广义正交码索引调制系统的性能分析

摘 要：为了提高码索引调制（code index modulation，CIM）系统的传输效率，提出了一种具有更低复杂度的单输入单输出（single input single output，SISO）的广义正交码索引调制（generalized orthogonal code index modulation，GQCIM）系统。CIM 系统使用扩频码和星座符号传输信息，但只能激活两个扩频码索引和一个调制符号。而 GQCIM 系统以一种新颖的方式克服了只激活一个调制符号的限制，同时充分利用了调制符号的正交性，增加扩频码索引以传输更多的额外信息位，提高了系统的传输效率。此外，分析了GQCIM系统的理论性能，推导了误码率性能的上界。通过蒙特卡罗仿真验证了GQCIM系统的性能，对比发现GQCIM系统的理论和仿真性能一致。而且在相同的传输效率下，结果显示GQCIM系统的性能优于同样具有正交性的调制系统，如广义码索引调制（generalized code index modulation，GCIM）系统、CIM系统、码索引调制-正交空间调制（code index modulation aided quadrature spatial modulation，CIM-QSM）系统、码索引调制-正交空间调制（code index modulation aided spatial modulation，CIM-SM）系统、脉冲索引调制（pulse index modulation，PIM）系统。     

A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small size and low computational burden. The model is 10 to 20 times smaller when compared to other networks designed for the same task, and more than 700 times smaller than general networks. Also, the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks. Despite its small size, the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.     

Sequential alignment attention model for scene text recognition

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state-of-the-art solutions usually depend on the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. Unfortunately, there often exists severe misalignment between feature areas and text labels in real-world scenarios. To address this problem, this paper proposes a sequential alignment attention model to enhance the alignment between input images and output character sequences. In this model, an attention gated recurrent unit (AGRU) is first devised to distinguish the text and background regions, and further extract the localized features focusing on sequential text regions. Furthermore, CTC guided decoding strategy is integrated into the popular attention-based decoder, which not only helps to boost the convergence of the training but also enhances the well-aligned sequence recognition. Extensive experiments on various benchmarks, including the IIIT5k, SVT, and ICDAR datasets, show that our method substantially outperforms the state-of-the-art methods.     

The thermochromic characteristics of Zn-doped VO2 that were prepared by the hydrothermal and post-annealing process and their polyurethane composite films

In this paper, Zn-doped VO₂ nanoparticles have been successfully fabricated by a two-step hydrothermal-annealing process, and the thermally induced visible light transmittance enhancement of Zn-doped VO₂ has been studied for the first time. It is found that Zn-doped VO₂ not only exhibits excellent solar modulation ability (ΔT_sol = 15.27%) but also can reduce the phase transition temperature and increase the visible light transmittance after the heat-induced phase transition (ΔT_lum=+5.78%). Moreover, with the increase of Zn doping concentration, the phase transition temperature (T_c) and phase transition hysteresis (ΔT) both decrease. It is shown that the Zn-doped VO₂-PU films not only have good solar light modulation ability and properties of improving visible light transmission after phase transition, but also have good durability. The research result is of great significance for improving the visible light transmittance after phase transition and realizing the practical application of VO₂ in the field of smart windows.     

The Role of Extracellular Vesicles in the Progression of Human Neuroblastoma

The long-underestimated role of extracellular vesicles in cancer is now reconsidered worldwide by basic and clinical scientists, who recently highlighted novel and crucial activities of these moieties. Extracellular vesicles are now considered as king transporters of specific cargoes, including molecular components of parent cells, thus mediating a wide variety of cellular activities both in normal and neoplastic tissues. Here, we discuss the multifunctional activities and underlying mechanisms of extracellular vesicles in neuroblastoma, the most frequent common extra-cranial tumor in childhood. The ability of extracellular vesicles to cross-talk with different cells in the tumor microenvironment and to modulate an anti-tumor immune response, tumorigenesis, tumor growth, metastasis and drug resistance will be pinpointed in detail. The results obtained on the role of extracellular vesicles may represent a panel of suggestions potentially useful in practice, due to their involvement in the response to chemotherapy, and, moreover, their ability to predict resistance to standard therapies—all issues of clinical relevance.     

