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Copyright of New Building Materials / Xinxing Jianzhu Cailiao is the property of New Building Materials Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dataspace is the transformation of cyberspace from "computing centric" to "data centric", which contains great technological issues and innovative opportunities. Similar to the internet, which is the main infrastructure of cyberspace, dataspace also needs a new "data-centric" infrastructure, whose core function is to realize the first-class entity of data. From the perspective of dataspace, the supports and shortcomings of mainstream technologies such as the internet, the World Wide Web, and the digital object architecture for the first-class entity of data were analyzed and summarized, and then the basic connotations and technical challenges of dataspace infrastructure were given. Finally, a first-class data substantialization method based on data pragmatics was proposed. Based on this method, a solution called the internet of data by integrating digital object architecture, distributed ledger, smart contract, and other technologies was proposed to support the construction and operation of internetscale dataspace infrastructure. [ABSTRACT FROM AUTHOR]

Copyright of Journal Of Sichuan University (Natural Sciences Division) / Sichuan Daxue Xuebao-Ziran Kexueban is the property of Editorial Department of Journal of Sichuan University Natural Science Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the problem of poor performance of the traditional DOA estimations in coherent signals, low signal-to-noise ratio(SNR) and non-uniform noise. This paper proposed a DOA method based on the modified matrix decomposition, with the best covariance matrix by the convex optimization. The modified matrix decomposition method could deal with the extraction of the coherent sources, while overcoming the aperture loss. Furthermore, the method reconstructed the noise free covariance matrix by the convex optimization. Finally, it used minimization search to calculate DOA. The simulation results show that, comparing to the MD algorithm, l1-SVD algorithm and SS-CRM algorithm, the method suppresses the non-uniform noise well and has good performance in low SNR. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of Beijing Institute of Technology is the property of Beijing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)