【Abstract】Metaverse-enabled healthcare is no longer hypothetical. Developers must now contend with ethical, legal and social hazards if they are to overcome the systematic inefficiencies and inequities that exist for patients who seek care in the real world.
【Abstract】Due to mobile Internet technology's rapid popularization, the Industrial Internet of Things (IIoT) can be seen everywhere in our daily lives. While IIoT brings us much convenience, a series of security and scalability issues related to permission operations rise to the surface during device communications. Hence, at present, a reliable and dynamic access control management system for IIoT is in urgent need. Up till now, numerous access control architectures have been proposed for IIoT. However, owing to centralized models and heterogeneous devices, security and scalability requirements still cannot be met. In this paper, we offer a smart contract token-based solution for decentralized access control in IIoT systems. Specifically, there are three smart contracts in our system, including the Token Issue Contract (TIC), User Register Contract (URC), and Manage Contract (MC). These three contracts collaboratively supervise and manage various events in IIoT environments. We also utilize the lightweight and post-quantum encryption algorithm-Nth-degree Truncated Polynomial Ring Units (NTRU) to preserve user privacy during the registration process. Subsequently, to evaluate our proposed architecture's performance, we build a prototype platform that connects to the local blockchain. Finally, experiment results show that our scheme has achieved secure and dynamic access control for the IIoT system compared with related research.
【Abstract】The main purpose of this paper is to add empirical data to the nascent field of metaverse learning and teaching by examining factors affecting student participation and their perceived experiences of different metaverse platforms. For data collection, 57 Korean undergraduates participated in a self-administered questionnaire and a short reflective essay regarding their experiences on three metaverse platforms (ifland, Gather Town, & Frame VR). For data analysis, exploratory factor analysis was first executed to derive the underlying factors that can explain student participation in metaverse platforms. The social and interactive learning as well as individualized and behavioral learning were identified as two main contributing factors. While the three platforms had no statistical difference in terms of social presence, students' sentimentally perceived differences among them. The sentiment analysis shows that 60.00% of ifland users were positive, followed by 53.66% of Frame VR users and 51.22% of Gather Town users. Furthermore, the additional keyword analysis shows why students expressed the perceived experiences of each platform in a different way. Given that the success of metaverse instruction can be dependent upon whether students regard it as beneficial, such measurements of student perception on the effectiveness of learning on metaverse platforms can offer meaningful recommendations for tech-savvy educators.
【Abstract】Given the growing pervasiveness of information systems (IS) in everyday life, recent research has acknowledged that IS technologies are often not value free but are instead infused with fundamental personal values. However, little is known about how such values explain why people assimilate these technologies and their affordances. In the intriguing case of Bitcoin, personal values-especially libertarian political values-played an essential role in clarifying the ideological underpinnings of Bitcoin and its early adoption. Consequently, we draw on research on personal values and affordance theory to develop and test a model explicating how these personal values guide individuals toward using IS applications with salient affordances that address their values. Specifically, we hypothesize and test how individuals' personal values (i.e., libertarian political values) influence their attitudes toward Bitcoin affordances and their Bitcoin use behavior using data from a multiple administration survey of 236 users and nonusers of Bitcoin. Our results indicate that libertarian political values affect individuals' attitudes toward Bitcoin affordances, which in turn mediate the effects of these values on actual Bitcoin use. Our findings advance the field by demonstrating the importance of integrating values into the conceptualization of IS technology affordances.
【Abstract】The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice. This study aimed to build a dynamic supervision model suited to the circulation characteristics of the rice supply chain and implement contractualization, analysis, and verification. First, based on an analysis of key information in the supervision of the rice supply chain, we built a dynamic supervision model framework based on blockchain and smart contracts. Second, under the logical framework of a regulatory model, we custom designed three types of smart contracts: initialization smart contract, model-verification smart contract, and credit-evaluation smart contract. To implement the model, we combined an asymmetric encryption algorithm, virtual regret minimization algorithm, and multisource heterogeneous fusion algorithm. We then analyzed the feasibility of the algorithm and the model operation process. Finally, based on the dynamic supervision model and smart contract, a prototype system is designed for example verification. The results showed that the dynamic supervision model and prototype system could achieve the real-time management of the rice supply chain in terms of business information, hazard information, and personnel information. It could also achieve dynamic and credible supervision of the rice supply chain's entire life cycle at the information level. This new research is to apply information technology to the digital management of grain supply chain. It can strengthen the digital supervision of the agricultural product industry.
