基于随机机器故障的柔性作业车间动态调度

为了有效快速地应对生产过程中出现的随机机器故障,构建了一个故障机器可恢复的动态柔性作业车间调度模型,采用事件和周期混合驱动的方式,设计了一个组合重调度策略.在组合重调度策略中,将改进的二叉树右移重调度与完全重调度进行组合,引入序位偏差和完工时间偏差为重调度评价指标,对重调度方法进行选择,并且在精英选择遗传算法(elite selection genetic algo-rithm,ESGA)基础上,对精英选择策略进行改进,以防止陷入局部最优.试验算例仿真结果表明,动态调度算法对随机机器故障下的柔性作业车间动态调度是有效的.     

基于淀粉经济、无毒的比色潜指纹检测

构建了一种基于淀粉的经济、无毒、实时的潜指纹比色检测方法.利用淀粉与指纹之间的氢键和范德华力作用,使淀粉有效识别出无孔和多孔基底上的潜指纹.通过将不同颜色的植物染料混合进淀粉,解决了由淀粉与基底之间顺色导致的检测对比度差的难题.该方法还表现出对老化潜指纹和重叠潜指纹的良好检测效果.     

用于有机磷农药及其水解产物可视化检测的荧光探针制备及性质研究

使用氯金酸和柠檬酸三钠回流法合成出荧光吸收峰在520 nm的金纳米颗粒,并与罗丹明B修饰合成探针.金纳米颗粒与罗丹明B发生荧光共振能量转移(FRET)作用使罗丹明B的荧光淬灭.在加入毒死蜱之后,毒死蜱及其水解产物能有效取代罗丹明B,使荧光恢复.金纳米颗粒探针对毒死蜱及其水解产物的浓度响应区间为(0～0.1)mm,低至0.1 nm也有响应,且荧光变化迅速,从而能够快速有效地检测超痕量有机磷农药毒死蜱及其水解产物.     

改进模型估计与平差的多幅异源影像匹配方法

针对多幅异源影像匹配准确性不高的问题，提出了一种改进模型估计与平差的多幅异源影像匹配方法。首先利用基于快速自适应鲁棒性尺度不变的特征检测子与鲁棒性交叠的标准特征描述子，来增强特征匹配的鲁棒性；然后提出改进的随机抽样一致性算法，来提高模型估计的执行效率，同时保证鲁棒性；最后提出针对多幅异源影像匹配的平差方法，来优化异源匹配结果。实验结果表明，在异源影像存在较大差异的情况下，改进模型估计与平差的多幅异源影像匹配方法具有精度高的优势。      

Side-Channel Attacks in a Real Scenario

Existing Side-Channel Attacks(SCAs) have several limitations and, rather than to be real attack methods,can only be considered to be security evaluation methods. Their limitations are mainly related to the sampling conditions, such as the trigger signal embedded in the source code of the encryption device, and the acquisition device that serves as the encryption-device controller. Apart from it being very difficult for an attacker to add a trigger into the original design before making an attack or to control the encryption device, there is a big gap in the capacity of existing SCAs to pose real threats to cipher devices. In this paper, we propose a new method, the sliding window SCA(SW-SCA), which can be applied in scenarios in which the acquisition device is independent of the encryption device and for which the encryption source code requires no trigger signal or modification. First,we describe the main issues in existing SCAs, then we theoretically analyze the effectiveness and complexity of our proposed SW-SCA —a method that can incorporate a sliding-window mechanism into almost all of the existing non-profiled SCAs. The experimental results for both simulated and physical traces verify the effectiveness of the SW-SCA and the appropriateness of its theoretical complexity.     

