Towards fast converging lattice sums : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Physics at Massey University, Albany, New Zealand

Thesis will be uploaded upon the expiry of the journal embargo on Chapter 10 in May 2023.In the field of solid state physics there are many open questions surrounding the best configuration of packing spheres to calculating binding energies to J/mol accuracy. Many of these problems have attracted attention from individuals in many faculties from mathematics, physics and chemistry over the course of the last four centuries. A significant amount of work has been done modernizing interaction potentials from the early twentieth century by the use of modern computers and quantum chemical software programs extending versions of the most common two-body potential. The historical survey of the methods leading up until the late nineteen eighties serves as the basis for where we step off for much of the analytic techniques for evaluating lattice sums and their use in answering these open questions. Investigations in to the stability of certain packing configurations compared to others in the solid state can be made with the use of fast techniques to evaluate the properties of such systems, many of which are developed here and used throughout the work in the various projects seen below. The aim of this work is to show that the evaluation of lattice constants and the formulae to calculate them can be given in a concise and efficient form with the use of mathematical and numerical methods. Analytical expressions can be found that are given in terms of real exponents and these expressions can be evaluated to arbitrary precision within a satisfactory amount of computer time. In contrast to the infinite structure that forms the lattice in the physical world, the techniques to calculate its sum have evolved from an infinite direct summation to methods that treat the sum associated with the quadratic form of the lattice re-expressing it as a sum of simple functions using number theoretic techniques and treating sums in terms of fast converging series or sums of hyperbolic functions. The results of this investigation are multiple new formulae for the cubic lattice systems, including expressions for the simple cubic lattice and famous Madelung constant in N--dimensions. A new expression was found for the hexagonal close packed structure that is computationally elegant and allowed the examination of the behaviour of the two-body Lennard--Jones potential in terms of the lattice parameters. A single parameter sum was found for the simple cubic system that was used to investigate the effect of pressure on body centered cubic system compared to the face centered cubic system

Small stories, small acts in sites of struggle: the establishmentof Māori wards in Taranaki

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Static Hand Gesture Recognition Using Capacitive Sensing and Machine Learning

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A kānuka silvopastoral system in New Zealand hill country : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Soil Science at Massey University, Manawatū, New Zealand

Thesis will be uploaded upon the expiry of the journal embargo on Chapter 5 in March 2024.Soil erosion, water quality issues, low production and climate change are some of the current challenges facing land managers and farmers in New Zealand hill country. ‘Tree-pasture’ silvopastoral systems that build soil resources could be integral land management practices for mitigating these issues and improving the health and production of these systems. Silvopastoral trees are already planted in New Zealand, although primarily used as soil conservation trees. Nevertheless, there are many other potentially facilitative effects of silvopastoral systems on other under researched silvopastoral outcomes. Researching these is vital for realising the full potential of silvopastoralism in New Zealand. The native genus kānuka (Kunzea spp.) in New Zealand has the potential to form intergenerational and multifunctional silvopastoral systems that build soil resources and positively impact pasture production. This is because of the genus’s potentially advantageous bio-physical tree attributes, such as its longevity, potentially reduced competition for soil water and nutrients compared to faster-growing and more resource intensive trees typically planted in hill country, and evergreen nature, potentially influencing livestock behaviour and soil organic matter return to the soil. Despite being locally very common in New Zealand hill country, this study is the first to measure the influence of kānuka silvopastoral trees on the pastoral environment at field scale. The study begins by presenting a novel framework that links bio-physical tree attributes to a wide range of silvopastoral outcomes. Poplar (Populus spp.), the most commonly planted soil conservation tree in New Zealand hill country, and kānuka, are then reviewed as silvopastoral trees within this framework. This process clearly conveyed the complexity of silvopastoral systems and highlights that there may be potential for kānuka to positively impact many silvopastoral outcomes such as longevity, pasture production, livestock welfare, biodiversity conservation and carbon sequestration. The study then investigated the impact of kānuka on pasture production and pasture stability, soil condition and surface runoff and sediment and nutrient losses within a kānuka silvopastoral system. At two sites over two years, there was on average 107.9% more pasture production under kānuka trees compared to open pasture. This pasture production increase was associated with significantly greater Olsen-phosphorus, potassium and porosity. Soil moisture was similar between kānuka pasture and open pasture positions. The improvements to the agricultural environment were hypothesised to be because of livestock excreta deposition under the trees in the sheltered tree environment and tree litterfall. The increased pasture production under the trees was the result of trees facilitating the growth of a few dominant and competitor pasture functional groups via the mass ratio effect such as perennial ryegrass (Lolium perenne), cocksfoot (Dactylis glomerata), soft brome (Bromus hordeaceus) and barley grass (Critesion murinum). Moreover, despite reduced species richness and functional richness in kānuka pasture, there was evidence that pasture stability was maintained under the trees because functional evenness and functional dispersion was statistically similar in kānuka pasture and open pasture, and the functional groups that grew had mixed (cocksfoot) or annual (soft brome and barley grass) survival strategies. This indicates that kānuka has the potential to increase pasture production sustainably by not negatively impacting the pasture’s response to stress. There was 53.8 mm annual surface runoff in kānuka pasture and 7.5 mm in open pasture, despite the improved soil conditions in kānuka pasture. Moreover, sediment and nutrient losses were 10–100 times greater in kānuka pasture. Sediment and nutrient losses were a function of surface runoff, and these differences were hypothesised to be because significantly less pasture biomass was present under the trees, decreasing surface runoff attenuation. The pasture biomass difference was likely because of livestock preferentially grazing the pasture under kānuka because of the sheltered environment and good condition pasture. This suggests that a choice between good condition pasture under trees and poor condition pasture away from trees can lead to negative impacts in terms of sediment and nutrient management under isolated silvopastoral trees. Overall, this study shows that tree configuration is a fundamental aspect in silvopastoral systems, and gives evidence that pasture biomass under silvopastoral trees is important for mitigating surface runoff and sediment and nutrient losses. The improved pasture production and pasture species composition under kānuka, in conjunction with the other potential environmental and cultural benefits of a kānuka silvopastoral system identified in the framework, shows that this genus may have potential to transform hill country landscapes by adding economic, environmental and cultural value to New Zealand farms. Nevertheless, because of the limitations of this study, such as the potential impact of site specific conditions and compounded livestock effects, more research is required to provide a full evaluation of the potential of kānuka silvopastoral systems in New Zealand hill country

