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.
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Interpretable deep learning for surgical tool management
(Springer, 2021)This paper presents a novel convolutional neural network framework for multi-level classification of surgical tools. Our classifications are obtained from multiple levels of the model, and high accuracy is obtained by ... -
Studying and exploiting the relationship between model accuracy and explanation quality
(Springer, 2021)Many explanation methods have been proposed to reveal insights about the internal procedures of black-box models like deep neural networks. Although these methods are able to generate explanations for individual predictions, ... -
AI augmented approach to identify shared ideas from large format public consultation
(MDPI AG, 2021)Public data, contributed by citizens, stakeholders and other potentially affected parties, are becoming increasingly used to collect the shared ideas of a wider community. Having collected large quantities of text data ... -
Barriers to diabetes self-management in a subset of New Zealand adults with Type 2 diabetes and poor glycaemic control
(Hindawi Ltd, 2021)Background. Despite the fact that there is an increasingly effective armoury of medications to treat diabetes, many people continue to have substantially elevated blood glucose levels. The purpose of this study was to ... -
Convergence of public participation, participatory design and NLP to co-develop circular economy
(Springer Science and Business Media LLC, 2021)The concept of a circular economy is at a crossroads. To date, it has been largely driven by top-down national or trans-national legislation such as EU Circular Economy Package or Chinese Circular Economy Promotion. Bottom-up ... -
Deep learning in diabetic foot ulcers detection: A comprehensive evaluation
(Elsevier BV, 2021)There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art ... -
River: Machine learning for streaming data in Python
(2021)River is a machine learning library for dynamic data streams and continual learning. It provides multiple state-of-the-art learning methods, data generators/transformers, performance metrics and evaluators for different ... -
Using task models to understand the intersection of numeracy skills and technical competence with medical device design
(Oxford University Press, 2021)Task models are used in many different ways throughout the design and development of interactive systems. When the interactive systems are safety critical, task models can play an important role in ensuring system behaviours ... -
Virtual bioprocess simulation laboratory for teaching and learning
(Ako Aotearoa, 2018)There is great potential in applying virtual technology to support teaching and learning. A 3D virtual bioprocess simulation will enable users to learn about both basics of laboratory safety and fermentation principles. ... -
Divergent stutter bisimulation abstraction for controller synthesis with linear temporal logic specifications
(Elsevier BV, 2021)This paper proposes a method to synthesise controllers for systems with possibly infinite number of states that satisfy a specification given as an LTL\◦ formula. A common approach to handle this problem is to first compute ... -
Adversarial risk analysis for first-price sealed-bid auctions.
(Wiley, 2021)Adversarial risk analysis (ARA) is an upcoming methodology that is considered to haveadvantages over the traditional decision-theoretic and game-theoretic approaches. ARAsolutions for first-price sealed-bid (FPSB) auctions ... -
Cylindrical spikes
(IOP Publishing LTD, 2021)The Geroch/Stephani transformation is a solution-generating transformation, and may generate spiky solutions. The spikes in solutions generated so far are either early-time permanent spikes or transient spikes. We want to ... -
FilmGrain
(2019)Films are an integral part of our cultural zeitgeist, as time goes on, they have become more than entertainment, they have become a mirror that we point at ourselves in order to explore issues and our position in the world. ... -
Dynamic property enforcement in programmable data planes
(2021)Network programmers can currently deploy an arbitrary set of protocols in forwarding devices through data plane programming languages such as P4. However, as any other type of software, P4 programs are subject to bugs and ... -
Slowdown and heating of interstellar neutral helium by elastic collisions beyond the heliopause
(IOP Publishing, 2021)Direct sampling of interstellar neutral (ISN) atoms close to the Sun enables studies of the very local interstellar medium (VLISM) around the heliosphere. The primary population of ISN helium atoms has, until now, been ... -
Concrete ephemeriality
(2020)Concrete ephemerality is a project designed to capture something that was once transitory and seeks to create something concrete from it. With ever more tracking and aggregation of our digital lives, online identities that ... -
A note on families over a p-adic disk, circa 2012
(2012)The following notes discuss how the local conditions H¹ₑ and H¹𝓰 of Bloch-Kato vary in an analytic family, culminating in the proof of a control theorem (Theorem 1.1). -
On ensemble techniques for data stream regression
(IEEE, 2020)An ensemble of learners tends to exceed the predictive performance of individual learners. This approach has been explored for both batch and online learning. Ensembles methods applied to data stream classification were ... -
Towards embedding data provenance in files
(IEEE, 2021)Data provenance (keeping track of who did what, where, when and how) boasts of various attractive use cases for distributed systems, such as intrusion detection, forensic analysis and secure information dependability. This ... -
CS-ARF: Compressed adaptive random forests for evolving data stream classification
(IEEE, 2020)Ensemble-based methods are one of the most often used methods in the classification task that have been adapted to the stream setting because of their high learning performance achievement. For instance, Adaptive Random ...
