7,955 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

    LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interface paradigms and interpretability

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    EEG-based recognition of activities and states involves the use of prior neuroscience knowledge to generate quantitative EEG features, which may limit BCI performance. Although neural network-based methods can effectively extract features, they often encounter issues such as poor generalization across datasets, high predicting volatility, and low model interpretability. Hence, we propose a novel lightweight multi-dimensional attention network, called LMDA-Net. By incorporating two novel attention modules designed specifically for EEG signals, the channel attention module and the depth attention module, LMDA-Net can effectively integrate features from multiple dimensions, resulting in improved classification performance across various BCI tasks. LMDA-Net was evaluated on four high-impact public datasets, including motor imagery (MI) and P300-Speller paradigms, and was compared with other representative models. The experimental results demonstrate that LMDA-Net outperforms other representative methods in terms of classification accuracy and predicting volatility, achieving the highest accuracy in all datasets within 300 training epochs. Ablation experiments further confirm the effectiveness of the channel attention module and the depth attention module. To facilitate an in-depth understanding of the features extracted by LMDA-Net, we propose class-specific neural network feature interpretability algorithms that are suitable for event-related potentials (ERPs) and event-related desynchronization/synchronization (ERD/ERS). By mapping the output of the specific layer of LMDA-Net to the time or spatial domain through class activation maps, the resulting feature visualizations can provide interpretable analysis and establish connections with EEG time-spatial analysis in neuroscience. In summary, LMDA-Net shows great potential as a general online decoding model for various EEG tasks.Comment: 20 pages, 7 Figure

    AnuĂĄrio cientĂ­fico da Escola Superior de Tecnologia da SaĂșde de Lisboa - 2021

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    É com grande prazer que apresentamos a mais recente edição (a 11.ÂȘ) do AnuĂĄrio CientĂ­fico da Escola Superior de Tecnologia da SaĂșde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa cientĂ­fica em todas as ĂĄreas do conhecimento que contemplam a nossa missĂŁo. Esta publicação tem como objetivo divulgar toda a produção cientĂ­fica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal nĂŁo Docente da ESTeSL durante 2021. Este AnuĂĄrio Ă©, assim, o reflexo do trabalho ĂĄrduo e dedicado da nossa comunidade, que se empenhou na produção de conteĂșdo cientĂ­fico de elevada qualidade e partilhada com a Sociedade na forma de livros, capĂ­tulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicaçÔes orais e pĂłsteres, bem como resultado dos trabalhos de 1Âș e 2Âș ciclo. Com isto, o conteĂșdo desta publicação abrange uma ampla variedade de tĂłpicos, desde temas mais fundamentais atĂ© estudos de aplicação prĂĄtica em contextos especĂ­ficos de SaĂșde, refletindo desta forma a pluralidade e diversidade de ĂĄreas que definem, e tornam Ășnica, a ESTeSL. Acreditamos que a investigação e pesquisa cientĂ­fica Ă© um eixo fundamental para o desenvolvimento da sociedade e Ă© por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prĂĄtica baseada na evidĂȘncia desde o inĂ­cio dos seus estudos na ESTeSL. Esta publicação Ă© um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade cientĂ­fica e o pĂșblico em geral. Esperamos que este AnuĂĄrio inspire e motive outros estudantes, profissionais de saĂșde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciĂȘncia e da tecnologia no corpo de conhecimento prĂłprio das ĂĄreas que compĂ”e a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuĂĄrio e desejamos uma leitura inspiradora e agradĂĄvel.info:eu-repo/semantics/publishedVersio

    TOWARDS AN UNDERSTANDING OF EFFORTFUL FUNDRAISING EXPERIENCES: USING INTERPRETATIVE PHENOMENOLOGICAL ANALYSIS IN FUNDRAISING RESEARCH

