A blockchain-based framework for data quality in edge-computing-enabled crowdsensing

With the rapid development of mobile technology and smart devices, crowdsensing has shown its large potential to collect massive data. Considering the limitation of calculation power, edge computing is introduced to release unnecessary data transmission. In edge-computing-enabled crowdsensing, massive data is required to be preliminary processed by edge computing devices (ECDs). Compared with the traditional central platform, these ECDs are limited by their own capability so they may only obtain part of relative factors and they can’t process data synthetically. ECDs involved in one task are required to cooperate to process the task data. The privacy of participants is important in crowdsensing, so blockchain is used due to its decentralization and tamper-resistance. In crowdsensing tasks, it is usually difficult to obtain the assessment criteria in advance so reinforcement learning is introduced. As mentioned before, ECDs can’t process task data comprehensively and they are required to cooperate quality assessment. Therefore, a blockchain-based framework for data quality in edge-computing-enabled crowdsensing (BFEC) is proposed in this paper. DPoR (Delegated Proof of Reputation), which is proposed in our previous work, is improved to be suitable in BFEC. Iteratively, the final result is calculated without revealing the privacy of participants. Experiments on the open datasets Adult, Blog, and Wine Quality show that our new framework outperforms existing methods in executing sensing tasks.     

基于有源滤波器自适应阻抗重塑的高速铁路谐波谐振抑制

针对电力机车和牵引网阻抗参数耦合所引起的牵引供电系统的谐波谐振现象,首先基于阻抗分析法建立了有源滤波器、电力机车和牵引网的小信号阻抗模型,使用广义奈奎斯特判据分析了牵引供电系统谐波谐振的机理以及有源滤波器对牵引供电系统谐波谐振的影响。其次,提出一种基于阻抗重塑的牵引供电系统谐波谐振抑制方法,通过并网点电压前馈的方式在有源滤波器中引入虚拟阻抗,并利用自适应参数设计提升了虚拟阻抗对动态系统的适应性。最后,在Matlab/Simulink中搭建了“牵引网-电力机车-有源滤波器”统一仿真模型,验证有源滤波器的自适应阻抗重塑对谐波谐振抑制的有效性。     

自适应高斯融合双通道的去雾算法

针对传统图像去雾算法存在的对比度下降和颜色偏移等问题,提出一种结合高斯融合的自适应双通道雾霾图像复原算法。首先,考虑到大气光应小于有雾图像最大值,且大于有雾图像最小值,根据亮度控制因子自适应控制的方式得到融合中通道,并获得中通道下的局部大气光;其次,提出双通道线性传输,即用最大值通道辅助完成线性传输,再用高斯函数加权融合的方法实现清晰图像最优通道估计,从而得到最优透射率;最后,结合复原模型恢复清晰图像。实验表明,所提方法有效解决了图像对比度下降与颜色偏移等问题,去雾效果良好、亮度适宜且颜色保真度更高。另外,该方法在定量指标上同样具有优越的表现。      

基于深度学习和灰度纹理特征的铁路接触网绝缘子状态检测

铁路接触网绝缘子状态检测对铁路行车安全有着 重大的意义,为解决目前人工对绝缘 子图像检测结果的不确定性,提出一种深度学习结合灰度纹理特征的检测方法。首先使用 Faster R-CNN (faster region-based convolutional neural network)目标检测算法对图像中绝缘子精确识别,再通过灰度共生矩阵对绝缘子纹理 特征进行分析提取,之后结合支持向量机将绝缘子分为正常绝缘子和异常绝缘子,实验数 据结果证明使用能量、熵、相关度3种纹理特征进行绝缘子状态分类时对实验数据中的正 常状态绝缘子的分类精度可达100%,异常状态绝缘子的分类精度达97.5%,最后依据绝缘 子图像灰度分布的周期性特点,利用灰度积分投影将异常绝缘子分为破损绝缘子和夹杂异 物绝缘子。实验结果表明所提方法可以有效对绝缘子状态进行检测分类。     

高分七号卫星多源遥感数据精度优化与评估

高分七号卫星是国内首个亚米级双线阵立体成像卫星,同时配有两套激光测高仪和激光足印相机,可同期获取多源遥感数据。文中采用高分七号卫星获取的多源遥感数据进行平面和高程精度优化,利用激光测高数据对立体影像密集匹配的DSM进行偏度、中值、线性和二阶多项式模型和高程优化评估,利用足印影像对DOM进行一阶仿射变换方法和平面优化评估,并利用外业控制点对无控平面高程、激光高程优化、足印-激光平面高程优化、外业-激光平面高程优化等不同优化模型的结果进行精度评估。实验结果表明,利用激光测高数据可明显优化DSM高程精度,无控DSM高程误差平均值为?4.268 m,中误差为4.518 m,经过中值模型优化后的DSM高程误差平均值提升为?0.272 m,中误差提升为1.508 m,经过线性模型优化后的DSM高程误差平均值提升为?0.320 m,中误差提升为1.351 m;利用足印影像可改善DOM的平面精度,平面误差平均值从13.606 m提升到5.341 m,中误差从13.626 m提升到5.495 m。     

