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Dao Viet Thang,Du Thi Xuan Thao,Nguyen Van Minh 한국자기학회 2016 Journal of Magnetics Vol.21 No.1
Nd-doped BiFeO₃ materials were synthesized via a sol–gel method. The crystal structure, magnetic properties, and complex impedance spectroscopy of multiferroic Bi1-xNdxFeO₃ (BNFO) materials were investigated by Xray diffraction (XRD), Raman scattering, vibrating sample magnetometer (VSM), and complex impedance spectroscopy. Our results show that the lattice crystal constants (a, c) and the ratio c/a of BNFO materials decreased with increasing Nd concentration. All samples exhibited weak ferromagnetism at room temperature, and the magnetization of samples was enhanced by the presence of Nd<SUP>3+</SUP> ions. There was an enhancement in the spontaneous magnetization of BFO with increasing Nd concentration, which is attributable to the collapse of the spin cycloid structure.
Huong, Truong Thu,Bac, Ta Phuong,Thang, Bui Doan,Long, Dao Minh,Quang, Le Anh,Dan, Nguyen Minh,Hoang, Nguyen Viet International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.6
Since machine learning was invented, there have been many different machine learning-based algorithms, from shallow learning to deep learning models, that provide solutions to the classification tasks. But then it poses a problem in choosing a suitable classification algorithm that can improve the classification/detection efficiency for a certain network context. With that comes whether an algorithm provides good performance, why it works in some problems and not in others. In this paper, we present a data-centric analysis to provide a way for selecting a suitable classification algorithm. This data-centric approach is a new viewpoint in exploring relationships between classification performance and facts and figures of data sets.