1,025 research outputs found

    From Aspiration to Actuality under Xi Jinping: Reinterpreting the Outcome-driven Debate towards the Role of Historical Materialism in China’s Rise, 1949–2021

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    DOES THE REVOLUTIONARY IDEOLOGY of socialist rising powers influence their rise to power? If so, how, when, and why? The literature on rising powers works on a set of historical assumptions which, when applied to China’s rise, predict an inevitable rise to power. In this literature, a new world order is imagined with China as a new kind of leading great power. For some, this development represents the correction of imperial China’s historical position in the world. This thesis disagrees with this outcome-based analytical approach to China’s rise. It instead posits another argument: in understanding the dynamics of a socialist rising power, the role of ideology matters more than the rising power literature suggests. In the Chinese context, this means bringing the Communist Party of China back into the story of its rise. This Party- state builds on a genuine belief in historical materialism and a teleology of success which it, presumably, represents. Treating the Xi Jinping era (2012 to the present) as a pivotal moment, this thesis understands the Chinese Dream of Great Rejuvenation as promethean. While it fits within the Chinese tradition of organising China in its own image, as a political actor it is entirely new. China’s rise, then, becomes much more than simply ensuring the Party’s self- perpetuation of its political rule. It is a grand historical narrative which may only be understood, and problema

