行政事业海量题库管理系统设计

提出了行政事业单位海量题库管理系统,给出了系统总体架构设计思路,论述了各主要功能模块的实现。着重讨论了题目重复度判别、题目难度系数调整等关键算法的实现,给出了系统部署、配置与应用实例。     

一种mIBS方案的分析与改进

魏松杰等人提出一种基于安全仲裁SEM（security mediator）的mIBS（identity based signature）方案,利用SEM节点实现用户身份实时撤销。mIBS方案中,SEM持有部分用户私钥,与签名者共同完成签名。对mIBS方案进行了安全性分析,发现该方案存在严重安全缺陷,并给出一个具体的攻击实例。在攻击实例中,签名者通过与SEM的一次正常签名交互,窃取SEM持有的部分私钥,进而绕开SEM单独实施签名,使得SEM失效。提出一种改进的mIBS方案（记为mIBSG）,对SEM持有的部分私钥增加了随机性保护。进一步,建立了mIBS方案安全模型mEUF-CMIA（existential unforgeability under adaptive chosen message and identity attacks）,重点讨论了其敌手模型。除传统IBS敌手外,mEUF-CMIA模型定义第二种类型敌手模拟一个恶意但合法的签名者,通过访问随机预言机,在没有SEM参与的情况下独立产生签名。在mEUF-CMIA模型下,mIBSG方案的不可伪造性被归约为求解循环群上的CDH问题。对比分析表明,mIBSG方案以较小的计算代价实现了可证明安全性。mIBSG方案可用于构建基于IBC的跨域认证系统。     

基于ADASYN-SFS-RF的欺诈检测模型泛化性能提升及可解释性研究

针对行业欺诈行为形式多样、操作隐蔽,且数据分布极端不平衡等问题,研究采用ADASYN（adaptive synthetic sampling approach for imbalanced learning）算法将分类决策边界向困难的实例进行自适应移动实现数据扩增,以解决不平衡数据造成的过拟合问题。采用基于随机森林的序列向前搜索策略算法筛选出最优特征子集对欺诈进行检测,降低ADASYN算法添加噪声数据对分类边界确定的影响,构建欺诈检测模型,并使用LIME对模型检测结果作出局部解释,提高模型的使用价值。实验表明,该模型可以较好地克服传统欺诈检测模型对多数类样本误分类的缺陷,有助于提高行业对交易欺诈行为识别的效率。同时,通过LIME对模型检测出的随机样本进行有效解析,便于决策者对算法模型的检测结果作出实证分析,起到明显的预警及决策参考价值。     

洪水预报智能模型在中国半干旱半湿润区的应用对比

为探究不同洪水预报智能模型在我国半干旱半湿润区的应用效果,选用决策树、多层感知器、随机森林和支持向量机4种模型在陕西省3个典型流域进行逐时洪水预报;选择相关系数、纳什效率系数、均方根误差、平均绝对误差和相对误差等评价指标,比较不同预见期下4种模型在半干旱半湿润典型流域洪水预报的适用性。结果表明:在短预见期预报中,4种模型在半湿润区典型流域均可获得较高的预报结果,在半干旱典型流域模拟精度相对偏低,仅支持向量机模型满足预报要求;随着预见期延长,不同模型性能变化差异大,支持向量机模型整体稳定,在小流域实时洪水预报中具有明显优势;随机森林模型与决策树模型精度随预见期延长而缓慢下降,前者适应性更好;多层感知器模型精度随预见期延长而骤减,模型稳定性较差。     

Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).     

一种鲁棒性的少样本学习方法

少样本学习是目前机器学习研究领域的一个热点,它能在少量的标记样本中学习到较好的分类模型.但是,在噪声的不确定环境中,传统的少样本学习模型泛化能力弱.针对这一问题,提出一种鲁棒性的少样本学习方法RFSL(Robust Few-Shot Learning).首先,使用核密度估计(Kernel Density Estimation,KDE)和图像滤波(Image Filtering)方法在训练集中加入不同的随机噪声,形成多个不同噪声下的训练集,并分别生成支持集和查询集.其次,利用关系网络的关系模块通过训练集端到端地学习多个基分类器.最后,采用投票的方式对各基分类器的最末Sigmoid层非线性分类结果进行融合.实验结果表明,RFSL模型可促进小样本学习快速收敛,同时,与R-Net以及其他主流少样本学习方法相比,RFSL具有更高的分类准确率,更强的鲁棒性.     

多重不确定的密码体制研究

针对现有密码体制中只有密钥不确定的特点,文章提出了多重不确定密码体制的概念,指出了可能实现的一些途径。文章分析了其优势,指出这类密码体制在大大增强安全性的同时,其可能带来的运算量的增加是可以忽略的。     

基于暂态零序能量的配电网故障选线方法研究

针对中性点经消弧线圈接地系统发生单相接地故障时因故障边界复杂、随机,故障稳态分量小,零序瞬时功率倒相而导致传统的单一特征量选线方法失效问题,提出了一种新的基于暂态零序能量的选线方法。该方法通过一种数字滤波器来滤除暂态零序电流中的不对称分量和稳态工频分量,得到各条线路零序电流和母线零序电压的暂态纯故障分量,由此构造暂态零序能量,并根据暂态零序能量的大小和方向判断故障类型及线路,即发生单相接地故障时,非故障线路暂态零序能量的方向为正,故障线路暂态零序能量的方向为负,且其绝对值为其余线路暂态零序能量之和;发生母线接地故障时,母线暂态零序能量的大小为其余线路暂态零序能量之和。针对母线暂态零序能量受噪声影响大而导致选线灵敏度低的问题,提出将自动重合闸技术应用到该选线方法中的方案。Matlab仿真结果表明,该选线方法的准确性、可靠性较高。     

On the predictability of the water-table variation in a ditch-drainage system

The irrigation in regions of brackish groundwater in many parts of the world results in the rise of the water-table very close to the groundsurface. The salinity of the productive soils is therefore increased. A proper layout of the ditch-drainage system and the prediction of the spatio-temporal variation of the water table under such conditions are of crucial importance in order to control the undesirable growth of the water-table. In this paper, an approximate solution of the nonlinear Boussinesq equation has been derived to describe the water-table variations in a ditch-drainage system with a random initial condition and transient recharge. The applications of the solution is discussed with the help of a synthetic example.Notations a lower value of the random variable representing the initial water-table height at the groundwater divide - a+b upper value of the random variable representing the initial water-table height at the groundwater divide - h variable water-table height measured from the base of the aquifer - K hydraulic conductivity - L half width between ditches - m ₀ initial water-table height at the groundwater divide - N(t) rate of transient recharge at time t - N ₀ initial rate of transient recharge - P N ₀/K - S Specific yield - t time of observation - t ₀ logarithmic decrement of the recharge function - T Kt/SL - x distance measured from the ditch boundary - X x/L - Y h/L - Y mean of Y - Y Variance of Y     

Parallel heap: An optimal parallel priority queue

We describe a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines. To our knowledge, it is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure. Employing p processors, the parallel heap allows deletions of (p) highest priority items and insertions of (p) new items, each in O(log n) time, where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n.This work was supported by U.S. Army's PM-TRADE contract N61339-88-g-0002, Florida High Technology and Industry grant 11-28-716, and Georgia State University's internal research support during spring and summer quarters, 1991.