6,583 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

    Neural Architecture Search: Insights from 1000 Papers

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    In the past decade, advances in deep learning have resulted in breakthroughs in a variety of areas, including computer vision, natural language understanding, speech recognition, and reinforcement learning. Specialized, high-performing neural architectures are crucial to the success of deep learning in these areas. Neural architecture search (NAS), the process of automating the design of neural architectures for a given task, is an inevitable next step in automating machine learning and has already outpaced the best human-designed architectures on many tasks. In the past few years, research in NAS has been progressing rapidly, with over 1000 papers released since 2020 (Deng and Lindauer, 2021). In this survey, we provide an organized and comprehensive guide to neural architecture search. We give a taxonomy of search spaces, algorithms, and speedup techniques, and we discuss resources such as benchmarks, best practices, other surveys, and open-source libraries

    Defining Service Level Agreements in Serverless Computing

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    The emergence of serverless computing has brought significant advancements to the delivery of computing resources to cloud users. With the abstraction of infrastructure, ecosystem, and execution environments, users could focus on their code while relying on the cloud provider to manage the abstracted layers. In addition, desirable features such as autoscaling and high availability became a provider’s responsibility and can be adopted by the user\u27s application at no extra overhead. Despite such advancements, significant challenges must be overcome as applications transition from monolithic stand-alone deployments to the ephemeral and stateless microservice model of serverless computing. These challenges pertain to the uniqueness of the conceptual and implementation models of serverless computing. One of the notable challenges is the complexity of defining Service Level Agreements (SLA) for serverless functions. As the serverless model shifts the administration of resources, ecosystem, and execution layers to the provider, users become mere consumers of the provider’s abstracted platform with no insight into its performance. Suboptimal conditions of the abstracted layers are not visible to the end-user who has no means to assess their performance. Thus, SLA in serverless computing must take into consideration the unique abstraction of its model. This work investigates the Service Level Agreement (SLA) modeling of serverless functions\u27 and serverless chains’ executions. We highlight how serverless SLA fundamentally differs from earlier cloud delivery models. We then propose an approach to define SLA for serverless functions by utilizing resource utilization fingerprints for functions\u27 executions and a method to assess if executions adhere to that SLA. We evaluate the approach’s accuracy in detecting SLA violations for a broad range of serverless application categories. Our validation results illustrate a high accuracy in detecting SLA violations resulting from resource contentions and provider’s ecosystem degradations. We conclude by presenting the empirical validation of our proposed approach, which could detect Execution-SLA violations with accuracy up to 99%

    Socio-endocrinology revisited: New tools to tackle old questions

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    Animals’ social environments impact their health and survival, but the proximate links between sociality and fitness are still not fully understood. In this thesis, I develop and apply new approaches to address an outstanding question within this sociality-fitness link: does grooming (a widely studied, positive social interaction) directly affect glucocorticoid concentrations (GCs; a group of steroid hormones indicating physiological stress) in a wild primate? To date, negative, long-term correlations between grooming and GCs have been found, but the logistical difficulties of studying proximate mechanisms in the wild leave knowledge gaps regarding the short-term, causal mechanisms that underpin this relationship. New technologies, such as collar-mounted tri-axial accelerometers, can provide the continuous behavioural data required to match grooming to non-invasive GC measures (Chapter 1). Using Chacma baboons (Papio ursinus) living on the Cape Peninsula, South Africa as a model system, I identify giving and receiving grooming using tri-axial accelerometers and supervised machine learning methods, with high overall accuracy (~80%) (Chapter 2). I then test what socio-ecological variables predict variation in faecal and urinary GCs (fGCs and uGCs) (Chapter 3). Shorter and rainy days are associated with higher fGCs and uGCs, respectively, suggesting that environmental conditions may impose stressors in the form of temporal bottlenecks. Indeed, I find that short days and days with more rain-hours are associated with reduced giving grooming (Chapter 4), and that this reduction is characterised by fewer and shorter grooming bouts. Finally, I test whether grooming predicts GCs, and find that while there is a long-term negative correlation between grooming and GCs, grooming in the short-term, in particular giving grooming, is associated with higher fGCs and uGCs (Chapter 5). I end with a discussion on how the new tools I applied have enabled me to advance our understanding of sociality and stress in primate social systems (Chapter 6)

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    A wind environment and Lorentz factors of tens explain gamma-ray bursts X-ray plateau

