609 research outputs found

    Data ethics : building trust : how digital technologies can serve humanity

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    Data is the magic word of the 21st century. As oil in the 20th century and electricity in the 19th century: For citizens, data means support in daily life in almost all activities, from watch to laptop, from kitchen to car, from mobile phone to politics. For business and politics, data means power, dominance, winning the race. Data can be used for good and bad, for services and hacking, for medicine and arms race. How can we build trust in this complex and ambiguous data world? How can digital technologies serve humanity? The 45 articles in this book represent a broad range of ethical reflections and recommendations in eight sections: a) Values, Trust and Law, b) AI, Robots and Humans, c) Health and Neuroscience, d) Religions for Digital Justice, e) Farming, Business, Finance, f) Security, War, Peace, g) Data Governance, Geopolitics, h) Media, Education, Communication. The authors and institutions come from all continents. The book serves as reading material for teachers, students, policy makers, politicians, business, hospitals, NGOs and religious organisations alike. It is an invitation for dialogue, debate and building trust! The book is a continuation of the volume “Cyber Ethics 4.0” published in 2018 by the same editors

    Contributions to time series analysis, modelling and forecasting to increase reliability in industrial environments.

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    356 p.La integración del Internet of Things en el sector industrial es clave para alcanzar la inteligencia empresarial. Este estudio se enfoca en mejorar o proponer nuevos enfoques para aumentar la confiabilidad de las soluciones de IA basadas en datos de series temporales en la industria. Se abordan tres fases: mejora de la calidad de los datos, modelos y errores. Se propone una definición estándar de métricas de calidad y se incluyen en el paquete dqts de R. Se exploran los pasos del modelado de series temporales, desde la extracción de características hasta la elección y aplicación del modelo de predicción más eficiente. El método KNPTS, basado en la búsqueda de patrones en el histórico, se presenta como un paquete de R para estimar datos futuros. Además, se sugiere el uso de medidas elásticas de similitud para evaluar modelos de regresión y la importancia de métricas adecuadas en problemas de clases desbalanceadas. Las contribuciones se validaron en casos de uso industrial de diferentes campos: calidad de producto, previsión de consumo eléctrico, detección de porosidad y diagnóstico de máquinas

    The potential of international cooperation in the Azorean space strategy

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    Dissertação de Mestrado, Relações Internacionais: O Espaço Euro-Atlântico, 17 de março de 2023, Universidade dos Açores.Esta investigação pretende abordar a essência da cooperação internacional do setor espacial na Região Autónoma dos Açores. O estudo centra-se, por isso, nos impactos que terão na economia, na criação de emprego qualificado, desenvolvimento tecnológico, capacidade geográfica dos Açores e nas problemáticas que a Região enfrentará.ABSTRACT: This investigation aims to study the essence of international cooperation in the space sector in the Autonomous Region of the Azores. The study, therefore, focuses on the resulting impacts on the economy, the creation of qualified employment, technological development, the geographic capacity of the Azores and the problems that the Region will face

    The future of liquified natural gas (LNG) in the energy transition: options and implications for the LNG industry in a decarbonising world

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    A global energy transition is currently taking place, driven primarily by the need to combat climate change. The Intergovernmental Panel on Climate Change (IPCC) has concluded that the current trajectory of global greenhouse gas emissions is not consistent with limiting global warming to below 1.5 or 2 °C, relative to pre-industrial levels, a threshold that could lead to severe economic damage and instability for the coming decades. Fossil fuel combustion, industry, transport, and electricity production contribute to approximately 80% of global greenhouse gas emissions. Energy systems must therefore decarbonise at dramatic rates to move towards a more sustainable environmental development path, but also to cater for population and economic growth in many parts of the world. Natural gas, a fuel with superior environmental credentials than other fossil fuels, has been touted as a “transition fuel” to support the low-carbon transition by promoting fuel-switching and supporting hard-to-abate sectors until largescale electrification with renewable resources and other solutions such as largescale batteries and hydrogen are developed and deployed. Utilising a bespoke meta-framework grounded in institutional theory, combining elements of techno-economic and socio-technical approaches, this study examines how institutional, political, and resource characteristics affect the use of liquified natural gas (LNG), the fastest growing sector within natural gas. Methodology includes the analysis of three country cases (UK, Japan, China). In addition, an in-depth analysis of the LNG industry is conducted, with a focus on the decarbonisation options and implications for the industry, including the impact of development of the hydrogen economy on LNG. The synthesis presents conclusions and findings on LNG’s role in future potential pathways in energy systems in various stages of the energy transition

    Assessment, Diagnosis and Service Life Prediction

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    Service life prediction is crucial for the adoption of more sustainable solutions, allowing developers to optimize the costs and environmental impact of buildings during their life cycle. An accurate assessment of the service life of buildings requires a thorough understanding of the degradation mechanisms and behaviour of the construction materials. Building pathology assessment methods characterize the deterioration state of buildings, using specific measurable properties as indicators. Based on this information, different service life prediction methodologies can be defined to provide reliable data concerning the most probable failure time of whole buildings and individual components according to their characteristics and their age. This Special Issue provides new perspectives on the existing knowledge related with various aspects of the Assessment, Diagnosis and Service Life Prediction of buildings and their components. The ten original research studies published in this Special Issue result from research centres and university departments of Civil and Construction Engineering, Safety Management, Environmental Engineering, Geotechnical Engineering, and Architecture and the Built Environment, with relevant contributions from experts from Australia, Brazil, the Czech Republic, Hong Kong, Iran, Israel, Norway, Portugal, and Taiwan. The studies included in this Special Issue address topics related to: Building pathology assessment methods; Diagnosis of defects in buildings and components; Appropriate intervention and repair techniques; Deterministic and stochastic service life prediction models
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