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Almost a century ago Modernism challenged the structure of the city and reshaped its physical space in order to, amongst other things, accommodate new transportation infrastructure and road networks proclaiming the, nowadays much-debated ‘scientificated’ pursuit of efficiency for the city. This transformation has had a great impact on the way humans still design, move in, occupy and experience the city. Today major cities in Europe, such as Paris and London, are considering banning vehicles from their historic centers. In parallel, significant effort is currently underway internationally by designers, architects, and engineers to integrate innovative technologies and sophisticated solutions for energy production, management, and storage, as well as for efficient energy consumption, into the architecture of buildings. In general, this effort seeks for new technologies and design methods (e.g., DesignBuilder with EnergyPlus simulation engine; Rhicoceros3D with Grasshopper plugin and Ecotect, Radiance and EnergyPlus tools) that would enable a holistic approach to the spatial design of Near-Zero Energy buildings, so that their ecological benefits are an added value to the architectural design and a building’s visual, and material, impact on its surrounding space. The paper inquires how the integration of such technological infrastructure and performance-orientated interfaces changes yet again the structure and form of cities, and to what extent it safeguards social rights and enables equal access to common resources. Drawing from preliminary results and initial considerations of ongoing research that involve the construction of four innovative NZE settlements across Europe, in the context of the EU-funded ZERO-PLUS project, this paper discusses the integration of novel infrastructure in communal spaces of these settlements. In doing so, it contributes to the debate about smart communities and their role in the sustainable management of housing developments and settlements that are designed and developed with the concept of smart territories.

Abstract Contemporary discourse points to the central role that heritage plays in the process of enabling groups of various cultural or ethnic background to strengthen their feeling of belonging and sharing in society. Safeguarding heritage is also valued highly in the priorities of the European Commission. As a result, there have been several long-term initiatives involving the digitisation, annotation and cataloguing of tangible cultural heritage in museums and collections. Specifically, for built heritage, a pressing challenge is that historical monuments such as buildings, temples, churches or city fortification infrastructures are hard to document due to their historic palimpsest; spatial transformations, actions of destruction, reuse of material, or continuous urban development that covers traces and changes the formal integrity and identity of a cultural heritage site. The ability to reason about a monument’s form is crucial for efficient documentation and cataloguing. This paper presents a 3D digitisation workflow through the involvement of reality capture technologies for the annotation and structure analysis of built heritage with the use of 3D Convolutional Neural Networks (3D CNNs) for classification purposes. The presented workflow contributes a new approach to the identification of a building’s architectural components (e.g., arch, dome) and to the study of the stylistic influences (e.g., Gothic, Byzantine) of building parts. In doing so this workflow can assist in tracking a building’s history, identifying its construction period and comparing it to other buildings of the same period. This process can contribute to educational and research activities, as well as facilitate the automated classification of datasets in digital repositories for scholarly research in digital humanities.

We investigated the evolution and transformation of scientific knowledge in the early modern period, analyzing more than 350 different editions of textbooks used for teaching astronomy in European universities from the late fifteenth century to mid-seventeenth century. These historical sources constitute the Sphaera Corpus. By examining different semantic relations among individual parts of each edition on record, we built a multiplex network consisting of six layers, as well as the aggregated network built from the superposition of all the layers. The network analysis reveals the emergence of five different communities. The contribution of each layer in shaping the communities and the properties of each community are studied. The most influential books in the corpus are found by calculating the average age of all the out-going and in-coming links for each book. A small group of editions is identified as a transmitter of knowledge as they bridge past knowledge to the future through a long temporal interval. Our analysis, moreover, identifies the most disruptive books. These books introduce new knowledge that is then adopted by almost all the books published afterwards until the end of the whole period of study. The historical research on the content of the identified books, as an empirical test, finally corroborates the results of all our analyses. Comment: 19 pages, 9 figures

We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. We present the approach by explaining its core paradigm that consists in pairing specific types of LRs with specific exercises, by detailing both its strengths and challenges, and by discussing how much these challenges have been addressed at present. Accordingly, we also report on on-going proof-of-concept efforts aiming at developing the first prototypical implementation of the approach in order to correct and extend an LR called ConceptNet based on the input crowdsourced from language learners. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of the generic approach. Finally, we exemplify how it can be used in several language learning scenarios to produce a multitude of NLP resources and how it can therefore alleviate the long-standing NLP issue of the lack of LRs. peer-reviewed