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    Gamma-ray bursts (GRBs) are known to have the most relativistic jets, with initial Lorentz factors in the order of a few hundreds. Many GRBs display an early X-ray light-curve plateau, which was not theoretically expected and therefore puzzled the community for many years. Here, we show that this observed signal is naturally obtained within the classical GRB "fireball" model, provided that the initial Lorentz factor is rather a few tens, and the expansion occurs into a medium-low density "wind". The range of Lorentz factors in GRB jets is thus much wider than previously thought and bridges an observational gap between mildly relativistic jets inferred in active galactic nuclei, to highly relativistic jets deduced in few extreme GRBs. Furthermore, long GRB progenitors are either not Wolf-Rayet stars, or the wind properties during the final stellar evolution phase are different than at earlier times. We discuss several testable predictions of this model.Comment: 61 pages, 24 figures, 9 tables. A final edited version will appear in Nature Communication

    Identification of Hindbrain Neural Substrates for Motor Initiation in the hatchling Xenopus laevis Tadpole

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    Animal survival profoundly depends on the ability to detect stimuli in the environment, process them and respond accordingly. In this respect, motor responses to a sensory stimulation evolved into a variety of coordinated movements, which involve the control of brain centres over spinal locomotor circuits. The hatchling Xenopus tadpole, even in its embryonic stage, is able to detect external sensory information and to swim away if the stimulus is considered noxious. To do so, the tadpole relies on well-known ascending sensory pathway, which carries the sensory information to the brain. When the stimulus is strong enough, descending interneurons are activated, leading to the excitation of spinal CPG neurons, which causes the undulatory movement of swimming. However, the activation of descending interneurons that marks the initiation of motor response appears after a long delay from the sensory stimulation. Furthermore, the long-latency response is variable in time, as observed in the slow-summating excitation measured in descending interneurons. These two features, i.e. long-latency and variability, cannot be explained by the firing time and pattern of the ascending sensory pathway of the Xenopus tadpole. Therefore, a novel neuronal population has been proposed to lie in the hindbrain of the tadpole, and being able to 'hold' the sensory information, thus accounting for the long and variable delay of swim initiation. In this work, the role of the hindbrain in the maintenance of the long and variable response to trunk skin stimulation is investigated in the Xenopustadpole at developmental stage 37/38. A multifaceted approach has been used to unravel the neuronal mechanisms underlying the delayed motor response, including behavioural experiments, electrophysiology analysis of fictive swimming, hindbrain extracellular recordings and imaging experiments. Two novel neuronal populations have been identified in the tadpole's hindbrain, which exhibit activation patterns compatible with the role of delaying the excitation of the spinal locomotor circuit. Future work on cellular properties and synaptic connections of these newly discovered populations might shed light on the mechanism of descending control active at embryonic stage. Identifying supraspinal neuronal populations in an embryonic organism could aid in understanding mechanisms of descending motor control in more complex vertebrates

    Optimización del rendimiento y la eficiencia energética en sistemas masivamente paralelos

