Wavelet Galerkin method for fractional elliptic differential equations

Under the guidance of the general theory developed for classical partial differential equations (PDEs), we investigate the Riesz bases of wavelets in the spaces where fractional PDEs usually work, and their applications in numerically solving fractional elliptic differential equations (FEDEs). The technique issues are solved and the detailed algorithm descriptions are provided. Compared with the ordinary Galerkin methods, the wavelet Galerkin method we propose for FEDEs has the striking benefit of efficiency, since the condition numbers of the corresponding stiffness matrixes are small and uniformly bounded; and the Toeplitz structure of the matrix still can be used to reduce cost. Numerical results and comparison with the ordinary Galerkin methods are presented to demonstrate the advantages of the wavelet Galerkin method we provide.Comment: 20 pages, 0 figure

Trans-disciplinarity and digital humanity: lessons learned from developing text mining tools for textual analysis

This peer-reviewed chapter advances social science research on text mining and data mining, which are key artificial intelligence technologies applied in the digital humanities. The chapter provides a detailed documentation of an interdisciplinary project conducted by a team consisting of social scientists, linguists and software engineers to develop a set of bespoke text-mining tools for researchers in the humanities. Through looking at the user-participatory development processes of the text-mining tools, this chapter aims to improve our understandings of digital humanities in the context of scholarly research and, from a pragmatist perspective, to highlight its trans-disciplinary potential. The paper both analyses and produces an empirical account of interdisciplinary research practices across the social sciences and humanities. It concludes with a discussion of some methodological and socio-technical challenges of the 'digital humanity' emerging in this shift towards trans-disciplinarity, particularly focusing on the topic of 'interpretative flexibility'. The edited collection, which is interdisciplinary in nature, develops knowledge of how the application of new computational techniques and visualisation technologies in the arts and humanities is resulting in fresh approaches and methodologies for the study of new and traditional corpora. It includes articles from internationally significant scholars such as N. Katherine Hayles and Lev Manovich. The realisation of this piece has benefited from discussion at the 2009 Media, Communication and Cultural Studies Association (MeCCSA) conference at Bradford, 14–16 January 2009, and the Computational Turn Workshop at Swansea on 9 March 2010, where an earlier version of this paper was presented

Open data and co-production of public value of BBC Backstage

Openly accessible data sets (open data) have been recognized as valuable assets for creating business opportunities, revitalizing innovation and transparentizing organizational conducts. Public Service Broadcasters (PSB) such as the British Broadcasting Corporation (BBC) have been motivated to experiment with open data and new forms of innovation in content making, delivery and audience engagement. Through a case study of the BBC Backstage project, this article examines how such open innovation processes of engaging the public in the reuse and remix of open data were conceived, supported, managed and maintained. The research found that BBC Backstage had played an important role in encouraging and motivating people to reuse and repurpose the open data released by the BBC. New forms of outputs have emerged, as seen in the Data Arts visualization project and the R&DTV clips mashups. The article argues that PSB public value can be co-produced through opening up data sets, encouraging reuse and remix, and building up a network of enthusiastic and capable active audiences, the techno-elites, whose status has been encouraged the open data culture and alike. Lessons learned can help understand the meanings of open data from the PSB perspective, and the implications in media industry thereby foster innovation in future media and creative industries

A reflective commentary of teaching critical thinking of privacy and surveillance in UK Higher Education

The importance of data literacy and the need of raising and improving it through formal educational channel or public engagement has been flagged up in each of the past ESRC-funded Data-Psst! seminar I attended in 2014-16. There is a real demand for action taking. I took advantage of the knowledge I learned from the Data-Psst seminars and devised a module teaching Level 5 undergraduate media students about critical issues in today’s data-centric digital society, including privacy and surveillance. In this article, I share how the class activities were devised and carried out, and how guided engagement with the current debate in privacy and surveillance were realised. I also draw on relevant pedagogical theories to discuss my educational approaches, student performance, the challenges of the project, and evaluate and reflect upon the outcomes. This report from the field provides fresh first-hand information about the data ethics of younger public who are practising media arts and their behaviours and attitudes towards privacy and surveillance. I hope the article will open up the discussion about the role educators play in enriching public engagement with critical thinking about big data. The lessons learned can also contextualise the pedagogical implication of the recent scholarly research on big data and privacy, and provide a framework for constructing future collaborative or creative projects