8,440 research outputs found

    Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse

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    This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses. This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups. In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in users’ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018—6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

    Learning disentangled speech representations

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    A variety of informational factors are contained within the speech signal and a single short recording of speech reveals much more than the spoken words. The best method to extract and represent informational factors from the speech signal ultimately depends on which informational factors are desired and how they will be used. In addition, sometimes methods will capture more than one informational factor at the same time such as speaker identity, spoken content, and speaker prosody. The goal of this dissertation is to explore different ways to deconstruct the speech signal into abstract representations that can be learned and later reused in various speech technology tasks. This task of deconstructing, also known as disentanglement, is a form of distributed representation learning. As a general approach to disentanglement, there are some guiding principles that elaborate what a learned representation should contain as well as how it should function. In particular, learned representations should contain all of the requisite information in a more compact manner, be interpretable, remove nuisance factors of irrelevant information, be useful in downstream tasks, and independent of the task at hand. The learned representations should also be able to answer counter-factual questions. In some cases, learned speech representations can be re-assembled in different ways according to the requirements of downstream applications. For example, in a voice conversion task, the speech content is retained while the speaker identity is changed. And in a content-privacy task, some targeted content may be concealed without affecting how surrounding words sound. While there is no single-best method to disentangle all types of factors, some end-to-end approaches demonstrate a promising degree of generalization to diverse speech tasks. This thesis explores a variety of use-cases for disentangled representations including phone recognition, speaker diarization, linguistic code-switching, voice conversion, and content-based privacy masking. Speech representations can also be utilised for automatically assessing the quality and authenticity of speech, such as automatic MOS ratings or detecting deep fakes. The meaning of the term "disentanglement" is not well defined in previous work, and it has acquired several meanings depending on the domain (e.g. image vs. speech). Sometimes the term "disentanglement" is used interchangeably with the term "factorization". This thesis proposes that disentanglement of speech is distinct, and offers a viewpoint of disentanglement that can be considered both theoretically and practically

    Cultivating Agrobiodiversity in the U.S.: Barriers and Bridges at Multiple Scales

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    The diversity of crops grown in the United States (U.S.) is declining, causing agricultural landscapes to become more and more simplified. This trend is concerning for the loss of important plant, insect, and animal species, as well as the pollution and degradation of our environment. Through three separate but related studies, this dissertation addresses the need to increase the diversity of these agricultural landscapes in the U.S., particularly through diversifying the type and number of crops grown. The first study uses multiple, openly accessible datasets related to agricultural land use and policies to document and visualize change over recent decades. Through this, I show that U.S. agriculture has gradually become more specialized in the crops grown, crop production is heavily concentrated in certain areas, and crop diversity is continuing to decline. Meanwhile, federal agricultural policy, while having become more influential over how U.S. agriculture operates, incentivizes this specialization. The second study uses nonlinear statistical modeling to identify and compare social, political, and ecological factors that best predict crop diversity across nine regions in the U.S. Factors of climate, prior land use, and farm inputs best predict diversity across regions, but regions show key differences in how factors are important, indicating that patterns at the regional scale constrain and enable further diversification. Finally, the third study relied on interviews with farmers and key informants in southern Idaho’s Magic Valley – a cluster of eight counties that is known to be agriculturally diverse. Interviews gauge what farmers are currently doing to manage crop diversity (the present) and how they imagine alternative landscapes (the imaginary). We found that farmers in the Magic Valley manage current diversity mainly through cover cropping and diverse crop rotations, but daily struggles and political barriers make experimenting with and imagining alternative landscapes difficult and unlikely to occur. Together, these three studies provide an integrated view of how and why U.S. agriculture landscapes simplify or diversify, as well as the barriers and bridges such pathways of diversification

    Early Neanderthal social and behavioural complexity during the Purfleet Interglacial: handaxes in the latest Lower Palaeolithic.

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    Only a handful of ‘flagship’ sites from the Purfleet Interglacial (Marine Isotope Stage 9, c. 350-290,000 years ago) have been properly examined, but the archaeological succession at the proposed type-site at Purfleet suggests a period of complexity and transition, with three techno-cultural groups represented in Britain. The first was a simple toolkit lacking handaxes (the Clactonian), and the last a more sophisticated technology presaging the coming Middle Palaeolithic (simple prepared core or proto-Levallois technology). Sandwiched between were Acheulean groups, whose handaxes comprise the great majority of the extant archaeological record of the period – these are the focus of this study. It has previously been suggested that some features of the Acheulean in the Purfleet Interglacial were chronologically restricted, particularly the co-occurrence of ficrons and cleavers. These distinctive forms may have exceeded pure functionality and were perhaps imbued with a deeper social and cultural meaning. This study supports both the previously suggested preference for narrow, pointed morphologies, and the chronologically restricted pairing of ficrons and cleavers. By drawing on a wide spatial and temporal range of sites these patterns could be identified beyond the handful of ‘flagship’ sites previously studied. Hypertrophic ‘giants’ have now also been identified as a chronologically restricted form. Greater metrical variability was found than had been anticipated, leading to the creation of two new sub-groups (IA and IB) which are tentatively suggested to represent spatial and perhaps temporal patterning. The picture in the far west of Britain remains unclear, but the possibility of different Acheulean groups operating in the Solent area, and a late survival of the Acheulean, are both suggested. Handaxes with backing and macroscopic asymmetry may represent prehensile or ergonomic considerations not commonly found on handaxes from earlier interglacial periods. It is argued that these forms anticipate similar developments in the Late Middle Palaeolithic in an example of convergent evolution

    Towards better support for high-functioning autistic learners in a mainstream sixth form classroom

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    This conceptual Dissertation emerged from my personal professional experiences as the Head of Additional Learning Support and Inclusion at a London Sixth Form College. The study considers the ways in which support for 16 to 19-year-old autistic learners who are deemed as high functioning might be improved. Initially I analyse current educational policy and legislation, using Martha Nussbaum’s version of the Capabilities Approach as an analytical lens. I argue that an education system based on a commodified, meritocratic, standardised, and neoliberal understanding of success has had a detrimental impact on both the flourishing and working relationships of high-functioning autistic learners and their teachers in the classroom. I contend that this type of education system focuses on employability skills using narrow understandings of human flourishing and what it means to be human. I suggest that Nussbaum’s Capabilities Approach offers an alternative value system based on the recognition of human dignity and a broader and deeper understanding of what it means to be human by acknowledging and embracing different ways of thinking and being. I then discuss the difficulties high-functioning autistic learners encounter with social communication and functioning and feeling misunderstood which, I argue, are compounded by the pressures caused by the current meritocratic commodified education system. Additionally, and following Nussbaum’s work on emotions, I argue that key to the improvement of the understanding and support of high-functioning autistic learners in the classroom is a dialogical, empathetic, and compassionate working relationship between the teacher and the learner, both of whom are on a mutual learning journey. I then discuss how this relationship can be enhanced with the values of Nussbaum’s Capabilities Approach practically implemented using Armstrong’s Positive Niche Construction. I contend, in my conclusion, that this approach to education will benefit not only high functioning autistic learners but all learners
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