Multi-source multimodal deep learning to improve situation awareness : an application of emergency traffic management : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Traditionally, disaster management has placed a great emphasis on institutional warning systems, and people have been treated as victims rather than active participants. However, with the evolution of communication technology, today, the general public significantly contributes towards performing disaster management tasks challenging traditional hierarchies in information distribution and acquisition. With mobile phones and Social Media (SM) platforms widely being used, people in disaster scenes act as non-technical sensors that provide contextual information in multiple modalities (e.g., text, image, audio and video) through these content-sharing applications. Research has shown that the general public has extensively used SM applications to report injuries or deaths, damage to infrastructure and utilities, caution, evacuation needs and missing or trapped people during disasters. Disaster responders significantly depend on data for their Situation Awareness (SA) or the dynamic understanding of “the big picture” in space and time for decision-making. However, despite the benefits, processing SM data for disaster response brings multiple challenges. Among them, the most significant challenge is that SM data contain rumours, fake information and false information. Thus, responding agencies have concerns regarding utilising SM for disaster response. Therefore, a high volume of important, real-time data that is very useful for disaster responders’ SA gets wasted. In addition to SM, many other data sources produce information during disasters, including CCTV monitoring, emergency call centres, and online news. The data from these sources come in multiple modalities such as text, images, video, audio and meta-data. To date, researchers have investigated how such data can be automatically processed for disaster response using machine learning and deep learning approaches using a single source/ single modality of data, and only a few have investigated the use of multiple sources and modalities. Furthermore, there is currently no real-time system designed and tested for real-world scenarios to improve responder SA while cross-validating and exploiting SM data. This doctoral project, written within a “PhD-thesis-withpublication” format, addresses this gap by investigating the use of SM data for disaster response while improving reliability through validating data from multiple sources in real-time. This doctoral research was guided by Design Science Research (DSR), which studies the creation of artefacts to solve practical problems of general interest. An artefact: a software prototype that integrates multisource multimodal data for disaster response was developed adopting a 5-stage design science method framework proposed by Johannesson et al. [175] as the roadmap for designing, developing and evaluating. First, the initial research problem was clearly stated, positioned, and root causes were identified. During this stage, the problem area was narrowed down to Emergency traffic management instead of all disaster types. This was done considering the real-time nature and data availability for the artefact’s design, development and evaluation. Second, the requirements for developing the software artefacts were captured using the interviewing technique. Interviews were conducted with stakeholders from a number of disaster and emergency management and transport and traffic agencies in New Zealand. Moreover, domain knowledge and experimental information were captured by analysing academic literature. Third, the artefact was designed and developed. The fourth and final step was focused on the demonstration and evaluation of the artefact. The outcomes of this doctoral research underpin the potential for using validated SM data to enhance the responder’s SA. Furthermore, the research explored appropriate ways to fuse text, visual and voice data in real-time, to provide a comprehensive picture for disaster responders. The achievement of data integration was made through multiple components. First, methodologies and algorithms were developed to estimate traffic flow from CCTV images and CCTV footage by counting vehicle objects. These outcomes extend the previous work by annotating a large New Zealand-based vehicle dataset for object detection and developing an algorithm for vehicle counting by vehicle class and movement direction. Second, a novel deep learning architecture is proposed for making short-term traffic flow predictions using weather data. Previous research has mostly used only traffic data for traffic flow prediction. This research goes beyond previous work by including the correlation between traffic flow and weather conditions. Third, an event extraction system is proposed to extract event templates from online news and SM text data, answering What (semantic), Where (spatial) and When (temporal) questions. Therefore, this doctoral project provides several contributions to the body of knowledge for deep learning and disaster research. In addition, an important practical outcome of this research is an extensible event extraction system for any disaster capable of generating event templates by integrating text and visual formats from online news and SM data that could assist disaster responders’ SA

