Emerging with the support of computing and communications technologies, Metaverse is expected to bring users unprecedented service experiences. However, the increase in the number of Metaverse users ...places a heavy demand on network resources, especially for Metaverse services that are based on graphical extended reality and require rendering a plethora of virtual objects. To make efficient use of network resources and improve the Quality-of-Experience (QoE), we design an attention-aware network resource allocation scheme to achieve customized Metaverse services. The aim is to allocate more network resources to virtual objects in which users are more interested. We first discuss several key techniques related to Metaverse services, including QoE analysis, eye-tracking, and remote rendering. We then review existing datasets and propose the user-object-attention level (UOAL) dataset that contains the ground truth attention of 30 users to 96 objects in 1, 000 images. A tutorial on how to use UOAL is presented. With the help of UOAL, we propose an attention-aware network resource allocation algorithm that has two steps, i.e., attention prediction and QoE maximization. Specially, we provide an overview of the designs of two types of attention prediction methods, i.e., interest-aware and time-aware prediction. By using the predicted user-object-attention values, network resources such as the rendering capacity of edge devices can be allocated optimally to maximize the QoE. Finally, we propose promising research directions related to Metaverse services.
In recent years, the application of the metaverse in higher education has attracted the attention of numerous educators and researchers. It allows students to engage in immersive experiential ...learning and to experience a variety of real human interaction modes. Researchers have pointed out that although the introduction of emerging technologies may bring a sense of novelty, it cannot sustain student learning for a long time. Learners' learning performance still depends on their learning motivation. The present study aimed to explore the conceptions and perceptions (i.e., growth mindset, learning attitudes, and self-efficacy) of students with different motivation levels regarding the metaverse in higher education. A draw-a-picture analysis and surveys were conducted. The results indicated that most students believed that with the metaverse, they could learn the knowledge of unspecified subject domains in any location, realizing the idea of studying for practical application. In the drawings of students with low motivation levels, they still conducted static learning activities (i.e., reading/studying, and searching for sources) in the metaverse learning environment. On the other hand, students with high motivation levels focused on experiential learning, operation, or practice (i.e., hands-on practicing/performance and observing/experiencing). Moreover, the students with high motivation levels generally show better growth mindsets, learning attitudes, and self-efficacy than those with low motivation levels. This implies that learning motivation could be an important factor affecting students’ growth mindsets, learning attitudes, and self-efficacy of learning with the metaverse. The findings of this study serve as a foundation for future research, and provide preliminary evidence for understanding the conceptions of students with different motivation levels regarding the metaverse in higher education. Lastly, based on the analytic results, this study puts forward suggestions for the learning approaches of students in the metaverse as a reference for future researchers and teachers in higher education to design related activities.
•Students' conceptions and perceptions of learning with the metaverse are analyzed.•The subjects are university students with different motivation levels.•A draw-a-picture analysis and surveys are employed in this study.•Most students believed that the metaverse would help them learn better.•High motivation students had better growth mindsets, attitudes, and self-efficacy.
The metaverse signifies the amalgamation of virtual and tangible realms through human-computer interaction. The seamless integration of human, cyber, and environments within ubiquitous computing ...plays a pivotal role in fully harnessing the metaverse’s capabilities. Nevertheless, metaverse operating systems face substantial hurdles in terms of accessing ubiquitous resources, processing information while safeguarding privacy and security, and furnishing artificial intelligence capabilities to downstream applications. To tackle these challenges, this paper introduces the UbiMeta model, a specialized ubiquitous operating system designed specifically for the metaverse. It extends the capabilities of traditional ubiquitous operating systems and focuses on adapting downstream models and operational capacity to effectively function within the metaverse. UbiMeta comprises four layers: the Ubiquitous Resource Management Layer (URML), the Autonomous Information Mastery Layer (AIML), the General Intelligence Mechanism Layer (GIML), and the Metaverse Ecological Model Layer (MEML). The URML facilitates the seamless incorporation and management of various external devices and resources. It provides a framework for integrating and controlling these resources, including virtualization, abstraction, and reuse. The AIML is responsible for perceiving information and safeguarding privacy and security during storage and processing. The GIML leverages large-scale pre-trained deep-learning feature extractors to obtain effective features for processing information. The MEML focuses on constructing metaverse applications using the principles of Model-as-a-Service (MaaS) and the OODA loop (Observation, Orientation, Decision, Action). It leverages the vast amount of information collected by the URML and AIML layers to build a robust metaverse ecosystem. Furthermore, this study explores how UbiMeta enhances user experiences and fosters innovation in various metaverse domains. It highlights the potential of UbiMeta in revolutionizing medical healthcare, industrial practices, education, and agriculture within the metaverse.
