【影响因子】17.521
【主题类别】
--
【Abstract】Recent advances in flexible wearable devices have boosted the remarkable development of devices for human-machine interfaces, which are of great value to emerging cybernetics, robotics, and Metaverse systems. However, the effectiveness of existing approaches is limited by the quality of sensor data and classification models with high computational costs. Here, a novel gesture recognition system with triboelectric smart wristbands and an adaptive accelerated learning (AAL) model is proposed. The sensor array is well deployed according to the wrist anatomy and retrieves hand motions from a distance, exhibiting highly sensitive and high-quality sensing capabilities beyond existing methods. Importantly, the anatomical design leads to the close correspondence between the actions of dominant muscle/tendon groups and gestures, and the resulting distinctive features in sensor signals are very valuable for differentiating gestures with data from 7 sensors. The AAL model realizes a 97.56% identification accuracy in training 21 classes with only one-third operands of the original neural network. The applications of the system are further exploited in real-time somatosensory teleoperations with a low latency of <1 s, revealing a new possibility for endowing cyber-human interactions with disruptive innovation and immersive experience.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】flexible electronics; gesture recognition; human-machine interfaces; machine learning
【发表时间】
【收录时间】2023-03-04
【文献类型】
【DOI】 10.1002/advs.202205960
【影响因子】8.839
【主题类别】
--
【Abstract】In recent years, blockchain holds promise to impact a wide range of application areas, but it still suffers from technical challenges such as security and scalability. The increase in the number of transactions puts blockchains under data storage pressure. The emergence of cross-chain technologies connects different blockchains and relieves the data storage pressure. However, the existing research generally focuses on the technical realization of cross chain, lacking in-depth research on consistency issues like data integ-rity verification of cross-chain interaction. In this paper, we propose a decentralized cross-chain data integrity verification scheme (DCIV) from the point of view of governing the chain by chain. We adopt su-pervision chain to audit the integrity of data in cross-chain interaction. We preprocess the off-chain orig-inal data in the form of Merkle tree. Before cross-chain interaction, we process the data with KZG polynomial commitment. During the auditing period, the supervision chain generates a challenge and verifies the integrity of cross-chain data. In particular, we add audit digests into the structure of transac-tions in blockchain to reduce the storage burden during auditing. Theoretical and experimental analyses demonstrate that DCIV can verify the integrity of data in cross-chain interaction, achieving secure and accurate cross-chain data sharing.(c) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Governing the chain by chain; Data integrity verification; Blockchain-enabled auditing; Cross chain; Smart contract
【发表时间】2022
【收录时间】2023-03-04
【文献类型】
【Author】 Li, Jiahao Zhang, Yong Yang, Xingyu Chen, Liangwei
【影响因子】7.466
【主题类别】
--
【Abstract】Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior results in many sequence modeling tasks. The ability of Transformer to capture long-range dependen-cies and interactions makes it possible to apply it in the field of portfolio management (PM). However, the built-in quadratic complexity of the Transformer prevents its direct application to the PM task. To solve this problem, in this paper, we propose a deep reinforcement learning -based PM framework called LSRE-CAAN, with two important components: a long sequence representations extractor and a cross-asset attention network. Direct Policy Gradient is used to solve the sequential decision problem in the PM process. We conduct numerical experiments in three aspects using four different cryptocurrency datasets, and the empirical results show that our framework is more effective than both traditional and state-of-the-art (SOTA) online portfolio strategies, achieving a 6x return on the best dataset. In terms of risk metrics, our framework has an average volatility risk of 0.46 and an average maximum drawdown risk of 0.27 across the four datasets, both of which are lower than the vast majority of SOTA strategies. In addition, while the vast majority of SOTA strategies maintain a poor turnover rate of approximately greater than 50% on average, our framework enjoys a relatively low turnover rate on all datasets, efficiency analysis illustrates that our framework no longer has the quadratic dependency limitation.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Portfolio management; Deep reinforcement learning; Cryptocurrency; Bitcoin; Online learning; High-frequency trading
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【影响因子】6.348
【主题类别】
--
