Electrodeposition preparation of Nafion-Pt-HxMoO3 and its activity toward methanol oxidation

A composite catalyst Nafion-Pt-HxMoO3 was prepared on a glassy carbon by cyclic voltammetry methods in sulfuric acid solution containing Na2MoO4, H2PtCl6 and Naton, and its activity for the methanol oxidation was studied with Pt-HxMoO3 as comparison. It is found that the electrocatalytic activity and the stability of Pt-HxMoO3 are improved by the Nation. The activity of Pt-HxMoO3 reaches its maximum when the content of Nation in the preparation solution is 0.012%（mass fraction）. In this case the oxidation peak current of methanol on Nation-Pt-HxMoO3 is 1.76 times larger than that on Pt-HxMoO3 and keeps unchanged when the potential is set at 0.3 V （vs Hg-Hg2SO4） for 5 000 s in 1 mol/LCH3OH＋0.5 mol/L U2SO4 solution. The results from energy dispersive spectroscopy show that the content of Nation in the composite is 0.57%. The results from scanning electron spectroscopy show that the composite of Nafion-Pt-HxMoO has a gain size of about 90 nm and distributes more uniformly than Pt-HxMoO3.     

Effect of alloying elements on response of nonoriented electrical steels to stamping operations

A suitable alloying design for improving the punchability of nonoriented electrical steels containing 0.1 % Si was investigated. The appropriate addition of sulfur to steels containing relatively high manganese content is very useful in obtaining good punchability without detrimental effects on magnetic properties.     

随机背包公钥密码的分析与改进

针对随机背包公钥密码方案,提出一种私钥恢复攻击方法.发现Wang等人所构造的随机背包公钥方案实际上是隐含使用了一个特殊的超递增背包.通过使用普通超递增背包代替该特殊超递增背包,将超递增背包隐藏在随机选择的背包中,对原方案进行了改进,提出一种新的基于中国剩余定理的背包公钥密码方案.改进后的方案消除了原方案存在的设计缺陷,能够抵抗针对原方案提出的格规约攻击、低密度攻击以及shamir攻击.     

基于ISA总线的线切割间隙控制板的设计

介绍了一种基于ISA总线的线切割间隙控制板的设计,给出了各部分的硬件工作原理并提供了部分控制程序.该控制板可以对线切割电极放电电压信号进行采集,实时控制加工状态,加工状态稳定,达到了实际加工的要求.     

An optimum design of robotic food handling by using Burger model

This paper discusses an optimum design approach on robotic food handling by considering the characteristics of viscoelasticity of object. We pick up a traditional Japanese food, “Norimaki” as a typical example with the viscoelastic characteristics. We first show that the dynamic characteristics of Norimaki can be expressed by utilizing the Burger model. After testing the parameter sensitivity, we show an example of the optimum design for determining the combination of the hand stiffness and the operating velocity. We further show that the resultant plastic deformation can be formulated with the exact solution.     

TEM characterization of Ge precipitates in an Al-1.6at% Ge alloy

The growth mechanism and morphology of Ge precipitates in an Al-Ge alloy was characterized by a combination of in-situ transmission electron microscopy, high-resolution transmission electron microscopy and three-dimensional electron tomography. Anisotropic growth of rod-shaped Ge precipitates was observed by in-situ transmission electron microscopy over different time periods, and faceting of the precipitates was clearly seen using high-resolution transmission electron microscopy and three-dimensional electron tomography. This anisotropic growth of rod-shaped Ge precipitates was enhanced by vacancy concentration as proposed previously, but also by surface diffusion as observed during the in-situ experiment. Furthermore, a variety of precipitate morphologies was identified by three-dimensional electron tomography.     

基于VMD与MFE的光纤周界安防入侵事件识别北大核心CSCD

为了提高周界入侵事件的识别率,本文提出一种基于超弱光纤光栅(UWFBG)阵列的光纤周界入侵事件识别方法。该方法通过变分模态分解(VMD)将入侵信号进行分解,然后选择最佳分量并提取其多尺度模糊熵(MFE),与信号过零率(ZCR)相结合构造特征向量,将其输入到Sigmoid函数拟合的支持向量机(SVM),实现对晃动、剪切、刮风、下雨和无入侵5种不同的事件的识别。实验表明,该方法可以准确识别5种常见的事件信号,平均识别率达到98%。此外,该方法可以在输出各入侵事件类别的同时输出各类事件发生的概率值。     

Recurrent infomax generates cell assemblies, neuronal avalanches, and simple cell-like selectivity

Recently multineuronal recording has allowed us to observe patterned firings, synchronization, oscillation, and global state transitions in the recurrent networks of central nervous systems. We propose a learning algorithm based on the process of information maximization in a recurrent network, which we call recurrent infomax (RI). RI maximizes information retention and thereby minimizes information loss through time in a network. We find that feeding in external inputs consisting of information obtained from photographs of natural scenes into an RI-based model of a recurrent network results in the appearance of Gabor-like selectivity quite similar to that existing in simple cells of the primary visual cortex. We find that without external input, this network exhibits cell assembly-like and synfire chain-like spontaneous activity as well as a critical neuronal avalanche. In addition, we find that RI embeds externally input temporal firing patterns to the network so that it spontaneously reproduces these patterns after learning. RI provides a simple framework to explain a wide range of phenomena observed in in vivo and in vitro neuronal networks, and it will provide a novel understanding of experimental results for multineuronal activity and plasticity from an information-theoretic point of view.     

Multi-contact vertical ladder climbing with an HRP-2 humanoid

We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.     

Object detection based on a robust and accurate statistical multi-point-pair model

In this paper, we propose a robust and accurate background model, called grayscale arranging pairs (GAP). The model is based on the statistical reach feature (SRF), which is defined as a set of statistical pair-wise features. Using the GAP model, moving objects are successfully detected under a variety of complex environmental conditions. The main concept of the proposed method is the use of multiple point pairs that exhibit a stable statistical intensity relationship as a background model. The intensity difference between pixels of the pair is much more stable than the intensity of a single pixel, especially in varying environments. Our proposed method focuses more on the history of global spatial correlations between pixels than on the history of any given pixel or local spatial correlations. Furthermore, we clarify how to reduce the GAP modeling time and present experimental results comparing GAP with existing object detection methods, demonstrating that superior object detection with higher precision and recall rates is achieved by GAP.