LINK Centre (Learning Information Networking Knowledge Centre)

Permanent URI for this communityhttps://wiredspace.wits.ac.za/handle/10539/19250

The Wits LINK Centre is a leading African academic research and training body focused on ICT ecosystem policy and practice. Based at the Wits Tshimologong Digital Innovation Precinct in Braamfontein, Johannesburg, LINK engages in knowledge production and capacity-building for the broad communications and information and communications technology (ICT) sector in Africa. Its focus spans across policy, regulation, management and practice in telecommunications, Internet, broadcasting, digital media, e-government, e-transformation and e-development, all with an emphasis on economic and social implications in African and other developing-world contexts. LINK publishesThe African Journal of Information and Communication (AJIC), which is accredited by the South African Department of Higher Education and Training (DHET). Director: Dr. Lucienne Abrahams: luciennesa@gmail.com

For technical questions regarding this collection, contact Nina Lewin, nina.lewin@wits.ac.za, who is the responsible librarian.

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Start date: 2010End date: 2019

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Now showing 1 - 10 of 161
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    Brief Overview: The State of Tech Hubs in South Africa
    (2017-08-31) Kedama, Yolisa; Abrahams, Lucienne
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    Editorial Note to AJIC Issue 13
    (2013-12-15) Abrahams, Lucienne; Ochara, Nixon
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    Editorial Note to AJIC Issue 15
    (LINK Centre, University of the Witwatersrand (Wits), 2015-12-15) Abrahams, Lucienne
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    Guest Editorial: Thematic Section: Informatics for Development
    (LINK Centre, University of the Witwatersrand (Wits), 2015-12-15) Pillay, Kiru
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    Guest Editorial: Thematic Section: Issues in Educational Informatics: Renewing our Human Resources for the Digital Economy
    (LINK Centre, University of the Witwatersrand (Wits), 2015-12-15) Cohen, Jason; Coleman, Emma
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    Briefing Note: People-Centered Internet Global Forum at Stanford: Beginning a Network of Networks
    (LINK Centre, University of the Witwatersrand (Wits), 2015-12-15) Abrahams, Lucienne; Hanna, Nagy
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    AJIC Issue 24, 2019 - Full Issue
    (LINK Centre, University of the Witwatersrand (Wits), Johannesburg, 2019-12-06)
    Issue 24 of The African Journal of Information and Communication (AJIC), published 6 December 2019.
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    AJIC Issue 24, 2019 - Full Issue - print-on-demand version
    (LINK Centre, University of the Witwatersrand (Wits), Johannesburg, 2019-12-06)
    Issue 24 of The African Journal of Information and Communication (AJIC), published 6 December 2019.
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    Assessing the Social Media Maturity of a Community Radio Station: The Case of Rhodes Music Radio in South Africa
    (LINK Centre, University of the Witwatersrand (Wits), Johannesburg, 2019-12-06) Gavaza, Mudiwa A.; Pearse, Noel J.
    Social media has become a major factor within the operations and functions of radio stations. This study used a social media maturity model (SMMM), developed from available literature, to assess the social media maturity of a South Africa community radio station, Rhodes Music Radio (RMR). The study found that RMR had a level 3 rating on a 5-level maturity scale, indicating that it was quite, but not yet fully, mature in its social media use. In addition to outlining the research and its findings, this article makes recommendations for how the station could increase the maturity of its social media use.
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    Intelligent Malware Detection Using a Neural Network Ensemble Based on a Hybrid Search Mechanism
    (LINK Centre, University of the Witwatersrand (Wits), Johannesburg, 2019-12-06) Akandwanaho, Stephen M.; Kooblal, Muni
    Malware threats have become increasingly dynamic and complex, and, accordingly, artificial intelligence techniques have become the focal point for cybersecurity, as they are viewed as being more suited to tackling modern malware incidents. Specifically, neural networks, with their strong generalisation performance capability, are able to address a wide range of cyber threats. This article outlines the development and testing of a neural network ensemble approach to malware detection, based on a hybrid search mechanism. In this mechanism, the optimising of individual networks is done by an adaptive memetic algorithm with tabu search, which is also used to improve hidden neurons and weights of neural networks. The adaptive memetic algorithm combines global and local search optimisation techniques in order to overcome premature convergence and obtain an optimal search outcome. The results from the testing prove that the proposed method is strongly adaptive and efficient in its detection of a range of malware threats, and that it generates better results than other existing methods.