Computing and Mathematical Sciences Papers
This collection houses research from the Faculty of Computing and Mathematical Sciences at the University of Waikato.
All items in Research Commons are provided only to permit fair dealing for the purposes of research or private study. They are protected by copyright with all rights reserved unless otherwise indicated.
Recently Added
Subscribe (RSS 1.0)-
Transfer of pretrained model weights substantially improves semi-supervised image classification
(Springer, 2020)Deep neural networks produce state-of-the-art results when trained on a large number of labeled examples but tend to overfit when small amounts of labeled examples are used for training. Creating a large number of labeled ... -
A comparison of machine learning methods for cross-domain few-shot learning
(Springer, 2020)We present an empirical evaluation of machine learning algorithms in cross-domain few-shot learning based on a fixed pre-trained feature extractor. Experiments were performed in five target domains (CropDisease, EuroSAT, ... -
On the generation of compressible mirror-mode fluctuations in the inner heliosheath
(IOP Publishing Ltd, 2020)Measurements made with the Voyager 1 spacecraft indicate that significant levels of compressive fluctuations exist in the inner heliosheath. Some studies have already been performed with respect to the mirror-mode instability ... -
Radiographic features associated with increased surgical invasiveness in pyogenic vertebral column osteomyelitis
(SAGE Publications, 2020)Study Design: Single center retrospective cohort study. Objectives: Assess the association between well-known radiographic features for spinal instability from the Spinal Instability in Neoplasia Score (SINS) and ... -
Adaptive XGBoost for evolving data streams
(IEEE, 2020)Boosting is an ensemble method that combines base models in a sequential manner to achieve high predictive accuracy. A popular learning algorithm based on this ensemble method is eXtreme Gradient Boosting (XGB). We present ... -
Performance measures for evolving predictions under delayed labelling classification
(IEEE, 2020)For many streaming classification tasks, the ground truth labels become available with a non-negligible latency. Given this delayed labelling setting, after the instance data arrives and before its true label is known, the ... -
Personas revisited: Extending the use of personas to enhance participatory design
(ACM, 2020)Personas are a well-established tool in interactive system development, largely used with designers and developers. They can also be included in work with potential and actual users, particularly in eliciting user needs ... -
Insights into WebAssembly: Compilation performance and shared code caching in node.js
(ACM, 2020)Alongside JavaScript, V8 and Node.js have become essential components of contemporary web and cloud applications. With the addition of WebAssembly to the web, developers finally have a fast platform for performance-critical ... -
The weakest link: Revealing and modeling the architectural patterns of microservice applications
(ACM, 2020)Cloud microservice applications comprise interconnected services packed into containers. Such applications generate complex communication patterns among their microservices. Studying such patterns can support assuring ... -
Swipe, scroll, add-to-cart: a case study of e-commerce gallery designs for small screen devices
(Design Research Society, 2020)With significant increase in mobile online shopping the design of user experiences that promote purchaser decisions and increase sales is highly desirable to retailers and their marketing and digital production companies. ... -
Urban narrative: Computational linguistic interpretation of large format public participation for urban infrastructure
(Cogitatio, 2020)Urban Narrative works at the interface between public participation and participatory design to support collaboration processes for urban planning and design. It applies computational linguistics to interpret large format ... -
Structure from randomness in halfspace learning with the zero-one loss
(AI Access Foundation, 2020)We prove risk bounds for halfspace learning when the data dimensionality is allowed to be larger than the sample size, using a notion of compressibility by random projection. In particular, we give upper bounds for the ... -
Enhancing interactivity: how has design exploration of physically and intellectually interactive picturebooks enhanced shared reading?
(Design Research Society, 2020)Children’s book design can have a significant impact on shared reading practices, interaction, and engagement. We hypothesise that books designed with the intention to specifically enhance the author’s story through ... -
The HfG Ulm and Sustainable Design: a comparative analysis
(2020)This article presents a comparative analysis between ideas of the HfG Ulm and the contemporary understanding of Sustainable Design. The Ulmer institution, through an innovative curriculum, an articulated discourse and a ... -
Interactive system testing using interaction sequences
(ACM Press, 2018)Interaction sequences (ISeqs) are an abstraction of interactive systems which allow us to inspect the interactive system behaviour. In this research, ISeqs are used to support interactive system testing. In interactive ... -
A diversity-aware model for majority vote ensemble accuracy
(Addison-Wesley, 2020)Ensemble classifiers are a successful and popular approach for classification, and are frequently found to have better generalization performance than single models in practice. Although it is widely recognized that ... -
From music ontology towards ethno-music-ontology
(2020)This paper presents exploratory work investigating the suitability of the Music Ontology [33] - the most widely used formal specification of the music domain - for modelling non-Western musical traditions. Four contrasting ... -
A perturbative approach to a nonlinear advection-diffusion equation of particle transport
(AIP Publishing, 2020)We explore analytical techniques for modeling the nonlinear cosmic ray transport in various astrophysical environments which is of significant current research interest. While nonlinearity is most often described by coupled ... -
Neural multi-class classification approach to blood glucose level forecasting with prediction uncertainty visualisation
(CEUR Workshop Proceedings, 2020)A machine learning-based method for blood glucose level prediction thirty and sixty minutes in advance based on highly multiclass classification (as opposed to the more traditional regression approach) is proposed. An ... -
In silico comparison of continuous glucose monitor failure mode strategies for an artificial pancreas
(CEUR Workshop Proceedings, 2020)An artificial pancreas is a medical Internet of Thingsbased system consisting of a continuous glucose monitor, an insulin pump, and a micro-controller. The use of artificial pancreas systems is becoming increasingly popular ...
