2015 Working Papers

Recent Submissions

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    Classification and regression algorithms for WEKA implemented in Python
    (Working Paper, University of Waikato, Department of Computer Science, 2015-10) Beckham, Christopher J.
    WEKA is a popular machine learning workbench written in Java that allows users to easily classify, process, and explore data. There are many ways WEKA can be used: through the WEKA Explorer, users can visualise data, train classifiers and examine performance metrics; in the WEKA Experimenter, datasets and algorithms can be compared in an automated fashion; or, it can simply be invoked on the command-line or used as an external library in a Java project.
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    Investigating the use of activity trackers to observe high-risk work environments
    (Working Paper, Department of Computer Science, The University of Waikato, 2015) Bowen, Judy; Hinze, Annika; Cunningham, Sally Jo; Parker, Richard
    The New Zealand forestry industry has the country's highest rate of workplace fatalities. The reasons are not well studied or understood and no large-scale systematic physical and physiological data has been recorded to investigate this. Current research focusses on developing mechanised solutions and changing worker behaviour. We believe the first step in identifying any successful solution is to develop a fine-grained understanding of the physical context of forestry work by performing large-scale data collection of the levels of physical activity the workers engage in as well as their sleep patterns over extended periods of time. Our goal is to use lightweight, wearable technology (so-called activity trackers) to collect this data. In order to do so we need a clear understanding of the capabilities and limitations of such devices, both in general and in the proposed use environment for forestry workers. In this paper we present the results of user studies and comparisons of six activity trackers and three mobile phone applications used to track activity and sleep. We also discuss our initial pilot study with forestry workers and discuss the problems encountered using the trackers in the environment.