【Author】 Abdullah, Mohammad Adeabah, David Abakah, Emmanuel Joel Aikins Lee, Chi-Chuan

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】This paper examines extreme return and volatility connectedness among real estate tokens, REITs, and other assets while accounting for global uncertainties' effect on connectedness and portfolio implications. The results indicate that the S & P 500 and REITs are the only assets with connectedness in a normal market, while extreme quantile results indicate higher network transmission. There is also evidence of a time-varying upsurge in connectedness, suggesting an event dependency effect. The results also indicate a significantly positive impact from all global uncertainty factors on a bear market. Finally, real estate tokens were found to be the cheapest hedge for oil and Bitcoin.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Connectedness; Cryptocurrency; Extreme returns and volatility; Global uncertainty factors; Portfolio implications; Real estate tokens; REITs

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.1016/j.frl.2023.104062

【Author】 Stephens, John Mehdian, Seyed Gherghina, Stefan Cristian Stoica, Ovidiu

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】This paper investigates the impact of the January 6 United States Capitol attack on financial markets. Minute-by-minute prices of Bitcoin, the Dow Jones Industrial Average Index, S & P 500 and the Nasdaq 100 index are used. Following the traditional event study approach, we document that the cumulative abnormal returns of Bitcoin drop after the attack while market indices rise following the event. These findings indicate that the Bitcoin market is marginally more efficient, but not statistically significant, after the attack than the financial markets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Financial markets; Intraday study; Event study

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.1016/j.frl.2023.104048

【Author】 Wang, Fang Gacesa, Marko

【Source】INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS

【影响因子】8.235

【主题类别】

区块链治理-市场治理-数字货币

【Abstract】This study extends the examination of the Efficient-Market Hypothesis in Bitcoin market during a five-year fluctuation period, from September 1 2017 to September 1 2022, by analyzing 28,739,514 qualified tweets containing the targeted topic "Bitcoin". Unlike previous studies, we extracted fundamental keywords as an informative proxy for carrying out the study of the EMH in the Bitcoin market rather than focusing on sentiment analysis, information volume, or price data. We tested market efficiency in hourly, 4-hourly, and daily time periods to understand the speed and accuracy of market reactions towards the information within different thresholds. A sequence of machine learning methods and textual analyses were used, including measurements of distances of semantic vector spaces of information, keywords extraction and encoding model, and Light Gradient Boosting Machine (LGBM) classifiers. Our results suggest that 78.06% (83.08%), 84.63% (87.77%), and 94.03% (94.60%) of hourly, 4-hourly, and daily bullish (bearish) market movements can be attributed to public information within organic tweets.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Efficient-market hypothesis; Twitter; Bitcoin; LightGBM; GloVe semantic vector spaces

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.1016/j.irfa.2023.102692

【Author】 Wang, Lei Xu, Ming Cheng, Hao

【Source】INFORMATION PROCESSING & MANAGEMENT

【影响因子】7.466

【主题类别】

区块链治理-技术治理-异常检测

【Abstract】Recently, phishing scams have become one of the most serious types of crime involved in Ethereum, the second-largest blockchain-based cryptocurrency platform. The existing phishing scams detection techniques for Ethereum mostly use traditional machine learning or network representation learning to mine the key information from the transaction network and identify phishing addresses. However, these methods typically crop the temporal transaction graph into snapshot sequences or construct temporal random wanderings to model the dynamic evolution of the topology of the transaction graph. In this paper, we propose PDTGA, a method that applies graph representation learning based on temporal graphs attention to improve the effectiveness of phishing scams detection in Ethereum. Specifically, we learn the functional representation of time directly and model the time signal through the interactions between the time encoding function and node features, edge features, and the topology of the graph. We collected a real-world Ethereum phishing scam dataset, containing over 250,000 transaction records between more than 100,000 account addresses, and divided them into three datasets of different sizes. Through data analysis, we first summarized the periodic pattern of Ethereum phishing scam activities. Then we constructed 14 kinds of account node features and 3 kinds of transaction edge features. Experimental evaluations based on the above three datasets demonstrate that PDTGA with 94.78% AUC score and 88.76% recall score outperforms the state-of-the-art methods.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Ethereum; Graph representation learning; Multilayer perceptron; Phishing scams detection; Temporal graph attention network; Temporal transaction information