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    Physical-activity oriented community fundraising has experienced an exponential growth in popularity over the past 15 years. The aim of this study was to explore the value of effortful fundraising experiences, from the point of view of participants, and explore the impact that these experiences have on people’s lives. This study used an IPA approach to interview 23 individuals, recognising the role of participants as proxy (nonprofessional) fundraisers for charitable organisations, and the unique organisation donor dynamic that this creates. It also bought together relevant psychological theory related to physical activity fundraising experiences (through a narrative literature review) and used primary interview data to substantiate these. Effortful fundraising experiences are examined in detail to understand their significance to participants, and how such experiences influence their connection with a charity or cause. This was done with an idiographic focus at first, before examining convergences and divergences across the sample. This study found that effortful fundraising experiences can have a profound positive impact upon community fundraisers in both the short and the long term. Additionally, it found that these experiences can be opportunities for charitable organisations to create lasting meaningful relationships with participants, and foster mutually beneficial lifetime relationships with them. Further research is needed to test specific psychological theory in this context, including self-esteem theory, self determination theory, and the martyrdom effect (among others)

    Measurement of Heart Rate and Heart Rate Variability with Wearable Devices: A Systematic Review

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    Wearables are a ubiquitous trend in both commercial and academic settings as they easily enable tracking and monitoring of physiological parameters such as heart rate (HR) and heart rate variability (HRV). This paper presents a literature review to survey the existing Neuro-Information-Systems (NeuroIS) literature on HR and HRV with a focus on measurement based on wearable devices. We addressed the following four research questions: Who published HR and HRV research? What kind of HR and HRV research has been published? With which wearable devices was HR and HRV measured? How reliable and valid are HR and HRV measurements based on wearable devices? Our review provides answers to these questions and concludes that further efforts are needed to advance the field from both a theoretical and methodological perspective

    The Impact of a Play Intervention on the Social-Emotional Development of Preschool Children in Riyadh, Saudi Arabia

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    Practitioners working with children have emphasized that play is vital to children’s development, Links between children’s social-emotional development and play have been widely documented. However, rigorous research evidence of these links remains limited. This study’s objectives were to measure the impact of play on children’s social-emotional development in the kingdom of Saudi Arabia; identify teachers’ viewpoints around the use of play intervention; and understand the children’s experience of play intervention. Fifty-nine children aged between five and six years, with mean age of 5.5 (SD 3.376) and eight teachers participated in the study. The study used a mixed-method strategy including questionnaires, interviews, and focus group discussions. Children’s social-emotional development was measured by using the Strengths and Difficulties Questioner (SDQ). A pre-/post-test counterbalanced design was used to measure the impact of the play intervention on children’s development. Teachers’ perspectives on play were obtained by interviewing eight teachers. Children’s views were gathered through focus group discussions. Repeated measures ANOVA was conducted to determine the differences in the SDQ score over three time points. Results showed that using unstructured loose parts play had positively impacted children’s social-emotional development. After participation in the play intervention, scores from the SDQ indicated that children demonstrated significantly less problematic emotional, conduct and peer relationship issues. They also scored significantly higher in their positive prosocial behaviour. These positive effects were sustained after six weeks of stopping the intervention. The play intervention did not however impact children’s hyperactivity level. The interviews analysis illustrates four main themes: concept and characteristics of play, play functions, developmental benefits of play, and play and practice. Regarding children’s discussion, affordance emerged as a main theme; this includes emotional, social, and functional affordances. Unstructured loose parts play intervention was demonstrated to have positive impacts on children’s social-emotional development. The study’s findings support the view that play is a way to increase children’s development