【Abstract】As an emerging distributed technology, blockchain has begun to penetrate into many fields such as finance, healthcare, supply chain, intelligent transportation. However, the interoperability and value exchange between different independent blockchain systems is restricting the expansion of blockchain. In this paper, a notary groupbased cross-chain interaction model is proposed to achieve the interoperability between different blockchains. Firstly, a notary election mechanism is proposed to choose one notary from the notary group to act as a bridge for cross-chain transactions. Secondly, a margin pool is introduced to limit the misconduct of the elected notary and ensure the value transfer between the involved blockchains. Moreover, a reputation based incentive mechanism is used to encourage members of the notary group to participate in cross-chain transactions. Ethereum-based experiments demonstrate that the proposed mechanism can provide an acceptable performance for cross-chain transactions and provide a higher security level than ordinary cross-chain mechanisms.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Cross -chain; Notary group; Reputation ranking; Incentive mechanisms
【发表时间】2022
【收录时间】2023-03-04
【文献类型】
【Author】 Ameyaw, Ernest E. Edwards, David J. Kumar, Bimal Thurairajah, Niraj Owusu-Manu, De-Graft Oppong, Goodenough D.
【影响因子】5.292
【主题类别】
--
【Abstract】Construction projects are premised upon contractual arrangements, and contracts constitute the basis of their success. A contract enables execution of work and transfer of payments, tracking of key performance indicators, and facilitation of collaboration among project stakeholders. Historically, construction projects have faced critical challenges due to poor alignment between clients' expectations, contract terms, and contractor performance. The advent of advanced digital technologies under the concept of Industry 4.0 has the potential to benefit construction projects through application of blockchain-enabled smart contracts. However, the adoption of smart contracts in construction projects is in its early stages, and the factors that will influence its adoption remain unclear. Therefore, this study aimed to explore and establish the critical factors influencing adoption of smart contracts in construction contractual arrangements. This study administered an international questionnaire survey among experienced construction practitioners with involvement in smart contract initiatives and activities. The results obtained from descriptive statistics and fuzzy set-based analysis show that trialability, relative advantage, competitive advantage, and compatibility of smart contracts are the important predictors of the adoption of such contracts. The findings suggest that practitioners share a view that technological characteristics of blockchain-enabled smart contracts are critical to their adoption, regarding the technology's perceived practicality in improving effectiveness and efficiency of construction projects. This study contributes to technology diffusion research in construction and highlights drivers that require practitioners' and industry leaders' attention to ensure successful adoption of smart contracts for cost-effective delivery of construction projects.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Smart contracts; Blockchain technology; Construction projects; Construction industry
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【Author】 Liu, Hexu Han, SangHyeok Zhu, Zhenhua
【影响因子】5.292
【主题类别】
区块链应用-实体经济-制造领域
【Abstract】The construction industry has been criticized for low productivity, lack of collaboration and information sharing, poor contract administration, and the like due to its decentralized and fragmented structure as well as sequential and chain-resembling nature. Recently, blockchain technology and its benefits have received wide attention and interest. This research synthesizes the research trends and needs of this growing area by means of a bibliometric-qualitative review method. Scopus and Web of Science were selected as the literature databases to retrieve relevant academic publications. Through a systematic literature search and screening, 181 related articles were identified for bibliometric analysis, and 149 publications were critically discussed in a qualitative review. The bibliometric results indicated the recent research regarding blockchain in construction is primarily directed into several clusters, such as "smart contract," "Building Information Modeling (BIM)," "supply chain management," "construction contract," "construction and project management," "digital twin," and "smart city." These clusters were further synthesized for a qualitative review revealing deep insight into research challenges and gaps. Both quantitative and qualitative review results were then mapped to the future directions. It was noted that future research needs to focus on (1) quantifying the cost-benefits of the blockchain applications in construction, e.g., return on investment, practitioners training, and improving industry readiness, (2) integration of blockchain with different project delivery systems, and (3) technology fusion with blockchain for construction management.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Construction management; Digital twin; Supply chain; Literature review
