基于完全互补码波形的非零多普勒目标检测

本文将完全互补码(Complete Complementary Code, CCC)应用于多输入多输出(Multiple Input Multiple Output, MIMO)雷达目标探测中，针对具有非零多普勒的多目标检测问题，提出一种基于广义普洛黑-修-莫尔斯(Generalized Prouhet-Thue-Morse, GPTM)序列和二项式系数加权的信号处理方法。该方法分别在发射端和接收端进行处理，在发射端采用GPTM序列设计方法调整脉冲的发射顺序，以降低由多普勒引起的距离旁瓣；在接收端通过二项式设计(Binomial Design, BD)方法为各接收脉冲加上不同权重，扩大目标多普勒附近的清洁区。为综合上述两次处理的优势，将两次处理得到的距离多普勒谱进行逐点最小化处理，得到最终的距离多普勒谱，然后进行有序恒虚警检测。仿真结果表明，本文所提的信号处理方法具有良好的旁瓣抑制效果和多普勒分辨率，能够有效检测出非零多普勒目标。     

Fabrication of crescent-shaped ceramic microparticles based on single emulsion microfluidics

Ceramic microparticles have great potentials in various fields such as materials engineering, biotechnology, microelectromechanical systems, etc. Morphology of the microparticle performs an important role on their application. To date, it remains difficult to find an effective and controllable way for fabricating nonspherical ceramic microparticles with 3D features. This work demonstrates a method that combines UV light lithography and single emulsion opaque-droplet-templated microfluidic molding to prepare the crescent-shaped ceramic microparticles. By tailoring the intensity of UV light and flow rate of fluid, the shapes of microparticles are accordingly tuned. Therefore, varieties of crescent-shaped microparticles and their variations have been fabricated. After sintering, the crescent-shaped alumina ceramic microparticles were obtained. Benefitting from the light absorption and scattering behavior of most ceramic nanoparticles, this system can serve as a general platform to produce crescent-shaped microparticles made from different materials, and hold great potentials for applications in microrobotics, structural materials in MEMS, and biotechnology.     

基于全U网络的混凝土路面裂缝检测算法

针对现有的混凝土裂缝检测算法在各种复杂环境中检测精度不够、鲁棒性不强的问题,根据深度学习理论和U-net模型,提出一种全U型网络的裂缝检测算法。首先,依照原U-net模型路线构建网络;然后,在每个池化层后都进行一次上采样,恢复其在池化层之前的特征图规格,并将其与池化之前的卷积层进行融合,将融合之后的特征图作为新的融合层与原U-net网络上采样之后的网络层进行融合;最后,为了验证算法的有效性,在测试集中进行实验。结果表明,所提算法的平均精确率可达到83.48%,召回率为85.08%,F1为84.11%,相较于原U-net分别提升了1.48%,4.68%和3.29%,在复杂环境中也能提取完整裂缝,保证了裂缝检测的鲁棒性。     

Electrospun Zn-doped Ga2O3 nanofibers and their application in photodegrading rhodamine B dye

Ultrawide band gap semiconductor materials have attracted considerable attention in recent years owing to their great potential in the photocatalytic field. In this study, Zn-doped Ga₂O₃ nanofibers with various concentrations were synthesized via electrospinning; they exhibited a superior photocatalytic degradation performance of rhodamine B dye compared to that of undoped Ga₂O₃ nanofibers. The Zn dopant replaced Ga sites via replacement doping, which could increase the concentration of oxygen vacancies and lead to enhanced photocatalytic properties. When the Zn concentration increased, a Ga₂O₃/ZnGa₂O₄ hybrid structure formed, which could further enhance the photocatalytic performance. The separation of photogenerated carriers due to Zn doping and heterojunctions were the primary causes of the enhanced photocatalytic performance. This study provides experimental data for the fabrication of high-performance photocatalysts based on Ga₂O₃ nanomaterials.     

基于双时间点检测的毫米波雷达人流量监测方法

针对现有基于视频监控的人流量统计方案成本高、算法复杂且不利于个人隐私保护的局限性，利用毫米波雷达体积小、成本低、分辨率高的特点，提出了一种基于双时间点检测的人流量监测方法。该方法先获取人体目标散射点位置和多普勒频移信息来构成点云数据，然后根据多普勒频移正负来判断人体的运动方向，并筛选具有高多普勒频移值的点云数据以降低干扰点对聚类结果的影响；在双时间点对特定区域内人员数量进行统计，并根据双时间点之间所获取的点云数据聚类结果对所统计人员数据进行修正。实验结果表明，该方法能够用匿名的方式以较高的正确率统计人员进出。     

基于物联网的智慧林业可持续发展策略研究

随着我国科技的不断进步,在“互联网+”大数据的背景下,林业的智慧化发展是必经之路。虽然我国智慧林业的发展已经取得了一定的突破,但是仍然存在着许多问题。基于此,文章在物联网技术的基础上,对智慧林业的可持续发展策略进行探讨。     

计及Spark和属性权重的售电套餐推荐方法

针对电力市场用户群庞大，交易过程中售电套餐选择困难的问题，在Spark环境下设计了一种售电套餐推荐方法，同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先，计算出每个套餐属性的权重值，从而计算得到售电套餐综合相似度。然后，计及用户和套餐两方面提出一种售电套餐推荐方法，实现售电套餐的精准推荐。实验表明，提出的推荐方法能够明显提高推荐的准确度，并且在分布式环境下具有良好的推荐效率和可扩展性。     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.