The continuous enhancement of living conditions imposes higher requirements for medical and healthcare services. Although improved to a certain extent, there still exist critical challenges in ...current medical pattern, such as the shortage of medical resources, inefficient medical treatment, and limited medical technology level. The metaverse can offer a novel mechanism to address these problems in traditional healthcare domain, and thus, to enhance the quality of medical services. Generally, the metaverse is a dynamic feedback system that facilitates the collaboration and coexistence between the virtual and physical worlds. By fostering collaboration and evolution between intelligent agents in the virtual world, knowledge of this interdependence can be reconstructed in the digital realm. This allows problems existed in the real world to be abstracted and represented in the digital space, where models can be established and computational experiments can be conducted. The outcomes obtained can dynamically guide or control the execution of strategies in the real world, with real-world execution results serving as dynamic data inputs to continually update the virtual world’s model. In addition, this paper summarizes the current research status of different healthcare application scenarios for metaverse, highlights the challenges and vision, and aims to inspire further research in this field.
Metaverse is a virtual world platform that enables users to create and explore 3D environments. Recently, this technology has gained traction due to its potential to revolutionize the way people ...interact and share information. This paper provides an overview of the current state of Metaverse technologies. It begins by introducing their core components and surveys recent research and development activities in the area. Next, the paper examines the potential applications of Metaverse technology in different domains, such as gaming, social networking, training, education, healthcare, and marketing. It then outlines the challenges and opportunities associated with the development and deployment of Metaverse technologies, including scalability, privacy, and security issues. Finally, the paper concludes with a discussion of the implications of Metaverse technologies for the future of digital communication and information sharing.
The present work endeavors to thoroughly examine the dependence of daily closing prices of Metaverse coins on external social media sentiment on Russia's military invasion of Ukraine and the ...potential benefits of Metaverse technology. We collate the worldwide media chatter on the Ukraine war and uncover the dynamic association with four Metaverse coins by applying wavelet coherence analysis. Subsequently, we systematically estimate the sentiment of discussions on the Reddit community on two topics, namely, the Russia-Ukraine Conflict and Metaverse, to gauge their impact separately on the chosen tokens. Nonlinear association mining and forecasting exercises are carried out to comprehend the predictability of the Metaverse financial assets using the respective sentiment components. The predictive framework utilizes Uniform Manifold Approximation and Projection (UMAP) and Particle Swarm Optimization (PSO)-tuned Extreme Gradient Boosting (XGBR) for feature transformation and fetching forecasts, respectively. Explainable Artificial Intelligence (XAI) methods are utilized to interpret the prediction process for unveiling the feature contributions. The findings suggest that the dependence between the Metaverse coins and media chatter on the Russia-Ukraine war primarily prevails in short and medium-run scales, and the Reddit sentiments on the same and Metaverse can be effectively leveraged for estimating future figures and trends.
•Decoding the nexus of Metaverse coins with media chatter and Reddit sentiment.•We estimate the Reddit sentiment on Russia-Ukraine Conflict and Metaverse.•Delving the dynamic interrelationship using wavelet coherence analysis.•We build predictive framework combining UMAP, PSO, and XGBR.•The contributions of the sentiment constructs are uncovered by XAI.•The sentiment indicators are useful for predicting and explaining the dynamics.
Background
Severe acute respiratory syndrome coronavirus 2 appeared in humans at the end of 2019 and caused a worldwide coronavirus disease‐19 (COVID‐19) pandemic. Our research is being conducted on ...consumers who are having difficulties in purchasing cosmetics due to the rapid change in non‐face‐to‐face society due to COVID‐19 on new normal period.
Objectives
This study technically investigates the customer experience of consumers in the cosmetic market on metaverse world, which has changed to a non‐face‐to‐face era after COVID‐19.
Methods
It was written with reference to keywords such as “COVID‐19,” “non‐face‐to‐face,” “fandom marketing,” “alpha generation,” and “metaverse.” This study was performed by searching on PubMed, Google Scholar, Scopus, and ResearchGate. A total of 378 papers were retrieved, of which 29 were successfully selected in this study.
Results
It focused on the transformational change of the metaverse beauty market that will be led by the alpha generation after COVID‐19. It was empirically analyzed targeting the alpha generation, who are users, to change the problems of users who test and purchase cosmetics face‐to‐face in the beauty market so that they can do fandom marketing and customer experience using metaverse in a non‐face‐to‐face society.
Conclusion
As a result, this article is expected to be used as an important marketing material for new changes in the market on metaverse world by clearly identifying the needs of consumers in the cosmetic industry that have changed in the untact era.
This study was conducted to identify users' motivations for using the metaverse from a uses and gratification perspective and to identify users' categories based on their motives. In addition, this ...research investigated whether the degree of flow differs according to a user's motivation and segment. This study also examined the relationship between flow and the frequency of offline activity. Five motives (seeking advantages, extended social interactions, extended entertainment, virtual experience, and transfer consciousness) were identified. Among these, seeking advantage, extended social interactions, extended entertainment, and transfer consciousness positively influenced the degree of flow when using metaverse. Furthermore, among three distinct groups of metaverse users (goalless drift, pursuing a new world, and ego-boosting) the segment of pursuing a new world had the highest degree of flow. In addition, we confirmed that flow was negatively correlated with the amount of offline activity.
