基于遗传算法和LSSVM的网络安全事件发生频率预测

Since the frequency of network security incidents is nonlinear, traditional prediction methods such as ARMA, Gray systems are difficult to deal with the problem. When the size of sample is small, methods based on artificial neural network may not reach a high degree of preciseness. Least Squares Support Vector Machines (LSSVM) is a kind of machine learning methods based on the statistics learning theory, it can be applied to solve small sample and non-linear problems very well. This paper applied LSSVM to predict the occur frequency of network security incidents. To improve the accuracy, it used an improved genetic algorithm to optimize the parameters of LSSVM. Verified by real data sets, the improved genetic algorithm (IGA) converges faster than the simple genetic algorithm (SGA), and has a higher efficiency in the optimization procedure. Specially, the optimized LSSVM model worked very well on the prediction of frequency of network security incidents.     

关系数据库语义缓存的研究进展

语义缓存是优化数据库性能的有效方法,在关系数据库领域得到了广泛研究和应用。它是将查询结果和相关语义信息缓存,从而为将来的查询提供解答。本文首先介绍了语义 缓存的基本概念和原理,然后对现有语义缓存技术进行了分类,最后结合语义缓存的发展趋势讨论了语义缓存的关键技术。     

一种星载光学遥感设备供配电设计

供配电是空间有效载荷的电子学"动力"。针对GF-5卫星某光学遥感设备的供配电设计进行了分析研究,其中包括保护电路设计、浪涌抑制电路设计、切换电路设计、滤波电路设计、可靠性设计等。设计结果既符合相关规范要求,又结合自身特点进行了针对性设计, 通过了鉴定级试验和验收测试。可靠性高,已经在轨应用,具有较高的工程实用价值。     

CCD相对光谱响应同步采样方法研究

连续可调谐均匀单色照明光源系统作为CCD辐射参量定量化专用测试系统,可用于CCD相对光谱响应度的测量。它与传统的测试装置相比,能够实现光谱分辨率1 nm的光谱响应度定标。但是其采用的大功率氙灯超高压供电引入了测试光源不稳定的问题,导致传统分时测量方法引起的测量不确定度较差,不能满足高精度遥感仪器的定标需求,因此提出了同步采样的方法。从理论和器件噪声模型出发,分别对两种方法的测量不确定度进行分析,得出同步采样的方法测得的定标不确定度优于1.03%,与传统分时测量方法相比不确定度提高了43%。分别采用两种方法对目标探测器进行了CCD相对光谱响应对比测试,结果显示,同步采样的方法获得的CCD相对光谱曲线更平坦,与出厂数据相比离散程度更低,进而验证了分析结论的正确性。     

医院试剂管理系统的设计与应用

针对医院在试剂管理上存在的突出问题,本文结合医院实际工作环境和管理需求,建立了一个基于B/S模式和C/S模式共用的,高效、稳定的试剂管理信息系统。     

基于带宽比特征的雷达辐射源信号识别

提出了用信号带宽比特征识别雷达辐射源的新方法。通过两次对雷达辐射源信号进行平方处理,提取两次处理前后信号带宽的比值组成二维特征向量。利用四种常见的雷达辐射源信号进行的仿真实验结果表明,带宽比特征类内聚集性强,类间分离度大,能达到非常满意的正确识别率,证实了所提方法的有效性。     

控制棒驱动机构自然循环冷却方式的可行性研究

传统的二代压水反应堆主要是采取鼓风机鼓风的方式对控制棒驱动机构(Control Rod Drive Mechanism,CRDM)进行强制通风冷却,该冷却方式耗能较大且无法保证绝对安全可靠。本文针对于大亚湾核电站中CRDM群的布置方式,采用中广核新型的EMC-B型控制棒驱动机构的结构及材料物性参数,运用了计算流体力学(Computational Fluid Dynamics,CFD)分析方法,研究了当采用空气自然循环冷却方式时,CRDM群及各线圈的温度分布,探索对CRDM群采用空气自然循环冷却方式的可行性。模拟分析结果表明:总体来看,处于外围和中心位置处的CRDM的线圈温度,要比中间区域的CRDM线圈温度高;对于给定计算工况,各线圈的最高温度为198°C,低于限制温度(200°C),表明对于所研究的CRDM群,依靠空气的自然对流,可以对CRDM进行有效冷却。计算结果可为新型CRDM群分布设计提供参考。     

铁皮石斛花总黄酮的绿色提取工艺优化

目的:为充分利用铁皮石斛花中的黄酮类物质,开发了一种绿色高效的总黄酮提取工艺。方法:以铁皮石斛花总黄酮得率为指标,使用新型低共熔溶剂,基于单因素实验结合响应面法（Response surface methodology, RSM）优化总黄酮提取工艺参数,并使用大孔吸附树脂考察溶剂的循环利用能力。结果:氯化胆碱、乙二醇（摩尔比1:4）组成的低共熔溶剂（Deep eutectic solvents,DESs）得率最高;最佳提取条件下（DESs含水量18.9%,温度88.2 ℃,液固比23.3:1 mL/g,时间38.0 min）,得率达到22.457 mg/g;大孔吸附树脂ADS-8对总黄酮吸附率、解吸率分别为78.32%、83.55%,回收后的DESs重复利用率达95.47%。结论:低共熔溶剂是一种高效绿色的提取方法,可循环利用铁皮石斛花中总黄酮的提取。     

基于多维熵序列分类的骨干网上流量异常检测

Detecting traffic anomalies is essential for diagnosing attacks. High-Speed Backbone Networks (HSBN) require Traffic Anomaly Detection Systems (TADS) which are accurate (high detection and low false positive rates) and efficient. The proposed approach utilizes entropy as traffic distributions metric over some traffic dimensions. An efficient algorithm, having low computational and space complexity, is used to estimate entropy. Entropy values over all dimensions are collected to form a detection vector for every sliding window. One class support vector machine classifies all detection vectors into one of two groups: abnormal vectors and normal vectors. A Multi-Windows Correlation Algorithm (MWCA) calculates comprehensive anomaly scores observed in a sequence of windows in order to reduce false positive rates and obtain high detection rates. Some real-world traffic traces have been used to validate and evaluate the efficiency and accuracy of this system through three experiments. In Experiment 1, the estimating algorithm of entropy which costs less memory and runs faster than traditional algorithms is more suitable for detection anomalies. In Experiment 2, the classification and correlation algorithms can improve the detection accuracy significantly. Experiment 3 compares the subject system and three well-known systems. Ours system is the most accurate one. Those results have indicated that the proposed system significantly improves the accuracy and efficiency.