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Wyszukujesz frazę "Jiang, W. B." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Study on recovery of lead, zinc, iron from jarosite residues and simultaneous sulfur fixation by direct reduction
Autorzy:
Wang, Y.
Yang, H.
Zhang, W.
Song, R.
Jiang, B.
Powiązania:
https://bibliotekanauki.pl/articles/110933.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
jarosite
direct reduction
recovery
valuable metal
sulfur fixation
Opis:
Jarosite residues, which are generated in a zinc production plant by a hydrometallurgical process, contain a large amount of valuable metal components. In this study, a method was proposed for the recovery of lead, zinc and iron from the residues and simultaneous sulfur fixation through direct reduction followed by magnetic separation. The influences of the roasting temperature, roasting time and the concentration of SO2 gas in the direct reduction process were researched in detail. Results showed that the volatilization rates of lead, zinc and sulfur were 96.97%, 99.89% and 1.09%, respectively, and the iron metallization rate was 91.97% under optimal reduction conditions; roasting temperature 1523 K for 60 min. The magnetic concentrate with the iron content of 90.59% and recovery rate of 50.87% was obtained from the optimal reduction product by grinding and magnetic separation. The optimum fineness for separation 96.56% less than 37 μm accounted with magnetic field strength 24 kA/m. The theoretical analysis was carried out by thermodynamics, X-ray powder diffraction, gas analysis and scanning electron microscopy.
Źródło:
Physicochemical Problems of Mineral Processing; 2018, 54, 2; 517-526
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Personal identification based on brain networks of EEG signals
Autorzy:
Kong, W.
Jiang, B.
Fan, Q.
Zhu, L.
Wei, X.
Powiązania:
https://bibliotekanauki.pl/articles/329856.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
electroencephalogram signal
personal identification
brain network
phase synchronization
elektroencefalogram
identyfikacja osobowa
sieć mózgowa
synchronizacja fazy
Opis:
Personal identification is particularly important in information security. There are numerous advantages of using electroencephalogram (EEG) signals for personal identification, such as uniqueness and anti-deceptiveness. Currently, many researchers focus on single-dataset personal identification, instead of the cross-dataset. In this paper, we propose a method for cross-dataset personal identification based on a brain network of EEG signals. First, brain functional networks are constructed from the phase synchronization values between EEG channels. Then, some attributes of the brain networks including the degree of a node, the clustering coefficient and global efficiency are computed to form a new feature vector. Lastly, we utilize linear discriminant analysis (LDA) to classify the extracted features for personal identification. The performance of the method is quantitatively evaluated on four datasets involving different cognitive tasks: (i) a four-class motor imagery task dataset in BCI Competition IV (2008), (ii) a two-class motor imagery dataset in the BNCI Horizon 2020 project, (iii) a neuromarketing dataset recorded by our laboratory, (iv) a fatigue driving dataset recorded by our laboratory. Empirical results of this paper show that the average identification accuracy of each data set was higher than 0.95 and the best one achieved was 0.99, indicating a promising application in personal identification.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2018, 28, 4; 745-757
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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