A blockchain-based transaction system for private data sharing and trading

To address the private data management problems and realize privacy-preserving data sharing, a blockchain-based transaction system named Ecare featuring information transparency, fairness and scalability is proposed. The proposed system formulates multiple private data access control strategies, and realizes data trading and sharing through on-chain transactions, which makes transaction records transparent and immutable. In our system, the private data are encrypted, and the role-based account model ensures that access to the data requires owner’s authorization. Moreover, a new consensus protocol named Proof of Transactions (PoT) proposed by ourselves has been used to improve consensus efficiency. The value of Ecare is not only that it aggregates telemedicine, data transactions, and other features, but also that it translates these actions into transaction events stored in the blockchain, making them transparent and immutable to all participants. The proposed system can be extended to more general big data privacy protection and data transaction scenarios.     

Crowd management COVID-19

Crowds are a source of transmission in the COVID-19 spread. Contention and mitigation measures have focused on reducing people’s mass gathering. Such efforts have led to a drop in the economy. The application of a vaccine at a world level represents a grand challenge for humanity, and it is not likely to accomplish even within months. In the meantime, we still need tools to allow the people integration into their regular routines reducing the risk of infection. In this context, this paper presents a solution for crowd management. The aim is to monitor and manage crowd levels in interior places or point-of-interests (POI), particularly shopping centers or stores. The solution is based on a POI recommendation system that suggests the nearest safe options upon request of a particular POI to visit by the user. In this sense, it recommends places near the user location with the least estimated crowd. The recommendation algorithm uses a top-K approach and behavioral game theory to predict the user’s choice and estimate the crowd level for the requested POI. To evaluate the efficiency of this technological intervention in terms of the potential number of contacts of possible COVID-19 infections and the recommendation quality, we have developed an agent-based model (ABM). The adoption level of new technologies can be related to the end-user experience and trust in such technologies. As the end-user follows a recommendation that leads to uncrowded places, both the end-user experience and trust increased. We study and model this process using the OCEAN model of personality. The results from the studied scenarios showed that the proposed solution is widely adopted by the agents, as the trust factor increased from 0.5 (initial set value) to 0.76. In terms of crowd level, these are effectively managed and reduced on average by 40%. The mobility contacts were reduced by 40%, decreasing the risk of COVID-19 infection. An APP has been designed to support the described crowd management and contact tracing functionality. This APP is available on GitHub.     

LBTM: A lightweight blockchain-based trust management system for social internet of things

The Journal of Supercomputing - In order for the Internet of things to facilitate information sharing, the technology needs trustworthy mechanisms to ensure safe communications and reliable...     

Machine learning applications for COVID-19 outbreak management

Neural Computing and Applications - Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted practically every area of human life. Several machine learning (ML)...     

A blockchain-based decentralized efficient investigation framework for IoT digital forensics

The Journal of Supercomputing - Until now, there has been little research on digital forensics in the IoT (Internet of Things)-based infrastructure. Current digital forensic tools, investigation...     

Managing digital accessibility at universities during the COVID-19 pandemic

Universal Access in the Information Society - Students, faculty and staff with disabilities at universities have faced many digital accessibility barriers during the COVID-19 pandemic. While the...     

Intelligent system for COVID-19 prognosis: a state-of-the-art survey

Applied Intelligence - This 21st century is notable for experiencing so many disturbances at economic, social, cultural, and political levels in the entire world. The outbreak of novel corona virus...     

面向开放互联网的多媒体数字版权保护系统

针对数字内容安全和跨平台用户共享的实际需求,提出并实现一种面向开放互联网的多媒体数字版权保护方案及综合化平台原型系统。采用XML语言生成数字权利证书,以证书与用户设备硬件信息绑定的方式,实现受保护内容在Android和Windows平台上的安全播放和使用控制,满足了以上两种平台上基于权利证书的跨平台数字权利分享功能。该方案广泛适用于多媒体音视频数字内容安全平台。     

A blockchain-based framework for automatic SLA management in fog computing environments

The Journal of Supercomputing - Fog computing has become a prominent paradigm in providing shared resources to serve different applications near the edge. Similar to other computing paradigms such...     

基于EasyDL的新冠肺炎检测系统研究

通过EasyDL平台搭建基于CT影像的新冠肺炎检测系统,利用人工智能在图像识别上能够自动学习图像特征及区分图像特征之间差异的特点,来检测病人是否患有新冠肺炎.实验结果显示,新冠肺炎识别精确度为100.00％,感染性肺疾病识别精确度为98.06％,非感染性肺疾病识别精确度为93.64％,正常肺部识别精确度为98.03％....     

Making universal digital access universal: lessons from COVID-19 in Singapore

Digital resources—which include devices, internet connection and digital literacy—have become basic needs. Thus with the global COVID-19 pandemic having accelerated digitalization, the urgency for universal digital inclusion has hastened. Otherwise, digital inequality will lead to social inequality and impede social mobility. Using Singapore as a case study, this article applies the insights learned from a participatory action research to recommend a policy framework for universal digital access, with practical humanistic steps towards full digital inclusion. Singapore is a digitally advanced nation with almost universal digital availability, yet when COVID-19 forced rapid digital adoption, gaps in access by vulnerable groups such as low-income households, elderly and migrant workers were found. From the learning points on gaps and measures taken by community groups, volunteers and policy-makers in our research, we recommend making access to all three digital resources automatic and affordable, with an undergirding principle to implement technology among the most digitally excluded first before national roll out. A public-community-corporate funding and partnership model is also proposed to sustain universal provision.