【发表时间】2023
【收录时间】2023-03-04
【文献类型】 综述
【Author】 Chen, Ge Huang, Baoxiang Yang, Jie Radenkovic, Milena Ge, Linyao Cao, Chuanchuan Chen, Xiaoyan Xia, Linghui Han, Guiyan Ma, Ying
【影响因子】5.247
【主题类别】
--
【Abstract】Oceans at a depth ranging from similar to 100 to similar to 1000-m (defined as the intermediate water here), though poorly understood compared to the sea surface, is a critical layer of the Earth system where many important oceanographic processes take place. Advances in ocean observation and computer technology have allowed ocean science to enter the era of big data (to be precise, big data for the surface layer, small data for the bottom layer, and the intermediate layer sits in between) and greatly promoted our understanding of near-surface ocean phenomena. During the past few decades, however, the intermediate ocean is also undergoing profound changes because of global warming, the research and prediction of which are of intensive concern. Due to the lack of three-dimensional ocean theories and field observations, how to remotely sense the intermediate ocean from space becomes a very attractive but challenging scientific issue. With the rapid development of the next generation of information technology, artificial intelligence (AI) has built a new bridge from data science to marine science (called Deep Blue AI, DBAI), which acts as a powerful weapon to extend the paradigm of modern oceanography in the era of the metaverse. This review first introduces the basic prior knowledge of water movement in the similar to 100 m ocean and vertical stratification within the similar to 1000-m depths as well as the data resources provided by satellite remote sensing, field observation, and model reanalysis for DBAI. Then, three universal DBAI methodologies, namely, associative statistical, physically informed, and mathematically driven neural networks, are elucidated in the context of intermediate ocean remote sensing. Finally, the unique advantages and potentials of DBAI in data mining and knowledge discovery are demonstrated in a top-down way of "surface-to-interior" via several typical examples in physical and biological oceanography.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】deep blue artificial intelligence; intermediate ocean; ocean remote sensing; associative statistical neural network; physically informed neural network; mathematically driven neural network
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【Author】 Indushree, M. Raj, Manish Mishra, Vipul Kumar Shashidhara, R. Das, Ashok Kumar Bhat, K. Vivekananda
CCF-C
【影响因子】5.047
【主题类别】
--
【Abstract】Designing a secure and efficient authentication protocol is crucial and challenging in the mobility network. Due to the seamless roaming of mobile users over multiple foreign agents and the broadcast nature of the communication channel, the mobile networks are often exposed to several network attacks. To achieve perfect authentication and secure communication among mobility entities like MU (Mobile User), FA (Foreign Agent) and HA (Home Agent), the researchers have proposed numerous authentication protocols in the past. However, the existing protocols for the mobility environments are insufficient to address the fundamental security concerns and an adversary can impersonate the mobile user at anytime. Thus, we propose Mobile-Chain, a secure blockchain-based authentication system for mobility environments. The proposed Mobile-Chain is de-signed to protect user privacy and guarantees provable security like authentication, anonymity, untraceability, confidentiality, data integrity, and decentralization. The implementation of the security framework has been done on the ethereum blockchain platform using smart contracts written in a solidity programming language. The security analysis reveals that Mobile-Chain is robust against various security threats to which mobility networks are vulnerable. Besides, the authentication framework has been measured through a formal security verification tool known as Automated Validation of Internet Security Protocol and Application (AVISPA). Notably, the performance evaluation of the proposed protocol proves that it maintains performance gain, computationally efficient, and implementable in resource-limited wireless and mobility environments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Mutual authentication; Blockchain; Smart-contracts; Mobility network; Security
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【影响因子】4.750
【主题类别】
--