投影寻踪分类模型在常见造纸纤维原料综合评价中的应用

将投影寻踪分类（PPC）模型与基于实数编码的加速遗传算法（RAGA）相结合，同时优化多个指标参数，将高维数据指标转化为低维空间上的一维投影值，建立RAGA-PPC模型，用于造纸纤维原料分类，并对造纸纤维原料进行综合评价。结果表明，基于RAGA-PPC模型的评价结果与造纸纤维原料实际分类结果一致，此方法客观可靠，精度高，具有一定的应用前景。     

Relaxor behavior and energy storage density induced by B-sites substitutions in (Ca0.28Ba0.72)2.1Na0.8Nb5O15 Tungsten bronze ceramics

Lead-free relaxor ferroelectrics (Ca_0.28Ba_0.72)_2.1Na_0.8Nb_5-xSb_xO₁₅ (CBNNS) and (Ca_0.28Ba_0.72)_2.1Na_0.8Nb_5-yTa_yO₁₅ (CBNNT) with tungsten bronze structure were fabricated via solid-state reactions. The obtained CBNNS and CBNNT ceramics showed different dielectric behaviors. Only the CBNNS ceramics revealed an intensified diffusion and relaxor-like characteristics, which could be verified by the modified Curie–Weiss law. The relaxor behaviors in CBNNS were attributed to the radii difference between Sb⁵⁺ and Nb⁵⁺ ions co-occupying in B-sites. For the substitution of Nb⁵⁺ by Sb⁵⁺ in CBNNS ceramics, the change from macroscopic polarization to local polarization could also give rise to the obvious relaxor behavior. The Raman spectra verified a larger off-centering of the cation and a higher distortion degree for BO₆ octahedron in the ab plane for CBNNS ceramics when compared with those of CBNNT. In addition, the ferroelectric properties of CBNNS ceramics further indicated the relaxor ferroelectric nature, and also confirmed that the relaxor behavior helped to improve the energy-storage performance.     

基于全相位预处理的时域多重信号分类波达方向估计方法

低信噪比下,针对宽带短脉冲情况下频域多重信号分类(MUSIC)中噪声子空间估计不稳定问题,提出一种基于全相位预处理的时域多重信号分类波达方向(DOA)估计方法。①对线列阵接收数据进行分组处理;②按搜索角度对各组数据进行相移预处理,并对各组数据预处理结果进行相加,得到一组新数据;③对线列阵接收数据在时域构建相移后的协方差矩阵,在更短数据长度下,稳定实现噪声子空间估计,并依据估计出的噪声子空间含有的正交特性,通过单位矩阵加法器得到相应空间谱估计值,实现波达方向估计。数值仿真和实测数据处理结果表明,相比频域MUSIC方法,该方法有效提高了线列阵接收数据协方差矩阵中信号含有量和信噪比,能够在更短数据长度情况下实现对噪声子空间的稳定估计,具有较好的稳定性和检测性能,提高了MUSIC方法在实际波达方向估计中的鲁棒性。     

基于单片机C8051F500的无刷直流电机控制研究

永磁无刷直流电机是近些年发展起来的一种新型电机,具有效率高、调速性能好、启动转矩大等诸多优点,在运动控制领域中的应用日趋广泛。基于电机专用控制芯片MC33035,采用单片机C8051F500为主控芯片,设计一款无刷直流电机智能控制器,实现对无刷直流电机启动停止、正反转、调速、转速显示等控制。通过简要介绍无刷直流电机工作原理,使用MATLAB/Simulink对控制系统进行建模仿真,对无刷直流电机控制系统进行软、硬件设计。实验结果表明,该控制系统运行稳定,抗干扰性强,具有良好的市场应用价值。