Rangahau Aranga: AUT Graduate Review
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Learning about the awa: My reflective journey of admission into a doctoral programme at Auckland University of Technology
Get PDFSupporting new Māori doctoral students on their academic journey as they begin requires them to adapt quickly and steadily to the universities structures and systems. Contemplating and thinking to take on doctoral studies entails a huge mind shift from worker to student, and also has to be taking onboard with your whānau (extended family) and the greater hapori (community). To successfully navigate the awa (river) involves meeting minimum entry requirements of a doctoral programme and then submitting a PGR2 proposal on a topic which you will be acquainted with. This paper aims to explore the awa, a metaphorical analogy of navigating and engaging in higher education as a mature student[1] based on their lived experiences as a Māori doctoral student when entering into a doctoral programme at Auckland University of Technology (AUT) and the details of their keys to success, and preparation needed to successfully complete the PGR2 pathway.
[1] Mature students can be considered to have careers, family commitments, significant life experiences, and are likely to hold down long-term debt like a mortgage (Howard & Davies, 2013). They tend to be over the age of 25 years old (Boston, 2017)
The influence of chronotropic incompetence on maximum aerobic capacity and heart rate responses during boxing in Parkinson’s disease
Get PDFNon-contact boxing (NCB) is a popular form of high-intensity interval training used to improve aerobic capacity (VO2peak) which may be reduced in people with Parkinson’s disease (PD). However, heart rate (HR) responses are likely to vary in this population due to chronotropic incompetence (CI), described as the inability to raise HR to at least 85% of predicted maximum HR (HRmax), and is present in 40-50% of the PD population. In this presentation, I describe the impact of CI on VO2peak and HR responses during NCB. 25 people with PD and 16 age-matched controls underwent a cardiopulmonary exercise test (CPET) to identify the presence of CI and to determine VO2peak, HRmax, and %HRmax. Two boxing sessions then were performed on different days, during which HR response was measured via Polar H10 and further expressed as %HRmax predicted (220-age), and %HRmax obtained during CPET. Results from this study show that CI was present in 11 participants with PD (PDCI), with peak HR on average 30 beats lower than those without CI (PDnonCI). There was also a trend for lower VO2peak in the PDCI group and a significantly lower HR during each boxing round (p≤0.001). However, data from CPET shows that all groups were able to exercise in the high-intensity training zone. This study is the first to show that people with PD have the capacity to exercise in a high-intensity zone during NCB despite the presence of CI, which is encouraging. The results also show that %HRmax based on predicted equations do not accurately reflect exercise intensity, especially for people with CI. They should therefore be used with caution as a basis for high-intensity training regimes
Unearthing my toki: The artist who found an adze
Get PDFI had a dream once where I was walking along a beach or river. I often saw a taonga (treasure) as toki (adze) submerged between the sand and the water flow. I remember not wanting to acknowledge that the toki was there and I would pretend I didn’t see it. Coincidently in my waking life, I was drawn to the art of Māori carving, I took up a journey of reconnection and rediscovery through toi whakairo (the art of carving). During my whakairo journey, between 2010 to 2018 I discovered research gaps in knowledge, specifically about wahine Māori carving and examples. My research enquiry investigates the experiences and perspectives of wahine kaiwhakairo (women carver) from a distinctive Ngāti Awa mana takatāpui position. The study contemplates the role of wahine in whakairo from a Māori worldview and the impacts of colonisation on contemporary Māori women carvers. This presentation is drawn from a Kaupapa Māori and practice-led Doctoral inquiry, activated through a pūrākau methodology. Pouwhare (2020) describes how a pūrākau methodology can synchronise a way of being Māori and artistic practice that enables a process of working from a distinctive ontological and epistemological position that recognises the role of the seen and unseen. This poster presentation will discuss the pūrākau methodology used to capture the narratives of what it means to be a distinctive Māori carver. Traditional gender roles and fluidity will be considered with references to takatāpui (an umbrella term for Māori diverse gender identities) and traditional Māori narratives. There will be a discussion on the creative research methods used to explore notions of gender fluidity within the practice of carving and the art form itself
Automating inspection of moveable lane barrier for Auckland Harbour Bridge traffic safety
