5,816 research outputs found

    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

    TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH

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    Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on people’s lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    Family, school and jobs: intergenerational social mobility in Next Steps

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    Young people’s higher education (HE) participation, and early access to labour markets, in the UK and other developed countries, are stratified according to their socio-economic origins and prior educational attainment. Such background factors are difficult to change in an individual’s lifetime, they are presumably not the only determinants of stratified outcomes, and anyway they could be mediated by peer influence and the issue of who goes to school with whom. This new study examines the relationships between a wide range of such social and economic factors relating to birth characteristics, family background, secondary schooling characteristics, and post-16 destinations, and it explores the possible reasons behind their links to HE and labour market outcomes. At the core of the study is an innovative combination of the large-scale nationally representative longitudinal Next Steps survey dataset linked to the robust administrative National Pupil Database (NPD) for England. In order to investigate the degree of social justice and equity in education, the study tracks the life course of a cohort of 5,192 state-school-educated young people in England from age 13 to age 25, to build a comprehensive picture of the journeys of these young people entering the labour market in their early adulthood. Analytical methods used include cross-tabulations, effect sizes, correlations and regression models. The main outcomes of interest are HE participation, and labour market outcomes as indicated by employment status and professional occupation status. The findings show a complex but relatively clear picture, providing some confirmatory and some new evidence on the correlates of intergenerational social mobility in a large cohort of people who are currently in their early 30s. Disadvantaged young people are consistently under-represented in HE participation and the labour market, especially in professional occupations. Bivariate analyses show that HE opportunities and labour market outcomes are systematically unbalanced between different socio-economic groups of young people, suggesting that destinations are strongly stratified by social origins. All of the factors considered in this study are independently associated with post-16 outcomes when analysed separately. Regression models reveal that, once birth characteristics are controlled for, the most important predictor of HE entry is prior educational attainment. This is followed by parental and pupil aspirations, parental occupation and education, material ownership at home, positive schooling experiences, and geographical location. In terms of employment status, doing an apprenticeship is the most powerful predictor of being employed at age 25 (although this may be skewed by the small number of young people still in formal education at that age). This is followed by prior educational attainment, material ownership at home, and prior HE entry. The relationship between the predictors and having a professional occupation status is slightly different. Regression analysis demonstrates that the key predictors of having a professional job are prior educational attainment, HE participation, parental and pupil aspirations, and positive schooling experiences. However, unlike generic employment status, evidence shows that having done an apprenticeship does not contribute to higher chances of landing a professional job. These findings collectively offer a core message in terms of fair access to life opportunities; the most import barriers to access to HE and professional occupations are stratified prior educational attainment and poverty-related factors at home. More crucially, the study also makes the first attempt to explore the level of segregation by background characteristics that is experienced at school as a potential factor in intergenerational social mobility. It is, to our knowledge, the only study to date which examines whether and to what extent who goes to school with whom might play a role in these outcomes beyond school. Bivariate analyses show that the clustering of pupils of similarly poorer socio-economic backgrounds at school is consistently linked to lower chances of HE participation and poorer labour market outcomes. Regression analyses further suggest that the level of between-school segregation an individual experiences plays a small role in all post-16 pathways, over and above that which can be explained by individual factors. In the light of these results, it appears that life destinations are still patterned by background inequality in modern England. However, there are promising signs that policy interventions – including creating a more socially mixed school intake, providing more financial support for low-income families such as travel bursaries, continuing and improving contextualised assessment in both university admissions and recruitment processes, and investing more in public transport in deprived areas – can help to improve fair access to HE and the labour market. These interventions can bring other long-term benefits such as life satisfaction too. Perhaps, instead of advocating or focusing on promoting social mobility, policymakers should devote more energy to and invest more money in tackling social inequality and improving equity in education and life opportunities. If this were to be done effectively, then social mobility could, presumably, look after itself

