萃取氧化法再生Pd/C催化剂的研究

通过甲醇用量、回流时间和硝酸浓度对催化剂活性的影响进行了讨论，研究了非那甾胺合成工艺中孕烯醇酮氢化Pd/C催化剂的再生方法。实验发现，对于1 g废Pd/C催化剂，以30 mL甲醇为萃取剂，回流萃取60 min，然后用35%的硝酸在80 ℃氧化30 min，可以达到满意的再生效果，新鲜和再生的Pd/C催化剂孕烯醇酮的氢化转化率分别为97.5%和98.5%。     

基于Gabor多尺度空间的不变兴趣点检测

针对以往仿射不变兴趣点的特征尺度不能直接断定的问题, 提出一种基于Gabor多尺度空间的不变兴趣点检测算法。该算法主要包括三个步骤：应用Gabor滤波器组与图像卷积建立图像Gabor多尺度空间; 通过极大值准则检测兴趣点并直接断定特征尺度; 采用二阶矩矩阵描述兴趣点局部结构。实验结果表明, 相比较其他Hessian-Affine、MSER等算法, 该算法在图像模糊和JPEG压缩情况下可重复率和可匹配率均取得最好结果, 是一种能有效直接提取特征尺度的兴趣点检测算法。     

基于MSP430F449的掺杂煤炭快速检测系统设计

介绍了一种基于MSP430F449的掺杂煤炭快速检测仪的设计,阐述了该系统的工作原理和系统设计方案。该系统以DDS芯片AD9833为核心设计激励源,采用24位高精度A/D转换器CS5532实现数据采集,通过RS—232实现上位机和下位机的通信。在煤炭阻抗数据预处理中,采用剔除疏失误差技术,并设计了基于LabVIEW的上位机数据库管理系统。实验证明:该仪器便于携带,低功耗,能够准确识别煤炭的掺杂情况,同时具有操作简单、稳定可靠、方便管理等特点。     

Two possible emission mechanisms involved in the arc discharge method of carbon nanotube preparation

By investigating the morphologies and microstructures of the cathode deposits prepared by self-sustained arc discharge between graphite rods, we consider that there are two electron emission mechanisms occurring on the cathode: field emission and thermionic emission. The former occurs mainly on the edge of the growing surface, by which we can explain the formation of the outer hard shell of the cathode deposit; while the latter occurs mainly on the growing surface except for the edge area and it is the main cause for the growth of carbon nanotubes.     

一种低功耗的社区机会网络消息路由算法

社区机会网络中节点的移动具有一定的相关性且不同的节点往往具有不同的移动特点,当前机会网络中主流的多拷贝路由算法并未充分考虑到这些特点,将该算法直接应用于这类网络会导致资源消耗较高、传输成功率低等问题。针对这些问题,提出一种基于社区的低功耗消息路由算法,其能自适应地控制消息拷贝数量,并根据节点与目标社区节点和本地社区节点相遇的历史信息来设置其目标社区和本地社区的活跃度,依靠活跃度较高的节点来完成消息传输。仿真结果表明,在延迟要求比较宽松的社区机会网络中,该算法在消息传输的成功率及占能耗最主要部分的消息转发次数方面明显优于Spray and Focus算法。     

Effect of H2O adsorption on the electrical transport properties of double-walled carbon nanotubes

Water molecules adsorbed on a double-walled carbon nanotube (DWCNT) serve as charge trapping centers when present in low density and as electron donors when present in high density. There is a discontinuous change between the low- and high-density regions. H₂O molecules are apt to be adsorbed on the outer surface of DWCNTs, and in this case the electrical transport properties are extremely sensitive to environment, which suggests that DWCNTs are hole doped and act as an electric dipole with the inner tube.     

具有副本抑制能力的多跳无线网络路由协议

针对多跳无线网络中机会路由的副本传输问题,提出一种新的机会路由协议。提出的策略不再简单采用单跳广播的方式转发数据,而是通过节点间的距离确定转发开销,再让数据包携带下一跳候选节点信息并根据候选节点的ACK选择下一跳节点,从而保证了每个数据包只有一个候选节点进行转发。仿真结果显示,提出的方案能减少不必要的传输行为,有效改善了网络吞吐率。     

An ICPSO-RBFNN nonlinear inversion for electrical resistivity imaging

To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network(RBFNN) based on information criterion(IC) and particle swarm optimization(PSO) is presented. In the proposed method, IC is applied to obtain the hidden layer structure by calculating the optimal IC value automatically and PSO algorithm is used to optimize the centers and widths of the radial basis functions in the hidden layer. Meanwhile, impacts of different information criteria to the inversion results are compared, and an implementation of the proposed ICPSO algorithm is given. The optimized neural network has one hidden layer with 261 nodes selected by AKAIKE's information criterion(AIC) and it is trained on 32 data sets and tested on another 8 synthetic data sets. Two complex synthetic examples are used to verify the feasibility and effectiveness of the proposed method with two learning stages. The results show that the proposed method has better performance and higher imaging quality than three-layer and four-layer back propagation neural networks(BPNNs) and traditional least square(LS) inversion.     

基于加权支持向量机的凸轮升程误差拟合方法

针对凸轮磨削加工过程中存在局部升程误差严重超差的问题,提出了加权支持向量机的凸轮升程误差补偿方法。首先根据圆率的符号判断凸轮升程误差值是否连续,然后建立了不连续点与相邻点之间夹角与加权值的关系。通过加权支持向量机对凸轮升程误差值进行拟合。然后将原始凸轮升程值减去经拟合后的凸轮升程误差值,获得新的凸轮升程值。再根据圆率自动调整加权值的系数,使凸轮升程值光滑点数最大,即获得最优的凸轮升程值。对上述算法进行仿真和编程,经YTM8336-16数控凸轮轴磨床进行磨削验证。实验表明,凸轮升程误差由原来的±0.059 mm降至±0.011 mm,表面粗糙度由Ra0.32μm降至Ra0.25μm,获得良好的效果。     

Fast local image inpainting based on the Allen–Cahn model

In this paper, we propose a fast local image inpainting algorithm based on the Allen–Cahn model. The proposed algorithm is applied only on the inpainting domain and has two features. The first feature is that the pixel values in the inpainting domain are obtained by curvature-driven diffusions and utilizing the image information from the outside of the inpainting region. The second feature is that the pixel values outside of the inpainting region are the same as those in the original input image since we do not compute the outside of the inpainting region. Thus the proposed method is computationally efficient. We split the governing equation into one linear equation and one nonlinear equation by using an operator splitting technique. The linear equation is discretized by using a fully implicit scheme and the nonlinear equation is solved analytically. We prove the unconditional stability of the proposed scheme. To demonstrate the robustness and accuracy of the proposed method, various numerical results on real and synthetic images are presented.