Get PDFA moveable lane barrier along the Auckland Harbour Bridge (AHB) enables two-way traffic flow optimisation and control. However, the AHB barrier transfer machines are not equipped with an automated solution for screening the pins that link the barrier segments. If the connecting metal pin pops out due to external force, the disjoined concrete barrier can be hazardous to motorist safety.After being restricted due to pandemic lockdowns, I reviewed previous research in anomaly detection to overcome the challenge of a small and unbalanced dataset. A technique was needed for a robust approach to data analysis and modelling on initially small and unbalanced datasets for similar circumstances where the expected dataset size may or may not become available within the expected timeframes. My research introduced a collectively synthetic minority-class data boosting, adaptive, incremental, and transfer learning method that utilises pre-trained neural networks. A novel technique for obtaining synthetic frames with different degrees of unsafe pin images cloned from the original video frames allowed a robust data analysis and modelling approach on small and unbalanced datasets. A universal system is produced for automated inspection that can ease the day-to-day work stress of the AHB safety inspectors. This system can be applied globally with minimum modifications to similar traffic management or anomaly detection and tracking scenarios.This presentation aims to introduce the proposed proof of concept (PoC) for supplementing movable lane barrier inspection. The produced PoC can be deployed on a vehicle or AHB barrier transfer machine to detect the unsafe pin and alert the user
Soil CO2 emission doubles depending on soil type in New Zealand dairy grassland
Get PDFSoil respiration (Rs), the second-largest carbon flux, is the CO2 released from plant roots and soil microbes. Soil respiration influences terrestrial carbon storage and cycling (i.e., how much carbon is released/stored), thus affecting atmospheric CO2 concentration and global climate (Xu & Shang, 2016). In situ Rs measurements in the southern hemisphere are underrepresented, especially regarding the interaction between soil type and environmental factors on Rs in dairy grassland (Bond-Lamberty & Thomson, 2010). The main objective of my research is to investigate Rs on common soil types (i.e., Ultic, Organic/Gley, Pumice and Pallic) in dairy grassland under varying environmental factors (e.g., soil temperature and moisture). The study also considers seasonal trends across four sites in Aotearoa New Zealand. Soil respiration is measured by the closed static chamber technique (Pumpanen et al., 2004). The chamber is equipped with a CO2 probe and a temperature/humidity probe. Surface vegetation was removed, and polyethylene collars were inserted into soil 24 hours prior to the first measurement. The chamber was then placed on the collars for the period of the measurement (c. 5 min). A generalised additive model approach was used to model Rs according to seasonality, soil type, and environmental factors. In this poster presentation, I aim to (1) summarise global and New Zealand Rs estimations, (2) evaluate the rate of Rs in New Zealand dairy grassland with four regionally representative soil types, and (3) investigate the effects of soil characteristics and environmental variables on Rs
A forecasting tool for predicting asthma related emergency department visits and hospitalizations using heterogeneous data sources
Get PDFNew Zealand (NZ) is one of the countries with the highest prevalence and mortality rate due to asthma. Organisation for Economic Co-operation and Development (OECD) statistics [3] indicate NZ has one of the highest hospital admission rates for asthma of OECD countries. According to recent records [1], on average 77 New Zealanders each year lost their battle to asthma. Furthermore, the cost burden of asthma to the NZ economy has not improved over the years [2]. Not much work has been accomplished in the direction of population health forecasting for asthma in NZ. The aim of this study is to develop a prediction model for anticipating asthma-related hospitalisations in Auckland, NZ while exploiting diverse heterogeneous data sources. These sources accounts for triggers that exacerbate asthma conditions like meteorological and air quality factors plus the social media resource accessed through Google search trends. The research work is divided into two parts; in the first phase I analysed the relationship between trigger parameters and asthma using the Pearson Correlation Coefficient. Subsequently, in part two a comparative examination has been conducted based upon the prediction models developed using different machine learning techniques on the continuous data of 1097 days. The experimental evaluation shows that the best forecasting tool could predict asthma-related hospitalisation with an accuracy of 78.87% while the precision and recall for the model were 79.80% and 78.87%. The outcome achieved from implementing such a model would be beneficial for public health surveillance, thereby helping in more efficient and timely healthcare resource deployment. 
Ata hāpara
Get PDFThe other day I was driving through the northern part of Rohe Pōtae o Maniapoto (the King Country). I grew up on a farm on the edge of Aohena. It is a beautiful place if you like the bush. I had left home in the dark, just as dawn was touching the sky. At that time of day, demarcations of time are very subtle, and I was reminded of one of my nannies who would greet the beauty of such a thing with a whisper:
Ki te whei ao (To the glimmer of dawn)Ki te ao mārama (To the bright light of day)Tihei mauri ora! (There is life!
Modelling and prediction of NZ's population wellbeing using machine learning techniques.
