62 research outputs found

    Africa's digital future

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    The main thrust of this book is to examine whether Africa is in a position to benefit from the digital age, given the continent’s many development challenges and slow adoption of digital technologies. While there is substantial literature on the digital economy and the quickening pace of the Fourth Industrial Revolution (4IR), comparatively little research has been conducted on what the digital age means for Africa. This book aims to close this research gap by using various qualitative and quantitative research methodologies to arrive at a cross-section of original findings and perspectives on how Africa can capitalise on the benefits of digital developments, including their potential to create jobs and bring about more inclusive growth. The book’s main contribution is its coverage of a range of topics that will affect Africa’s digital future, including industrialisation, global value chains, transport and logistics, trade facilitation, labour-market dynamics, employment and education. The theme of digital trade forms a backdrop to many of the chapters, along with references to the COVID-19 pandemic. The book acknowledges that although African countries should learn from international best practices, they need to chart their own course according to their own particular circumstances. By adopting a digital mindset, countries should be able to diversify economically and extend their market reach across the continent. Furthermore, while Africa should be looking to the future and determining how digital technologies can become effective tools of sustainable development, the continent has much catching up to do

    Africa's digital future

    Get PDF
    The main thrust of this book is to examine whether Africa is in a position to benefit from the digital age, given the continent’s many development challenges and slow adoption of digital technologies. While there is substantial literature on the digital economy and the quickening pace of the Fourth Industrial Revolution (4IR), comparatively little research has been conducted on what the digital age means for Africa. This book aims to close this research gap by using various qualitative and quantitative research methodologies to arrive at a cross-section of original findings and perspectives on how Africa can capitalise on the benefits of digital developments, including their potential to create jobs and bring about more inclusive growth. The book’s main contribution is its coverage of a range of topics that will affect Africa’s digital future, including industrialisation, global value chains, transport and logistics, trade facilitation, labour-market dynamics, employment and education. The theme of digital trade forms a backdrop to many of the chapters, along with references to the COVID-19 pandemic. The book acknowledges that although African countries should learn from international best practices, they need to chart their own course according to their own particular circumstances. By adopting a digital mindset, countries should be able to diversify economically and extend their market reach across the continent. Furthermore, while Africa should be looking to the future and determining how digital technologies can become effective tools of sustainable development, the continent has much catching up to do

    Korea’s green growth experience

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    Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

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    A novel multi-level and community-based agent ecosystem to support customers dynamic decision-making in smart grids

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    Electrical systems have evolved at a fast pace over the past years, particularly in response to the current environmental and climate challenges. Consequently, the European Union and the United Nations have encouraged the development of a more sustainable energy strategy. This strategy triggered a paradigm shift in energy consumption and production, which becoming increasingly distributed, resulted in the development and emergence of smart energy grids. Multi-agent systems are one of the most widely used artificial intelligence concepts in smart grids. Both multi-agent systems and smart grids are distributed, so there is correspondence between the used technology and the network's complex reality. Due to the wide variety of multi-agent systems applied to smart grids, which typically have very specific goals, the ability to model the network as a whole may be compromised, as communication between systems is typically non-existent. This dissertation, therefore, proposes an agent-based ecosystem to model smart grids in which different agent-based systems can coexist. This dissertation aims to conceive, implement, test, and validate a new agent-based ecosystem, entitled A4SG (agent-based ecosystem for smart grids modelling), which combines the concepts of multi-agent systems and agent communities to enable the modelling and representation of smart grids and the entities that compose them. The proposed ecosystem employs an innovative methodology for managing static or dynamic interactions present in smart grids. The creation of a solution that allows the integration of existing systems into an ecosystem, enables the representation of smart grids in a realistic and comprehensive manner. A4SG integrates several functionalities that support the ecosystem's management, also conceived, implemented, tested, and validated in this dissertation. Two mobility functionalities are proposed: one that allows agents to move between physical machines and another that allows "virtual" mobility, where agents move between agent communities to improve the context for the achievement of their objectives. In order to prevent an agent from becoming overloaded, a novel functionality is proposed to enable the creation of agents that function as extensions of the main agent (i.e., branch agents), allowing the distribution of objectives among the various extensions of the main agent. Several case studies, which test the proposed services and functionalities individually and the ecosystem as a whole, were used to test and validate the proposed solution. These case studies were conducted in realistic contexts using data from multiple sources, including energy communities. The results indicate that the used methodologies can increase participation in demand response events, increasing the fitting between consumers and aggregators from 12 % to 69 %, and improve the strategies used in energy transaction markets, allowing an energy community of 50 customers to save 77.0 EUR per week.Os últimos anos têm sido de mudança nos sistemas elétricos, especialmente devido aos atuais desafios ambientais e climáticos. A procura por uma estratégia mais sustentável para o domínio da energia tem sido promovida pela União Europeia e pela Organização das Nações Unidas. A mudança de paradigma no que toca ao consumo e produção de energia, que acontece, cada vez mais, de forma distribuída, tem levado à emergência das redes elétricas inteligentes. Os sistemas multi-agente são um dos conceitos, no domínio da inteligência artificial, mais aplicados em redes inteligentes. Tanto os sistemas multi-agente como as redes inteligentes têm uma natureza distribuída, existindo por isso um alinhamento entre a tecnologia usada e a realidade complexa da rede. Devido a existir uma vasta oferta de sistemas multi-agente aplicados a redes inteligentes, normalmente com objetivos bastante específicos, a capacidade de modelar a rede como um todo pode ficar comprometida, porque a comunicação entre sistemas é, geralmente, inexistente. Por isso, esta dissertação propõe um ecossistema baseado em agentes para modelar as redes inteligentes, onde vários sistemas de agentes coexistem. Esta dissertação pretende conceber, implementar, testar, e validar um novo ecossistema multiagente, intitulado A4SG (agent-based ecosystem for smart grids modelling), que combina os conceitos de sistemas multi-agente e comunidades de agentes, permitindo a modelação e representação de redes inteligentes e das suas entidades. O ecossistema proposto utiliza uma metodologia inovadora para gerir as interações presentes nas redes inteligentes, sejam elas estáticas ou dinâmicas. A criação de um ecossistema que permite a integração de sistemas já existentes, cria a possibilidade de uma representação realista e detalhada das redes de energia. O A4SG integra diversas funcionalidades, também estas concebidas, implementadas, testadas, e validadas nesta dissertação, que suportam a gestão do próprio ecossistema. São propostas duas funcionalidades de mobilidade, uma que permite aos agentes mover-se entre máquinas físicas, e uma que permite uma mobilidade “virtual”, onde os agentes se movem entre comunidades de agentes, de forma a melhorar o contexto para a execução dos seus objetivos. É também proposta uma nova funcionalidade que permite a criação de agentes que funcionam como uma extensão de um agente principal, com o objetivo de evitar a sobrecarga de um agente, permitindo a distribuição de objetivos entre as várias extensões do agente principal. A solução proposta foi testada e validada por vários casos de estudo, que testam os serviços e funcionalidades propostas individualmente, e o ecossistema como um todo. Estes casos de estudo foram executados em contextos realistas, usando dados provenientes de diversas fontes, tais como comunidades de energia. Os resultados demonstram que as metodologias utilizadas podem melhorar a participação em eventos de demand response, subindo a adequação entre consumidores e agregadores de 12 % para 69 %, e melhorar as estratégias utilizadas em mercados de transações de energia, permitindo a uma comunidade de energia com 50 consumidores poupar 77,0 EUR por semana

    The Cambridge Handbook of Health Research Regulation

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