【Abstract】PurposeThis study investigated the internal factors that influence the adoption of cryptocurrencies for remittance transactions in the United Arab Emirates (UAE) by examining the relationships between behavioural intention (BI) and perceived risk (PR), as well as the mediating effect of consumer innovation (CI).Design/methodology/approachThe authors developed a structural model using scales from the literature. The authors distributed an online questionnaire, evaluated by five cryptocurrency experts, using a snowball approach and collected 270 responses.FindingsThe results revealed that CI mediates the relationship between PR and BI. Also, CI enhances intentions to use cryptocurrencies for remittance transactions. However, PR has a negative impact on BI.Research limitations/implicationsThis research adds to the body of knowledge by examining the acceptance and implementation of cryptocurrencies in the UAE and by developing and evaluating new constructs based on current notions. The study also contributes to the current understanding of cryptocurrencies and blockchain adoption. This article focusses on the mediating impact of CI on intentions to employ cryptocurrency instruments for international money transfers.Practical implicationsThe conclusions of the research give advice for marketers on how to boost the commercialisation of cryptocurrencies in the UAE remittance market and may pave the way for other studies to assist impending developments in the UAE cryptocurrency industry.Originality/valueThis research offers novel insights into CI as a significant predictor of bitcoin product uptake in the remittance business.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Cryptocurrencies; Blockchain; Remittances; Innovation; Financial inclusion
【发表时间】
【收录时间】2023-03-04
【文献类型】
【Author】 Kaka, Nirja Sethi, Yashendra Patel, Neil Kaiwan, Okashah Al-Inaya, Yana Manchanda, Kshitij Uniyal, Nidhi
【影响因子】4.477
【主题类别】
--
【Abstract】Background: Chronic Kidney Disease (CKD) shows a wide range of renal abnormalities including the excretory, metabolic, endocrine, and homeostatic function of the kid-ney. The prognostic impact of the 'endocrine manifestations' which are often overlooked by clinicians cannot be over-stated.Methods and objectives: A systematic review was attempted to provide a comprehensive overview of all endocrine abnor-malities of CKD and their evolving principles of management, searching databases of PubMed, Embase, and Scopus and covering the literature between 2002 and 2022. Results: The endocrine derangements in CKD can be at-tributed to a myriad of pathologic processes, in particular decreased clearance, impaired endogenous hormone pro-duction, uremia-induced cellular dysfunction, and activation of systemic inflammatory pathways. The major disorders include anemia, hyperprolactinemia, insulin resistance, reproductive hormone deficiency, thyroid hormone defi-ciency, and serum FGF (Fibroblast Growth Factor) alteration. Long-term effects of CKD also include malnutrition and increased cardiovascular risk. The recent times have unveiled their detailed pathogenesis and have seen an evolution in the principles of management which necessitates a revision of current guidelines. Conclusion: Increased advertence regarding the pathology, impact, and management of these endocrine derangements can help in reducing morbidity as well as mortality in the CKD patients by allowing prompt individualized treatment. Moreover, with timely and appropriate intervention, a long-term reduction in complications, as well as an enhanced quality of life, can be achieved in patients with CKD.(c) 2022 Elsevier Inc. All rights reserved.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】CKD; Endocrine; Hormones; Anemia in CKD; MIA (malnutrition-inflammation-atherosclerosis); syndrome
【发表时间】2022
【收录时间】2023-03-04
【文献类型】
【Author】 Liu, Tao Yuan, Yi Yu, Zhongyang
【影响因子】3.476
【主题类别】
--
【Abstract】This paper uses blockchain technology to conduct in-depth research and analysis on enterprise cost optimization control. Based on the analysis of the cost control status in enterprises, the concept of target cost optimization control and specific control ideas are proposed. And the study of optimization control under target cost based on genetic algorithm is carried out in combination with the current three major controls of quality, schedule, and cost. It provides the technical basis for the realization of the target profit of the enterprise. The Optimized Scalable Byzantine Fault Tolerance (OSBFT) algorithm, which is suitable for spectrum sharing, is proposed based on PBFT (Practical Byzantine Fault Tolerance) algorithm. So, in this paper, an improved consensus algorithm OSBFT (Optimized Scalable Byzantine Fault Tolerance) is proposed based on it. The improved genetic algorithm is used to solve the objective function and verify the validity, reasonableness and applicability of the model and algorithm. It is shown that the introduction of delay cost in the multilevel inventory model reduces the total cost of the optimized model by 16.87% compared to previous studies. The algorithm reduces the consensus steps, incorporates a data synchronization mechanism, and enables nodes to join and exit consensus.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Intelligent optimization control; blockchain; enterprise cost; information security; machine learning
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【Author】 Sundareswaran, N. Sasirekha, S.
