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  • Open Access

    ARTICLE

    A Framework Based on the DAO and NFT in Blockchain for Electronic Document Sharing

    Lin Chen1, Jiaming Zhu1, Yuting Xu1, Huanqin Zheng1, Shen Su1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2373-2395, 2024, DOI:10.32604/cmes.2024.049996 - 08 July 2024

    Abstract In the information age, electronic documents (e-documents) have become a popular alternative to paper documents due to their lower costs, higher dissemination rates, and ease of knowledge sharing. However, digital copyright infringements occur frequently due to the ease of copying, which not only infringes on the rights of creators but also weakens their creative enthusiasm. Therefore, it is crucial to establish an e-document sharing system that enforces copyright protection. However, the existing centralized system has outstanding vulnerabilities, and the plagiarism detection algorithm used cannot fully detect the context, semantics, style, and other factors of the… More >

  • Open Access

    ARTICLE

    NFT Security Matrix: Towards Modeling NFT Ecosystem Threat

    Peng Liao1, Chaoge Liu2, Jie Yin1,3,*, Zhi Wang2, Xiang Cui2

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3255-3285, 2024, DOI:10.32604/cmes.2024.043855 - 11 March 2024

    Abstract Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens (NFTs). To be specific, the total trading volume of digital assets reached an astounding $55.5 billion in 2022. Nevertheless, numerous security concerns have been raised by the rapid expansion of the NFT ecosystem. NFT holders are exposed to a plethora of scams and traps, putting their digital assets at risk of being lost. However, academic research on NFT security is scarce, and the security issues have aroused rare attention. In this study, the NFT ecological process is comprehensively explored. This… More >

  • Open Access

    ARTICLE

    Prediction of NFT Sale Price Fluctuations on OpenSea Using Machine Learning Approaches

    Zixiong Wang, Qiuying Chen, Sang-Joon Lee*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.037553 - 31 March 2023

    Abstract The rapid expansion of the non-fungible token (NFT) market has attracted many investors. However, studies on the NFT price fluctuations have been relatively limited. To date, the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction. The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea, the world’s largest NFT marketplace. We used Python programs to collect data and summarized them as: NFT information, collection information, and related account information. AdaBoost and Random… More >

  • Open Access

    ARTICLE

    The Non-Singular Fast Terminal Sliding Mode Control of Interior Permanent Magnet Synchronous Motor Based on Deep Flux Weakening Switching Point Tracking

    Xiangfei Li, Yang Yin, Yang Zhou, Wenchang Liu, Kaihui Zhao*

    Energy Engineering, Vol.120, No.2, pp. 277-297, 2023, DOI:10.32604/ee.2023.022461 - 29 November 2022

    Abstract This paper presents a novel non-singular fast terminal sliding mode control (NFTSMC) based on the deep flux weakening switching point tracking method in order to improve the control performance of permanent interior magnet synchronous motor (IPMSM) drive systems. The mathematical model of flux weakening (FW) control is established, and the deep flux weakening switching point is calculated accurately by analyzing the relationship between the torque curve and voltage decline curve. Next, a second-order NFTSMC is designed for the speed loop controller to ensure that the system converges to the equilibrium state in finite time. Then, More > Graphic Abstract

    The Non-Singular Fast Terminal Sliding Mode Control of Interior Permanent Magnet Synchronous Motor Based on Deep Flux Weakening Switching Point Tracking

  • Open Access

    ARTICLE

    Blockchain-Enabled Digital Rights Management for Museum-Digital Property Rights

    Liutao Zhao1,2, Jiawan Zhang1,3,*, Hairong Jing4

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1785-1801, 2022, DOI:10.32604/iasc.2022.029693 - 25 May 2022

    Abstract With the rapid development of digitization technology, digital copyright of museum has become more and more valuable. Its collections can be opened to and shared with the people through the Internet. However, centralized authorization, untransparent transaction information and risk of tampering data in traditional digital rights management have a strong impact on system normal operation. In this paper, we proposed a blockchain-based digital rights management scheme (BMDRM) that realizes a distributed digital rights management and authorization system by introducing non-fungible tokens (NFTs) and smart contracts. To ensure the security and efficiency of transactions and authorization, More >

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