• 首页
  • 每日更新
  • 文献
  • 会议文献
  • 政策法规
  • 研究专题
  • 区块链游戏
logo 区块链前沿
  • 区块链前沿
  • 首页
  • 每日更新
  • 文献
  • 会议文献
  • 政策法规
  • 研究专题
  • 区块链游戏
  • 文章创新角色
  • 科研创新指数
  • 区块链领域本体
  • 热点主题挖掘
  • 主题展示
  • 专利文献
  • 排行榜
  • DAO治理
  • 文献上传
  • 积分获取规则
  • 大语言模型解析
  • 期刊发文分布
注册 登录

2022年01月18日 7篇

文献来源

  • 7

主题分类

      • 2
      • 2
      • 1
      • 2

文献类型

  • 5
  • 2
筛选
订阅
<< 前一天 后一天 >>

A continuous-time consensus algorithm using neurodynamic system for distributed time-varying optimization with inequality constraints

【Author】 He, Shuang He, Xing Huang, Tingwen

【影响因子】4.246

【主题类别】

区块链技术--

【Abstract】In this paper, a distributed time-varying convex optimization problem with inequality constraints is discussed based on neurodynamic system. The goal is to minimize the sum of agents & rsquo; local time varying objective functions subject to some time-varying inequality constraints, each of which is known only to an individual agent. Here, the optimal solution is time-varying instead of constant. Under an undirected and connected graph, a distributed continuous-time consensus algorithm is designed by using neurodynamic system, signum functions and log-barrier penalty functions. The proposed algorithm can be understood through two parts: one part is used to reach consensus and the other is used to achieve gradient descent to track the optimal solution. Theoretical studies indicate that all agents will achieve consensus and the proposed algorithm can track the optimal solution of the time-varying convex problem. Two numerical examples are provided to validate the theoretical results. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】

【发表时间】2021

【收录时间】2022-01-18

【文献类型】 期刊

【DOI】 10.1016/j.jfranklin.2021.07.007

Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains

【Author】 Zhang, Hongwei Hong, Huojun Guo, Yaoqi Yang, Cai

【影响因子】3.399

【主题类别】

区块链治理--

【Abstract】Many scholars have explored the COVID-19 impact on the crude oil, gold, and Bitcoin markets, whereas most have ignored the media coverage influence. This paper focuses on examining information spillover from epidemic-related news to the crude oil, gold, and Bitcoin markets with the time-frequency analysis method. The empirical results reveal that both the return and volatility spillovers from epidemic-related news to the crude oil, gold, and Bitcoin markets are stronger in the short term (less than 1 week). In the long term, only the media sentiment index notably impacts crude oil, gold, and Bitcoin market returns. The volatility spillover from media coverage to crude oil mainly occurs in the short term. Regarding the gold and Bitcoin markets, the long-term volatility spillovers are significant. An obvious risk contagion path is found. Media hype is the main risk transmitter and transmits vast shocks to these three markets, especially the Bitcoin market, which subsequently transmits these shocks to the gold market. Risk accumulates systemically in the gold and Bitcoin markets. These findings have crucial empirical implications for policymakers and investors when formulating related short- or long-term decisions during the pandemic.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】COVID-19; Media coverage; Bitcoin; Gold; Crude oil; Time-frequency analysis

【发表时间】2022

【收录时间】2022-01-18

【文献类型】 期刊

【DOI】 10.1016/j.iref.2021.12.005

Lottery-like momentum in the cryptocurrency market

【Author】 Lin, Chiao-Han Yen, Kuang-Chieh Cheng, Hui-Pei

【影响因子】3.136

【主题类别】

区块链治理--

【Abstract】Following the methodology of Bali et al. (2011), we construct the lottery-like portfolio based on the maximum return. First, we find that a higher maximum return leads to a higher future return among 64 cryptocurrencies. This phenomenon is called the lottery-like momentum. Controlling for the momentum effect, the lottery-like momentum still exists in the cryptocurrency market. In addition, we find that the major cryptocurrencies-Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC)-are less likely to have extreme positive returns. And the absence of extreme positive returns is persistent.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Bitcoin; Cryptocurrencies; Lottery; Momentum

【发表时间】2021

【收录时间】2022-01-18

【文献类型】 期刊

【DOI】 10.1016/j.najef.2021.101552

Cultural heritage preservation by using blockchain technologies

【Author】 Trcek, Denis

【影响因子】2.843

【主题类别】

区块链应用--

【Abstract】Ubiquitous digitization enables promising options for cultural heritage preservation. Therefore, a new approach is presented that considers deployment scenarios by linking heritage science to tourism. Such an approach is necessary because neither technology nor society views can be treated separately to obtain deployable solutions of a wider social, and even national importance. Clearly, while the traditional approaches to cultural heritage preservation will remain a gold standard, they will be increasingly complemented by digital preservation techniques. Thus, based on practical implementations and lessons learnt in other areas, this multidisciplinary framework paper analyses existing disruptive information technologies deployments. In line with the findings it presents a novel technological architecture tailored to the needs of cultural heritage preservation that deploys an open blockchain architecture. The architecture preserves the advantages of traditional blockchains, which made this technology so important, while enabling energy efficient implementations that can be deployed in mobile applications. By additionally using the contribution-ware principle it links it to tourism, where the identification of users focused incentives and business models play a central role. It is obvious that tourism is a good candidate in such preservation efforts due to the organic links between it and cultural heritage and can support further developments in the heritage preservation domain.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Cultural heritage; Preservation; Digitization; Blockchain; Business models

