基于树搜索算法的多用户MIMO系统的自由度分配

针对最大化多用户MIMO系统的和速率的问题,提出了将迭代式干扰对齐技术（Iterative Interference Alignment：ⅡA）和系统自由度（DoF）分配策略相结合的一种算法.系统的DoF分配是通过树搜索算法（Tree search）来实现的.理论分析及实验仿真结果表明,该算法获得的系统容量,接近遍历法（exhausting search：EX）的结果,但是在算法复杂性及收敛时间上明显优于遍历法.     

企业内部信息系统的故障监控研究与应用

针对大型企业内部网络中信息系统的故障监控缺乏有效手段的问题,从Web网页、应用服务器、数据库服务器、服务器网络硬件、C/S系统等多个角度入手进行研究,提出一个对内网信息系统进行实时监控的故障监控系统,并详述了它的工作流程和实现细节。目前实现的系统通过试用效果良好,方案亦被证明是行之有效的,并可在相近环境中推广应用。     

基于Windows平行文件系统下的平行I/O

近年来,平行档案系统被广泛的用来解决这个问题,除此之外,由于电脑被使用于平行处理平台的普及率逐步上升,造成使用于电脑上的平行处理软体需求量持续增加,但是,却有可能缺乏平行I/O的系统。因此,文章旨在研究与分析Windows平行文件系统下的平行I/O的特点与实现方式。     

Simultaneous spectrophotometric determination of copper(II), lead(II) and cadrnium(II)

The full spectrum technique in the fourier domain was studied for simultaneous determination of Cu(II), Pb(II) and Cd(II) with 4-(2-pyridylazo) resorcinol (PAR). A program called SPGRFSQ. was designed to perform the calculations. Seven error functions were calculated for deducing the number of factors. Data reduction was performed using principal component analysis (PCA) algorithm. Experimental results showed the method to be successful even where there was severe overlap of spectra.     

Reprint of “Suppressing propylene carbonate decomposition by coating graphite electrode foil with silver”

A method has been developed to suppress the decomposition of propylene carbonate (PC) by coating graphite electrode foil with a layer of silver. Results from electrochemical impedance measurements show that the Ag-coated graphite electrode presents lower charge transfer resistance and faster diffusion of lithium ions in comparison with the virginal one. Cyclic voltammograms and discharge-charge measurements suggest that the decomposition of propylene carbonate and co-intercalation of solvated lithium ions are prevented, and lithium ions can reversibly intercalate into and deintercalate from the Ag-coated graphite electrode. These results indicate that Ag-coating is a good way to improve the electrochemical performance of graphitic carbon in PC-based electrolyte solutions.     

A low‐profile antenna with circularly polarized reconfigurable and omnidirectional radiation patterns

A low profile circularly polarized (CP) antenna with reconfigurable polarization is designed and presented, which can radiate omnidirectional patterns that can be switched between left‐hand circularly polarized (LHCP) and right‐hand circularly polarized (RHCP). A pair of arc‐shaped complementary dipoles is acted as reconfigurable elements by bridging four pin diodes at the dipole arced arms. A meander phase shift line is employed to connected the arc dipole arms and plate cavity to adjust the phase relationship of two sources. The proposed antenna exhibits the omnidirectional radiation pattern by combining six identical elements placed in a circular array configuration. 24 p‐i‐n diodes are exploited to six elements, by manipulating the dc bias voltage across the diodes, the polarization state of the antenna can be switched. The patterns of the antenna are similar to that of a dipole, but its size is only about Φ0.87 × 0.029λ₀ at 5.8 GHz. The overlapped bandwidth of measured 3‐dB axial ratio (AR) and 10‐dB return loss is 5.724‐5.87 and 5.738‐5.91 GHz for two polarization states, which are right on the target of ISM band. It can be well adapted to medical diagnosis systems.     

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

In this paper, a robust video zero-watermarking scheme for copyright protection using a combination of convolutional neural network (CNN) and self-organizing map (SOM) in polar complex exponential transform (PCET) space is presented. The scheme is developed not only to remedy the existing problems of lacking in some performance assessments but also to enhance the robustness. It starts with extracting the content feature of each frame by CNN and then some significant frames are selected using SOM clustering and maximum entropy. Secondly, the PCET is applied to all selected frames to abstract invariant moments, and further, is scrambled by a chaotic logistic map and is reduced in dimensions by singular value decomposition (SVD). Next, a binary sequence is generated by comparing adjacent values of the obtained compact PCET moments in the previous step, and further is permuted to produce a binary matrix. Finally, a bitwise exclusive-OR operation is imposed on the binary matrix and the encrypted watermark by the chaotic map to generate a zero-watermark signal. Experimental results demonstrate that the proposed scheme has adequate equalization and distinguishability of zero-watermarks as well as strong robustness against common signal processing, geometric, compression, and inter-frame attacks. Also, compared with existing video zero-watermarking and traditional video watermarking methods, the proposed scheme exhibits superior robustness.

     

A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.

     

TP-FER：基于优化卷积神经网络的三通道人脸表情识别方法

针对人脸五官在表达不同情绪时所起的作用不同,利用单一的卷积神经网络对人脸面部特征进行特征提取和表情识别可能会导致提取表情关键特征信息时聚焦性不够,而仅对眼部或者嘴部等重点部位进行特征提取,又有可能造成特征提取不够充分的问题,提出了一种基于优化卷积神经网络的三通道人脸表情识别方法TP-FER(tri-path networks for facial expression recognition).该方法基于构建的卷积神经网络训练,采用三个输入渠道,分别聚焦面部、眼部和嘴部区域进行特征提取和表情判别,最后采用基于决策层的融合技术将三个渠道的识别结果进行相对多数投票决策,获取整体最优识别率.将此方法应用于JCK+数据集和自建数据集上进行了实验判别分析,结果表明该方法在两个数据集上均提高了整体表情识别率.该方法既考虑了脸部整体特征的提取,又兼顾了某些表情主要聚焦在眼部、嘴部表达的特性,相互辅助,整体提高了表情的识别率;该方法也能对神经心理学研究提供数据支持.     

Research and Practice of Hybrid Teaching for Software Testing based on Interactive Learning

To address the problems of insufficient number of personalized exercises and cases and teachers' lack of grasp of students' weak knowledge points in the current software testing online courses, we study the strategy of establishing and updating intelligent exercise sets and case libraries and analyze the answers and dig out the weak points of knowledge through group intelligence reasoning and interactive machine learning methods. This will help teachers to make uniform and targeted explanations, reduce manual judgment, and achieve intelligent teaching quality reform, and implement the educational concepts of "keeping up with the times" and "teaching according to students' abilities".