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.1016/j.ipm.2023.103412

【Author】 Yang, Yin Siau, Keng Xie, Wen Sun, Yan

【Source】JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING

【影响因子】7.400

【主题类别】

--

【Abstract】In recent decades, healthcare organizations around the world have increasingly appreciated the value of information technologies for a variety of applications. Three of the new technological advancements that are impacting smart health are metaverse, artificial intelligence (AI), and data science. The metaverse is the intersection of three major technologies - AI, augmented reality (AR), and virtual reality (VR). Metaverse provides new possibilities and potential that are still emerging. The increased work efficiency enabled by artificial intelligence and data science in hospitals not only improves patient care but also cuts costs and workload for healthcare providers. Artificial intelligence, coupled with machine learning, is transforming the healthcare industry. The availability of big data enables data scientists to use the data for descriptive, predictive, and prescriptive analytics. This article reviews multiple case studies and the literature on AI and data science applications in hospital administration. The article also presents unresolved research questions and challenges in the applications of the metaverse, AI, and data science in the smart health context. For researchers, in addition to providing a good synopsis of the development and applications of the metaverse, AI, and data science in the healthcare area, this article identifies possible future research directions and discusses the possibilities of the metaverse, artificial intelligence, and data science in smart health. For practitioners, this article provides both hospital decision-makers and healthcare workers with practical guidelines and a smart health management model.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Artificial Intelligence; Data Science; Hospital Management; Smart Health; Smart Hospital

【发表时间】2022

【收录时间】2023-07-12

【文献类型】

【DOI】 10.4018/JOEUC.308814

【Author】 Malakhov, Ivan Marin, Andrea Rossi, Sabina

【Source】FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE

【影响因子】7.307

【主题类别】

--

【Abstract】In blockchain networks driven by Proof of Work, clients spend a certain amount of cryptocurrency (called fees) to control the speed of confirmation of the transactions that they generate. In fact, transactions are confirmed according to a strong priority policy that favors those offering the highest fees. The problem of determining the optimal fee to offer to satisfy certain delay requirements is still widely open and, at the state of the art, mainly reactive methods based on historical data are available. In this work, we propose a queueing model based on the exact transient analysis of a M/MB/1 system to address this problem. The model takes into account (i) the state of the Mempool (the backlog of pending work) when the transaction is generated, (ii) the current transaction arrival intensity and (iii) the distribution of the fees offered by other transactions to the miners. We apply the model to study the performance of the Bitcoin blockchain. Its parameterization is based on an extensive statistical analysis of the transaction characteristics. To this aim, we collected data from over 1.5 million of pending transactions observed in the Mempool of our Bitcoin node. The outcome of our analysis allows us to provide an algorithm to quickly compute the expected transaction confirmation time given the blockchain state, and to highlight new insights on the relations between the transaction fees and confirmation time in BTC blockchain.& COPY; 2023 Elsevier B.V. All rights reserved.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; Proof of work; Queueing model

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.1016/j.future.2023.04.016

【Author】 Jia, Xiaofeng Yu, Zhe Shao, Jun Lu, Rongxing Wei, Guiyi Liu, Zhenguang

【Source】IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY CCF-A

【影响因子】7.231

【主题类别】

--

【Abstract】With the emergence of countless independent blockchain systems in recent years, cross-chain transactions have attracted considerable attention, and lots of solutions have been put forth by both industry and academia. However, most of the existing solutions suffer from either centralization or scalability issues. To mitigate these issues, in this paper, we propose the concept of cross-chain virtual payment channels, which allows two users in different blockchain systems to conduct limitless off-chain transactions with the help of an intermediate node, hence solving the centralization and scalability issues. Furthermore, as the intermediate node is only involved in the channel open and close operations, it further improves the efficiency of cross-chain transactions, and to a certain extent, it even enhances the privacy of the cross-chain transaction. Meanwhile, we also present the first concrete cross-chain virtual payment channel scheme, which only requires one of the blockchain systems supporting the Turing-complete scripting language. The corresponding detailed security analysis in the Universal Composability framework demonstrates that our proposal holds the Consensus on Open, Update, and Close. Finally, we implement and deploy our cross-chain virtual payment channel scheme on the Ethereum and Bitcoin test networks. The extensive experimental results show that our proposal dramatically improves the efficiency of cross-chain transactions, and the advantage becomes more pronounced as the number of transactions increases.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Blockchain; payment channel; virtual payment channel; cross-chain; cross-chain virtual payment channel

