11,165 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

    Hardware Acceleration of Neural Graphics

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    Rendering and inverse-rendering algorithms that drive conventional computer graphics have recently been superseded by neural representations (NR). NRs have recently been used to learn the geometric and the material properties of the scenes and use the information to synthesize photorealistic imagery, thereby promising a replacement for traditional rendering algorithms with scalable quality and predictable performance. In this work we ask the question: Does neural graphics (NG) need hardware support? We studied representative NG applications showing that, if we want to render 4k res. at 60FPS there is a gap of 1.5X-55X in the desired performance on current GPUs. For AR/VR applications, there is an even larger gap of 2-4 OOM between the desired performance and the required system power. We identify that the input encoding and the MLP kernels are the performance bottlenecks, consuming 72%,60% and 59% of application time for multi res. hashgrid, multi res. densegrid and low res. densegrid encodings, respectively. We propose a NG processing cluster, a scalable and flexible hardware architecture that directly accelerates the input encoding and MLP kernels through dedicated engines and supports a wide range of NG applications. We also accelerate the rest of the kernels by fusing them together in Vulkan, which leads to 9.94X kernel-level performance improvement compared to un-fused implementation of the pre-processing and the post-processing kernels. Our results show that, NGPC gives up to 58X end-to-end application-level performance improvement, for multi res. hashgrid encoding on average across the four NG applications, the performance benefits are 12X,20X,33X and 39X for the scaling factor of 8,16,32 and 64, respectively. Our results show that with multi res. hashgrid encoding, NGPC enables the rendering of 4k res. at 30FPS for NeRF and 8k res. at 120FPS for all our other NG applications

    ENTL: Embodied Navigation Trajectory Learner

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    We propose Embodied Navigation Trajectory Learner (ENTL), a method for extracting long sequence representations for embodied navigation. Our approach unifies world modeling, localization and imitation learning into a single sequence prediction task. We train our model using vector-quantized predictions of future states conditioned on current states and actions. ENTL's generic architecture enables the sharing of the the spatio-temporal sequence encoder for multiple challenging embodied tasks. We achieve competitive performance on navigation tasks using significantly less data than strong baselines while performing auxiliary tasks such as localization and future frame prediction (a proxy for world modeling). A key property of our approach is that the model is pre-trained without any explicit reward signal, which makes the resulting model generalizable to multiple tasks and environments

    Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review

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    Globally, the external Internet is increasingly being connected to the contemporary industrial control system. As a result, there is an immediate need to protect the network from several threats. The key infrastructure of industrial activity may be protected from harm by using an intrusion detection system (IDS), a preventive measure mechanism, to recognize new kinds of dangerous threats and hostile activities. The most recent artificial intelligence (AI) techniques used to create IDS in many kinds of industrial control networks are examined in this study, with a particular emphasis on IDS-based deep transfer learning (DTL). This latter can be seen as a type of information fusion that merge, and/or adapt knowledge from multiple domains to enhance the performance of the target task, particularly when the labeled data in the target domain is scarce. Publications issued after 2015 were taken into account. These selected publications were divided into three categories: DTL-only and IDS-only are involved in the introduction and background, and DTL-based IDS papers are involved in the core papers of this review. Researchers will be able to have a better grasp of the current state of DTL approaches used in IDS in many different types of networks by reading this review paper. Other useful information, such as the datasets used, the sort of DTL employed, the pre-trained network, IDS techniques, the evaluation metrics including accuracy/F-score and false alarm rate (FAR), and the improvement gained, were also covered. The algorithms, and methods used in several studies, or illustrate deeply and clearly the principle in any DTL-based IDS subcategory are presented to the reader

    Victims' Access to Justice in Trinidad and Tobago: An exploratory study of experiences and challenges of accessing criminal justice in a post-colonial society

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    This thesis investigates victims' access to justice in Trinidad and Tobago, using their own narratives. It seeks to capture how their experiences affected their identities as victims and citizens, alongside their perceptions of legitimacy regarding the criminal justice system. While there have been some reforms in the administration of criminal justice in Trinidad and Tobago, such reforms have not focused on victims' accessibility to the justice system. Using grounded theory methodology, qualitative data was collected through 31 in-depth interviews with victims and victim advocates. The analysis found that victims experienced interpersonal, structural, and systemic barriers at varying levels throughout the criminal justice system, which manifested as institutionalized secondary victimization, silencing and inequality. This thesis argues that such experiences not only served to appropriate conflict but demonstrates that access is often given in a very narrow sense. Furthermore, it shows a failure to encompass access to justice as appropriated conflicts are left to stagnate in the system as there is often very little resolution. Adopting a postcolonial lens to analyse victims' experiences, the analysis identified othering practices that served to institutionalize the vulnerability and powerlessness associated with victim identities. Here, it is argued that these othering practices also affected the rights consciousness of victims, delegitimating their identities as citizens. Moreover, as a result of their experiences, victims had mixed perceptions of the justice system. It is argued that while the system is a legitimate authority victims' endorsement of the system is questionable, therefore victims' experiences suggest that there is a reinforcement of the system's legal hegemony. The findings suggest that within the legal system of Trinidad and Tobago, legacies of colonialism shape the postcolonial present as the psychology and inequalities of the past are present in the interactions and processes of justice. These findings are relevant for policymakers in Trinidad and Tobago and other regions. From this study it is recognized that, to improve access to justice for victims, there needs to be a move towards victim empowerment that promotes resilience and enhances social capital. Going forward it is noted that there is a need for further research

    Strategies for Early Learners

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    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp

    Sponsorship image and value creation in E-sports

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    .E-sports games can drive the sports industry forward and sponsorship is the best way to engage consumers of this new sport. The purpose of this study is to examine the effect of sponsorship image and consumer participation in co-creation consumption activities on fans’ sponsorship response (represented by the variables interest, purchase intention and word of mouth) in e-sports. Four antecedent variables build sponsorship image (i.e., ubiquity of sport, sincerity of sponsor, attitude to sponsor and team identification). A quantitative approach is used for the purposes of this study. Some 445 questionnaires were filled in by fans who watch e-sports in Spain; these are analyzed using partial least squares structural equation modeling (PLS-SEM). The outcomes show that sponsor antecedents are crucial factors if a sponsor wants to change their sponsorship image and influence sponsorship response, and that it is also possible to use participation to improve responsesS
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