Get PDFThe importance of population wellbeing is gaining traction and acknowledgment across the globe. In 2019, the government administered NZ’s first ever ‘wellbeing budget’ after recognising that although NZ had strong economic growth, there were high rates of child poverty, homelessness, and suicide. In NZ, detailed wellbeing measures are available from the General Social Survey (GSS), a biennial survey of approximately 10,000 individuals. Although the GSS sample is considered representative of the NZ population, a major limitation is that the survey sample is not representative of certain groups of the population that may be of high policy interest. For example, the wellbeing of social housing tenants is a key area of government focus, but the number of social housing tenants represented in the GSS survey is sparse. Therefore, it is impractical to explore what/how government policies are associated with wellbeing in these smaller subsets of the population. To overcome this challenge, population-level wellbeing data is required. The government’s push for cross-agency data integration over the last several decades led to the development of the Integrated Data Infrastructure (IDI). The IDI is a complex population-level government research database containing anonymised individual response data (microdata) relating to people and households that can be linked longitudinally over time. Extrapolating wellbeing data to the full NZ population may be possible by applying advanced modelling techniques on the IDI data. In this study, I propose to use machine learning algorithms (such as random forests, neural networks) to model and predict various GSS-based wellbeing outcomes for the full NZ population. If successful, the outcome of this study (a population-level measure of wellbeing) would enable researchers to easily incorporate wellbeing measures into IDI-based policy analysis. Ultimately, it would improve our understanding of how the political, social, and economic environment influences the wellbeing and functioning of New Zealanders
Relevance of supplementary fair value disclosures under market uncertainty: Effects on audit fees and investors’ pricing
Get PDFFair value (FV) means the market value of an asset, which can be observed directly (Level 1), or indirectly (Level 2). In some cases, the FVs are not observable in the market and managers of companies estimate the valuation internally using statistical models based on the best information available. These are known as Level 3 FV. The measurement uncertainty is the highest for Level 3 FVs as they rely on managerial discretion, creating concerns about their representational faithfulness and relevance among auditors and investors. This concern is likely to be heightened in the wake of market uncertainty during 2020 caused by the COVID pandemic. Regulators (e.g., ASIC) suggested that disclosing supplementary information (i.e., beyond the minimum required by regulation) on FV can help mitigate such concerns. In this study, I examine the relevance of supplementary disclosures intended to improve the representational faithfulness and relevance of Level 3 FV by investigating their impacts on audit fees and investors’ valuation in the uncertain market condition of 2020. My sample comprises Level 3 investment properties held by Australian real estate companies. I find that managers of real estate companies increased supplementary FV disclosures during 2020. I document a negative association between supplementary disclosures and audit fees, implying that disclosures reduce the audit risk effect by signalling higher transparency. However, I find no incremental impact of disclosures on audit fees during the pandemic. Additionally, I find that investors’ pricing of FV increased with the increase in disclosures during the market uncertainty of 2020, while in the pre-uncertainty period, their pricing influence was not significant. The findings of this study inform regulators and other financial reporting stakeholders about the role of supplementary FV disclosures in mitigating the perceived audit risk for auditors and the faithful representation concerns for investors in a distressed market environment
Simulated satiation: A scale measure of satiation in reality-enhancing technologies
Get PDFSatiation occurs when consumers no longer enjoy an experience, and it can be experienced physiologically as a bodily response, as well as in cognition and affect (Redden, 2015; Galak & Redden, 2018). Satiation prominently influences consumers’ behaviours, reducing consumption desires and increasing product/service replacement and disposal. This creates a critical challenge for marketers. Research pertaining to how satiation occurs and influences the customer journey and consumer decision making process within the context of virtual reality technology is embryonic and requires investigation. The purpose of this research is to examine the impact of satiation on consumer decision making on primarily virtual reality, but also augmented and mixed reality applications (VR, AR, and MR). Various factors in VR and AR platforms can influence consumers’ decisions and perceptions, such as latency-rendering issues that delay feedback, discrepancy, and simply knowing that the experience is just a simulation. Such factors cannot be experienced in real-life settings; therefore, this study will explore satiation via reality-enhancing technology perspective and aims to create a “simulated satiation” scale. I define simulated satiation as any attenuation in perceived benefits that occurs within or results from vicarious and simulated intermediary sources. To create a “simulated satiation” scale, this research will employ four phases: item generation and content validity, scale purification and confirming the scale structure, testing convergent and divergent validities of the scale, and designing a predictive validity study to show how the scale can aid research. Following this, in this presentation, I will illustrate how to create the “simulated satiation” scale and its potential impact on the marketing world