    Analyzing smart city development through an evolutionary approach

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    Cities have always been places where agglomeration economies attained their highest yields, producing cultural, economic, and social benefits being the main locus of entrepreneurship and innovation. However, rapid urbanization created many problems such as inequality, pollution, diseases, insecurity and so on, that end up restraining the dynamic of value creation in 21st century. This is challenging ‘industrial cities’ to rethink and to reshape their structures to overcome these issues. In this sense, the ‘smart city’ model has gained prominence in urban development. Many cities from different countries are designing strategies and implementing them through initiatives and projects towards smart city development. It is noted that these experiences are idiosyncratic, because cities are inherently different and have different issues that must be solved in a particular way. The first question that arise is: how to make a city smarter? Despite the contrasting view of frameworks and their multitude of dimensions and approaches, the literature points out that cities must have specific elements to induce innovation processes through digital solutions and the collaboration between stakeholders in order to address local challenges and, thus, increase local competitiveness and quality of life. However, it does not an easy task and involves a set of stakeholders that may not prone to collaborate and to promote smart city development. In fact, the main difficulties of a strategy emerge during the implementation phase, because many of the challenges for cities to become or to be smart exceed the scope and capabilities of their current organizations, institutional arrangements, and governance structures. Indeed, the lack of appropriate structural and organizational formations does not foster the involvement of local stakeholders and makes it difficult to organize and coordinate the different activities needed to achieve sustainable urban development. Then, the second question that emerge is: what kind of organization can foster smart city development? In this sense, the literature sheds light on the need to discuss alternative governance models to overcome those challenges by combining political and social support with strategic planning and creative thinking in order to deal with smart city complexity. Some authors point out that it is necessary to create a dedicated organization to lead the collaboration between those stakeholders in this process of urban transformation. From that discussion, what seems clear is that the analysis of the development process of a smart city in its different dimensions and units of analysis demands a theoretical background that enables academia and industry to capture the dynamics of evolution and, therefore, understand how smart cities change over time. It is necessary to incorporate theories and concepts that consider not only the notion of space-time, but especially that delve into how the relationships between the elements of the ecosystem interact and complement each other. Then, our third question is: how to analyze this dynamic, context-dependent, long-term process of urban development so that a city becomes smarter? Some authors point out the possibility of a theoretical approximation between evolutionary approach and smart city literature affirming that due to complexity of smart city development, smart city planning is shaped by evolutionary processes too. Thus, it is necessary to incorporate the notion of evolution in the processes of urban transformation and that they occur in a certain geographical location being conditioned by local contextual factors. As aforementioned, cities are inherently different and have different issues. Thus, to measure the existing level of development is crucial to foresee the right steps to enhance urban smartness. Smartness should be seen as a continuum, in which stakeholders may implement initiatives to create, improve or alter smart city elements across those different city dimensions. The notion of smartness may help cities to understand how this process of urban transformation affects their dimensions and their performance, and, consequently, analyze what should be done to accelerate it. In this sense, it is important that cities assess their current stage of development. The assessment of smart city development may bring multiple benefits for different stakeholders. It enables the identification of city strengths and weaknesses, comparison among cities, monitoring and racking projects implementation, increasing transparency on investments, enabling to make policies based on evidences, enhancing citizen awareness, and so on. The fourth question that emerges is: how to measure the smartness of a city? In terms of smart city assessment, many scholars, organizations and companies have developed indexes, toolkits, and benchmarking to measure and rank smart cities. These assessments schemes may provide a good overview about the city’s characteristics and both its strengths and weaknesses, as well as being used to showcase its competitive position. However, most of them neglect the multiple interrelated processes related to the smart city development by adopting a summative approach. This approach presents some limitations that do not properly capture the smartness of a city. Considering that, the objectives of this study are to (1) identify the dimensions and the driving elements to make a city smarter, (2) to understand the role of smart city dedicated organization on smart city governance, (3) to propose an evolutionary framework for the analysis of smart city development and (4) to create a model to measure the smartness of a city using different methods, considering the type of data, its manipulation and analysis. To achieve these objectives, the research focused on understanding the concept of smart cities and that their development depends on a non-linear process, which should make some steps like designing strategies, implementing them through projects to solve the current urban issues. For that, the establishment of a governance structure is crucial to smart city development succeed since collaboration is needed to create complex solutions and the legitimacy of a vision. Therefore, a dedicated organization is important to articulate the stakeholders and boost the development of projects and initiatives. However, just collaborative networks will not solve the urban issues per se. It should be identified how to create, improve, change the elements from the hard and soft dimensions of a city (i.e., economy, social, environment). It is important to highlight that a smart strategy, project, or solution to be smart in fact must consider that these dimensions are integrated and then affect and are affected by each other. In addition, it is needed to incorporate in this urban planning and management discourse the notion of time and space, because past events can affect the current stage of development and the present decisions will impact future of the city. As an evolutionary process, each city will certainly follow different paths, because the dynamics of its development depends on how the (eco)system is configured and which is his level of smartness. It also should be considered the history of city and its context to define more assertive strategies and projects. Thus, for the analysis of smart city development, it is necessary to apply an evolutionary framework capable to link micro-behavior to macro- processes that occur in each territory over time. By considering smart city development as a process that changes the urban realm and the behavior of stakeholders over time, there is a need to measure how this is in fact helping (or not) the urban performance and, how cities can achieve a sustainable development in a more efficient way. In this study, it focusses on the measurement of smartness of an urban innovation ecosystem, because it provides an overview of the current stage of development and the relationship among the elements and dimensions, which could guide policymakers and the society on what invest, how to design a comprehensive strategy and when to implement it.As cidades sempre foram locais onde as economias de aglomeração atingiram seus maiores rendimentos, produzindo benefícios culturais, econômicos e sociais sendo o principal locus de empreendedorismo e inovação. No entanto, a rápida urbanização criou muitos problemas como desigualdade, poluição, doenças, insegurança e assim por diante, que acabam por restringir a dinâmica de criação