     

一种弱中心化的银行可信数据管理方案

针对传统银行系统的中心化数据存储模式高效便捷但不透明、而新兴的去中心化的应用系统公开透明但共识机制低效的问题,提出了一种面向银行系统的总分双链的弱中心化可信数据管理方案。该模式的核心思想是应用区块链技术打造彼此交叉且相互印证的总分双链的数据存储结构,并利用分户账回溯定位技术,结合大量轻客户端基于密码学技术的分布式监督为个体提供交易验证的可能,从而实现数据的中心化可信存储与管理。它将中心化的数据存储与去中心化的数据验证相结合,从而兼有中心化管理的高效性和分布式机制的透明性,其本质上是一种民主监督下的中心模式,在满足银行独立,完全掌控数据的同时能够自证清白,并兼顾隐私与监督之间的平衡。     

CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing

World Wide Web - The healthcare industry faces serious problems with health data. Firstly, health data is fragmented and its quality needs to be improved. Data fragmentation means that it is...     

Enabling remote learning system for virtual personalized preferences during COVID-19 pandemic

Multimedia Tools and Applications - The education system worldwide has been affected by the Corona Virus Diseases 2019 (COVID-19) pandemic, resulting in the interruption of all educational...     

超级计算支撑的新冠肺炎CT影像综合分析辅助系统应用

目的 新冠肺炎（COVID-19）已经成为全球大流行疾病,在全球范围数百万人确诊。基于计算机断层扫描（computed tomography,CT）数据的影像学分析是临床诊断的重要手段。为了实现快速高效高精度地检测,提出了一种超级计算支撑的新冠肺炎CT影像综合分析辅助系统构建方法。方法 系统整个处理流程依次包括输入处理模块、预处理模块、影像学分析子系统和人工智能（artifiaial intelligence,AI）分析子系统4部分。其中影像学分析子系统通过分析肺实变、磨玻璃影和铺路石等影像学典型特征检测是否有肺炎和典型新冠肺炎特征,给出肺炎影像分析结论;AI分析子系统通过构建深度学习模型来区分普通病毒肺炎与新冠肺炎,增加肺炎的筛查甄别能力。结果 系统发布以来,持续稳定地为国内外超过三十家医院与一百多家科研机构提供了新冠肺炎辅助诊断服务和科研支撑,为抗击疫情提供重要支撑。结论 本文提出的超级计算支撑的新冠肺炎CT影像综合分析辅助系统构建方法,取得了应用效果,是一种有效实现快速部署服务、对突发疫情提供高效支撑的服务方式。     

A digital twin-driven human-robot collaborative assembly approach in the wake of COVID-19

In the wake of COVID-19, the production demand of medical equipment is increasing rapidly. This type of products is mainly assembled by hand or fixed program with complex and flexible structure. However, the low efficiency and adaptability in current assembly mode are unable to meet the assembly requirements. So in this paper, a new framework of human-robot collaborative (HRC) assembly based on digital twin (DT) is proposed. The data management system of proposed framework integrates all kinds of data from digital twin spaces. In order to obtain the HRC strategy and action sequence in dynamic environment, the double deep deterministic policy gradient (D-DDPG) is applied as optimization model in DT. During assembly, the performance model is adopted to evaluate the quality of resilience assembly. The proposed framework is finally validated by an alternator assembly case, which proves that DT-based HRC assembly has a significant effect on improving assembly efficiency and safety.     

A Web-based monitor and management system architecture for enterprise virtual private network

Virtual private network (VPN) not only possesses the low cost, inexpensive fees, and excellent support advantages of the Internet, it also has the benefit of the security as the leased line. How to properly manage the VPN is an issue in which the enterprise IT engineers have to take seriously.

This research is based on the new network management technologies such as policy-based network management, mobile agent, etc., to design a VPN monitor and management system architecture that contains high level management with low network traffic load. This system architecture integrates both VPN devices and general network devices, such the feature can integrate the monitor and manage the VPN and Intranet at the same time.

The result of this research provides enterprises with a VPN architecture for monitoring and managing the enterprises, as well as to establish a prototype for the enterprise VPN monitor and management system. Such system architecture can effectively assist the semiconductor companies to monitor and manage their enterprise VPN in order to utilize the Internet resources, and to reduce the possible operation off time. The prototype system could proof the feasibility of the systematic architecture, it can automatically detect and activate the backup mechanism according to the preset management policy, and to achieve the effective and fast solution for the enterprise network problems.     

数字孪生水利建设保障体系应用与思考

推进数字孪生水利建设是贯彻落实“节水优先、空间均衡、系统治理、两手发力”治水思路和《数字中国建设整体布局规划》的明确要求,为保障数字孪生水利建设有力有序进行,亟须构建一套结构合理、系统全面的保障体系予以支撑。紧扣“需求牵引、应用至上、数字赋能、提升能力”的总体要求,提出数字孪生水利建设保障体系,通过2022年水利部开展的数字孪生流域建设先行先试予以实践验证,对进一步做好数字孪生水利建设保障工作提出建议,为数字孪生水利建设全过程管理提供有力支撑。通过实践应用,有效保障数字孪生流域建设先行先试中期评估工作顺利完成,并形成一批可复制和可推广的应用案例,成效良好,可为有关单位开展先行先试或其他专项工作提供参考借鉴。     

GBRM: a graph embedding and blockchain-based resource management framework for 5G MEC

The Journal of Supercomputing - In the 5G scenario of the convergence of information technology (IT) and communication technology (CT), multi-operators collaborate to form edge computing, which...