11,213 research outputs found
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory
Mining data streams is one of the main studies in machine learning area due
to its application in many knowledge areas. One of the major challenges on
mining data streams is concept drift, which requires the learner to discard the
current concept and adapt to a new one. Ensemble-based drift detection
algorithms have been used successfully to the classification task but usually
maintain a fixed size ensemble of learners running the risk of needlessly
spending processing time and memory. In this paper we present improvements to
the Scale-free Network Regressor (SFNR), a dynamic ensemble-based method for
regression that employs social networks theory. In order to detect concept
drifts SFNR uses the Adaptive Window (ADWIN) algorithm. Results show
improvements in accuracy, especially in concept drift situations and better
performance compared to other state-of-the-art algorithms in both real and
synthetic data
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
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
Strategies for Early Learners
Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp
Towards a sociology of conspiracy theories: An investigation into conspiratorial thinking on Dönmes
This thesis investigates the social and political significance of conspiracy theories, which has been an academically neglected topic despite its historical relevance. The academic literature focuses on the methodology, social significance and political impacts of these theories in a secluded manner and lacks empirical analyses. In response, this research provides a comprehensive theoretical framework for conspiracy theories by considering their methodology, political impacts and social significance in the light of empirical data. Theoretically, the thesis uses Adorno's semi-erudition theory along with Girardian approach. It proposes that conspiracy theories are methodologically semi-erudite narratives, i.e. they are biased in favour of a belief and use reason only to prove it. It suggests that conspiracy theories appear in times of power vacuum and provide semi-erudite cognitive maps that relieve alienation and ontological insecurities of people and groups. In so doing, they enforce social control over their audience due to their essentialist, closed-to-interpretation narratives. In order to verify the theory, the study analyses empirically the social and political significance of conspiracy theories about the Dönme community in Turkey. The analysis comprises interviews with conspiracy theorists, conspiracy theory readers and political parties, alongside a frame analysis of the popular conspiracy theory books on Dönmes. These confirm the theoretical framework by showing that the conspiracy theories are fed by the ontological insecurities of Turkish society. Hence, conspiracy theorists, most readers and some political parties respond to their own ontological insecurities and political frustrations through scapegoating Dönmes. Consequently, this work shows that conspiracy theories are important symptoms of society, which, while relieving ontological insecurities, do not provide politically prolific narratives
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Meaning-Making Practices of Emergent Arabic–English Bilingual Kindergarten Children in Cairo
The number of British Schools in the Middle East and North Africa (MENA) region is growing. The National Curriculum of England is used by an increasing number of such schools. As well as exporting a culturally-specific curriculum, these schools usually adopt an ideology of monolingualism, thus potentially limiting communication for emergent bilinguals and failing to acknowledge the multiple ways of meaning-making.
Current studies of translanguaging are moving the focus to multimodal forms of communication as a resource for thinking and communicating (GarcÃa and Wei 2014, Wei 2018). Building on the work of Kress (1997, 2010) I explore pre-school emergent bilinguals’ wider signifying practices and create an analytical framework, which I call MMTL (multimodal translanguaging), used as a lens to illustrate meaning-making.
Valley Hill in Cairo, Egypt is a British school which encourages ‘English-only’ as the medium of instruction in the kindergarten. Using a case study methodology, this research explores the meaning-making practices of eight emergent bilingual children aged 3–4 during child-initiated play, later reduced to four in the thesis to provide a detailed multimodal analysis. The principal aim is to explore their speech, gaze, gesture, and their engagement (layout/position) with artefacts during play.
The findings of this study suggest that although there is an ‘English-only’ approach, these young emergent bilingual children are meaning-making in a variety of ways. Children are translanguaging but it is never in isolation from other modes of communication. Emergent bilinguals use a range of modes to mediate their understanding and communication with others. They use gesture, gaze, and artefacts alongside translingual practices to move meaning across to more accessible modes, enabling communication and understanding. The implications for schools should be to embrace such hybrid practices and for teachers to be more responsive to young children’s meaning-making to enable learning
Um modelo para suporte automatizado ao reconhecimento, extração, personalização e reconstrução de gráficos estáticos
Data charts are widely used in our daily lives, being present in regular media,
such as newspapers, magazines, web pages, books, and many others. A well constructed
data chart leads to an intuitive understanding of its underlying data
and in the same way, when data charts have wrong design choices, a redesign
of these representations might be needed. However, in most cases, these
charts are shown as a static image, which means that the original data are not
usually available. Therefore, automatic methods could be applied to extract the
underlying data from the chart images to allow these changes. The task of
recognizing charts and extracting data from them is complex, largely due to the
variety of chart types and their visual characteristics.
Computer Vision techniques for image classification and object detection are
widely used for the problem of recognizing charts, but only in images without
any disturbance. Other features in real-world images that can make this task
difficult are not present in most literature works, like photo distortions, noise,
alignment, etc. Two computer vision techniques that can assist this task and
have been little explored in this context are perspective detection and
correction. These methods transform a distorted and noisy chart in a clear
chart, with its type ready for data extraction or other uses. The task of
reconstructing data is straightforward, as long the data is available the
visualization can be reconstructed, but the scenario of reconstructing it on the
same context is complex.
