Computing and Mathematical Sciences: Recently added

Now showing items 21-40 of 1624

  • Māori loanwords: a corpus of New Zealand English tweets

    Trye, David; Calude, Andreea S.; Bravo-Marquez, Felipe; Keegan, Te Taka Adrian Gregory (2019)
    Māori loanwords are widely used in New Zealand English for various social functions by New Zealanders within and outside of the Māori community. Motivated by the lack of linguistic resources for studying how Māori loanwords ...
  • Effectiveness of entropy-based features in high-and low-intensity DDoS attacks detection

    Koay, Abigail; Welch, Ian; Seah, Winston K.G. (Springer, 2019)
    DDoS attack detection using entropy-based features in network traffic has become a popular approach among researchers in the last five years. The use of traffic distribution features constructed using entropy measures has ...
  • Security visualization intelligence model for law enforcement investigations

    Garae, Jeffery; Ko, Ryan K.L.; Apperley, Mark; Schlickmann, Silvino J. (2018)
    Data analytic methods and techniques have proven crucial in aiding law enforcement investigations and day-to-day operations. However, the rise of cyber-attacks across transnational jurisdictions creates a challenge to share ...
  • Behaviour based ransomware detection

    Chew, Christopher J.W.; Kumar, Vimal (EasyChair, 2019)
    Ransomware is an ever-increasing threat in the world of cyber security targeting vulnerable users and companies, but what is lacking is an easier way to group, and devise practical and easy solutions which every day users ...
  • Identifying the interplay of design artifacts and decisions in practice: A Case Study

    Bowen, Judy; Dittmar, Anke (Springer, 2017)
    Interaction design is a complex and challenging process. It encompasses skills and knowledge from design in general as well as from HCI and software design in particular. In order to find better ways to support interaction ...
  • Investigating Wearable Technology for Fatigue Identification in the Workplace

    Griffiths, Christopher John Gilder; Bowen, Judy; Hinze, Annika (Springer, 2017)
    Fatigue has been identified as a significant contributor to workplace accident rates. However, risk minimisation is a process largely based on self-reporting methodologies, which are not suitable for fatigue identification ...
  • Using abstraction with interaction sequences for interactive system modelling

    Turner, Jessica Dawn; Bowen, Judy; Reeves, Steve (Springer, 2018)
    Interaction sequences can be used as an abstraction of an interactive system. We can use such models to consider or verify properties of a system for testing purposes. However, interaction sequences have the potential to ...
  • Investigating real-time monitoring of fatigue indicators of New Zealand forestry workers

    Bowen, Judy; Hinze, Annika; Griffiths, Christopher John Gilder (Elsevier, 2019)
    The New Zealand forestry industry has one of the highest fatality and injury rates of any industrial sector in the country. Worker fatigue has been identified as one of the main contributing factors. Currently no independent ...
  • Spiking Neural Networks and online learning: An overview and perspectives

    Lobo, Jesus L.; Del Ser, Javier; Bifet, Albert; Kasabov, Nikola (2020)
    Applications that generate huge amounts of data in the form of fast streams are becoming increasingly prevalent, being therefore necessary to learn in an online manner. These conditions usually impose memory and processing ...
  • Comparing classical criteria for selecting intra-class correlated features in Multimix

    Hunt, Lynette Anne; Basford, Kaye E. (Elsevier, 2016)
    The mixture approach to clustering requires the user to specify both the number of components to be fitted to the model and the form of the component distributions. In the Multimix class of models, the user also has to ...
  • The online performance estimation framework: heterogeneous ensemble learning for data streams

    van Rijn, Jan N.; Holmes, Geoffrey; Pfahringer, Bernhard; Vanschoren, Joaquin (Springer, 2018)
    Ensembles of classifiers are among the best performing classifiers available in many data mining applications, including the mining of data streams. Rather than training one classifier, multiple classifiers are trained, ...
  • Proof-of-learning: A blockchain consensus mechanism based on machine learning competitions

    Bravo-Marquez, Felipe; Reeves, Steve; Ugarte, Martin (IEEE, 2019)
    This article presents WekaCoin, a peer-to-peer cryptocurrency based on a new distributed consensus protocol called Proof-of-Learning. Proof-of-learning achieves distributed consensus by ranking machine learning systems for ...
  • On calibration of nested dichotomies

    Leathart, Tim; Frank, Eibe; Pfahringer, Bernhard; Holmes, Geoffrey (Springer, 2019)
    Nested dichotomies (NDs) are used as a method of transforming a multiclass classification problem into a series of binary problems. A tree structure is induced that recursively splits the set of classes into subsets, and ...
  • Maintaining SLOs of cloud-native applications via self-adaptive resource sharing

    Podolskiy, Vladimir; Mayo, Michael; Koay, Abigail; Gerndt, Michael; Patros, Panos (IEEE, 2019)
    With changing workloads, cloud service providers can leverage vertical container scaling (adding/removing resources) so that Service Level Objective (SLO) violations are minimized and spare resources are maximized. In this ...
  • The use of Māori words in National Science Challenge online discourse

    Calude, Andreea S.; Stevenson, Louise; Whaanga, Hēmi; Keegan, Te Taka Adrian Gregory (2018)
    This paper presents data relating to the use of Maori borrowings as they occur in a corpus of scientific discourse on the websites of the eleven National Science Challenges (NSCs) and their associated Twitter feeds.
  • Node.js scalability investigation in the cloud

    Zhu, Jiapeng; Patros, Panagiotis; Kent, Kenneth B.; Dawson, Michael (ACM, 2018)
    Node.js has gained popularity in cloud development due to its asynchronous, non-blocking and event-driven nature. However, scalability issues can limit the number of concurrent requests while achieving an acceptable level ...
  • Collecting sensitive personal data in a multi-cultural environment

    Hinze, Annika; Timpany, Claire; Bowen, Judy; Chang, Carole; Starkey, Nicola J.; Elder, Hinemoa (2018)
    Traumatic Brain Injury (TBI) has long-term effects on memory and cognitive functions. This paper discusses the challenges encountered and lessons learned from developing augmented memory aids for people with TBI. In ...
  • Using the HTRC Data Capsule Model to promote reuse and evolution of experimental analysis of digital library data: a case study of topic modeling

    Bainbridge, David; Nichols, David M.; Hinze, Annika; Downie, J. Stephen (IEEE, 2019)
    We report on a case-study to independently reproduce the work given in a publicly available blog on how to develop a topic model sourced from a collection of texts, where both the data set and source code used are readily ...
  • Cross-helically forced and decaying hydromagnetic turbulence

    Brandenburg, Axel; Oughton, Sean (WILEY-V C H VERLAG GMBH, 2018)
    We study the evolution of kinetic and magnetic energy spectra in magnetohydrodynamic flows in the presence of strong cross helicity. For forced turbulence, we find a weak inverse transfer of kinetic energy toward the ...
  • Research and development absorptive capacity: a Māori perspective

    Ruckstuhl, Katharina; Amoamo, Maria; Hart, Ngaire Hiria; Martin, William John; Keegan, Te Taka Adrian Gregory; Pollock, Richard (The Royal Society of New Zealand, 2019)
    This paper presents a view of research and development absorptive capacity from a Māori perspective. The assessment is part of a case study of a longitudinal programme – Science for Technological Innovation: Kia kotahi mai ...