    Managing global virtual teams in the London FinTech industry

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    Today, the number of organisations that are adopting virtual working arrangements has exploded, and the London FinTech industry is no exception. During recent years, FinTech companies have increasingly developed virtual teams as a means of connecting and engaging geographically dispersed workers, lowering costs, and enabling greater speed and adaptability. As the first study in the United Kingdom regarding global virtual team management in the FinTech industry, this DBA research seeks answers to the question, “What makes for the successful management of a global virtual team in the London FinTech industry?”. Straussian grounded-theory method was chosen as this qualitative approach lets participants have their own voice and offers some flexibility. It also allows the researcher to have preconceived ideas about the research undertaking. The research work makes the case for appreciating the voice of people with lived experiences. Ten London-based FinTech Managers with considerable experience running virtual teams agreed to take part in this study. These Managers had spent time working at large, household-name firms with significant global reach, and one had recently become founder and CEO of his own firm, taking on clients and hiring contract staff from around the world. At least eight of the other participants were senior ‘Heads’ of various technology teams and one was a Managing Director working at a ‘Big Four’ consultancy. They had all (and many still did) spent years running geographically distributed teams with members as far away as Pacific Asia and they were all keen to discuss that breadth of experience and the challenges they faced. Results from these in-depth interviews suggested that there are myriad reasons for a global virtual team, from providing 24 hour, follow-the-sun service to locating the most cost-effective resources with the highest skills. It also confirmed that there are unique challenges to virtual management and new techniques are required to help navigate virtual managers through them. Managing a global virtual team requires much more than the traditional management competencies. Based on discussion with the respondents, a set of practical recommendations for global virtual team management was developed and covered a wide range of issues related to recruitment and selection, team building, developing standard operating procedures, communication, motivation, performance management, and building trust

    Strung pieces: on the aesthetics of television fiction series

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    As layered and long works, television fiction series have aesthetic properties that are built over time, bit by bit. This thesis develops a group of concepts that enable the study of these properties, It argues that a series is made of strung pieces, a system of related elements. The text begins by considering this sequential form within the fields of film and television. This opening chapter defines the object and methodology of research, arguing for a non-essentialist distinction between cinema and television and against the adequacy of textual and contextual analyses as approaches to the aesthetics of these shows. It proposes instead that these programmes should be described as televisual works that can be scrutinised through aesthetic analysis. The next chapters propose a sequence of interrelated concepts. The second chapter contends that series are composed of building blocks that can be either units into which series are divided or motifs that unify series and are dispersed across their pans. These blocks are patterned according to four kinds of relations or principles of composition. Repetition and variation are treated in tandem in the third chapter because of their close connection, given that variation emerges from established repetition. Exception and progression are also discussed together in the fourth chapter since they both require a long view of these serial works. The former, in order to be recognised as a deviation from the patterns of repetition and variation. The latter, In order to be understood in Its many dimensions as the series advances. Each of these concepts is further detailed with additional distinctions between types of units, motifs, repetitions, variations, and exceptions, using illustrative examples from numerous shows. In contrast, the section on progression uses a single series as case study, Carnivàle (2003-05), because this is the overarching principle that encompasses all the others. The conclusion considers the findings of the research and suggests avenues for their application

    ‘We the People: Supporting Food SMEs towards a Circular Food Economy’

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    This single Case Study locates SME (small and medium-size enterprise) hospitality and food services (HaFS) within a complex food waste system. It examines collaborative support for business change from linear resource wastage (‘take, use, dump), towards a circular food economy (CfE)- where ‘designing out’ food waste may reap savings. The objective is to support SME uptake of waste aversion practices so that they may thrive. The qualitative research centers on a London-based project promoting food waste valorization and healthy nutrition, in 15 boroughs. That project’s outreach for broad-based, collective impact included HaFS that are SMEs. Cross-sector liaison was the research focus for this Case Study which utilizes a hybrid philosophy and meta-framework, based on Critical Realism and Systemic Thinking. Some reference to Interpretivism highlights stewardship values for transforming individual behaviour. The Study also uses a multi-method design, borrowing soft systems from Management Science and Operational Research. Its blended approach includes: participant observation, mapping and rich picture techniques, semi-structured interviews and focus groups. The main research questions align concepts such as: circular economy, cross-sector collaboration and food waste management- with HaFS that are SMEs. A framework method and Leximancer software supported coding and qualitative thematic analysis. Primary findings include interesting categories of analytical, NGO and policy literature. Although conversations flagged up pivotal roles for our health and education sectors, the food SME element still seems peripheral in this transition to regenerative business. A ‘people vibe’ is enabling some HaFS’ kitchen waste action and food redistribution and, academia is a potential contributor to this information resource flow among stakeholders. The Study’s unique onto-epistemological framework enhances philosophical and theoretical knowledge about promoting SME resource stewardship. It spans Systemic Thinking (overt connections and acute complexities) and Critical Realism (deep mechanisms and institutional power differentials, impacting change). As an interpretive lens, the framework’s contribution to praxis was tested by shadowing the London TRiFOCAL project. This research could inform a business policy shift from traditional supply chain thinking, towards active UK food citizenship
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