15,543 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

    One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era

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    OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quickly attracted numerous users with extensive media coverage. Such unprecedented attention has also motivated numerous researchers to investigate ChatGPT from various aspects. According to Google scholar, there are more than 500 articles with ChatGPT in their titles or mentioning it in their abstracts. Considering this, a review is urgently needed, and our work fills this gap. Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges. Moreover, we present an outlook on how ChatGPT might evolve to realize general-purpose AIGC (a.k.a. AI-generated content), which will be a significant milestone for the development of AGI.Comment: A Survey on ChatGPT and GPT-4, 29 pages. Feedback is appreciated ([email protected]

    Design of Flipped Lessons in the Classroom and Opinions of Teachers with Different Degrees of Experience

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    The flipped classroom approach has gained significant popularity recently due to its ability to facilitate active learning and leverage technology to enhance student's learning habits. Previous research has explored the benefits and drawbacks of this approach, highlighting its potential to improve student engagement, motivation, and achievement. However, despite the growing interest in flipped classroom approach, more is needed to know about teachers' perceptions of this model and how these perceptions may vary based on years of experience.The current study aims to address this gap in the literature by examining 73 Kindergarten through 12th-grade teachers' perceptions of flipped classroom approach and identifying differences in these perceptions based on years of experience. To this end, the study utilized a survey instrument developed by Gough et al. (2017) to gather data on teachers' attitudes toward flipped classroom approach across five domains, including instructional practices, student considerations, technology use, communication, and practice.By analyzing the survey data, the study identified significant differences in teachers' perceptions of flipped classroom approach based on years of experience. Specifically, teachers with 0-3, 3-5, and more than 5 years of teaching experience had different judgments in instructional practices and student considerations. These findings suggest that teachers' perceptions of flipped classroom approach may be influenced by their experience level and that targeted professional development and training may be necessary to support teachers in adopting this approach effectively.Overall, this study contributes to the literature on flipped classroom approach by shedding light on teachers' perceptions of this model and how these perceptions vary based on years of experience. The findings provide insights into the elements that could enhance the effectiveness of flipped classroom approach, such as differentiation, more videos for specific learners, communication with all parties, and practice. The practical implications of these findings for K12 settings are discussed in the subsequent sections of this article. Keywords: Flipped classroom, teacher perceptions, K12 classrooms, teaching experience DOI: 10.7176/JEP/14-9-05 Publication date:March 31st 202

    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

    A Visual Modeling Method for Spatiotemporal and Multidimensional Features in Epidemiological Analysis: Applied COVID-19 Aggregated Datasets

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    The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological analysis. However, most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation, resulting in a lack of quantitative and qualitative evidence. To address this issue, we have developed a portrait-based visual modeling method called +msRNAer. This method considers the spatiotemporal features of virus transmission patterns and the multidimensional features of objective risk factors in communities, enabling portrait-based exploration and comparison in epidemiological analysis. We applied +msRNAer to aggregate COVID-19-related datasets in New South Wales, Australia, which combined COVID-19 case number trends, geo-information, intervention events, and expert-supervised risk factors extracted from LGA-based censuses. We perfected the +msRNAer workflow with collaborative views and evaluated its feasibility, effectiveness, and usefulness through one user study and three subject-driven case studies. Positive feedback from experts indicates that +msRNAer provides a general understanding of analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical, timeline, and other factor comparisons. By adopting interactions, experts discovered functional and practical implications for potential patterns of long-standing community factors against the vulnerability faced by the pandemic. Experts confirmed that +msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios

    Identifying and responding to people with mild learning disabilities in the probation service

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    It has long been recognised that, like many other individuals, people with learningdisabilities find their way into the criminal justice system. This fact is not disputed. Whathas been disputed, however, is the extent to which those with learning disabilities arerepresented within the various agencies of the criminal justice system and the ways inwhich the criminal justice system (and society) should address this. Recently, social andlegislative confusion over the best way to deal with offenders with learning disabilities andmental health problems has meant that the waters have become even more muddied.Despite current government uncertainty concerning the best way to support offenders withlearning disabilities, the probation service is likely to continue to play a key role in thesupervision of such offenders. The three studies contained herein aim to clarify the extentto which those with learning disabilities are represented in the probation service, toexamine the effectiveness of probation for them and to explore some of the ways in whichprobation could be adapted to fit their needs.Study 1 and study 2 showed that around 10% of offenders on probation in Kent appearedto have an IQ below 75, putting them in the bottom 5% of the general population. Study 3was designed to assess some of the support needs of those with learning disabilities in theprobation service, finding that many of the materials used by the probation service arelikely to be too complex for those with learning disabilities to use effectively. To addressthis, a model for service provision is tentatively suggested. This is based on the findings ofthe three studies and a pragmatic assessment of what the probation service is likely to becapable of achieving in the near future

    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

    Learning disentangled speech representations

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    A variety of informational factors are contained within the speech signal and a single short recording of speech reveals much more than the spoken words. The best method to extract and represent informational factors from the speech signal ultimately depends on which informational factors are desired and how they will be used. In addition, sometimes methods will capture more than one informational factor at the same time such as speaker identity, spoken content, and speaker prosody. The goal of this dissertation is to explore different ways to deconstruct the speech signal into abstract representations that can be learned and later reused in various speech technology tasks. This task of deconstructing, also known as disentanglement, is a form of distributed representation learning. As a general approach to disentanglement, there are some guiding principles that elaborate what a learned representation should contain as well as how it should function. In particular, learned representations should contain all of the requisite information in a more compact manner, be interpretable, remove nuisance factors of irrelevant information, be useful in downstream tasks, and independent of the task at hand. The learned representations should also be able to answer counter-factual questions. In some cases, learned speech representations can be re-assembled in different ways according to the requirements of downstream applications. For example, in a voice conversion task, the speech content is retained while the speaker identity is changed. And in a content-privacy task, some targeted content may be concealed without affecting how surrounding words sound. While there is no single-best method to disentangle all types of factors, some end-to-end approaches demonstrate a promising degree of generalization to diverse speech tasks. This thesis explores a variety of use-cases for disentangled representations including phone recognition, speaker diarization, linguistic code-switching, voice conversion, and content-based privacy masking. Speech representations can also be utilised for automatically assessing the quality and authenticity of speech, such as automatic MOS ratings or detecting deep fakes. The meaning of the term "disentanglement" is not well defined in previous work, and it has acquired several meanings depending on the domain (e.g. image vs. speech). Sometimes the term "disentanglement" is used interchangeably with the term "factorization". This thesis proposes that disentanglement of speech is distinct, and offers a viewpoint of disentanglement that can be considered both theoretically and practically
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