11,053 research outputs found

    The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

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    The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    L’Asie du Sud-Est 2023 : bilan, enjeux et perspectives

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    Chaque année, l’Institut de recherche sur l’Asie du Sud-Est contemporaine (IRASEC), basé à Bangkok, mobilise une vingtaine de chercheurs et d’experts pour mieux comprendre l’actualité régionale de ce carrefour économique, culturel et religieux, au cœur de l’Indo-Pacifique. Cette collection permet de suivre au fil des ans l’évolution des grands enjeux contemporains de cette région continentale et archipélagique de plus de 680 millions d’habitants, et d’en comprendre les dynamiques d’intégration régionale et de connectivités avec le reste du monde. L’Asie du Sud-Est 2023 propose une analyse synthétique et détaillée des principaux événements politiques et diplomatiques, ainsi que des évolutions économiques, sociales et environnementales de l’année 2022 dans chacun des onze pays de la région. Ce décryptage est complété pour chaque pays par un focus sur deux personnalités de l’année et une actualité marquante en image. L’ouvrage propose également cinq dossiers thématiques qui abordent des sujets traités à l’échelle régionale sud-est asiatique : les ressorts institutionnels de l’approche de santé intégrée One Health, le vieillissement de la population et sa prise en compte par les politiques publiques, les câbles sous-marins au cœur de la connectivité sud-est asiatique, l’aménagement du bassin du Mékong et ses multiples acteurs, et les enjeux politiques et linguistiques des langues transnationales. Des outils pratiques sont également disponibles : une fiche et une chronologie par pays et un cahier des principaux indicateurs démographiques, sociaux, économiques et environnementaux

    Urban endoliths: incidental microbial communities occurring inside concrete

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    Concrete is now a prevalent type of synthetic rock, and its production and usage have major environmental implications. Yet, assessments of ordinary concrete have rarely considered that concrete itself is potential habitat for a globally important microbial guild, the endolithic microbes, which live inside rocks and other mineralized substrates. We sought evidence that many common concrete structures harbor endolithic microbial communities and that these communities vary widely depending on the conditions imposed by the concrete. In Summer 2022, we obtained samples from various concrete structures found throughout Lubbock, Texas, USA and subjected the internal (non-surface) portions of each sample to controlled microbial life detection tests including culture tests, DNA quantifications, DNA amplification tests, and ATP assays. The great preponderance of positive life detection results from our concrete samples suggests that most modern concrete hosts cryptic endolith communities composed of bacteria, sometimes co-occurring with fungi and/or archaea. Moreover, many of these microbes are viable, culturable, and identifiable via genetic analysis. Endolith signatures varied widely across concrete samples; some samples only yielded trace evidence of possibly dormant microbes while other samples contained much more microbial biomass and diversity, on par with some low-biomass soils. Pre-cast masonry units and fragments of poured concrete found underwater generally had the most endolith signatures, suggesting that concrete forms and environmental positioning affect endolithy. Endolith biosignatures were generally greater in less dense and less alkaline concrete samples. So, concrete endolith communities may be as ubiquitous and diverse as the concrete structures they inhabit. We propose further research of concrete endoliths to help clarify the role of modern concrete in our rapidly urbanizing biosphere

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    Post-Millennial Queer Sensibility: Collaborative Authorship as Disidentification in Queer Intertextual Commodities