Bidirectional Feedback Dynamic Particle Filter with Big Data for the Particle Degeneracy Problem

Particle Filter(PF) is a data assimilation method to solve recursive state estimation problem which does not depend on the assumption of Gaussian noise, and is able to be applied for various systems even with non-linear and non-Gaussian noise. However, while applying PF in dynamic systems, PF undergoes particle degeneracy,sample impoverishment, and problems of high computational complexity. Rapidly developing sensing technologies are providing highly convenient availability of real-time big traffic data from the system under study like never before. Moreover, some sensors can even receive control commands to adjust their monitoring parameters. To address these problems, a bidirectional dynamic data-driven improvement framework for PF(B3 DPF) is proposed.The B3 DPF enhances feedback between the simulation model and the big traffic data collected by the sensors,which means the execution strategies(sensor data management, parameters used in the weight computation,resampling) of B3 DPF can be optimized based on the simulation results and the types and dimensions of traffic data injected into B3 DPF can be adjusted dynamically. The first experiment indicates that the B3 DPF overcomes particle degeneracy and sample impoverishment problems and accurately estimates the state at a faster speed than the normal PF. More importantly, the new method has higher accuracy for multidimensional random systems.In the rest of experiments, the proposed framework is applied to estimate the traffic state on a real road network and obtains satisfactory results. More experiments can be designed to validate the universal properties of B3 DPF.     

A 12-bit 250-MS/s Charge-Domain Pipelined Analog-to-Digital Converter with Feed-Forward Common-Mode Charge Control

A feed-forward Common-Mode(CM) charge control circuit for a high-speed Charge-Domain(CD)pipelined Analog-to-Digital Converter(ADC) is presented herein.This study aims at solving the problem whereby the precision of CD pipelined ADCs is restricted by the variation in input CM charge,which can compensate for CM charge errors caused by a variation in CM charge input in real time.Based on the feed-forward CM charge control circuit,a 12-bit 250-MS/s CD pipelined ADC is designed and realized using a 1 P6 M 0.18-μm CMOS process.The ADC achieved a Spurious Free Dynamic Range(SFDR) of 78.1 d B and a Signal-to-Noise-and-Distortion Ratio(SNDR) of 64.6 d B for a 20.1-MHz input:a SFDR of 74.9 d B and SNDR of 62.0 d B were achieved for a 239.9-MHz input at full sampling rate.The variation in signal-to-noise ratio was less than 3 d B over a 0–1.2 V input CM voltage range.The power consumption of the prototype ADC is only 85 m W at 1.8 V supply,and it occupies an active die area of 2.24 mm~2.     

迹为整数的3×3阶正交矩阵的谱

讨论了3×3阶正交矩阵的特征值和迹的关系,证明了迹为整数的3×3阶正交矩阵的谱可由迹确定,为应用广泛的3×3阶正交矩阵的谱的计算提供了简单实用的方法.     

移动荷载作用下结构弹塑性安定分析方法及其应用研究

为了研究移动荷载作用下结构的安定性问题,以Melan静力型安定定理为基础,通过构造满足静力平衡条件的最佳残余应力场,并求解移动荷载作用下结构中的真实弹性应力场,发展了一种弹塑性安定性计算方法.该方法摆脱了传统安定性分析方法中的数学规划运算,解决了计算中维数障碍的问题.通过与前人研究结果对比,说明本方法的正确性.基于此方法,研究了列车荷载直接作用下路基的静力安定极限的第一类上限kI和静力安定极限kSD,进行轮载间距L和铁轨间距B对路基安定极限的敏感性分析,发现当轮载间距L和铁轨间距B大于等于10a时,轮载间距L和铁轨间距B对路基安定极限不再产生影响;通过分析材料泊松比v和内摩擦角φ对安定极限的影响,表明安定极限随着路基泊松比的增大略有减小,但随着内摩擦角的增大而有明显增加;并提出了一种基于安定极限荷载包络图的路基安定性评价方法和设计方法,据此可对铁路路基进行设计指导和安全性评价.     

设施拥堵状态下的层次性备用覆盖网络模型与改进遗传算法

经典的分层覆盖位置问题(HCLP)是在有限预算内找到设施位置以提供分层服务的问题.这个过程中,需求点的差异化服务需求可以来自层次型网络中不同服务可用性的设施.我们设计了混合服务可用性的层次型网络,通过讨论层次型设施数量为定量和变量的情况构建混合层次网络备用覆盖问题的整数规划模型,并设计、改进元启发式算法来求解问题.结果表明考虑变量的混合服务可用性的优化模型在一次覆盖中能更好的满足客户的需求,而其备用覆盖能力和系统造价并非始终优于单类型层次网络;建议的启发式算法在合理的计算时间内产生高质量的解.