Biblio

Filters: Author is Hua, Y.  [Clear All Filters]
2020-11-30
Song, W., Li, X., Lou, L., Hua, Y., Zhang, Q., Huang, G., Hou, F., Zhang, X..  2018.  High-Temperature Magnetic Properties of Anisotropic SmCo7/Fe(Co) Bulk Nanocomposite Magnets. IEEE Transactions on Magnetics. 54:1–5.
High-temperature magnetic properties of the anisotropic bulk SmCo7/Fe(Co) nanocomposite magnets prepared by multistep deformation have been investigated and compared with the corresponding isotropic nanocomposites. The anisotropic SmCo7/Fe(Co) nanocomposites with a Fe(Co) fraction of 28% exhibit much higher energy products than the corresponding isotropic nanocomposites at both room and high temperatures. These magnets show a small remanence (α = -0.022%/K) and a coercivity (β = -0.25%/K) temperature coefficient which can be comparable to those of the conventional SmCo5 and Sm2Co17 high-temperature magnets. The magnetic properties of these nanocomposites at high temperatures are sensitive to the weight fractions of the Fe(Co) phase. This paper demonstrates that the anisotropic bulk SmCo7/Fe(Co) nanocomposites have better high-temperature magnetic properties than the corresponding isotropic ones.
2018-04-02
Guan, X., Ma, Y., Hua, Y..  2017.  An Attack Intention Recognition Method Based on Evaluation Index System of Electric Power Information System. 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). :1544–1548.

With the increasing scale of the network, the power information system has many characteristics, such as large number of nodes, complicated structure, diverse network protocols and abundant data, which make the network intrusion detection system difficult to detect real alarms. The current security technologies cannot meet the actual power system network security operation and protection requirements. Based on the attacker ability, the vulnerability information and the existing security protection configuration, we construct the attack sub-graphs by using the parallel distributed computing method and combine them into the whole network attack graph. The vulnerability exploit degree, attacker knowledge, attack proficiency, attacker willingness and the confidence level of the attack evidence are used to construct the security evaluation index system of the power information network system to calculate the attack probability value of each node of the attack graph. According to the probability of occurrence of each node attack, the pre-order attack path will be formed and then the most likely attack path and attack targets will be got to achieve the identification of attack intent.