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.1109/TIFS.2023.3281064

【Author】 Aditama, Mint H. R. Atmoko, Adi Hidayah, Nur Ramli, M. Selfiardy, Syafrida

【Source】JOURNAL OF PUBLIC HEALTH

【影响因子】5.058

【主题类别】

--

【Abstract】

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】COVID-19; Educational settings; Public health

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.1093/pubmed/fdad075

【Author】 Wang, Minglu Liu, Shanshan Hu, Lingling Lee, Jong-Yoon

【Source】SUSTAINABILITY

【影响因子】3.889

【主题类别】

--

【Abstract】With the development of information technology, many well-known art museums and galleries have adopted metaverse exhibitions for online display and dissemination of art information, building sustainable ways to participate in and experience art. Users can access the metaverse exhibition platform through the internet and enjoy classic artworks in the virtual space, which has gained many forms of artistic perception and improved physical and mental health. Currently, the factors affecting user use intentions in existing metaverse exhibition studies still need to be clarified and need to be studied in depth. This paper explores the relationship between users' entertainment experience, educational experience, presence, affective responses, and use intention through a survey of 536 users who had experienced a metaverse exhibition. The research results show that users' use intentions are influenced by entertainment experiences and educational experiences. Presence mediates between entertainment experiences and educational experiences on use intention. Affective responses play a moderating role between the educational experience and use intention. This study provides a relevant theoretical basis for sustainable urban and socio-economic development from a digital perspective. At the same time, this study enables the metaverse exhibition platform to design and create valuable and healthy artistic content with higher quality. The emotional state of the user's experience was better attended to so that mental health was enhanced and managed. Furthermore, it also provided a guidance program for the development of educational experience and economic sustainability of the exhibition industry.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】entertainment experience; educational experience; sustainability; use intention; psychological state

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.3390/su15129153

【Author】 Lu, Kuo-Chen Chen, Kuo-Shing

【Source】FRACTAL AND FRACTIONAL

【影响因子】3.577

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】This study aimed to uncover the impact of COVID-19 on the leading cryptocurrency (Bitcoin) and on sustainable finance with specific attention to their potential long memory properties. In this article, the application of the selected methodologies is based on a fractal and entropy analysis of the econometric model in the financial market. To detect the regularity/irregularity property of a time series, approximate entropy is introduced to measure deterministic chaos. Using daily data for Bitcoin and sustainable finance, namely DJSW, Green Bond, Carbon, and Clean Energy, we examine long memory behaviour by employing a rescaled range statistic (R/S) methodology. The results of the research present that the returns of Bitcoin, the Dow Jones Sustainability World Index (DJSW), Green Bond, Carbon, and Clean Energy have a significant long memory. Contrastingly, an interdisciplinary approach, namely wavelet analysis, is also used to obtain complementary results. Wavelet analysis can provide warning information about turmoil phenomena and offer insights into co-movements in the time-frequency space. Our findings reveal that approximate entropy shows crisis (turmoil) conditions in the Bitcoin market, despite the nature of the pandemic's origin. Crucially, compared to Bitcoin assets, sustainable financial assets may play a better safe haven role during a pandemic turmoil period. The policy implications of this study could improve trading strategies for the sake of portfolio managers and investors during crisis and non-crisis periods.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】approximate entropy; COVID-19 impact; Hurst exponent; (R; S) fractal analysis; wavelet entropy