【Abstract】Critics decry cryptocurrency mining as a huge waste of energy, while proponents insist on claiming that it is a green industry. Is Bitcoin mining really worth the energy it consumes? The high power consumption of cryptocurrency mining has become the latest global flashpoint. In this paper, we define the Mining Domestic Production (MDP) as a method to account for the final outcome of the Bitcoin mining industry's production activities in a certain period time, calculate the carbon emission per unit output value of the Bitcoin mining industry in China, and compare it with three other traditional industries. The results show that Bitcoin mining does not always have the highest when compared with others. The contribution of this paper is that we give a new perspective on thinking whether Bitcoin mining is more efficient to make more profit, in terms of the same amount of carbon emissions per unit compared to other industries. Moreover, it could even be argued that Bitcoin may present an opportunity for some developing countries to build out their electrical capacity and generate revenue.
【Abstract】The exponential growth in the global population and significant advancements in healthcare broadened the scope of intervention for e-Healthcare through decentralized data access and in-formation exchange, making complex clinical decisions. e-Healthcare can perform several func-tionalities, including EHR communication, telemedicine, and complex clinical decision systems (CCDS), but large-scale users still find it challenging to maintain interoperability, stability, and scalability. Accommodating an extensive array of stakeholders, which includes patients, doctors, hospitals, and laboratories, demands interoperability to serve scalable services. FHIR frameworks have played a vital role in e-Healthcare designs. Most of the existing HL7-FHIR frameworks have used REST-API using HTTP-query for CRUD tasks that impose numerous rules and constraints, making the process more complex and time-consuming, violating the quality-of-service (QoS) standards on different levels. This paper develops a novel, robust Smart-Contract Authentication Assisted HL7-FHIR framework toward an interoperable e-Healthcare solution. Unlike classical REST API-based FHIR, our proposed method applies a Graph-mapping concept that transforms each resource variable into an equivalent Graph-Mapped Data Structure (GMS), which is subse-quently stored in the NoSQL MongoDB database, reducing computational costs and time to meet QoS demands. The proposed model employs three key components, GMS-driven HL7 FHIR Gateway Model, Smart Contract Authentication and Client Model. The Smart Contract function helped verify and authenticate users to ensure privacy and secure EHR exchange. The assessment of the performance of the proposed model reveals a significant reduction in computational time with optimal resource utilization making it a significant and viable option to better the real-world e-Healthcare mechanisms.
【Abstract】Smart contracts are becoming the forefront of blockchain technology, allowing the performance of credible transactions without third parties. However, smart contracts on blockchain are not immune to vulnerability exploitation and cannot be modified after being deployed on the blockchain. Therefore, it is imperative to assure the security of smart contracts via intelligent vulnerability detection tools with the exponential increase in the number of smart contracts. The remarkably developing deep learning technology provides a promising way to detect potential smart contract vulnerabilities. Nevertheless, existing deep learning-based approaches fail to effectively capture the rich syntax and semantic information embedded in smart contracts for vulnerability detection. In this paper, we tackle the problem of smart contract vulnerability detection at the function level by constructing a novel semantic graph (SG) for each function and learning the SGs using graph convolutional networks (GCNs) with residual blocks and edge attention. Our proposed method consists of three stages. In the first stage, we create the SG which contains rich syntax and semantic information including the data-data, instruction-instruction and instruction-data relationships, variables, operations, etc., by building an abstract syntax tree (AST) from the code of each function, removing the unimportant nodes in the AST, and adding edges between the nodes to represent the data flows and the execution sequence of the statements. In the second stage, we propose a new graph convolutional network model EA-RGCN to learn the content and semantic features of the code. EA-RGCN contains three parts: node and edge representation via word2vec, content feature extraction with a residual GCN (RGCN) module, and semantic feature extraction using an edge attention (EA) module. In the third stage, we concatenate the code content features and the semantic features to obtain the global code feature and use a classifier to identify whether the function is vulnerable. We conduct experiments on the datasets constructed from real-world smart contracts. Experimental results demonstrate that the proposed semantic graph and the EA-RGCN model can effectively improve the performance in terms of accuracy, precision, recall, and F1-score on smart contract vulnerability detection.(c) 2023 Elsevier Inc. All rights reserved.