Using a Visualization Grammar for this scenario is a key component, as these
grammars usually have extensions for interaction, chart layers, and multiple
views without requiring extra development effort.
This work presents a model for automated support for custom recognition, and
reconstruction of charts in images. The model automatically performs the
process steps, such as reverse engineering, turning a static chart back into its
data table for later reconstruction, while allowing the user to make modifications
in case of uncertainties. This work also features a model-based architecture
along with prototypes for various use cases. Validation is performed step by
step, with methods inspired by the literature. This work features three use
cases providing proof of concept and validation of the model.
The first use case features usage of chart recognition methods focused on
documents in the real-world, the second use case focus on vocalization of
charts, using a visualization grammar to reconstruct a chart in audio format,
and the third use case presents an Augmented Reality application that
recognizes and reconstructs charts in the same context (a piece of paper)
overlaying the new chart and interaction widgets. The results showed that with
slight changes, chart recognition and reconstruction methods are now ready for
real-world charts, when taking time, accuracy and precision into consideration.Os gráficos de dados são amplamente utilizados na nossa vida diária, estando
presentes nos meios de comunicação regulares, tais como jornais, revistas,
páginas web, livros, e muitos outros. Um gráfico bem construÃdo leva a uma
compreensão intuitiva dos seus dados inerentes e da mesma forma, quando
os gráficos de dados têm escolhas de conceção erradas, poderá ser
necessário um redesenho destas representações. Contudo, na maioria dos
casos, estes gráficos são mostrados como uma imagem estática, o que
significa que os dados originais não estão normalmente disponÃveis. Portanto,
poderiam ser aplicados métodos automáticos para extrair os dados inerentes
das imagens dos gráficos, a fim de permitir estas alterações. A tarefa de
reconhecer os gráficos e extrair dados dos mesmos é complexa, em grande
parte devido à variedade de tipos de gráficos e à s suas caracterÃsticas visuais.
As técnicas de Visão Computacional para classificação de imagens e deteção
de objetos são amplamente utilizadas para o problema de reconhecimento de
gráficos, mas apenas em imagens sem qualquer ruÃdo. Outras caracterÃsticas
das imagens do mundo real que podem dificultar esta tarefa não estão
presentes na maioria das obras literárias, como distorções fotográficas, ruÃdo,
alinhamento, etc. Duas técnicas de visão computacional que podem ajudar
nesta tarefa e que têm sido pouco exploradas neste contexto são a deteção e
correção da perspetiva. Estes métodos transformam um gráfico distorcido e
ruidoso em um gráfico limpo, com o seu tipo pronto para extração de dados
ou outras utilizações. A tarefa de reconstrução de dados é simples, desde que
os dados estejam disponÃveis a visualização pode ser reconstruÃda, mas o
cenário de reconstrução no mesmo contexto é complexo.
A utilização de uma Gramática de Visualização para este cenário é um
componente chave, uma vez que estas gramáticas têm normalmente
extensões para interação, camadas de gráficos, e visões múltiplas sem exigir
um esforço extra de desenvolvimento.
Este trabalho apresenta um modelo de suporte automatizado para o
reconhecimento personalizado, e reconstrução de gráficos em imagens
estáticas. O modelo executa automaticamente as etapas do processo, tais
como engenharia inversa, transformando um gráfico estático novamente na
sua tabela de dados para posterior reconstrução, ao mesmo tempo que
permite ao utilizador fazer modificações em caso de incertezas. Este trabalho
também apresenta uma arquitetura baseada em modelos, juntamente com
protótipos para vários casos de utilização. A validação é efetuada passo a
passo, com métodos inspirados na literatura. Este trabalho apresenta três
casos de uso, fornecendo prova de conceito e validação do modelo.
O primeiro caso de uso apresenta a utilização de métodos de reconhecimento
de gráficos focando em documentos no mundo real, o segundo caso de uso
centra-se na vocalização de gráficos, utilizando uma gramática de visualização
para reconstruir um gráfico em formato áudio, e o terceiro caso de uso
apresenta uma aplicação de Realidade Aumentada que reconhece e reconstrói
gráficos no mesmo contexto (um pedaço de papel) sobrepondo os novos
gráficos e widgets de interação. Os resultados mostraram que com pequenas
alterações, os métodos de reconhecimento e reconstrução dos gráficos estão
agora prontos para os gráficos do mundo real, tendo em consideração o
tempo, a acurácia e a precisão.Programa Doutoral em Engenharia Informátic
Material Economies of South Yorkshire. The Organisation of Metal Production in Roman South Yorkshire.
This thesis aims to develop a model for the social organisation and production of ferrous and non-ferrous metals in South Yorkshire during the Roman period. This characterisation of the organisation of metallurgical activities is achieved through a combined methodology that will gather data from grey literature, published literature, as well as chemical, visual and microstructural analysis of metallurgical debris. The metallurgical practices in the study area are primarily rural in nature. These results are looked at through the lenses of Agency, Habitus, and the social construction of craft production. The movement of materials and people within the study area and local specialist practices are central in the interpretation of regional metalworking practices. Furthermore, models of craft production are critiqued, and an alternative modelisation process is suggested to characterise and understand the organisation of metal production in Roman South Yorkshire
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