Employee empowerment and HR flexibility in Information Technology SMEs

CAUL read and publish agreement 2023HR systems in IT organizations need to be flexible to enable them to adjust to the fast rate of technological change. Employee empowerment, often practiced at IT organizations under the banner of agile practices, has been highlighted as likely to enable HR flexibility. Based on a research panel based survey of top managers at 163 IT organizations in New Zealand and Australia, we confirmed positive effects of employee empowerment on four dimensions of HR flexibility: resource flexibility in employee skills and behaviors, coordination flexibility in employee skills and behaviors, resource flexibility in HR practices, and coordination flexibility in HR practices. The results are consistent with the view that, at IT organizations, employee empowerment both promotes employee ability and willingness to be flexible and facilitates the organizational structures and practices that enable flexible use of HR resources.fals

Hate Speech Patterns in Social Media: A Methodological Framework and Fat Stigma Investigation Incorporating Sentiment Analysis, Topic Modelling and Discourse Analysis

© 2023 The Author/sSocial media offers users an online platform to freely express themselves; however, when users post opinionated and offensive comments that target certain individuals or communities, this could instigate animosity towards them. Widespread condemnation of obesity (fatness) has led to much fat stigmatizing content being posted online. A methodological framework that uses a novel mixed-method approach for unearthing hate speech patterns from large text-based corpora gathered from social media is proposed. We explain the use of computer-mediated quantitative methods comprising natural language processing techniques such as sentiment analysis, emotion analysis and topic modelling, along with qualitative discourse analysis. Next, we have applied the framework to a corpus of texts on gendered and weight-based data that have been extracted from Twitter and Reddit. This assisted in the detection of different emotions being expressed, the composition of word frequency patterns and the broader fat-based themes underpinning the hateful content posted online. The framework has provided a synthesis of quantitative and qualitative methods that draw on social science and data mining techniques to build real-world knowledge in hate speech detection. Current information systems research is limited in its use of mixed analytic approaches for studying hate speech in social media. Our study therefore contributes to future research by establishing a roadmap for conducting mixed-method analyses for better comprehension and understanding of hate speech patterns.fals

‘Listening closely’ to mediated intimacies and podcast intimacies in Song Exploder

CAUL Read and Publish 2023Intimacy is an important and growing concept in both media studies and podcast studies. But research regarding intimacies in both disciplines has yet to fully account for the connection between sound and normativity, which is essential to podcasting and important to mediated intimacies more broadly. In this article, we mobilise scholarship from these two fields to analyse the award-winning music podcast Song Exploder. Our study highlights that attending to intimacies in podcasting involves both analysing how the story structure aligns with social norms and listening critically to the ways the sound design and audio editing complements and complicates these intimate stories. We contend that identifying the intersection of sound and normativity in this podcast contributes to understanding the cultural work of podcasting and underscores the key role of sound in mediated intimacies.Publishe

Tension and Paradox in Women-Oriented Sustainable Hybrid Organizations: A Duality of Ethics

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Co-Selection of Bacterial Metal and Antibiotic Resistance in Soil Laboratory Microcosms.

Copyright: © 2023 by the authors.Accumulation of heavy metals (HMs) in agricultural soil following the application of superphosphate fertilisers seems to induce resistance of soil bacteria to HMs and appears to co-select for resistance to antibiotics (Ab). This study aimed to investigate the selection of co-resistance of soil bacteria to HMs and Ab in uncontaminated soil incubated for 6 weeks at 25 °C in laboratory microcosms spiked with ranges of concentrations of cadmium (Cd), zinc (Zn) and mercury (Hg). Co-selection of HM and Ab resistance was assessed using plate culture on media with a range of HM and Ab concentrations, and pollution-induced community tolerance (PICT) assays. Bacterial diversity was profiled via terminal restriction fragment length polymorphism (TRFLP) assay and 16S rDNA sequencing of genomic DNA isolated from selected microcosms. Based on sequence data, the microbial communities exposed to HMs were found to differ significantly compared to control microcosms with no added HM across a range of taxonomic levels.Published onlin