large security appliances would cause major security policy complexities and choke points in the cloud infrastructure. We will investigate to propose a network security pattern based approach for cloud infrastructure and its optimal placement in the cloud.
The Resident Assessment Instrument Minimum Data Set (RAI-MDS) is used by health authorities for collecting information about individuals in continuing care facilities. Collected quarterly, RAI-MDS records contain more than 500 data elements, including cognition, psychosocial well-being, health conditions, communication, physical function, and activity patterns. Because of this it has great potential for providing an incomparable quantitative view on the lives of the oldest and most vulnerable Canadians.
The project involves conducting a study to evaluate human performance in executing simple drawing tasks like drawing curves and lines from various directions. The study will help ascertain the accuracy and ergonomic aspects of 3D drawing. We will then use the results of the study to design a 3D sketching system combining augmented reality glasses with traditional drawing tablets. The tablet can provide a physical constraint to aid drawing tasks while also reducing the amount of fatigue the artist faces.
UrtheCast is developing advanced cameras and sensors flying on a constellation of 16 satellites orbiting the earth in tandem pairs. The unprecedented data set requires innovation in advanced earth observation algorithms and applications, which will require novel techniques for analysis, simulations and advanced big data processing. The objective of this project is to put this data to good use. Never before has the world been viewed with such detail and precision.
Information and Communication Technologies (ICT) adoption in livestock production landscape has been transformative and has led to a fundamental need for sophisticated data management and exchange solutions. Building an interoperable data management system requires an understanding of data context, stakeholders needs, data usage conditions, as well as contractual and legal requirements. Only through understanding the data and business management ecosystem, we can develop a proactive plan that ensures appropriate data usage, addresses business goals, and creates shared values.
This project will develop a new mechanism for grouping objects in a dynamic environment, where new objects are regularly added with limited or incomplete information. Furthermore, the information about the existing and new objects increases over time. This new grouping mechanism will be called dynamic clustering of temporally incremental patterns. The proposal will be tested using energy consumption patterns for a large number of buildings. The types of the buildings will vary based on their usage such as office buildings, warehouse, shopping malls, hospitals, educational institutes, etc.