    Examining the Impact of Personal Social Media Use at Work on Workplace Outcomes

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    A noticable shift is underway in today’s multi-generational workforce. As younger employees propel digital workforce transformation and embrace technology adoption in the workplace, organisations need to show they are forward-thinking in their digital transformation strategies, and the emergent integration of social media in organisations is reshaping internal communication strategies, in a bid to improve corporate reputations and foster employee engagement. However, the impact of personal social media use on psychological and behavioural workplace outcomes is still debatebale with contrasting results in the literature identifying both positive and negative effects on workplace outcomes among organisational employees. This study seeks to examine this debate through the lens of social capital theory and study personal social media use at work using distinct variables of social use, cognitive use, and hedonic use. A quantitative analysis of data from 419 organisational employees in Jordan using SEM-PLS reveals that personal social media use at work is a double-edged sword as its impact differs by usage types. First, the social use of personal social media at work reduces job burnout, turnover intention, presenteeism, and absenteeism; it also increases job involvement and organisational citizen behaviour. Second, the cognitive use of personal social media at work increases job involvement, organisational citizen behaviour, employee adaptability, and decreases presenteeism and absenteeism; it also increases job burnout and turnover intention. Finally, the hedonic use of personal social media at work carries only negative effects by increasing job burnout and turnover intention. This study contributes to managerial understanding by showing the impact of different types of personal social media usage and recommends that organisations not limit employee access to personal social media within work time, but rather focus on raising awareness of the negative effects of excessive usage on employee well-being and encourage low to moderate use of personal social media at work and other personal and work-related online interaction associated with positive workplace outcomes. It also clarifies the need for further research in regions such as the Middle East with distinct cultural and socio-economic contexts

    Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning

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    Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving rise to a new family of approaches. Especially, the advances in deep learning over the past couple of years have led to neural approaches to natural language generation (NLG). These methods combine generative language learning techniques with neural-networks based frameworks. With a wide range of applications in natural language processing, neural NLG (NNLG) is a new and fast growing field of research. In this state-of-the-art report, we investigate the recent developments and applications of NNLG in its full extent from a multidimensional view, covering critical perspectives such as multimodality, multilinguality, controllability and learning strategies. We summarize the fundamental building blocks of NNLG approaches from these aspects and provide detailed reviews of commonly used preprocessing steps and basic neural architectures. This report also focuses on the seminal applications of these NNLG models such as machine translation, description generation, automatic speech recognition, abstractive summarization, text simplification, question answering and generation, and dialogue generation. Finally, we conclude with a thorough discussion of the described frameworks by pointing out some open research directions.This work has been partially supported by the European Commission ICT COST Action “Multi-task, Multilingual, Multi-modal Language Generation” (CA18231). AE was supported by BAGEP 2021 Award of the Science Academy. EE was supported in part by TUBA GEBIP 2018 Award. BP is in in part funded by Independent Research Fund Denmark (DFF) grant 9063-00077B. IC has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 838188. EL is partly funded by Generalitat Valenciana and the Spanish Government throught projects PROMETEU/2018/089 and RTI2018-094649-B-I00, respectively. SMI is partly funded by UNIRI project uniri-drustv-18-20. GB is partly supported by the Ministry of Innovation and the National Research, Development and Innovation Office within the framework of the Hungarian Artificial Intelligence National Laboratory Programme. COT is partially funded by the Romanian Ministry of European Investments and Projects through the Competitiveness Operational Program (POC) project “HOLOTRAIN” (grant no. 29/221 ap2/07.04.2020, SMIS code: 129077) and by the German Academic Exchange Service (DAAD) through the project “AWAKEN: content-Aware and netWork-Aware faKE News mitigation” (grant no. 91809005). ESA is partially funded by the German Academic Exchange Service (DAAD) through the project “Deep-Learning Anomaly Detection for Human and Automated Users Behavior” (grant no. 91809358)

    International Conference Shaping light for health and wellbeing in cities

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    The book collects contributions presented during the international conference “Shaping light for health and wellbeing in cities” organized in the framework of the H2020 ENLIGHTENme project. The conference has investigated the multifaceted consequences light has on life in cities, by adopting a multidisciplinary and integrated approach to explore the complexity of challenges urban lighting poses on health and wellbeing, urban realm and social life. Papers cover several disciplines such as clinical and biomedical sciences, ethics and Responsible Research & Innovation, urban planning and architecture, data accessibility and interoperability, as well as social sciences and economics, and provide multifaceted insights that inspire further explorations. Contributions represent a step towards the development of innovative policies for improving health and wellbeing in our cities, addressing indoor and outdoor lighting
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