The current research on the blockchain includes study on network architecture and the incentive. In this paper, an introduction to the architecture of information technology was given and the goal and research status ...The current research on the blockchain includes study on network architecture and the incentive. In this paper, an introduction to the architecture of information technology was given and the goal and research status of the incentive layer of blockchain were illustrated with digital economy development as the backdrop. The existing issuance of token was elaborated from computation, storage and transmission, three core facets of network technology. The development of the token allocation and the path was analyzed to confirm its rationality. It discusses the possible directions and challenges of the future research on blockchain incentive.展开更多
Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the lon...Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the long-standing challenges in the application of AI to scientific problems.To meet this challenge in the burgeoning field of AI for chemistry,we may adopt the paradigm of knowledge graph.Herein,focusing on catalytic chemical reactions,we have developed a semantic knowledge graph framework based on both structured and unstructured data,the latter of which are extracted from the text of 220,000articles on catalysts for organic molecules.The framework captures the latent knowledge of reactant-catalyst-product relationships and can therefore provide accurate recommendation on potential catalysts for targeted reaction,which especially facilitates the research involving large molecules.This study presents a viable pathway towards the implementation of literature-based data management in a catalyst recommendation platform.展开更多
Reliable identity management and authentication are significant for network security.In recent years,as traditional centralized identity management systems suffer from security and scalability problems,decentralized i...Reliable identity management and authentication are significant for network security.In recent years,as traditional centralized identity management systems suffer from security and scalability problems,decentralized identity management has received considerable attention in academia and industry.However,with the increasing sharing interaction among each domain,management and authentication of decentralized identity has raised higher requirements for cross-domain trust and faced implementation challenges galore.To solve these problems,we propose BIdM,a decentralized crossdomain identity management system based on blockchain.We design a decentralized identifier(DID)for naming identities based on the consortium blockchain technique.Since the identity subject fully controls the life cycle and ownership of the proposed DID,it can be signed and issued without a central authentication node’s intervention.Simultaneously,every node in the system can participate in identity authentication and trust establishment,thereby solving the centralized mechanism’s single point of failure problem.To further improve authentication efficiency and protect users’privacy,BIdM introduces a one-way accumulator as an identity data structure,which guarantees the validity of entity identity.We theoretically analyze the feasibility and performance of BIdM and conduct evaluations on a prototype implementation.The experimental results demonstrate that BIdM achieves excellent optimization on cross-domain authentication compared with existing identity management systems.展开更多
文摘The current research on the blockchain includes study on network architecture and the incentive. In this paper, an introduction to the architecture of information technology was given and the goal and research status of the incentive layer of blockchain were illustrated with digital economy development as the backdrop. The existing issuance of token was elaborated from computation, storage and transmission, three core facets of network technology. The development of the token allocation and the path was analyzed to confirm its rationality. It discusses the possible directions and challenges of the future research on blockchain incentive.
基金supported by Guangdong Basic and Applied Basic Research Foundation(2023A1515011391 and 2020A1515110843)the Soft Science Research Project of Guangdong Province(2017B030301013)+2 种基金the National Key Research and Development Program of China(2022YFB2702301)the Key-Area Research and Development Program of Guangdong Province(2020B0101090003)the Major Science and Technology Infrastructure Project of Material Genome Big-science Facilities Platform supported by Municipal Development and Reform Commission of Shenzhen
文摘Our ability to perceive the correlation of different substances in the world is one of the key aspects of human intelligence.The passing of this faculty to artificial intelligence(AI)represents arguably one of the long-standing challenges in the application of AI to scientific problems.To meet this challenge in the burgeoning field of AI for chemistry,we may adopt the paradigm of knowledge graph.Herein,focusing on catalytic chemical reactions,we have developed a semantic knowledge graph framework based on both structured and unstructured data,the latter of which are extracted from the text of 220,000articles on catalysts for organic molecules.The framework captures the latent knowledge of reactant-catalyst-product relationships and can therefore provide accurate recommendation on potential catalysts for targeted reaction,which especially facilitates the research involving large molecules.This study presents a viable pathway towards the implementation of literature-based data management in a catalyst recommendation platform.
基金Key-Area Research and Development Program of Guangdong Province(2020B0101090003)National Natural Science Foundation of China(62072012)+2 种基金Shenzhen Research Project(JSGG20191129110603831)Shenzhen Key Laboratory Project(ZDSYS201802051831427)the project PCL Future Regional Network Facilities for Large Scale Experiments and Applications。
文摘Reliable identity management and authentication are significant for network security.In recent years,as traditional centralized identity management systems suffer from security and scalability problems,decentralized identity management has received considerable attention in academia and industry.However,with the increasing sharing interaction among each domain,management and authentication of decentralized identity has raised higher requirements for cross-domain trust and faced implementation challenges galore.To solve these problems,we propose BIdM,a decentralized crossdomain identity management system based on blockchain.We design a decentralized identifier(DID)for naming identities based on the consortium blockchain technique.Since the identity subject fully controls the life cycle and ownership of the proposed DID,it can be signed and issued without a central authentication node’s intervention.Simultaneously,every node in the system can participate in identity authentication and trust establishment,thereby solving the centralized mechanism’s single point of failure problem.To further improve authentication efficiency and protect users’privacy,BIdM introduces a one-way accumulator as an identity data structure,which guarantees the validity of entity identity.We theoretically analyze the feasibility and performance of BIdM and conduct evaluations on a prototype implementation.The experimental results demonstrate that BIdM achieves excellent optimization on cross-domain authentication compared with existing identity management systems.
