程控交换机用户线测试系统

介绍一种新型的程控交换机用户线测试系统。本系统可以自动完成受理、测试、派工等一系列１１２测量台的日常工作，同时还可对本地电话网的用户线路资料进行集中管理     

话音－数据综合传输控制分析

分析了一种基于时分复用（ＴＤＭ）的可移动边界型语音－数据综合传输控制模型，采用逐次逼近算法求出了在一定性能准则条件下的最佳信道容量分配方案。数值结果表明，以允许的话音失真为代价，可提高系统总的吞吐量     

非线性规划的极大熵方法

使用极大熵方法详细研究了光滑逼近函数的解收敛到原优化问题的解的所谓收敛性定理．     

Ag-NiMnGa颗粒膜分析

利用离子束溅射技术制备了AgNiMnGa颗粒膜的系列样品.分别采用广角X射线衍射(WXRD)技术和掠入射X射线散射(GIXS)技术分析了样品的物相组成和膜面与内层结构,NiMnGa颗粒平均尺寸为5 5nm;样品膜厚度为463nm.对样品电磁性能的研究表明:颗粒膜在室温下磁场扫描测量中呈现明显的磁致电阻效应;其伴随有振荡的非线形电流电压关系揭示了介观系统具有的输运特征.     

基于峰态的盲信号分离

就一种基于信号峰态(kurtosis)极值化的盲信号分离方法进行了探讨．首先介绍算法理论，然后提出了一种简化快速的最速下降算法，解决了收敛指向性的问题，并将对混合语音信号的分离扩展到混合图像信号的分离．实验结果表明，同其他基于峰态的盲分离算法相比，其分离效果好，而且在收敛速度、运算复杂度方面有显著的优势．     

壬基酚对鲫鱼(Carassius auratus)巨噬细胞的免疫毒性

从鲫鱼(Carassius auratus)头肾中分离巨噬细胞，体外暴露雌二醇和壬基酚后，用MTT法测定它们对鲫鱼巨噬细胞增殖的影响，用化学发光法测定它们对鲫鱼巨噬细胞呼吸爆发的影响，评价壬基酚的免疫毒性，并与天然激素雌二醇的免疫效应相比较．结果表明，雌二醇对鲫鱼巨噬细胞的增殖有明显的诱导作用，壬基酚对鲫鱼巨噬细胞增殖在低浓度表现为诱导作用，高浓度表现为抑制作用．雌二醇、壬基酚对鲫鱼巨噬细胞呼吸爆发有明显的诱导作用．研究结果表明壬基酚对鲫鱼具有潜在的免疫毒性．与天然激素雌二醇的免疫作用效应比较，进一步证明了壬基酚的弱雌激素活性．     

多不饱和脂肪酸对谷氨酸诱导的大鼠海马神经细胞损伤的双重影响

通过测定原代培养的谷氨酸诱导的受损海马神经的细胞存活率,谷胱甘肽过氧化物酶活性,以及谷胱甘肽和一氧化氮的水平,研究多不饱和脂肪酸,如二十二碳六烯酸(docosahexaenoic acid,DHA)、花生四烯酸(arachidonic acid,AA),对大鼠海马神经细胞损伤的影响.海马神经元用神经特异性烯醇化酶进行鉴定.研究发现:(1)DHA 5～50 mg/L能有效的对抗谷氨酸诱导的海马神经细胞的损害作用.表现在细胞存活率、谷胱甘肽过氧化物酶的活性较谷氨酸处理组明显提高,NO水平降低,谷胱甘肽含量与对照组相比变化不大.(2)5 mg/LAA对损伤没有影响,而30和50 mg/LAA对损伤具有加重作用,其细胞存活率、GSH-Px活性、GSH水平较谷氨酸处理组明显降低.结果表明,多不饱和脂肪酸对谷氨酸诱导的神经细胞损伤具有双重作用.     

Secure Two-Party Distance Computation Protocol Based on Privacy Homomorphism and Scalar Product in Wireless Sensor Networks

Numerous privacy-preserving issues have emerged along with the fast development of the Internet of Things. In addressing privacy protection problems in Wireless Sensor Networks(WSN), secure multi-party computation is considered vital, where obtaining the Euclidian distance between two nodes with no disclosure of either side’s secrets has become the focus of location-privacy-related applications. This paper proposes a novel Privacy-Preserving Scalar Product Protocol(PPSPP) for wireless sensor networks. Based on PPSPP, we then propose a Homomorphic-Encryption-based Euclidean Distance Protocol(HEEDP) without third parties. This protocol can achieve secure distance computation between two sensor nodes. Correctness proofs of PPSPP and HEEDP are provided, followed by security validation and analysis. Performance evaluations via comparisons among similar protocols demonstrate that HEEDP is superior; it is most efficient in terms of both communication and computation on a wide range of data types, especially in wireless sensor networks.     

Multi-dimensional scattering properties diagnosis system of scale aircraft model in an anechoic chamber

Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional （2-D） imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional （3-D） height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional （l-D） RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber.     

基于遗传算法的直觉模糊C均值聚类算法

 针对一般直觉模糊C均值聚类算法在寻优过程中易陷入局部最优解的问题,利用遗传算法具备全局寻优的优点,提出了一种基于遗传算法的直觉模糊C均值聚类算法。在该算法中聚类中心为直觉模糊数,这使得遗传过程中个体信息变得复杂,进而增大了约束问题的处理难度。本文对产生的个体采用适时分段的归一化方法,很好地解决了该问题。仿真结果表明该算法所得聚类结果不仅准确而且更为细致。