Ontology-based approaches that formally represent the meaning of information in a system, offer the hope of dealing with semantic heterogeneity when integrating heterogeneous data sources [Halevy 2001, Noy 2004, Wache et ...

Grid computing enables the selection and aggregation of a wide variety of geographically distributed resources as a single unified computing resource, for solving large scale compute and data intensive computing ...

This thesis presents a generic framework for grid-enabled visualisation and computational steering that is amenable to characterisation using mathematical models based on benchmarked resources. The models enable designers, ...

Mobile context-aware computing is a paradigm in which mobile devices have access to information, known as context, about the situation in which they are being used, and dynamically adapt application behaviour to support ...

Stochastic differential equations (SDEs) are widely used to model numerous real-life phenomena. However, transition densities of most of the SDE models used in practice are not known, making both likelihood based and ...

This study uses a grounded theory approach to develop a theoretical understanding of the formation, nature, and impact of a blended community on the educational experience of part-time higher education students. Within ...

This work describes novel methods and techniques to decrease the cost of employing active learning in text categorisation problems. The cost of performing active learning is a combination of labelling effort and computational ...

Adaptive eLearning appears well suited to Grid education because of the distributed and heterogeneous nature of grid users and their asynchronous training demand. This thesis explores the application of adaptive eLearning ...

Automatic topic segmentation in meeting recordings is intensively investigated due to the fact that topic is a salient discourse structure and it indicates natural reference points for contents. Unlike commonly used ...