Improving usage pattern quality by comparing different sequential pattern mining methods and the effect of considering additional user information

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 […]

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Game private networks and game server performance emulation and evaluation

This infrastructure will allow new servers to be automatically deployed and configured for use as private game servers, while also monitoring their performance and usage statistics. By using the novel predictive models, which are to be developed in this proposed project, new virtual servers will be automatically created and added when the traffic levels require […]

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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 […]

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Image matching for purposes of consumer recommendation

The purpose of this project is to develop a highly accurate e-commerce recommender system able to select products across databases and recommend them to prospective customers both in real-time and off-line. Leveraging the historical inventory of sold products, browsing history, purchase history, and expressed preferences helps the recommender to formulate highly accurate product suggestions to […]

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Developing Prediction Models on London Stock Exchange (LSE) Equitiesand Indicies using Microsoft Azure Machine Learning and Data Mining

I am to import ten year’s 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 […]

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Advanced Earth Observation Technologies

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 […]

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Load Adaptive Consistency Protocol

In a cloud context, it is important to synchronize the information between nodes of the system. This research looks as existing problems and provides improvements in terms of performance and availability. For that reason, cloud management solutions are needed which will benefit Ericsson with new mechanisms for uniformity of information between nodes. And, the same […]

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Mobile Augmentative and Alternative Communication (AAC) Technology

The research project will involve the development of features and techniques to aid people with communication disabilities through the use of consumer mobile devices (ex. smartphones) and tablet computers. Some of the major areas of interest include: location aware vocabularies, predictive sentence construction, and support for alternative input for people that also suffer from motor […]

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Designing a Usable Software Lifecycle Traceability Language Part 2

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. Supporting communication between all these teams is challenging: […]

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Utilization of Machine Learning in an Automated Framework for Evaluation and Management of Information Security Risk

During the internship in collaboration with RootCellar Technologies, research will be conducted towards the design of an adaptive machine-learning solution and its integration with the existing RootCellar framework for automated evaluation and management of information security risk in small and medium size enterprise networks. The existing framework is very advanced in terms of end-point risk […]

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Compromis entre efficacité énergétique et protection aux pannes dans les « Software Defined Networks ».

Les réseaux de communications, notamment l’Internet, connaissent une importante croissance ses dernières années. Cette croissance s’accompagne d’une complexité grandissante ainsi que d’une consommation énergétique de plus en plus élevée. Les technologies actuellement déployées ne sont pas adaptées pour faciliter l’économie d’énergie sur des réseaux de grandes tailles. La technologie SDN nous offre un meilleur contrôle […]

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Learning Approaches to Graph Structure Discovery

The project would explore the use of modern techniques from the field of Machine Learning to identify networks from observational data. This is an important area of research in fields such as neuroscience and genetics, where it can shed light on the nature of various disease. Other applications include discovering influencers and communities in social […]

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