【Abstract】Traditional trade processes suffer from a great number of issues about intermediaries, information latency and trust, which, in turn, hinder overall process efficiency. The emerging blockchain technology may have potentials to mitigate those issues by revolutionizing business processes across enterprise borders in various industries. The security of smart contract technology and anti-money-laundering is utilized in tandem to combat the flaws of traditional banking. By decentralizing we can circumvent some of its defects, and achieve autonomous, fast and safe foreign goods trade. The purpose of this paper is to examine the current obstacles in letter of credit and bank transfers related to the imported foreign goods, and suggest a solution using the blockchain technology. Comparative analysis and feasibility study were conducted to identify and validate the prospects, in terms of facilitating process flow and enhancing overall trade perfor-mance, of the proposed blockchain-based international trade process model. This study contrib-utes to the conceptual design of a blockchain-and smart-contract based process along with a provision of practical case in business process re-engineering. Further endeavors devoted to blockchain research and application across different sectors are suggested to reach better per-formance of business process operations.
【Abstract】This paper studies time-frequency connectedness among carbon assets, Bitcoin, and global stock markets by using the Diebold and Yilmaz method and the Barunik and Krehlik method, to investigate the hedging ability of carbon assets and Bitcoin in global stock markets. Our study finds that both carbon assets and Bitcoin play hedging roles in global stock markets. However, their strength of hedging is negatively correlated with the degree of economic uncertainty and tends to change in different frequency domains. We also show that carbon assets and Bitcoin can act as each other's hedging assets in a great majority of cases. Our results provide useful knowledge for investors to reduce risks and for regulators to regulate carbon assets and cryptocurrency speculation.
【Abstract】The metaverse is an alternative digital world, accessed by means of dedicated audiovisual devices. In this parallel world, various forms of artificial intelligence meet, including individuals in the form of digital copies of real people (avatars), able to interact socially. Metaverse in medicine may be used in many different ways. The possibility to perform surgery at a distance of thousands of miles separating the patient from the surgeon, who could have also the possibility to visualize in real-time patient's clinical data, including diagnostic images, obviously is very appealing. It would be also possible to perform medical treatments and to adopt pharmacological protocols on human avatars clinically similar to the patients, thus observing treatment effects in advance and significantly reducing the clinical trials duration. Metaverse may reveal an exceptional educational tool, offering the possibility of interactive digital lessons, allowing to dissect and to study an anatomical apparatus in detail, to navigate within it, not only to study, but also to see the evolution of the pathological process, and to simulate in advance surgical or medical procedures on virtual patients. However, while artificial intelligence is now an established reality in the clinical practice, the metaverse is still in its initial stages, and to figure out its potential usefulness and reliability, further developments are expected.
【Abstract】The World Health Organization has defined "digital health" as the use of information and communication technologies to improve health. In recent years, there has been a strong acceleration in the adoption of these digital tools, which has had a major impact on traditional healthcare models.We are currently witnessing the emergence of a large immersive virtual environment called the "metaverse." Its emergence creates new and challenging opportunities in health care. This article explores some metaverse-related concepts, provides specific examples of its use in pediatrics, describes experiences in the hospital setting, and finally delves into the resulting challenges and opportunities.