Microstructure investigations of ball milled materials

HREM and FEG TEM were emphasized and extensively used to follow the most subtle changes in the structure and composition of ball-milled Cu, Fe-Cu, and thermally decomposed Fe60Cu40. Some significant results are obtained and summarized as follows: HREM shows that the deformation of ball-milled copper proceeds mainly by twinning and shear bands (SBs) formation. The nano-grains formed during ball milling (BM) contain a high density of dislocations. The grain boundaries (GBs) of nanocrystalline (NC) Cu prepared by BM are ordered, curved, and strained, but disordering, lattice distortion, and nanovoids in local regions were frequently observed. Nanoscale composition analysis on mechanically alloyed Fe16Cu84 shows that the average Fe content in both the interior of grains and the GBs is close to the designed composition, which proves that a supersaturated solid solution has really formed. However, the Fe content is rather inhomogeneous between the larger and smaller grains, which infers the inhomogeneous mixing of Fe and Cu during mechanical alloying (MA). NC structure and the mechanical force-enhanced fast diffusion are the reasons of the formation of supersaturated solid solutions in immiscible systems with positive enthalpy of mixing. HREM observations carried out with the thermally decomposed Fe60Cu40 solid solution show that the Nishiyama (N-W) or Kurdyumov-Sachs (K-S) orientation relationships exist between alpha-Fe and Cu. Energy dispersive X-ray spectra (EDXS) results show that the Cu content in these alpha-Fe grains reaches as high as 9.5 at.% even after heating to 1,400 degrees C, which is even higher than the maximum solubility of Cu in gamma-Fe at 1,094 degrees C.     

层次式级联多网络模型及其性能

本文提出了一种层次式级联多网络结构，论述了其训练算法，并验证了该结构的收敛性。这种结构在处理高阶非线性分布数据的分类问题方面具有优良的性能，用北京谱仪事例过滤进行性能测试结果表明，其训练和泛化性能都优于单个ＢＰ网络。     

温度,压力对漂移室气体增益的影响

研究了温度及气体压力对漂移室（工作于正比区）气体放大倍数的影响，温度和气体压力的变化范围分别是５￣４０℃及９０￣１０５ｋＰａ。用实验数据拟合得到了函数关系并测量了几种饱和度下函数中的参数值。     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Authority updating: An expert authority evaluation algorithm considering post‐evaluation and power indices in social networks

In group assessment, the focus is on finding high‐authority experts to improve the reliability of assessment results. In this study, we propose an authority updating algorithm while considering the power and judgement reliability of an expert on the basis of social networks and post‐evaluations. A network power index is established and used to reflect the power of an expert while considering social networks. The measurement of the judgement reliability of an expert considers the post‐evaluation of the objects selected by experts, thereby more scientifically reflecting the reliability of experts. The analysis shows the following: although the social‐network structure influences the authority of experts, the influence weakens when the assessment group is a highly or even fully connected group; the network effect may increase the authority of some experts and reduce that of others, and it will weaken as the network connectivity increases; moreover, the judgement reliability and authority of an expert while considering post‐evaluation can encourage him/her to make fair assessments and strive to reduce his/her motivation and cognitive biases.     

Protect privacy of deep classification networks by exploiting their generative power

Machine Learning - Research showed that deep learning models are vulnerable to membership inference attacks, which aim to determine if an example is in the training set of the model. We propose a...     

Granular multiple kernel learning for identifying RNA-binding protein residues via integrating sequence and structure information

Neural Computing and Applications - RNA-binding proteins play an important role in the biological process. However, the traditional experiment technology to predict RNA-binding residues is...     

文科《多媒体技术与应用》课程设置与教学研究

多媒体技术是以数字技术为基础的综合技术。本文结合文科学生的特点,探讨了《多媒体技术与应用》课程设置与教学。     

Pd/Mg(OH)2 Heterogeneous Nanocatalysts Synthesized by a Facile One-Pot Hydrothermal Method for CO Direct Esterification to Dimethyl Oxalate

Catalysis Letters - Pd-based heterogeneous nanocatalysts have wide application in chemical industry. However, the traditional synthesis process contains multi-steps such as impregnation, dry,...     

An Analytical Model Including Interface Traps and Temperature Effects in Negative Capacitance Double Gate Field Effect Transistor

Silicon - In this paper, an analytical model for negative capacitance double gate field effect transistor (NC-DG-FET) is proposed. This model includes interface traps and temperature effects, which...