基于时空图卷积网络的交通事故风险预测研究

交通事故的预测是通过对过去路段发生的交通事故进行分析,在综合考虑影响交通事故的相关因素后,对未来路段的交通事故发生状态进行预测。以往的大多数研究通常采用传统机器学习方法或单一深度学习模型预测法,利用网格化确定预测空间的单位,忽略了影响交通事故的天气、路况等外部因素,导致模型的预测性能不佳。提出一种基于时空特性的城市交通事故风险预测模型,在模型中使用改进的时空图卷积网络,利用图卷积网络（GCN）提取空间相关特征,并加入批标准化层解决梯度消失爆炸问题。在时间维度上采用门控线性单元（GLU）实现一维卷积操作,提取时间相关特征,并将GCN和GLU组合成时空卷积模块提取时空相关特征,使用均方误差损失函数解决样本数据零膨胀问题。实验结果表明,与GLU、SDCAE和ConvLSTM模型相比,该模型的RMSE指标分别降低了28%、4.87%、4.19%,能有效捕获时空相关性,综合性能得到较大提升。     

Ferromagnetism and the Optical Properties of Mn-Doped CdSe with the Wurtzite Structure

The geometrical structure of CdSe was optimized by using the ultrasoft pseudopotential method of a total energy plane wave based on density functional theory. The band structure, density of states, and optical properties were calculated and discussed in detail. The Mn-doped CdSe is found to be a half-metallic ferromagnet with 100% carrier spin polarization at the Fermi level. At a Mn concentration of 12.5%, the calculated total energy of the spin-polarized state is 614 meV lower than that of the nonspin-polarized state. The net magnetic moment of 5 μ _B is found per supercell for 12.5% Mn-doped CdSe. The estimated Curie temperature of 748.6 K for Mn-doped CdSe is above room temperature. The ferromagnetic ground state in Mn-doped CdSe can be explained in terms of the p ? d hybridization mechanism. These results suggest that Mn-doped CdSe may present a promising dilute magnetic semiconductor, and may have potential applications in the field of spintronics.     

墨汁碳纳米粒增强壳聚糖复合膜的制备及性能研究

利用墨汁中碳纳米粒为增强体,以流延法制备墨汁/壳聚糖复合膜。采用扫描电子显微镜(SEM)对复合膜的结构进行了表征,研究不同的墨汁加入量对墨汁/壳聚糖复合膜力学、耐水以及光透过率等性能的影响。结果表明低含量墨汁中碳纳米粒可均匀分散在壳聚糖基体中。与纯壳聚糖膜相比,加入墨汁后的复合膜的力学性能和耐水性能得到了明显的提高。复合膜的光透过率随着复合膜中墨汁含量的增加急剧下降,具有非常优异的光阻隔性能。     

Synthesis and microstructure characterization of tetragonal Zr1–xTixO2 (x = 0–1) solid solutions

Oxide powders of Zr_1–xTi_xO₂ (x = 0–1) solid solutions with micron-sized particles were synthesized via a solution combustion method. The synthesis process and Zr/Ti molar ratio were optimized to produce powders with the tetragonal crystal structure. X-ray diffraction, Raman spectroscopy and transmission electron spectroscopy results confirm that a full crystallization microstructure with the single tetragonal phase is obtained after calcination at 600 °C while maintaining the crystallite size <30 nm. Zr/Ti oxide mixtures with Zr ≥ 67 mol% exhibit a tetragonal crystal structure and the embedding Ti in ZrO₂ improves the structure stability. The nitrogen sorption results indicate that the powders possess mesoporous morphology with medium specific surface areas (∼10–50 m²/g). Chemical stability tests show that these powders are relatively stable with negligible removal of titanium and zirconium after elution by 0.5 mol/L HCl. Density functional theory was used to calculate the most stable structure with low energy for the selected composition.     

基于贝叶斯推理的包装件动力学模型优化选择研究

目的 在多种类型的模型中挑选出最优包装件模型,并实现参数识别的方法。方法 文中将包装件模型构建为参数不确定模型,在贝叶斯推理的框架下,采用马尔可夫链蒙特卡洛法识别模型参数,采用偏差信息准则(DIC)计算各备选模型的DIC参数,选择出最优包装件模型。结果 在振动实验台用质量块–缓冲材料模拟包装件并进行随机振动测试,分析结果表明,Bouc–Wen(n=2)模型为文中包装系统的最佳模型。结论 文中提出的基于贝叶斯推理的包装件模型优化选择和参数识别方法考虑了模型不确定性,构建的模型可准确预测包装件在随机振动下加速度响应的时域信号。