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    RESUMEN Los sistemas heterogéneos son cada vez más relevantes, debido a sus capacidades de rendimiento y eficiencia energética, estando presentes en todo tipo de plataformas de cómputo, desde dispositivos embebidos y servidores, hasta nodos HPC de grandes centros de datos. Su complejidad hace que sean habitualmente usados bajo el paradigma de tareas y el modelo de programación host-device. Esto penaliza fuertemente el aprovechamiento de los aceleradores y el consumo energético del sistema, además de dificultar la adaptación de las aplicaciones. La co-ejecución permite que todos los dispositivos cooperen para computar el mismo problema, consumiendo menos tiempo y energía. No obstante, los programadores deben encargarse de toda la gestión de los dispositivos, la distribución de la carga y la portabilidad del código entre sistemas, complicando notablemente su programación. Esta tesis ofrece contribuciones para mejorar el rendimiento y la eficiencia energética en estos sistemas masivamente paralelos. Se realizan propuestas que abordan objetivos generalmente contrapuestos: se mejora la usabilidad y la programabilidad, a la vez que se garantiza una mayor abstracción y extensibilidad del sistema, y al mismo tiempo se aumenta el rendimiento, la escalabilidad y la eficiencia energética. Para ello, se proponen dos motores de ejecución con enfoques completamente distintos. EngineCL, centrado en OpenCL y con una API de alto nivel, favorece la máxima compatibilidad entre todo tipo de dispositivos y proporciona un sistema modular extensible. Su versatilidad permite adaptarlo a entornos para los que no fue concebido, como aplicaciones con ejecuciones restringidas por tiempo o simuladores HPC de dinámica molecular, como el utilizado en un centro de investigación internacional. Considerando las tendencias industriales y enfatizando la aplicabilidad profesional, CoexecutorRuntime proporciona un sistema flexible centrado en C++/SYCL que dota de soporte a la co-ejecución a la tecnología oneAPI. Este runtime acerca a los programadores al dominio del problema, posibilitando la explotación de estrategias dinámicas adaptativas que mejoran la eficiencia en todo tipo de aplicaciones.ABSTRACT Heterogeneous systems are becoming increasingly relevant, due to their performance and energy efficiency capabilities, being present in all types of computing platforms, from embedded devices and servers to HPC nodes in large data centers. Their complexity implies that they are usually used under the task paradigm and the host-device programming model. This strongly penalizes accelerator utilization and system energy consumption, as well as making it difficult to adapt applications. Co-execution allows all devices to simultaneously compute the same problem, cooperating to consume less time and energy. However, programmers must handle all device management, workload distribution and code portability between systems, significantly complicating their programming. This thesis offers contributions to improve performance and energy efficiency in these massively parallel systems. The proposals address the following generally conflicting objectives: usability and programmability are improved, while ensuring enhanced system abstraction and extensibility, and at the same time performance, scalability and energy efficiency are increased. To achieve this, two runtime systems with completely different approaches are proposed. EngineCL, focused on OpenCL and with a high-level API, provides an extensible modular system and favors maximum compatibility between all types of devices. Its versatility allows it to be adapted to environments for which it was not originally designed, including applications with time-constrained executions or molecular dynamics HPC simulators, such as the one used in an international research center. Considering industrial trends and emphasizing professional applicability, CoexecutorRuntime provides a flexible C++/SYCL-based system that provides co-execution support for oneAPI technology. This runtime brings programmers closer to the problem domain, enabling the exploitation of dynamic adaptive strategies that improve efficiency in all types of applications.Funding: This PhD has been supported by the Spanish Ministry of Education (FPU16/03299 grant), the Spanish Science and Technology Commission under contracts TIN2016-76635-C2-2-R and PID2019-105660RB-C22. This work has also been partially supported by the Mont-Blanc 3: European Scalable and Power Efficient HPC Platform based on Low-Power Embedded Technology project (G.A. No. 671697) from the European Union’s Horizon 2020 Research and Innovation Programme (H2020 Programme). Some activities have also been funded by the Spanish Science and Technology Commission under contract TIN2016-81840-REDT (CAPAP-H6 network). The Integration II: Hybrid programming models of Chapter 4 has been partially performed under the Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC Research Innovation Action under the H2020 Programme. In particular, the author gratefully acknowledges the support of the SPMT Department of the High Performance Computing Center Stuttgart (HLRS)

    A Novel Neurorehabilitation Model Designed to Examine the Neural Plasticity Involved in Disease

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    Parkinson's disease (PD) is a progressive neurodegenerative disorder that that is most often characterised for its motor impairments. However, people with PD (PwPD) often experience a range of mental health and non-motor issues alongside their physical symptoms. Exercise has shown to positively impact and improve PD motor symptoms, less research observations have been shown in PD mental health and non-motor symptoms. Dance is a great form of exercise which provides both aerobic and anaerobic movements. Dance is constantly changing providing a creative outlet, dance provides flexibility and balance/coordination, develops social skills thereby improving mental health, and lastly dance with music combination allows this form of exercise to be unique in that it encompasses a multisensory component that exercise alone cannot provide. My dissertation aims to understand how dance impacts PD motor, non-motor symptoms and if the changes are associated to specific brain related alterations. Using behavioral, motor and EEG approaches, I will present three separate experiments to test the effects of dance on people with PD by first studying the potential impacts of dance on short-term behavioral changes in PwPD and their overall Quality of Life (QoL) after a 12-week dance intervention. Second I will present a novel examination of the interaction of dance on both behavioural measures and electroencephalography (EEG) activity before and after the short-term (1.25 hour) course of a single dance class. The third study is a novel examination of the interaction of dance on the progression of both behavioural measures and non-motor symptoms over the long-term course of participating in multiple dance classes over a 3-year period of time. Finally, EEG activity changes over the long-term course of participating in multiple dance classes over a 3-year period of time is presented. The results of these studies strengthen the idea of dance being an alternative or additional therapy for PwPD and also provides putative neuroplastic changes in the diseased brain
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