113 research outputs found

    METROPOLITAN ENCHANTMENT AND DISENCHANTMENT. METROPOLITAN ANTHROPOLOGY FOR THE CONTEMPORARY LIVING MAP CONSTRUCTION

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    We can no longer interpret the contemporary metropolis as we did in the last century. The thought of civil economy regarding the contemporary Metropolis conflicts more or less radically with the merely acquisitive dimension of the behaviour of its citizens. What is needed is therefore a new capacity for imagining the economic-productive future of the city: hybrid social enterprises, economically sustainable, structured and capable of using technologies, could be a solution for producing value and distributing it fairly and inclusively. Metropolitan Urbanity is another issue to establish. Metropolis needs new spaces where inclusion can occur, and where a repository of the imagery can be recreated. What is the ontology behind the technique of metropolitan planning and management, its vision and its symbols? Competitiveness, speed, and meritocracy are political words, not technical ones. Metropolitan Urbanity is the characteristic of a polis that expresses itself in its public places. Today, however, public places are private ones that are destined for public use. The Common Good has always had a space of representation in the city, which was the public space. Today, the Green-Grey Infrastructure is the metropolitan city's monument that communicates a value for future generations and must therefore be recognised and imagined; it is the production of the metropolitan symbolic imagery, the new magic of the city

    Sensing the Cultural Significance with AI for Social Inclusion

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    Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes

    Building Blocks for IoT Analytics Internet-of-Things Analytics

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    Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

    Landscape and Tourism, Landscapes of Tourism

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    Landscape is central to tourism. It is key to the development, marketing/promotion, and consumption of tourism destinations, to triggering and sustaining tourism markets, and to enticing tourist dreams, fantasies, and behaviors. From ‘sight-seeing’ practices—at the basis of all tourism activities—landscape figures prominently all the way to the overall spatial planning and management of a destination for tourism development. The intertwined relationship between tourism and landscape comes with a series of costs and benefits, in the context of tourism landscapes. Landscapes of tourism reflect and stage recreational trends, multifunctional livelihood systems, conflicts and opportunities for employment and income generation, as well as human, cultural, and natural resource management and use. This Special Issue aims to enhance the interdisciplinary scientific dialogue on these issues and challenges, while highlighting their range and significance for tourism and the landscape, in terms of theory, empirical practice, approach, policy, ethics, and future prospects. Some of the questions posed for consideration here are: What are landscapes of tourism, for whom and how/why? What is the role of the landscape in tourism promotion, attraction, and experience? How does tourism affect the landscape? What lessons do the history and geography of tourism have to offer to tourism landscape stewardship? How may we best plan for and manage the landscape in the context of various forms of tourism growth and spread, at various scales? Scholarly advances in the past few decades have steadily built on a diverse—but spread-out and not adequately connected—bibliographical basis for future research. Much remains to be understood and exchanged as landscape and tourism—two highly complex and multifaceted scientific areas—come together in the scope of this Special Issue in a variety of ways across time, space, and culture

    Data Science in Healthcare

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    Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management

    Electronic Evidence and Electronic Signatures

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    In this updated edition of the well-established practitioner text, Stephen Mason and Daniel Seng have brought together a team of experts in the field to provide an exhaustive treatment of electronic evidence and electronic signatures. This fifth edition continues to follow the tradition in English evidence text books by basing the text on the law of England and Wales, with appropriate citations of relevant case law and legislation from other jurisdictions. Stephen Mason (of the Middle Temple, Barrister) is a leading authority on electronic evidence and electronic signatures, having advised global corporations and governments on these topics. He is also the editor of International Electronic Evidence (British Institute of International and Comparative Law 2008), and he founded the innovative international open access journal Digital Evidence and Electronic Signatures Law Review in 2004. Daniel Seng (Associate Professor, National University of Singapore) is the Director of the Centre for Technology, Robotics, AI and the Law (TRAIL). He teaches and researches information technology law and evidence law. Daniel was previously a partner and head of the technology practice at Messrs Rajah & Tann. He is also an active consultant to the World Intellectual Property Organization, where he has researched, delivered papers and published monographs on copyright exceptions for academic institutions, music copyright in the Asia Pacific and the liability of Internet intermediaries

    Algoritmos bio-inspirados para la detección de comunidades dinámicas en redes complejas

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    Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 22-07-202

    TMS Algarve 2022: sustainability challenges in tourism, hospitality and management – Tourism & Management Studies International Conference 16 - 19 November - Olhão, Portugal: Programme and abstracts

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    Book of abstracts of the TMS Algarve 2022 (Tourism & Management Studies International Conference) entitled Sustainability Challenges in Tourism, Hospitality and Management, held on Real Marina Hotel & Spa, Olhão, Portugal, 16-19 November 2022info:eu-repo/semantics/publishedVersio
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