Association rules are interesting correlations among attributes in a database. These rules have many applications in areas ranging from e-commerce to sports to census analysis to medical diagnosis. The discovery of association rules is an extremely computationally expensive task and it is therefore imperative to have fast scalable algorithms for mining these rules. In this thesis, we present eÆ...

E xtracting rules from trained artiicial neural networks adds more powerful features to their output decisions. The explanation, validation, and cross-referencing are some of these powerful features. This paper introduces a new rule ordering and evaluation algorithm that orders extracted rules based on three performance measures so they can be used by any generic inference engine. Moreover, it ...

Making the science and technology of computer music comprehensible to musicians and composers who had little or no background therein was a part of Max Mathews’ genius. In this presentation I will show how a simple diagram led to the essential understanding of Claude Shannon’s sampling theorem, which in turn opened up a conceptual path to composing music for loudspeakers that had nothing to do ...

AbstractImage color harmonization algorithm aims to automatically match the distribution of foreground and background images captured in different conditions. Previous deep learning based models neglect two issues that are critical for practical applications, namely high resolution (HR) image processing model comprehensibility. In this paper, we propose a novel Deep Comprehensible Color Filter ...

This work describes a freely available web-based facility which can be used to analyse raw or processed mass spectrometric data from metabolomics experiments and display the metabolites identified--and changes in their experimental abundance--in the context of the metabolic pathways in which they occur. The facility, Pathos (http://motif.gla.ac.uk/Pathos/), employs Java servlets and is underpin...