【影响因子】3.401
【主题类别】
--
【Abstract】Smart internet of things (IoT) devices are used to manage domestic and industrial energy needs using sustainable and renewable energy sources. Due to cyber infiltration and a lack of transparency, the traditional transaction process is inefficient, unsafe and expensive. Smart grid systems are now efficient, safe and transparent owing to the development of blockchain (BC) technology and its smart contract (SC) solution. In this study, federated learning extreme gradient boosting (FL-XGB) framework has been developed along with BC to learn the intrusion inside the smart energy system. FL is best suited for a decentralized BC-enabled system to adapt learning models for trustworthy and reliable transactions. Many features and attributes of the Third International Knowledge Discovery and Data mining Tools Competition (KDD Cup 1999) dataset have been used in this study to perform experimental analysis. The likelihood of intrusions in the network is mathematically stated. The participant nodes run the BC based FLgated learning results from the experiment that was 99% accurate in predicting network intrusion. The experimentally determined block storage gain and retrieval gain were 97.5% and 95.4% respectively. The intrusion in the smart grid network was evaluated, and the data indicated that there was 1.2% illegal access. Moreover, the learning system's accuracy, retrieval and storage intrusions, legal access and transaction processing times were considered for comparison. The proposed system outperformed contemporary research-developed systems targeted for the same application. Therefore, this study provides a guaranteed intrusion learning system and secure transaction system for smart grids.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; federated learning system; intrusion detection; internet of things; smart grids
【发表时间】2023
【收录时间】2023-03-04
【文献类型】
【Author】 Li, Rong Wang, Shangping Xie, Na
CCF-C
【影响因子】1.968
【主题类别】
--
【Abstract】Because of the characteristics of decentralization, immutability, and transparency, blockchain has gradually become a new and revolutionary technology, which has far-reaching significance for the development of modern technology. However, the traditional Bitcoin blockchain that supports synchronous consensus suffers from the fatal flaw of low throughput. To improve throughput, a number of DAG distributed ledgers have been proposed that support asynchronous consensus, all of which allow multiple nodes to process concurrent transactions asynchronously. However, most DAG distributed ledgers do not implement consistent sorting of transactions, making it difficult to deploy smart contracts. To overcome this problem, in this paper, an epoch-based transaction consistency sorting protocol for DAG distributed ledger is proposed, which not only provides the possibility for the deployment of smart contracts but also can be used to resolve conflicting transactions in the ledger. Transaction consistency sorting protocol provides a more reasonably ordered list of all transactions by taking scalars, such as the set of their own past and future, parent block, and timestamp. In addition, through theoretical analysis, the stability and rationality of the transaction consistency sorting protocol are proved, and there is no Condorcet cycle. Finally, the simulation results demonstrate the protocol is efficient and achieve a throughput of at least 2000 transactions per second.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】