de valor no século XXI. Isso está desafiando as "cidades industriais" a repensar e remodelar suas estruturas para superar esses problemas. Nesse sentido, o modelo de 'cidade inteligente' tem ganhado destaque no desenvolvimento urbano. Muitas cidades de diferentes países estão desenhando estratégias e implementando-as por meio de iniciativas e projetos para o desenvolvimento de cidades inteligentes. Nota-se que essas experiências são idiossincráticas, pois as cidades são inerentemente diferentes e possuem questões diversas que devem ser resolvidas de forma particular. A primeira questão que surge é: como tornar uma cidade mais inteligente? Apesar da visão contrastante dos frameworks e de sua multiplicidade de dimensões e abordagens, a literatura aponta que as cidades devem ter elementos específicos para induzir processos de inovação por meio de soluções digitais e da colaboração entre stakeholders para enfrentar os desafios locais e, assim, aumentar a competitividade local e qualidade de vida. No entanto, não é uma tarefa fácil e envolve um conjunto de stakeholders que podem não estar dispostos a colaborar e promover o desenvolvimento de cidades inteligentes. De fato, as principais dificuldades de uma estratégia surgem durante a fase de implementação, pois muitos dos desafios para as cidades se tornarem ou serem inteligentes excedem o escopo e as capacidades de suas atuais organizações, arranjos institucionais e estruturas de governança. De fato, as principais dificuldades de uma estratégia surgem durante a fase de implementação, pois muitos dos desafios para as cidades se tornarem ou serem inteligentes excedem o escopo e as capacidades de suas atuais organizações, arranjos institucionais e estruturas de governança. Com efeito, a falta de formações estruturais e organizativas adequadas não favorece o envolvimento dos atores locais e dificulta a organização e coordenação das diferentes atividades necessárias para alcançar um desenvolvimento urbano sustentável. Então, a segunda questão que surge é: que tipo de organização pode fomentar o desenvolvimento de cidades inteligentes? Nesse sentido, a literatura lança luz sobre a necessidade de discutir modelos alternativos de governança para superar esses desafios, combinando apoio político e social com planejamento estratégico e pensamento criativo para lidar com a complexidade da cidade inteligente. Alguns autores apontam que é necessário criar uma organização dedicada a liderar a colaboração entre as partes interessadas neste processo de transformação urbana. A partir dessa discussão, o que parece claro é que a análise do processo de desenvolvimento de uma smart city em suas diferentes dimensões e unidades de análise demanda um embasamento teórico que permita à academia e à indústria captar a dinâmica da evolução e, assim, compreender como as smart cities mudam com o tempo. É preciso incorporar teorias e conceitos que considerem não apenas a noção de espaço-tempo, mas principalmente que se aprofundem em como as relações entre os elementos do ecossistema interagem e se complementam. Então, nossa terceira pergunta é: como analisar esse processo de desenvolvimento urbano dinâmico, dependente do contexto e de longo prazo para que uma cidade se torne mais inteligente? Alguns autores apontam a possibilidade de uma aproximação teórica entre a abordagem evolutiva e a literatura de cidades inteligentes, afirmando que devido à complexidade do desenvolvimento de cidades inteligentes, o planejamento de cidades inteligentes também é moldado por processos evolutivos. Assim, é necessário incorporar a noção de evolução nos processos de transformação urbana e que eles ocorram em uma determinada localização geográfica sendo condicionados por fatores contextuais locais. Como mencionado anteriormente, as cidades são inerentemente diferentes e têm problemas diferentes. Assim, medir o nível de desenvolvimento existente é crucial para prever os passos certos para aumentar a inteligência urbana. A inteligência deve ser vista como um continuum, no qual as partes interessadas podem implementar iniciativas para criar, melhorar ou alterar os elementos da cidade inteligente nessas diferentes dimensões da cidade. A noção de smartness pode ajudar as cidades a entender como esse processo de transformação urbana afeta suas dimensões e seu desempenho e, consequentemente, analisar o que deve ser feito para acelerá- lo. Nesse sentido, é importante que as cidades avaliem seu atual estágio de desenvolvimento. A avaliação do desenvolvimento de cidades inteligentes pode trazer múltiplos benefícios para diferentes partes interessadas. Permite identificar os pontos fortes e fracos da cidade, comparar cidades, monitorar e acompanhar a implementação de projetos, aumentar a transparência nos investimentos, possibilitar a formulação de políticas com base em evidências, aumentar a conscientização do cidadão e assim por diante. A quarta questão que surge é: como medir a inteligência de uma cidade? Em termos de avaliação de cidades inteligentes, muitos acadêmicos, organizações e empresas desenvolveram índices, kits de ferramentas e benchmarking para medir e classificar cidades inteligentes. Esses esquemas de avaliação podem fornecer uma boa visão geral sobre as características da cidade e seus pontos fortes e fracos, além de serem usados para mostrar sua posição competitiva. No entanto, a maioria deles negligencia os múltiplos processos inter-relacionados relacionados ao desenvolvimento da cidade inteligente, adotando uma abordagem somativa. Essa abordagem apresenta algumas limitações que não capturam adequadamente a inteligência de uma cidade. Considerando isso, os objetivos deste estudo são (1) identificar as dimensões e os elementos impulsionadores para tornar uma cidade mais inteligente, (2) entender o papel da organização dedicada a cidades inteligentes na governança de cidades inteligentes, (3) propor uma abordagem evolutiva framework para a análise do desenvolvimento de cidades inteligentes e (4) criar um modelo para medir a inteligência de uma cidade usando diferentes métodos, considerando o tipo de dados, sua manipulação e análise. Para atingir esses objetivos, a pesquisa se concentrou em entender o conceito de cidades inteligentes e que seu desenvolvimento depende de um processo não linear, que deve seguir algumas etapas como desenhar estratégias, implementá-las por meio de projetos para resolver os problemas urbanos atuais. Para isso, o estabelecimento de uma estrutura de governança é crucial para o sucesso do desenvolvimento de cidades inteligentes, pois é necessária a colaboração para criar soluções complexas e a legitimidade de uma visão. Portanto, uma organização dedicada é importante para articular as partes interessadas e impulsionar o desenvolvimento de projetos e iniciativas. No entanto, apenas redes colaborativas não resolverão os problemas urbanos per se. Deve ser identificado como criar, melhorar, mudar os elementos das dimensões hard e soft de uma cidade (ou seja, econômica, social, ambiental). É importante destacar que uma estratégia, projeto ou solução inteligente para ser inteligente de fato deve considerar que essas dimensões estão integradas e então afetam e são afetadas umas pelas outras. Além disso, é necessário incorporar neste discurso de planejamento e gestão urbana a noção de tempo e espaço, pois eventos passados podem afetar o atual estágio de desenvolvimento e as decisões presentes impactarão o futuro da cidade. Como processo evolutivo, cada cidade certamente seguirá caminhos diferentes, pois a dinâmica de seu desenvolvimento depende de como o (eco)sistema se configura e qual é o seu nível de inteligência. Também deve ser considerada a história da cidade e seu contexto para definir estratégias e projetos mais assertivos. Assim, para a análise do desenvolvimento de cidades inteligentes, é necessário aplicar um quadro evolutivo capaz de vincular o microcomportamento aos macroprocessos que ocorrem em cada território ao longo do tempo. Ao considerar o desenvolvimento de cidades inteligentes como um processo que muda o ambiente urbana e o comportamento dos stakeholders ao longo do tempo, há a necessidade de medir como isso está de fato ajudando (ou não) o desempenho urbano e como as cidades podem alcançar um desenvolvimento sustentável em uma forma mais eficiente. Este artigo tem como foco a mensuração da inteligência de um ecossistema de inovação urbana, pois fornece uma visão geral do estágio atual de desenvolvimento e a relação entre os elementos e dimensões, o que poderá orientar os formuladores de políticas e a sociedade sobre o que investir, como projetar uma estratégia abrangente e quando implementá-la

    Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study

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    This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machine’s ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Resilience and food security in a food systems context

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    This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners

    Evaluation of Multi-frequency Synthetic Aperture Radar for Subsurface Archaeological Prospection in Arid Environments

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    The discovery of the subsurface paleochannels in the Saharan Desert with the 1981 Shuttle Imaging Radar (SIR-A) sensor was hugely significant in the field of synthetic aperture radar (SAR) remote sensing. Although previous studies had indicated the ability of microwaves to penetrate the earth’s surface in arid environments, this was the first applicable instance of subsurface imaging using a spaceborne sensor. And the discovery of the ‘radar rivers’ with associated archaeological evidence in this inhospitable environment proved the existence of an earlier less arid paleoclimate that supported past populations. Since the 1980’s SAR subsurface prospection in arid environments has progressed, albeit primarily in the fields of hydrology and geology, with archaeology being investigated to a lesser extent. Currently there is a lack of standardised methods for data acquisition and processing regarding subsurface imaging, difficulties in image interpretation and insufficient supporting quantitative verification. These barriers keep SAR technology from becoming as integral as other remote sensing techniques in archaeological practice The main objective of this thesis is to undertake a multi-frequency SAR analysis across different site types in arid landscapes to evaluate and enhance techniques for analysing SAR within the context of archaeological subsurface prospection. The analysis and associated fieldwork aim to address the gap in the literature regarding field verification of SAR image interpretation and contribute to the understanding of SAR microwave penetration in arid environments. The results presented in this thesis demonstrate successful subsurface imaging of subtle feature(s) at the site of ‘Uqdat al-Bakrah, Oman with X-band data. Because shorter wavelengths are often ignored due to their limited penetration depths as compared to the C-band or L-band data, the effectiveness of X-band sensors in archaeological prospection at this site is significant. In addition, the associated ground penetrating radar and excavation fieldwork undertaken at ‘Uqdat al-Bakrah confirm the image interpretation and support the quantitative information regarding microwave penetration