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    This dissertation is examining LGBTQ+ audiences and creatives collaborating in the creation of new media texts like web shows, podcasts, and video games. The study focuses on three main objects or media texts: Carmilla (web series), Welcome to Night Vale (podcast), and Undertale (video game). These texts are transmedia objects or intertextual commodities. I argue that by using queer gestures of collaborative authorship that reaches out to the audience for canonical contribution create an emerging queer production culture that disidentifies with capitalism even as it negotiates capitalistic structures. The post-millennial queer sensibility is a constellation of aesthetics, self-representation, alternative financing, and interactivity that prioritizes community, trust, and authenticity using new technologies for co-creation. Within my study, there are four key tactics or queer gestures being explored: remediation, radical ambiguity and multi-forms as queer aesthetics, audience self-representation, alternative financing like micropatronage & licensed fan-made merchandise, and interactivity as performance. The goal of this project is to better understand the changing conceptions of authorship/ownership, canon/fanon (official text/fan created extensions), and community/capitalism in queer subcultures as an indicator of the potential change in more mainstream cultural attitudes. The project takes into consideration a variety of intersecting identities including gender, race, class, and of course sexual orientation in its analysis. By examining the legal discourse around collaborative authorship, the real-life production practices, and audience-creator interactions and attitudes, this study provides insight into how media creatives work with audiences to co-create self-representative media, the motivations, and rewards for creative, audiences, and owners. This study aims to contribute towards a fuller understanding of queer production cultures and audience reception of these media texts, of which there is relatively little academic information. Specifically, the study mines for insights into the changing attitudes towards authorship, ownership, and collaboration within queer indie media projects, especially as these objects are relying on the self-representation of both audiences and creatives in the formation of the text

    Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana

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    Tesis por compendio[ES] Actualmente, los responsables de tomar decisiones contra el cambio climático carecen de herramientas para desarrollar inventarios de emisiones de gases de efecto invernadero (GEI) con suficiente rigor científico-técnico y precisión para priorizar e invertir los recursos disponibles de manera eficiente en las medidas necesarias para luchar contra el cambio climático. Por ello, en esta tesis se expone el desarrollo de un sistema de información territorial y sectorial (SITE) para monitorear las emisiones de GEI que sirva como herramienta de gobernanza climática local y regional. SITE combina las ventajas de los enfoques metodológicos descendente o top-down (de arriba hacia abajo) y ascendente o bottom-up (de abajo hacia arriba), para lograr un enfoque híbrido innovador para contabilizar y gestionar de manera eficiente las emisiones de GEI. Por tanto, en esta tesis se definen los diferentes desarrollos metodológicos, tanto generales como específicos de sectores clave del Panel Intergubernamental de Cambio Climático (IPPC) (edificación, transporte, sector forestal, etc.), un desarrollo informático para la parte de SITE que se ejecuta del lado del servidor, que de ahora en adelante denominaremos back-end del sistema, y siete implementaciones como casos de estudio representativos, a diferentes escalas y aplicados sobre diferentes sectores. Estas implementaciones a diferentes escalas y sectores demuestran el potencial del sistema como herramienta de apoyo en la toma de decisión contra el cambio climático a nivel regional y local. Las diferentes implementaciones en casos piloto representativos, tanto a nivel regional en la Comunitat Valenciana como a nivel local en municipios grandes (València) y medianos (Quart de Poblet y Llíria) muestran el potencial de adaptación territorial y sectorial que tiene la herramienta. Las metodologías desarrolladas para los sectores específicos de tráfico rodado, edificación o sector forestal, ofrecen cuantificaciones con una resolución espacial con gran capacidad de optimizar las políticas locales y regionales. Por tanto, la herramienta cuenta con un gran potencial de escalabilidad y gran capacidad de mejora continua mediante la inclusión de nuevos enfoques metodológicos, adaptación de las metodologías a la disponibilidad de datos, metodologías concretas para sectores clave y actualización a las mejores metodologías disponibles derivadas de actividades de investigación de la comunidad científica.[CA] Actualment, els responsables de prendre decisions contra el canvi climàtic no tenen eines per aconseguir inventaris d'emissions de gasos d'efecte hivernacle (GEH) amb prou cientificotècnic rigor, precisió i integritat per invertir els recursos disponibles de manera eficient en les mesures necessàries contra el canvi climàtic. Per això, en aquesta tesis se exposa el desenvolupa un sistema d'informació territorial i sectorial (SITE) per monitoritzar les emissions de GEH com a eina de governança climàtica local i regional. Aquest sistema combina els avantatges dels enfocaments metodològics descendent o top-down (de dalt a baix) i ascendent o bottom-up (de baix a dalt), per aconseguir un enfocament híbrid innovador per comptabilitzar i gestionar de manera eficient les emissions de GEH. Per tant, en aquesta tesi doctoral es descriuen els diferents desenvolupaments metodològics, tant generals com específics de sectors clau del Panel Intergovernamental contra el Canvi Climàtic (edificació, transport, forestal, etc.), un desenvolupament informàtic per al back-end del sistema i set implementacions com a casos d'estudi representatius, a diferents escales, amb els diferents enfocaments metodològics i aplicats sobre diferents sectors. Això queda descrit en sis capítols. Aquestes implementacions a diferents escales i sectors demostren el potencial del sistema com a eina de suport en la presa de decisió contra el canvi climàtic a nivell regional i local. Les diferents implementacions en casos pilot representatius, tant a nivell regional a la Comunitat Valenciana com a nivell local en municipis grans (València) i mitjans (Quart de Poblet i Llíria,) mostren el potencial d'adaptació territorial i sectorial que té l'eina. Les metodologies desenvolupades per als sectors específics de trànsit rodat, edificació i forestal, ofereixen quantificacions amb una resolució espacial amb gran capacitat d'optimitzar les polítiques locals i regionals. Per tant, l'eina compta amb un gran potencial d'escalabilitat i gran capacitat de millora contínua mitjançant la inclusió de nous enfocaments metodològics, adaptació de les metodologies a la disponibilitat de dades, metodologies concretes per a sectors clau, i actualització a les millors metodologies disponibles derivades de activitats de investigació de la comunitat científica.[EN] Currently, regional and local decision-makers lack of tools to achieve greenhouse gases (GHG) emissions inventories with enough rigor, accuracy and completeness in order to prioritize available resources efficiently against climate change. Thus, in this thesis the development of a territorial and sectoral information system (SITE) to monitor GHG emissions as a local and regional climate governance tool is exposed. This system combines the advantages of both, top-down and bottom-up approaches, to achieve an innovative hybrid approach to account and manage efficiently GHG emissions. Furthermore, this thesis defines the methodologies developed, a computer proposal for the back-end of the system and seven implementations as representative case studies at different scales (local and regional level), with the different methodological approaches and applied to different sectors. Thus, these implementations demonstrate the potential of the system as decision-making tool against climate change at the regional and local level as climate governance tool. The different implementations in representative pilot cases, both at the regional level in the Valencian Community and at the local level in large (Valencia) and medium-sized municipalities (Quart de Poblet and Llíria) demonstrate the potential for territorial and sectoral adaptation of the system developed. The methodologies developed for the specific sectors of road transport, building and forestry, offer quantifications with a spatial resolution with a great capacity to optimize local and regional policies. Therefore, the tool has a great potential for scalability and a great capacity for continuous improvement through the inclusion of new methodological approaches, adapting the methodologies to the availability of data, specific methodologies for key sectors, and updating to the best methodologies available in the scientific community.Lorenzo Sáez, E. (2022). Desarrollo de una herramienta integral de gestión de gases de efecto invernadero para la toma de decisión contra el cambio climático a nivel regional y local en la Comunitat Valenciana [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181662TESISCompendi

    Organizations decentered: data objects, technology and knowledge

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    Data are no longer simply a component of administrative and managerial work but a pervasive resource and medium through which organizations come to know and act upon the contingencies they confront. We theorize how the ongoing technological developments reinforce the traditional functions of data as instruments of management and control but also reframe and extend their role. By rendering data as technical entities, digital technologies transform the process of knowing and the knowledge functions data fulfil in socioeconomic life. These functions are most of the times mediated by putting together disperse and steadily updatable data in more stable entities we refer to as data objects. Users, customers, products, and physical machines rendered as data objects become the technical and cognitive means through which organizational knowledge, patterns, and practices develop. Such conditions loosen the dependence of data from domain knowledge, reorder the relative significance of internal versus external references in organizations, and contribute to a paradigmatic contemporary development that we identify with the decentering of organizations of which digital platforms are an important specimen
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