Digital libraries on an iPod: Beyond the client-server model

This paper describes an experimental system that enhanced an iPod with digital library capabilities. Using the open source digital library software Greenstone as a base, this paper more specifically maps out the technical steps necessary to achieve this, along with an account of our subsequent experimentation. This included command-line usage of Greenstone's basic runtime system on the device, augmenting the iPod’s main interactive menu-driven application to include searching and hierarchical browsing of digital library collections stored locally, and a selection of "launcher" applications for target documents such as text files, images and audio. Media rich applications for digital stories and collaging were also developed. We also configured the iPod to run as a web server to provide digital library content to others over a network, effectively turning the traditional mobile client-server upsidedown

Massive ontology interface

This paper describes the Massive Ontology Interface (MOI), a web portal which facilitates interaction with a large ontology (over 200,000 concepts and 1.6M assertions) that is built automatically using OpenCyc as a backbone. The aim of the interface is to simplify interaction with the massive amounts of information and guide the user towards understanding the ontology’s data. Using either a text or graph-based representation, users can discuss and edit the ontology. Social elements utilizing gamification techniques are included to encourage users to create and collaborate on stored knowledge as part of a web community. An evaluation by 30 users comparing MOI with OpenCyc’s original interface showed significant improvements in user understanding of the ontology, although full testing of the interface’s social elements lies in the future

Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting

Machine learning algorithms, when applied to sensitive data, pose a distinct threat to privacy. A growing body of prior work demonstrates that models produced by these algorithms may leak specific private information in the training data to an attacker, either through the models' structure or their observable behavior. However, the underlying cause of this privacy risk is not well understood beyond a handful of anecdotal accounts that suggest overfitting and influence might play a role. This paper examines the effect that overfitting and influence have on the ability of an attacker to learn information about the training data from machine learning models, either through training set membership inference or attribute inference attacks. Using both formal and empirical analyses, we illustrate a clear relationship between these factors and the privacy risk that arises in several popular machine learning algorithms. We find that overfitting is sufficient to allow an attacker to perform membership inference and, when the target attribute meets certain conditions about its influence, attribute inference attacks. Interestingly, our formal analysis also shows that overfitting is not necessary for these attacks and begins to shed light on what other factors may be in play. Finally, we explore the connection between membership inference and attribute inference, showing that there are deep connections between the two that lead to effective new attacks

Exploring (the poetics of) strange (and fractal) hypertexts

The ACM Hypertext conference has a rich history of challenging the node-link hegemony of the web. At Hypertext 2011 Pisarski [12] suggested that to refocus on nodes in hypertext might unlock a new poetics, and at Hypertext 2001 Bernstein [3] lamented the lack of strange hypertexts: playful tools that experiment with hypertext structure and form. As part of the emerging Strange Hypertexts community project we have been exploring a number of exotic hypertext tools, and in this paper we set out an early experiment with media and creative writing undergraduates to see what effect one particular form – Fractal Narratives, a hypertext where readers drill down into text in a reoccurring pattern – would have on their writing. In this particular trial, we found that most students did not engage in the structure from a storytelling point of view, although they did find value from a planning point of view. Participants conceptually saw the value in non-linear storytelling but few exploited the fractal structure to actually do this. Participant feedback leads us to conclude that while new poetics do emerge from strange hypertexts, this should be viewed as an ongoing process that can be reinforced and encouraged by designing tools that highlight and support those emerging poetics in a series of feedback loops, and by providing writing contexts where they can be highlighted and collaboratively explore

On the functional group tolerance of ester hydrogenation and polyester depolymerisation catalysed by ruthenium complexes of tridentate aminophosphine ligands

The synthesis of a range of phosphine-diamine, phosphine-amino-alcohol, and phosphine-amino-amide ligands and their ruthenium(II) complexes are reported. Five of these were characterised by X-ray crystallography. The activity of this collection of catalysts was initially compared for the hydrogenation of two model ester hydrogenations. Turnover frequencies up to 2400 h-1 were observed at 85 oC. The catalysts turnover, albeit slowly at near ambient temperatures. Using a phosphine diamine RuII complex that was identified as the most active catalyst, a range of aromatic esters were reduced in high yield. The hydrogenation of alkene-, diene-, and alkyne functionalised esters was also studied. Substrates with a remote, but reactive terminal alkene substitutent could be reduced chemoselectively in the presence of 4-dimethylaminopyridine (DMAP) co-catalyst. The chemoselective reduction of the ester function in conjugated dienoate ethyl sorbate could deliver (2E,4E)-hexa-2,4-dien-1-ol, a precursor to leaf alcohol. The mono-unsaturated alcohol (E)-hex-4-en-1-ol was produced with reasonable selectivity, but complete chemoselectivity of C=O over the diene is elusive. High chemoselectivity for the reduction of an ester over an alkyne group was observed in the hydrogenation of an alkynoate for the first time. The catalysts were also active in the depolymerisation reduction of samples of waste PET to produce benzene dimethanol. These depolymerisations were found to be poisoned by the ethylene glycol side product, although good yields could still be achieved.PostprintPeer reviewe