8,536 research outputs found

    The stumbling block in ‘the race of our lives’: transition-critical materials, financial risks and the NGFS climate scenarios

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    Several ‘critical’ raw materials, including metals, minerals and Rare Earth Elements (REEs), play a central role in the low-carbon transition and are needed to expand the deployment of low-carbon technologies. The reliable and affordable supply of these resources is subject to supply-side risks and demand-induced pressures. This paper empirically estimates the material demand requirements for ‘Transition-Critical Materials’ (TCMs) implied under two NGFS Climate Scenarios, namely the ‘Net Zero by 2050’ and ‘Delayed Transition’ scenarios. We apply material intensity estimates to the underlying assumptions on the deployment of low-carbon technologies to determine the implied material demand between 2021 and 2040 for nine TCMs. We find several materials to be subject to significant demand-induced pressures under both scenarios. Subsequently, the paper examines the possible emergence of material bottlenecks for three materials, namely copper, lithium and nickel. The results indicate possible substantial mismatches between supply and demand, which would be further exacerbated if the transition is delayed rather than realised immediately. We discuss these findings in the context of different possible transmission channels through which these bottlenecks could affect financial and price stability, and propose avenues for future research

    Information Extraction from Documents: Question Answering vs Token Classification in real-world setups

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    Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in both natural language processing (NLP) and computer vision helped building document-focused pre-training methods, leveraging a multimodal understanding of the document text, layout and image modalities. However, these breakthroughs also led to the emergence of a new DocKIE subtask of extractive document Question Answering (DocQA), as part of the Machine Reading Comprehension (MRC) research field. In this work, we compare the Question Answering approach with the classical token classification approach for document key information extraction. We designed experiments to benchmark five different experimental setups : raw performances, robustness to noisy environment, capacity to extract long entities, fine-tuning speed on Few-Shot Learning and finally Zero-Shot Learning. Our research showed that when dealing with clean and relatively short entities, it is still best to use token classification-based approach, while the QA approach could be a good alternative for noisy environment or long entities use-cases

    Transformation of the business model to establish sustainable value in the consumer durables super store industry of Sri Lanka

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    The business model of an organization, operates as the fundamental blue print of the planning process, which shapes the nature of the strategies executed during the course of operation. These strategies in turn are responsible for the value creation or value erosion that takes place during the operation of the organization determining its sustainability, and in a broader context the sustainability of the industry. The research is done for the Consumer Durables Super Store (CDSS) industry of Sri Lanka concerning the existing business model, the value erosion occurring as a result of it and the risk it carries to the sustainability of the industry. The theoretical aspect of the research to develop a relationship based business model was anchored on the understanding of existing frameworks relating to sustainable value and extracting relevant areas of each of these frameworks (alignment of value, transforming current strategies and service offerings to create sustainable value) to develop a suitable hybrid framework with modifications to the literature to suite the research context.Ten in-depth interviews with CDSS organizational representatives holding leadership, sales and marketing management positions, and two focus group sessions with fifty selected customers were conducted in a virtual environment due to the prevailing pandemic situation. The data collected were analyzed with NVIVO 12, with themes relevant to the research utilized as codes, giving a clear understanding over the buyer and seller purview on the themes of the research. The findings surfaced the value erosion caused due to the financially driven strategies originated from the transactional orientation of the existing business model. The theories adopted to construct the relationship oriented business model to rectify the value erosion taking place, based on sustainable value, value alignment and service offerings, were modified to incorporate ‘quality of trade’ to bridge the gap, leading towards the creation and delivery of sustainable value to the buyer-seller eco system of the industry

    Um modelo para suporte automatizado ao reconhecimento, extração, personalização e reconstrução de gráficos estáticos

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    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 construído 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 disponíveis. 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 às suas características 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 ruído. Outras características das imagens do mundo real que podem dificultar esta tarefa não estão presentes na maioria das obras literárias, como distorções fotográficas, ruído, 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 disponíveis a visualização pode ser reconstruída, 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

    Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme

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    In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools

    Sexual violence as a form of social control : the role of hostile and benevolent sexism

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    This thesis examines the feminist hypothesis that rape functions as a tool of social control through which women are kept in subordinate social positions (Brownmiller, 1975). In examining this hypothesis, the current thesis explores the role of benevolent and hostile sexism in accounting for people's responses to different types of rape (i.e. stranger vs. acquaintance rape). An examination of the literature suggests that there are general societal beliefs in the distinction between "good" and "bad" rape victims (Pollard, 1992). Interestingly, researchers have observed that benevolent sexism (BS) is related to the idealisation of women in traditional gender roles (i.e. "good" women; Glick et aI., 2000). It is, therefore, argued that individuals who idealise women in traditional roles (i.e. high BS individuals) are more likely to negatively evaluate rape victims who can be perceived as violating these norms. Nine empirical studies are presented in this thesis. Study 1 examines the potential role of BS in accounting for previously observed differences in the amount of blame attributed to stranger and acquaintance rape victims (e.g. Pollard, 1992). Studies 2 and 3 examine the psychological mechanisms that underlie the relationship between BS and victim blame in acquaintance rape situations. Studies 2 and 4 also explore the psychological mechanisms that underlie the relationship between hostile sexism (HS) and self reported rape proclivity in acquaintance rape situations (c.f. Viki, 2000). In Study 5, the relationship between BS and paternalistic chivalry (attitudes that are simultaneously courteous and restrictive to women) is examined. Studies 6 and 7 examine the role of BS in accounting for participants' responses to stranger vs. acquaintance rape perpetrators. The last two studies (Studies 8 and 9) examine the potential role of legal verdicts in moderating the relationship between BS and victim blame in acquaintance rape cases. Taken together, the results support the argument that BS provides a psychological mechanism through which differences in the amount of blame attributed to stranger and acquaintance rape victims can be explained. In contrast, HS provides a mechanism for explaining differences in self-reported proclivity to commit stranger and acquaintance rape. The thesis concludes with a summary of the findings, a discussion of the methodological limitations of the studies and suggestions of directions for future research

    Walking with the Earth: Intercultural Perspectives on Ethics of Ecological Caring

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    It is commonly believed that considering nature different from us, human beings (qua rational, cultural, religious and social actors), is detrimental to our engagement for the preservation of nature. An obvious example is animal rights, a deep concern for all living beings, including non-human living creatures, which is understandable only if we approach nature, without fearing it, as something which should remain outside of our true home. “Walking with the earth” aims at questioning any similar preconceptions in the wide sense, including allegoric-poetic contributions. We invited 14 authors from 4 continents to express all sorts of ways of saying why caring is so important, why togetherness, being-with each others, as a spiritual but also embodied ethics is important in a divided world
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