    Towards an integrated vulnerability-based approach for evaluating, managing and mitigating earthquake risk in urban areas

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    Tese de doutoramento em Civil EngineeringSismos de grande intensidade, como aqueles que ocorreram na Turquía-Síria (2023) ou México (2017) deviam chamar a atenção para o projeto e implementação de ações proativas que conduzam à identificação de bens vulneráveis. A presente tese propõe um fluxo de trabalho relativamente simples para efetuar avaliações da vulnerabilidade sísmica à escala urbana mediante ferramentas digitais. Um modelo de vulnerabilidade baseado em parâmetros é adotado devido à afinidade que possui com o Catálogo Nacional de Monumentos Históricos mexicano. Uma primeira implementação do método (a grande escala) foi efetuada na cidade histórica de Atlixco (Puebla, México), demonstrando a sua aplicabilidade e algumas limitações, o que permitiu o desenvolvimento de uma estratégia para quantificar e considerar as incertezas epistémicas encontradas nos processos de aquisição de dados. Devido ao volume de dados tratado, foi preciso desenvolver meios robustos para obter, armazenar e gerir informações. O uso de Sistemas de Informação Geográfica, com programas à medida baseados em linguagem Python e a distribuição de ficheiros na ”nuvem”, facilitou a criação de bases de dados de escala urbana para facilitar a aquisição de dados em campo, os cálculos de vulnerabilidade e dano e, finalmente, a representação dos resultados. Este desenvolvimento foi a base para um segundo conjunto de trabalhos em municípios do estado de Morelos (México). A caracterização da vulnerabilidade sísmica de mais de 160 construções permitiu a avaliação da representatividade do método paramétrico pela comparação entre os níveis de dano teórico e os danos observados depois do terramoto de Puebla-Morelos (2017). Esta comparação foi a base para efetuar processos de calibração e ajuste assistidos por algoritmos de aprendizagem de máquina (Machine Learning), fornecendo bases para o desenvolvimento de modelos de vulnerabilidade à medida (mediante o uso de Inteligência Artificial), apoiados nas evidências de eventos sísmicos prévios.Strong seismic events like the ones of Türkiye-Syria (2023) or Mexico (2017) should guide our attention to the design and implementation of proactive actions aimed to identify vulnerable assets. This work is aimed to propose a suitable and easy-to-implement workflow for performing large-scale seismic vulnerability assessments in historic environments by means of digital tools. A vulnerability-oriented model based on parameters is adopted given its affinity with the Mexican Catalogue of Historical Monuments. A first large-scale implementation of this method in the historical city of Atlixco (Puebla, Mexico) demonstrated its suitability and some limitations, which lead to develop a strategy for quantifying and involving the epistemic uncertainties found during the data acquisition process. Given the volume of data that these analyses involve, it was necessary to develop robust data acquisition, storing and management strategies. The use of Geographical Information System environments together with customised Python-based programs and cloud-based distribution permitted to assemble urban databases for facilitating field data acquisition, performing vulnerability and damage calculations, and representing outcomes. This development was the base for performing a second large-scale assessment in selected municipalities of the state of Morelos (Mexico). The characterisation of the seismic vulnerability of more than 160 buildings permitted to assess the representativeness of the parametric vulnerability approach by comparing the theoretical damage estimations against the damages observed after the Puebla-Morelos 2017 Earthquakes. Such comparison is the base for performing a Machine Learning assisted process of calibration and adjustment, representing a feasible strategy for calibrating these vulnerability models by using Machine-Learning algorithms and the empirical evidence of damage in post-seismic scenarios.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), reference UIDB/04029/2020. This research had financial support provided by the Portuguese Foundation of Science and Technology (FCT) through the Analysis and Mitigation of Risks in Infrastructures (InfraRisk) program under the PhD grant PD/BD/150385/2019
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