基于三相幅度测量的相控阵天线快速校准方法

提出了一种基于三相幅度测量的相控阵天线快速校准方法。该方法将天线阵列进行分组,利用每种分组在三种配相下的阵面合成场幅度测量值,可解算出各个天线单元的初始幅相值。该方法仅需幅度测量,避免了相位测量误差影响单元幅相值的计算精度,而且所需幅度测量次数仅为(2N+1)次,可显著提高校准时效性。另外,利用分组思想,同时改变多个单元相位,使总辐射场的幅度变化显著,提升校准准确性。仿真结果表明:校准后相位均方根误差为2.2°,幅度均方根误差为0.2 dB。     

Effect of an abrupt change in pulling rate on microstructures of directionally solidified Al2O3-Er3Al5O12 eutectic and off-eutectic composite ceramics

Directionally solidified microstructures of Al₂O₃-Er₃Al₅O₁₂ eutectic and off-eutectic in situ composite ceramics were explored under abrupt-change pulling rate conditions. Corresponding temperature distributions and interface locations were studied. In eutectic composition, fluctuation of eutectic spacing occurred when the pulling rate increased abruptly. A gradually increase or abrupt increase in eutectic spacing was observed when the pulling rate decreased abruptly. In hypoeutectic and hypereutectic compositions, formation of the primary phases were suppressed when the pulling rate increased abruptly from 10?µm/s to 100?µm/s, while primary phases precipitated when the pulling rate decreased abruptly from 100?µm/s to 10?µm/s. The interface altitude decreased after the pulling rate increased abruptly, but increased after the pulling rate decreased abruptly. The liquid composition restriction (around the eutectic composition) at the eutectic interface plays an important role in the suppression of the primary dendrite and coupled eutectic oxides can be obtained in off-eutectic compositions even under higher solidification rate conditions.     

Extending SSD Lifespan with Comprehensive Non-Volatile Memory-Based Write Buffers

Journal of Computer Science and Technology - New non-volatile memory (NVM) technologies are expected to replace main memory DRAM (dynamic random access memory) in the near future. NAND flash...     

A computer aided design method for car form and its application based on shape parameters

In the early design stage, automotive modeling should both meet the requirements of aesthetics and engineering. Therefore, a vehicle CAD (computer aided design) model that can be easily adjusted by feedbacks is necessary. Based on CE-Bézier surface, this paper presents a set of algorithms for parametric segmentation and fairing surface generation in a car model. This model is defined by a simplified automotive template and relevant control points, shape parameters and segmentation parameters, which can be modified to alter the car form efficiently. With this model and the corresponding adjustment method, more than fifty various vehicle models are established in this research according to different parameters. And two methods for calculating similarity index between car models are constructed, which are suitable for brand design trend analysis and modelling design decisionmaking.     

Study on the Height of the Mining-Induced Water-Conducting Fracture Zone Under the Q 2l Loess Cover of the Jurassic Coal Seam in Northern Shaanxi,China

A method to calculate the height of a water-conducting fractured zone (HWCFZ) was developed based on the plate and shell theory, and the development of the HWCFZ in bedrock and Q2l loess strata is discussed in detail. First, the subsidence-deflection curve equation of the overlying stratum is theoretically derived, and then the ultimate deflection and free space height of rock strata are calculated. Moreover, the strata tensile strain is calculated by using integral calculus. In addition, the failure state of the rock is analyzed by comparing the theoretically calculated tensile strain with the experimentally measured yield tensile strain, allowing one to attain the maximum value of HWCFZ. This approach was tested at the Jinjitan coal mine; the theoretically predicted, experimentally measured, and numerically computed maximum HWCFZ values were 189.5, 187.3, and 188.5 m, respectively, demonstrating the accuracy of the proposed method. These results are highly significant for safe and environment-friendly coal mining in northwest Shaanxi, China.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.