【发表时间】2022
【收录时间】2023-03-04
【文献类型】
【DOI】 10.1155/2022/3930858
【Author】 Sopher, Hadas Lescop, Laurent
【影响因子】0.000
【主题类别】
--
【Abstract】PurposeThis paper aims to describe the immersive atelier model (IAM), a pedagogical model for remote inter-university studios that promotes quality education. The IAM uses multi-user virtual environments (MUVEs) in two atelier types: A predefined MUVE and a student-shaped one. The study questions how the IAM, using MUVEs, meets the needs of remote inter-university studios. The research explores how MUVE types are used and experienced by students.Design/methodology/approachForty-six students that participated in a remote studio course involving three universities were monitored through observations and a post-course questionnaire, responded to by twenty-five students.FindingsFindings provide insights into the learners' experience and a rich description of the teaching and learning acts that emerged while using the MUVEs types. Student-shaped MUVEs were found particularly supportive of acts associated with indirect learning and conceptualization. The study identifies subtypes of student-shaped MUVEs that support these desired educational acts.Research limitations/implicationsFindings provide encouraging insights for expanding the traditional atelier beyond its physical constraints and supporting sustainable quality education in remote inter-university studios.Practical implicationsThe IAM can assist tutors in designing future virtual design studios to achieve diverse knowledge and learning progress.Social implicationsThis paper fulfills an identified need to update the atelier pedagogical model to support sustainable quality education in remote inter-university studios. Based on the affordances of MUVEs, the IAM expands the traditional atelier with types of virtual ateliers to support the learners' sense of belongingness and engagement.Originality/valueInnovatively, the IAM simultaneously uses MUVEs as educational and design spaces that enhance learning.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Multi-user virtual environments; Immersion; SDG; Learning spaces; Learning experience; Virtual design studio
【发表时间】
【收录时间】2023-03-04
【文献类型】
【作者】 颜亮;葛丽娜;胡政;
【作者单位】广西民族大学人工智能学院;
【文献来源】计算机应用研究
【复合影响因子】1.888
【综合影响因子】1.138
【主题类别】
--
【摘要】对云数据进行访问控制能够限制非法访问、提高数据隐私安全，属性基可搜索加密是实现数据细粒度访问控制的关键技术之一。针对云数据访问中单一授权性能瓶颈、搜索功能局限等问题，提出一种基于区块链的属性基多关键词排序搜索方案。该方案采用多授权机制降低了系统计算负担，同时将属性基可搜索加密技术与区块链技术相结合，实现了云数据的细粒度访问控制与公平搜索。此外，引入向量空间模型和TF-IDF加权技术实现了多关键词搜索结果排序，提高了搜索效率。安全性分析、性能分析表明该方案能抵抗选择明文攻击和关键词猜测攻击，并具备较低的通信和计算开销。
【关键词】区块链;;属性基加密;;多授权中心;;多关键词排序搜索;;访问控制
【文献类型】
【发表时间】2023-03-04
【作者】 李志文;徐贤浩;关旭;柏庆国;陈程;
【作者单位】华中科技大学管理学院;曲阜师范大学管理学院;江汉大学人工智能学院;
【文献来源】中国管理科学
【复合影响因子】
【综合影响因子】
【主题类别】
区块链应用-实体经济-农牧领域
【摘要】为减轻消费者对农产品质量的担忧和增强消费者对产品质量的感知，企业正尝试利用区块链对农产品进行品质溯源和质量披露。运用信号博弈理论和演化博弈理论探究了农产品市场双寡头的区块链采纳决策问题，并进一步分析了忠诚型消费者的存在和政府的补贴机制对区块链采纳决策演化均衡的影响。研究表明：双寡头区块链采纳决策的演化均衡结果取决于区块链的附加值与农产品的附加值比值的大小，当该比值很小且不断增大时，双寡头将依次经历三个阶段，即从均不采纳，到在均采纳和均不采纳之间摇摆，再到均采纳。忠诚型消费者的存在将使企业更容易陷入到摇摆阶段，而政府的补贴政策可以帮助企业跳出摇摆阶段，也即使双寡头均采纳区块链。
【关键词】农产品;;双寡头;;区块链;;信号博弈;;演化博弈
【文献类型】 理论模型
【发表时间】2023-03-04