X线乳腺图像中微钙化检测的快速排除无病变区域法

介绍一种通过去除数字化乳腺x线照片中的无病变区域（TNR）间接地获取感兴趣区域（ROI）的方法。该方法可通过3个步骤来实现：（1）将图像划分为若干个不重合的相等大小块，并为每块计算5个特征；（2）通过域值法进行粗分析，排除肯定不含有病变的块；（3）使用代价敏感的支持向量分类器作更精细的分析，以进一步排除肯定不含有病变的块。在真实的数字化X线乳腺照片上的实验表明：该方法可以有效地去除高达81．71％的无病变区域。     

基于虚拟仪器的切削力监控技术研究

研制了一种基于虚拟仪器界面、供现场使用的高精度、高效率的金属切削过程监控系统。研究中采用回归分析、叠加原理及抛物线插值的方法建立切削力模型 ,并基于该模型进行参数估计来提取切削状态特征 ,进而监控整个切削过程     

Microphysics of Magnetic Reconnection

Magnetic reconnection is a universal phenomenon where energy is efficiently converted from the magnetic field to charged particles as a result of global magnetic topology changes during which earlier separated plasma regions become magnetically connected. While the reconnection affects large volumes in space most of the topology changes and of the energization occur within small localized regions. Regions of special importance are the X-region and the separatrix region. The understanding of the microphysics of these regions is crucial for the overall understanding of the reconnection. The Earth magnetosphere is the best environment where the details of these regions can be studied in situ. We summarize their main properties and discuss recent spacecraft observations.     

圆柱度误差最小区域评定方法述评

本文简介圆柱度误差评定的常用数学模型，并对用最小区域法评定圆柱度误差的几种近似方法及其优缺点展开讨论。     

多等级区域侦察弹性星座设计方法

针对传统侦察星座目标单一、弹性低的问题，提出了多等级区域侦察弹性星座的设计方法。该方法将星座设计过程按区域等级信息分为多个子星座逐步设计，直到整体星座对所有的区域性能满足设计要求。以区域被划分为3个等级为例，首先对星座设计需求、设计指标及设计步骤进行了分析。其次推导了地面最低分辨率和轨道高度的关系并确定了不同子星座的轨道高度。最后考虑轨道倾角、一箭多星发射、光照和升交点漂移同步约束，构建基础星座、子星座1和子星座2的优化模型。最终设计星座为3层混合星座，共8个轨道面和70颗卫星，星座对各等级区域的最大重访时间分别为10937s，12241s和17437s，弹性指数为2213%，2420%和6361%。结果表明该方法设计的星座可实现对区域覆盖和弹性分级的设计要求，证明了方法的有效性。对比Walker星座设计方法，在同等设计要求下，Walker星座所需卫星数为156颗，多等级区域侦察弹性星座所需卫星数远低于Walker星座，结果进一步证明了该星座设计方法的优越性。     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

机载系统NANDFlash存储技术

为了发挥NANDFlash在机载环境中非易失性、体积小、固态性、重量轻、低功耗、抗震动等特点,介绍了NANDFlash的存储特性,对NANDFlash存储的关键技术进行了改进,提出了基于域机制的地址映射方式和基于阈值的损耗均衡方法,为机载系统能够更加可靠、实时和安全地进行数据存储提供了选择。     

Association of optical tracklets from a geosynchronous belt survey via the direct Bayesian admissible region approach

The direct Bayesian admissible region approach is an a priori state free measurement association and initial orbit determination technique for optical tracks. In this paper, we test a hybrid approach that appends a least squares estimator to the direct Bayesian method on measurements taken at the Zimmerwald Observatory of the Astronomical Institute at the University of Bern. Over half of the association pairs agreed with conventional geometric track correlation and least squares techniques. The remaining pairs cast light on the fundamental limits of conducting tracklet association based solely on dynamical and geometrical information.     

Spatial transformation of general sampling-aliasing frequency region for rotating-blade parameter identification with emphasis on single-probe blade tip-timing measurement

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades. Blade-Tip Timing (BTT) is considered as the most promising technique for operational blade-vibration monitoring, which obtains the parameters that characterize the blade condition from recorded signals. However, its application is hindered by severe undersampling and stringent probe layouts. An inappropriate probe layout can make most of the existing methods invalid or inaccurate. Additionally, a general conflict arises between the allowed and required layouts because of arrangement restrictions. For the sake of economy and safety, parameter identification based on fewer probes has been preferred by users. In this work, a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement. To present the general Sampling-Aliasing Frequency (SAFE) map definition, the traditional time–frequency analysis methods are extended to a time-sampling frequency. Then, a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters, which can be physically interpreted as an engine order and a natural frequency using coordinate transformation. Finally, the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.     

强短波衰落事件的太阳活动区磁场位形先兆

本文利用北京天文台提供的高空间分辨率的活动区纵场磁图对1988年的18个活动区进行分析研究,以寻求强SWF耀斑的先兆.结果表明,一磁流在异极性磁流区浮现,同极性磁流合并、异极性磁流侵入和纵向磁场强度剧增4种磁位形演化与强SWF耀斑有密切关系。文中还用1988年9—10月份的25个活动区的磁图和耀斑资料佐证上面的结果。