15,832 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

    Welcome to Planet B - Fruit Art- Ars Electronica 2022

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     8K 3D Stereo Gigapixel immersive fruit art-based experience, gravitating around the invisible world of fruit. Visitors are virtually transferred “inside” the intriguing kinetic world of fruit (that is to say the “mature ovaries of nature” the fleshy or dry ripened ovary of a flowering plant, enclosing the seed/s.) Gaining unthinkable insights into the fruit’s secret wonders and triggering emotional connections and affinity to the natural world. The avatar “AIAG” (the reverse of GAIA) coexists within FA-RVsVR's METAVERSE. A 3D hybrid anthropomorphic, winged creature, with special power and abilities. She is in part a human/ Franz Fischnaller (IT) With the collaboration of: Dr. Satre Stuelke (US) and Jéssica Roude (AR) FRUIT ART... REAL Vs.—VIRTUAL LIFE (FA-RVsVR) woman, a cyborg, a birth, and a tree. Her wings are covered by smart skin and leaves and her tail is a root tree. Tech: Digital animation, visual effects (VFX), CT SCAN [computed tomography scan], scientific data visualization, blended with 3D Immersive point clouds and Photogrammetry visualization, mixed and arranged with music and special sound effects. Franz Fischnaller (IT) / With the collaboration of Dr. Satre Stuelke (US), Jéssica Roude (AR) / 3D modeling assistance: Bingqing Dong. / 0riginal CT and MRI fruits scanners have been provided by Dr. Satre Stuelke. </p

    Bayesian networks for disease diagnosis: What are they, who has used them and how?

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    A Bayesian network (BN) is a probabilistic graph based on Bayes' theorem, used to show dependencies or cause-and-effect relationships between variables. They are widely applied in diagnostic processes since they allow the incorporation of medical knowledge to the model while expressing uncertainty in terms of probability. This systematic review presents the state of the art in the applications of BNs in medicine in general and in the diagnosis and prognosis of diseases in particular. Indexed articles from the last 40 years were included. The studies generally used the typical measures of diagnostic and prognostic accuracy: sensitivity, specificity, accuracy, precision, and the area under the ROC curve. Overall, we found that disease diagnosis and prognosis based on BNs can be successfully used to model complex medical problems that require reasoning under conditions of uncertainty.Comment: 22 pages, 5 figures, 1 table, Student PhD first pape

    Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective

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    This paper introduces a comprehensive, multi-stage machine learning methodology that effectively integrates information systems and artificial intelligence to enhance decision-making processes within the domain of operations research. The proposed framework adeptly addresses common limitations of existing solutions, such as the neglect of data-driven estimation for vital production parameters, exclusive generation of point forecasts without considering model uncertainty, and lacking explanations regarding the sources of such uncertainty. Our approach employs Quantile Regression Forests for generating interval predictions, alongside both local and global variants of SHapley Additive Explanations for the examined predictive process monitoring problem. The practical applicability of the proposed methodology is substantiated through a real-world production planning case study, emphasizing the potential of prescriptive analytics in refining decision-making procedures. This paper accentuates the imperative of addressing these challenges to fully harness the extensive and rich data resources accessible for well-informed decision-making

    Grand challenges in entomology: Priorities for action in the coming decades

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    Entomology is key to understanding terrestrial and freshwater ecosystems at a time of unprecedented anthropogenic environmental change and offers substantial untapped potential to benefit humanity in a variety of ways, from improving agricultural practices to managing vector-borne diseases and inspiring technological advances. We identified high priority challenges for entomology using an inclusive, open, and democratic four-stage prioritisation approach, conducted among the membership and affiliates (hereafter ‘members’) of the UK-based Royal Entomological Society (RES). A list of 710 challenges was gathered from 189 RES members. Thematic analysis was used to group suggestions, followed by an online vote to determine initial priorities, which were subsequently ranked during an online workshop involving 37 participants. The outcome was a set of 61 priority challenges within four groupings of related themes: (i) ‘Fundamental Research’ (themes: Taxonomy, ‘Blue Skies’ [defined as research ideas without immediate practical application], Methods and Techniques); (ii) ‘Anthropogenic Impacts and Conservation’ (themes: Anthropogenic Impacts, Conservation Options); (iii) ‘Uses, Ecosystem Services and Disservices’ (themes: Ecosystem Benefits, Technology and Resources [use of insects as a resource, or as inspiration], Pests); (iv) ‘Collaboration, Engagement and Training’ (themes: Knowledge Access, Training and Collaboration, Societal Engagement). Priority challenges encompass research questions, funding objectives, new technologies, and priorities for outreach and engagement. Examples include training taxonomists, establishing a global network of insect monitoring sites, understanding the extent of insect declines, exploring roles of cultivated insects in food supply chains, and connecting professional with amateur entomologists. Responses to different challenges could be led by amateur and professional entomologists, at all career stages. Overall, the challenges provide a diverse array of options to inspire and initiate entomological activities and reveal the potential of entomology to contribute to addressing global challenges related to human health and well-being, and environmental change