【发表时间】2022

【收录时间】2022-01-18

【文献类型】 期刊

【DOI】 10.1186/s40494-021-00643-9

Scaling Membership of Byzantine Consensus

【Author】 Canakci, Burcu Van Renesse, Robbert

CCF-A

【影响因子】1.692

【主题类别】

区块链技术--

【Abstract】Scaling Byzantine Fault Tolerant (BFT) systems in terms of membership is important for secure applications with large participation such as blockchains. While traditional protocols have low latency, they cannot handle many processors. Conversely, blockchains often have hundreds to thousands of processors to increase robustness, but they typically have high latency or energy costs. We describe various sources of unscalability in BFT consensus protocols. To improve performance, many BFT protocols optimize the normal case, where there are no failures. This can be done in a modular fashion by wrapping existing BFT protocols with a building block that we call alliance. In normal case executions, alliance can scalably determine if the initial conditions of a BFT consensus protocol predetermine the outcome, obviating running the consensus protocol. We give examples of existing protocols that solve alliance. We show that a solution based on hypercubes and MACs has desirable scalability and performance in normal case executions, with only a modest overhead otherwise. We provide important optimizations. Finally, we evaluate our solution using the ns3 simulator and show that it scales up to thousands of processors and compare with prior work in various network topologies.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Scalability; reliability; byzantine; consensus; blockchain; asynchronous

【发表时间】2021

【收录时间】2022-01-18

【文献类型】 期刊

【DOI】 10.1145/3473138

Using artificial intelligence technology to fight COVID-19: a review

【Author】 Peng, Yong Liu, Enbin Peng, Shanbi Chen, Qikun Li, Dangjian Lian, Dianpeng

【影响因子】9.588

【主题类别】

综述--

【Abstract】In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. The introduction of artificial intelligence technology has provided a huge contribution to the suppression of the new coronavirus. This article discusses the main application of artificial intelligence technology in the suppression of coronavirus from three major aspects of identification, prediction, and development through a large amount of literature research, and puts forward the current main challenges and possible development directions. The results show that it is an effective measure to combine artificial intelligence technology with a variety of new technologies to predict and identify COVID-19 patients.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】Artificial intelligence; COVID-19; Epidemic prevention and control; Internet of Things; Cloud computing; Blockchain

【发表时间】

【收录时间】2022-01-18

【文献类型】 综述

【DOI】 10.1007/s10462-021-10106-z

The Health Care Sector's Experience of Blockchain: A Cross-disciplinary Investigation of Its Real Transformative Potential

【Author】 Yeung, Karen

【影响因子】7.076

【主题类别】

综述--

【Abstract】Background: Academic literature highlights blockchain's potential to transform health care, particularly by seamlessly and securely integrating existing data silos while enabling patients to exercise automated, fine-grained control over access to their electronic health records. However, no serious scholarly attempt has been made to assess how these technologies have in fact been applied to real-world health care contexts. Objective: The primary aim of this paper is to assess whether blockchain's theoretical potential to deliver transformative benefits to health care is likely to become a reality by undertaking a critical investigation of the health care sector's actual experience of blockchain technologies to date. Methods: This mixed methods study entailed a series of iterative, in-depth, theoretically oriented, desk-based investigations and 2 focus group investigations. It builds on the findings of a companion research study documenting real-world engagement with blockchain technologies in health care. Data were sourced from academic and gray literature from multiple disciplinary perspectives concerned with the configuration, design, and functionality of blockchain technologies. The analysis proceeded in 3 stages. First, it undertook a qualitative investigation of observed patterns of blockchain for health care engagement to identify the application domains, data-sharing problems, and the challenges encountered to date. Second, it critically compared these experiences with claims about blockchain's potential benefits in health care. Third, it developed a theoretical account of challenges that arise in implementing blockchain in health care contexts, thus providing a firmer foundation for appraising its future prospects in health care. Results: Health care organizations have actively experimented with blockchain technologies since 2016 and have demonstrated proof of concept for several applications (use cases) primarily concerned with administrative data and to facilitate medical research by enabling algorithmic models to be trained on multiple disparately located sets of patient data in a secure, privacy-preserving manner. However, blockchain technology is yet to be implemented at scale in health care, remaining largely in its infancy. These early experiences have demonstrated blockchain's potential to generate meaningful value to health care by facilitating data sharing between organizations in circumstances where computational trust can overcome a lack of social trust that might otherwise prevent valuable cooperation. Although there are genuine prospects of using blockchain to bring about positive transformations in health care, the successful development of blockchain for health care applications faces a number of very significant, multidimensional, and highly complex challenges. Early experience suggests that blockchain is unlikely to rapidly and radically revolutionize health care. Conclusions: The successful development of blockchain for health care applications faces numerous significant, multidimensional, and complex challenges that will not be easily overcome, suggesting that blockchain technologies are unlikely to revolutionize health care in the near future.

你可以尝试使用大模型来生成摘要 立即生成

【Keywords】blockchain; health information management; health information systems; electronic health record; data sharing; health services administration; privacy of patient data; computer security; mobile phone

【发表时间】2021

【收录时间】2022-01-18

【文献类型】 综述

【DOI】 10.2196/24109

在线标注

备案号: 苏ICP备17025947号-5

评论回复