使用深度学习的社交物联网信任预测模型

社交物联网是社交网络概念在物联网中整合后兴起的一个蓬勃发展的研究领域。提出了一种适用于社交物联网网络的改进型节点级信任模型,并通过与其他信任模型的对比仿真实验证明在恶意节点的攻击下,提出的模型拥有更好的稳定性和适用性,总体波动较小。同时,针对实际社交物联网网络中新加入网络的陌生节点可能遇到的网络延迟影响信任值评估的问题,在改进型节点级信任模型的基础上进一步使用了深度学习模型对其进行信任值预测。仿真证明,使用深度学习预测后模型的系统性能明显优于不使用深度学习的模型,成功交互率提升约1.8%。     

Productivity impact of drought tolerant maize varieties under rainfall stress in Malawi: A continuous treatment approach

Drought tolerant (DT) maize varieties have received massive support in sub‐Saharan Africa because of their potential to protect smallholder farmers against drought‐related maize yield losses. Using four waves of household farm panel data from six districts in Malawi, we examine the impact heterogeneity of this technology on maize productivity using a continuous treatment approach. We find strong evidence of positive correlation between maize yield and adoption of DT maize varieties. On average, an increase by one hectare in the area allocated to DT varieties increases maize yield by 547 Kg/ha representing a 44% increase from the average maize yield of 1,254 Kg/ha for our sample. Our findings give evidence that DT maize technology has potential to protect smallholder farmers against drought‐related production losses. Policies that promote increased allocation of maize area to DT maize hold potential to enhance food security. Smallholder farmers especially in drought‐prone areas should be encouraged to allocate at least one‐third of the maize plot to DT varieties while breeders continue with the efforts of breeding a DT variety that is not only drought tolerant but also adapted to all weather conditions. More importantly, the government should ensure provision of timely ex ante weather information to guide farmers on decision‐making with respect to maize varietal choices.     

基于神经网络的无刷直流电机故障诊断和容错控制方法的研究

提出并设计了一种针对无刷直流电机控制器的故障诊断和容错控制方法。该神经网络状态观测器由实际非线性控制系统进行训练,根据实际系统和神经网络观测器输出残差,容错控制系统能够被确定下来。针对系统控制器、电流和速度传感器的故障条件进行了仿真分析,容错控制通过使用补偿控制器实现,保证系统故障条件下的稳定性和性能。结果表明,所提出的方法能有效地定位错误故障和时间,消除干扰并提高系统的鲁棒性。     

延迟容忍网络自适应差错控制方法

根据延迟容忍网络的时延较大、误码率较高等特点,在现有的传输控制层和MAC层差错控制 的基础上改进,结合IEEE 802.11 DCF机制的特点,提出一种基于MAC层丢包率的自适应差错 控 制方案。该方案能有效改善延迟容忍网络的传输时延,满足对时延要求比较敏感的业务的要 求 。     

A POISSON PROCESS APPROXIMATION FOR GENERALIZED K–S CONFIDENCE REG

One–sided confidence regions for continuous cumulative distribution functions are constructed using empirical cumulative distribution functions and the generalized Kolmogorov–Smimov distance. The band width of such regions becomes narrower in the right or left tail of the distribution. To avoid tedious computation of confidence levels and critical values, an approximation based on the Poisson process is introduced. This approximation provides a conservative confidence region; moreover, the approximation error decreases monotonically to 0 as sample size increases. Critical values necessary for implementation are given. Applications are made to the areas of risk analysis, investment modelling, and analysis of fault–tolerant systems.     

多变量网络控制系统鲁棒容错控制研究

文章研究了一类具有时延和丢包且执行器故障的多变量网络控制系统鲁棒容错控制器设计问题,基于系统中的不确定性,推导了该类网络控制系统的诱导时滞数学模型,并利用李雅普诺夫第二法和自由权矩阵方法,分析了系统的渐近稳定性,得到了系统稳定运行的最大允许时延的条件。最后,通过仿真分析证实了本文所提理论的有效性,以及稳定判据的可行性。     

自适应帧同步器的设计与实现

“9·11”事件后美国发起了全球范围内的金融反恐战,本文介绍了金融反恐的由来、国际上关于金融反恐的标准、世界上主要国家目前的反洗钱反恐融资(AML/CFT)机制以及我国金融反恐的现状,并分析了金融反恐目前存在的问题和困难。     

Multi-Site Bundling of Drought Tolerant Maize Varieties and Index Insurance

Drought Tolerant Maize Varieties (DTMV) and Rainfall Index Insurance (RII) are potential complements, though with limited empirical basis. We employ a multivariate spatial framework to investigate the potential for bundling DTMV with a simulated multi-site and multi-environment RII, designed to insure against mild, moderate and severe drought risk. We use yield data from on-farm trials conducted by the International Maize and Wheat Improvement Center (CIMMYT) and partners over 49 locations in Eastern and Southern Africa spanning 8 countries and 5 mega-environments (dry lowland, dry mid altitude, wet lower mid altitude, low wetland and wet upper mid altitude) in which 19 different improved maize varieties including DTMV were tested at each location. Spatially correlated daily rainfall data are generated from a first-order two-state Markov chain process and used to calibrate the index and predict yields with a hierarchical Bayes multivariate spatial model. Results show high variation in the performance and benefits of different bundles which depend on the maize variety, the risk layer insured, and the type of environment, with high chances of selecting a sub-optimal and unattractive contract. We find that complementing RII with a specific DTMV produces contracts with lower premiums and higher guaranteed returns especially in dry lowland increasing the chances of scaling up RII within this environment.     

Neighbors follow early adopters under stress: panel data analysis of submergence‐tolerant rice in northern Bangladesh

The benefits of a stress‐tolerant crop become visible under the stresses that the crop is tolerant against. We investigate the adoption of submergence‐tolerant rice in northern Bangladesh by using panel data of 461 households, interviewed in 2013 and 2015. The sample households were randomly selected in 31 villages where submergence‐tolerant rice seeds were given to a small number of farmers in each village. The results from the household fixed‐effects model indicate that submergence in the previous year increased the adoption of submergence‐tolerant rice. The adoption impact was larger among farmers who were neighbors of early seed recipients. Our results suggest that being neighbors of early seed recipients may have helped the neighboring farmers observe the benefits of the submergence‐tolerant rice under submergence. The results indicate the importance of the information flow from early recipients to neighboring farmers.     

延迟容忍网络中一种多信息融合的改进概率路由算法

综合利用节点物理状态信息（位置和速度矢量信息）和社会关系信息（历史相遇信息）,提出一种多信息融合的概率路由算法（PRMF）。该算法依据节点间距离的远近程度动态调整两类信息在预测相遇关系中的权重,以选择合适的信息来计算传输概率,并依据传输概率的大小选择转发节点。另外,还引入有效的分组副本控制和分组散播策略,并结合预测信息改进了节点缓存管理方法。仿真结果表明：与现有的几种路由算法相比,PRMF保持了较低的平均开销,同时具有最高的投递率和最小的平均延迟。