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.3390/fractalfract7060424

【Author】 Liu, Zhenpeng Ren, Lele Feng, Yongjiang Wang, Shuo Wei, Jianhang

【Source】IEEE ACCESS

【影响因子】3.476

【主题类别】

--

【Abstract】Cloud storage is an essential method for data storage. Verifying the integrity of data in the cloud is critical for the client. Traditional cloud storage approaches rely on third-party auditors (TPAs) to accomplish auditing tasks. However, third-party auditors are often not trusted. To eliminate over-reliance on third-party auditors, this paper designs a blockchain-based auditing scheme that uses blockchain instead of third-party auditors to ensure the reliability of data auditing. Meanwhile, our scheme is based on the audit method of the quad Merkle hash tree, using the root of the quad Merkle hash tree to verify the integrity of data, which significantly improves computing and storage efficiency. Automated verification of auditing activities by deploying smart contracts on the blockchain allows us to have a more up-to-date picture of data integrity. The performance of the scheme is evaluated through security analysis and experiments, which prove that the proposed scheme is secure and effective.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Integrity auditing; blockchain; Merkle tree; smart contract

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.1109/ACCESS.2023.3240066

【Author】 Wei, Yu Wang, Yizhi Lucey, Brian M. Vigne, Samuel A.

【Source】JOURNAL OF COMMODITY MARKETS

【影响因子】3.317

【主题类别】

区块链治理-市场治理-市场分析

【Abstract】Several common properties shared by cryptocurrencies and precious metals, such as safe haven, hedge and diversification for risk assets, have been widely discussed since Bitcoin was created in 2008. However, no studies have explored whether cryptocurrency market uncertainties can help to explain and forecast volatilities in precious metal markets. By using the GARCH-MIDAS model incorporating cryptocurrency policy and price uncertainty, as well as several other commonly used uncertainty measures, this paper compares the in-sample impacts and out-of -sample predictive abilities of these uncertainties on volatility forecasts of COMEX gold and silver futures markets. The in-sample results demonstrate the significant impacts of cryptocurrency uncertainty on the volatilities of precious metal futures markets, and the out-of-sample evidence further confirms the superior predictive power of cryptocurrency uncertainty on volatility forecasting of the precious metal market. Our conclusions are robust through various model evaluation approaches based not only on predicting errors but also on forecasting directions across different forecasting time horizons.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cryptocurrency uncertainty; Precious metal; Volatility forecasting; Model evaluation

【发表时间】2023

【收录时间】2023-07-12

【文献类型】 实证数据

【DOI】 10.1016/j.jcomm.2022.100305

【Author】 Honari, Kimia Rouhani, Sara Falak, Nida E. Liu, Yuan Li, Yunwei Liang, Hao Dick, Scott Miller, James

【Source】ENERGIES

【影响因子】3.252

【主题类别】

--

【Abstract】Blockchain technology and, in particular, smart contracts based on it, offers a new, decentralized mechanism for entering into and fulfilling contracts in diverse markets. Energy markets are no exception, and indeed, the decentralized nature of the blockchain may be particularly important for them as the penetration of residential prosumers offering microgeneration to the grid grows. At this time, however, the literature on smart contracts in energy markets-and particularly their interaction with the technical infrastructure of the smart grid-is limited and scattered. There is a need to consolidate these studies into a comprehensive understanding of the state-of-the-art in smart contract design for the smart grid. However, no existing reviews focus on smart contracts in energy systems. The scope of our study is the role of smart contracts in energy systems and what limitations they encounter. We conduct a systematic review of this topic, focusing on systems that have been implemented as prototypes. These studies provide key evidence on the scalability of smart contracts for energy systems and their interaction with the technical elements of the smart grid. We selected a pool of 76 papers meeting our criteria, with three others excluded for misinterpreting fundamental aspects of blockchains and smart contracts. After reviewing each paper, we found that this literature falls into four categories: market operations, ancillary services, auditing and monitoring, and cybersecurity. We then identify and examine the cross-cutting concerns of data storage in and interoperability between blockchains. We finally discuss the implications of our findings for future research. In particular, there is likely to be a complex interplay between the data generated and stored via the blockchain versus the data required to meet energy system reliability targets and market obligations for participants.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】energy systems; distributed; BC; smart contract; smart grid; energy market

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.3390/en16124797

【Author】 Abdullah, Ali Mutawa, A. M.