    Corporate Social Responsibility: the institutionalization of ESG

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    Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective

    Re-prioritizing climate services for agriculture: Insights from Bangladesh

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    Considerable progress has been made in establishing climate service capabilities over the last few decades, but the gap between the resulting services and national needs remains large. Using climate services for agriculture in Bangladesh as a case study example, we highlight mismatches between local needs on the one hand, and international initiatives that have focused largely on prediction on the other, and we make suggestions for addressing such mismatches in similar settings. To achieve greater benefit at the national level, there should be a stronger focus on addressing important preliminaries for building services. These preliminaries include the identification of priorities, the definition of responsibilities and expectations, the development of climate services skills, and the construction of a high-quality and easily usable national climate record. Once appropriate institutional, human resources and data infrastructure are in place, the implementation of a climate monitoring and watch system would form a more logical basis for initial climate service implementation than attempting to promote sub-seasonal to seasonal climate forecasting, especially when and where the inherent predictability is limited at best. When and where forecasting at these scales is viable, efforts should focus on defining and predicting high-impact events important for decision making, rather than on simple seasonal aggregates that often correlate poorly with outcomes. Some such forecasts may be more skillful than the 3- to 4-month seasonal aggregates that have become the internationally adopted standard. By establishing a firm foundation for climate services within National Meteorological Services, there is a greater chance that individual climate service development initiatives will be sustainable after their respective project lifetimes

    Study on the determination of the body and mental state of adult age patients

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    Our study comes from the desire to highlight certain problems faced by adulthood, as well as the awareness of practicing physical exercise in water and on land, in order to combat them. Hypothesis of the work; it is assumed that through a thorough study in terms of body composition and mental status of patients of adult age, we will identify some problems that arise during this period of life and at the same time we will be able to develop truthful programs by applying physical means. The purpose of our work consists in highlighting the main problems of normoponderality and mental status on the patients subjected to the study by applying various tests that will highlight these aspects. Objectives of the study: Identification of body composition and mental status of adult patients; Patients' awareness of the normoponderality and mental problems arising from the applied tests; Promoting physical activities on land and in water, in adulthood. The result of questioning the subjects subjected to the study on the evaluation of the mental status revealed the fact that they have a temporal, spatial orientation, an adequate memory and attention, as well as a reading-writing and copying capacity corresponding to the age, and the determination of the body composition was achieved with the help of the "Tanita" device through which it was found an average of the group of subjects of 43.13% fat, 25,80 % muscle mass, 6,83 % bone mass, and water 42,22 %

    Countermeasures for the majority attack in blockchain distributed systems

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    La tecnología Blockchain es considerada como uno de los paradigmas informáticos más importantes posterior al Internet; en función a sus características únicas que la hacen ideal para registrar, verificar y administrar información de diferentes transacciones. A pesar de esto, Blockchain se enfrenta a diferentes problemas de seguridad, siendo el ataque del 51% o ataque mayoritario uno de los más importantes. Este consiste en que uno o más mineros tomen el control de al menos el 51% del Hash extraído o del cómputo en una red; de modo que un minero puede manipular y modificar arbitrariamente la información registrada en esta tecnología. Este trabajo se enfocó en diseñar e implementar estrategias de detección y mitigación de ataques mayoritarios (51% de ataque) en un sistema distribuido Blockchain, a partir de la caracterización del comportamiento de los mineros. Para lograr esto, se analizó y evaluó el Hash Rate / Share de los mineros de Bitcoin y Crypto Ethereum, seguido del diseño e implementación de un protocolo de consenso para controlar el poder de cómputo de los mineros. Posteriormente, se realizó la exploración y evaluación de modelos de Machine Learning para detectar software malicioso de tipo Cryptojacking.DoctoradoDoctor en Ingeniería de Sistemas y Computació

    Worldtube excision method for intermediate-mass-ratio inspirals: scalar-field model in 3+1 dimensions

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    Binary black hole simulations become increasingly more computationally expensive with smaller mass ratios, partly because of the longer evolution time, and partly because the lengthscale disparity dictates smaller time steps. The program initiated by Dhesi et al. (arXiv:2109.03531) explores a method for alleviating the scale disparity in simulations with mass ratios in the intermediate astrophysical range (104q10210^{-4} \lesssim q \lesssim 10^{-2}), where purely perturbative methods may not be adequate. A region ("worldtube") much larger than the small black hole is excised from the numerical domain, and replaced with an analytical model approximating a tidally deformed black hole. Here we apply this idea to a toy model of a scalar charge in a fixed circular geodesic orbit around a Schwarzschild black hole, solving for the massless Klein-Gordon field. This is a first implementation of the worldtube excision method in full 3+1 dimensions. We demonstrate the accuracy and efficiency of the method, and discuss the steps towards applying it for evolving orbits and, ultimately, in the binary black-hole scenario. Our implementation is publicly accessible in the SpECTRE numerical relativity code.Comment: 19 pages, 10 figure
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