RED算法的改进及其性能分析

随机早期检测（RED）算法作为主动队列管理（AQM）中有效的实现算法，其性能研究近来已成为网络研究 的一个热点。介绍了原始RED算法，并在此基础上对该算法进行了改进，仿真结果和实验数据表明，改进算法能 显著地降低丢包率，提高网络的链路利用率。     

“Can you help me count these pennies?”: Surfacing preschoolers’ understandings of counting

ABSTRACT

Capturing the breadth and variety of children’s understanding is critical if studies of children’s mathematical thinking are to inform policy and practice in early childhood education. This article presents an investigation of young children’s counting. Detailed coding and analyses of assessment interviews with 476 preschoolers revealed understandings that would be overlooked by solely assessing the accuracy of their responses. In particular, many children demonstrated understandings of counting principles on a challenging task that were not captured by other, simpler tasks. We conclude that common approaches to capturing young children’s mathematical understanding are likely underestimating their capabilities. This study contributes to researchers’ understanding of what making sense of counting looks and sounds like for preschool age children (3–5 years), the development and relations among counting principles (one-to-one, cardinal, and patterns of the number sequence), and the affordances of challenging, open-ended tasks. We close by considering the implications of recognizing and building from what children know and can do for researchers, practitioners, and policymakers.     

具预警功能的三部件并联可修复系统的可靠性分析

研究了具有预警功能的三部件并联且有两个热备器的可修复系统,系统可转化为一个Banch空间上的抽象Cauchy问题.首先利用半群理论证明了该系统强解的存在唯一性,其次运用了代数方法证明了0是系统算子的简单本征值,最后对系统和不含预警功能的系统的可用度进行了比较分析.     

地下水脆弱性风险预警和评估的区间三角模糊多属性决策模型

应用基于逼近理想解排序法的区间三角模糊多属性决策模型,对三江平原六大分区地下水脆弱性进行了风险预警和评估.评估结果与前人吻合,可为有关决策部门采取相应降低环境风险的措施提供参考.实例验证表明,模型具有更高的计算精度和更好的评价效果,为有关环境风险决策部门对地下水风险预警和评估提供了新的思路和方法.     

家电行业并购的财务风险预警研究

通过对家电行业的特点及其并购过程中财务风险的分析,建立了家电行业并购的财务风险评价指标体系,运用层次分析法确定各指标权重,给出了我国家电行业并购财务风险预警的模糊综合评价模型,并通过四川长虹与美菱电器的并购案例进行了实证分析,对并购活动中财务风险防范与控制方面存在的问题进行了分析,明确了财务风险防范与控制的重点.     

基于神经网络技术的水质预测

随着地表饮用水源的藻类高发程度的加重和藻毒素的对健康的危害性逐渐被认识,供水企业需建立水源水质预警系统以确保供水水质和实现水厂经济运行,而水源水质预测是预警系统的基础.收集天津引滦源水1744天的水质检测资料,通过相关及指标聚类两种方法分析,确定建立预测2天后源水水质-叶绿素-a的神经网络模型的输入变量选择方案共26个,每个方案经10次试验,比选出模型最优输入变量和模型结构.为建立具有代表性的模型,使用前1209天数据训练模型,训练后的模型对剩余数据的仿真输出值与实际值间相关系数达0.88,其预测准确率为85%,满足水厂运行要求.     

A Pricing Model for American Options with Gaussian Interest Rates

In this paper we introduce a new methodology to price American put options under stochastic interest rates. We derive an analytic approximation that can be evaluated very fast and is fairly accurate. The method uses the so-called forward risk adjusted measure to derive analytic prices. We show that for American puts the correlation between the stock price and the interest rate has different influences on European option values and early exercise premiums.     

Indicator space configuration for early warning of violent political conflicts by genetic algorithms

Recognition of preconflict situations has a powerful potential for early warning of violent political conflicts. This paper focuses on the design and application of artificial neural networks as classifiers of preconflict situations. Achieving a desired level of performance of the neural network relies on the appropriate construction of recognition space (selection of indicators) and the choice of network architecture. A fast and effective method for the design of reliable neural recognition systems is described. It is based on genetic algorithm techniques and optimizes both the configuration of input space and the network parameters. The implementation of the methodology provides for increased performance of the classifier in terms of accuracy, generalization capacity, computational and data requirements. This revised version was published online in June 2006 with corrections to the Cover Date.     

S波段微波热致超声成像系统研究

微波热致超声成像技术通过向物体发射微波脉冲, 导致物体吸收电磁波温度迅速升高, 产生瞬时压力波, 从而激发产生超声波信号, 通过传感器对产生的超声波信号进行采集并成像, 最终还原了反映物体吸收电磁波能量特性的图像, 由于此方法兼具了微波成像的高对比性和超声成像的高分辨率特点, 理论上验证了热声成像技术对早期乳腺肿瘤检测的可行性. 本实验兼顾系统成像深度和分辨率, 采用S波段的微波脉冲信号源对物体进行辐射, 利用圆形扫描方式对待测物体进行检测, 同时为了更好的验证成像性能, 本实验同时使用了肿瘤仿体及实际生物组织进行成像实验. 通过实验分析, 验证了该系统对肿瘤仿体和生物组织检测的有效性, 以及系统的高分辨率和高对比度特性, 为早期乳房肿瘤检测提供了进一步的理论支撑.     

A single dual-mode gas sensor for early safety warning of Li-ion batteries: Micro-scale Li dendrite and electrolyte leakage

Li dendrites and electrolyte leakage are common causes of Li-ion battery failure. H₂, generated by Li dendrites, and electrolyte vapors have been regarded as gas markers of the early safety warning of Li-ion batteries. SnO₂-based gas sensors, widely used for a variety of applications, are promising for the early safety detection of Li-ion batteries, which are necessary and urgently required for the development of Li-ion battery systems. However, the traditional SnO₂ sensor, with a single signal, cannot demonstrate intelligent multi-gas recognition. Here, a single dual-mode (direct and alternating current modes) SnO₂ sensor demonstrates clear discrimination of electrolyte vapors and H₂, released in different states of Li-ion batteries, together with principal component analysis (PCA) analysis. This work provides insight into the intelligent technology of single gas sensors.