【Source】SYMMETRY-BASEL

【影响因子】2.940

【主题类别】

--

【Abstract】The Lightning Network (LN), a second-layer protocol built atop Bitcoin, promises swift, low-cost transactions, thereby addressing blockchain scalability and enhancing user privacy. As the global financial technology landscape evolves, the LN's importance in the future of fintech and the Fourth Industrial Revolution (4IR) becomes increasingly pivotal. The anticipated rise of blockchain-based payments and smart contracts in businesses demands a more agile and secure payment system. However, the LN's early stage raises valid concerns about security and reliability, especially when implemented on a huge asymmetric network such as the Internet, potentially hindering its broader adoption. Malicious nodes could intentionally cause payment failures or initiate attacks, such as DDoS attacks, by overwhelming other nodes in the network with channel-opening requests. As a result, users will be discouraged from using the LN; hence, the technology will become obsolete as individuals will not waste the time and power investment required for using this technology. Addressing these issues, this paper proposes an innovative invitation model protocol (IMP) to reinforce the LN's security and reliability. The IMP creates an exclusive 'Club' within the LN, admitting only nodes verified as honest, thereby bolstering network security and reliability. The protocol empowers Club Founders to expel members exhibiting malicious activities, thereby preserving the invested time, energy, and funds of the network's users. The IMP was rigorously tested using Amazon Web Services Virtual Machines within the Bitcoin and Lightning Network's Testnet environment, which is a highly asymmetric network. The results demonstrated the protocol's efficacy in fulfilling its objectives, marking a significant step towards a safer and more efficient blockchain transaction network. As the blockchain continues to revolutionize the financial sector, implementing robust security measures such as the IMP becomes essential. This research paper introduces a novel approach to enhancing the reliability and security of a Lightning Network (LN), and thus distinguishes itself from the existing literature, by introducing an additional step before establishing or joining such a network. The research underscores the critical role of such protocols in realizing the potential of the LN in powering the next wave of fintech and industrial innovation.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】bitcoin; blockchain; Asymmetric Lightning Network; Club membership; trustless peer-to-peer network

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.3390/sym15061273

【Author】 Xia, Jianting Li, Haohua He, Zhou

【Source】SYSTEMS

【影响因子】2.895

【主题类别】

--

【Abstract】Blockchain technology, as a revolutionary technology that has emerged in recent years, holds significant potential for application in supply chain operations. This paper provides a systematic review of blockchain-based supply chain case studies. The existing literature primarily focuses on the food, agriculture, and pharmaceutical sectors, highlighting the advantages of blockchain technology in terms of traceability and transparency. However, there is a limited number of studies addressing the improvement of collaboration efficiency in supply chains, particularly within the realm of information technology enterprises. By conducting semi-structured interviews, we present a case study of Lenovo, a leading enterprise utilizing blockchain technology, to elucidate the advantages of using blockchain technology. Subsequently, it proposes a conceptual model for a blockchain-based information collaboration system and discusses the potential applications of blockchain technology in supply chain collaboration. Our study contributes to the existing work on blockchain applications to enhance supply chain collaboration.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; supply chain collaboration; smart contract; data collaboration

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.3390/systems11060299

【Author】 Li, Chunxiao Wang, Haodi Zhao, Yu Xi, Yuxin Xu, Enliang Wang, Shenling

【Source】MATHEMATICS

【影响因子】2.592

【主题类别】

--

【Abstract】Machine learning model sharing markets have emerged as a popular platform for individuals and companies to share and access machine learning models. These markets enable more people to benefit from the field of artificial intelligence and to leverage its advantages on a broader scale. However, these markets face challenges in designing effective incentives for model owners to share their models, and for model users to provide honest feedback on model quality. This paper proposes a novel game theoretic framework for machine learning model sharing markets that addresses these challenges. Our framework includes two main components: a mechanism for incentivizing model owners to share their models, and a mechanism for encouraging the honest evaluation of model quality by the model users. To evaluate the effectiveness of our framework, we conducted experiments and the results demonstrate that our mechanism for incentivizing model owners is effective at encouraging high-quality model sharing, and our reputation system encourages the honest evaluation of model quality.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】model sharing; MLaaS; incentive mechanism; smart contract

【发表时间】2023

【收录时间】2023-07-12

【文献类型】

【DOI】 10.3390/math11122636