基于注意力机制和生成对抗网络的飞行器短期航迹预测模型

针对单一长短时记忆（LSTM）网络在航迹预测上无法有效提取关键信息以及难以精准拟合数据分布等问题,提出基于注意力机制和生成对抗网络（GAN）的飞行器短期轨迹预测模型。首先,引入注意力机制对航迹赋予不同的权重,以提升航迹中重要特征的影响力;其次,基于LSTM提取航迹序列特征,并经汇聚层汇集时间步长内所有的飞行器特征;最后,利用GAN在对抗博弈下不断优化的特性来优化模型,从而提高模型的准确性。相较于社会生成对抗网络（SGAN）,所提模型在处于爬升阶段的数据集上的平均位移误差（ADE）、最终位移误差（FDE）及最大位移误差（MDE）分别降低了20.0%、20.4%和18.3%。实验结果表明,所提模型能更精确地预测未来航迹。     

Clavulanic acid production estimation based on color and structural features of streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively.     

基于GSM和WSNs的实验室温湿度采集报警系统设计

针对计量校准实验室严格的环境条件要求,设计了一种基于无线传感器网络(WSNs)的实验室温湿度采集报警系统.以STC12C5A60S2微处理器为控制核心,收集、处理和储存各校准实验室内传感器节点数据信息,并通过GTM900C模块实现数据信息的远程传输.当实验室内温湿度超出设定的阈值时,系统可自动传输超限报警信息.系统精确度高、实用性强、性能稳定可靠,能准确监测、记录实验室的温湿度,有效规避在环境不合格的条件下进行检定、校准及测试项目,具有很强的实际应用价值.     

Thermochemical analysis for the reduction behavior of FeO in EAF slag via Aluminothermic Smelting Reduction (ASR) process: Part II. Effect of aluminum dross and lime fluxing on Fe and Mn recovery

We investigated Fe recovery from EAF slag by means of aluminothermic smelting reduction (ASR) at 1773 K with Al dross as the reductant, especially the effect of the added amount of the fluxing agent CaO on the Fe recovery. The maximum reaction temperature calculated using FactSage™ 7.0 decreased with increasing CaO addition, but the experimentally measured maximum temperatures increased with increasing CaO addition. We calculated the amounts of various phases before and after Al dross addition under different conditions of added CaO. FeO and Al₂O₃ contents in molten slag sharply varied within the first 5 min of the reaction, stabilizing soon thereafter. The aluminothermic reduction of FeO appeared to proceed rapidly and in good stoichiometric balance, based upon the mass balance between the consumption of FeO and MnO (ΔFeO and ΔMnO) and the production of Al₂O₃ (∆Al₂O₃). Iron recovery from EAF slag was maximized at about 90% when 40 g of CaO was added to 100 g slag. Furthermore, Mn could also be reduced from the EAF slags by the metallic Al in the Al dross reductant. The solid compounds of spinel (MgO∙Al₂O₃) and MgO were precipitated from the slag during the FeO reduction reaction, as confirmed by means of XRD analysis and thermochemical computations. To maximize Fe recovery from EAF slag, it is crucial to control the slag composition, namely to ensure high fluidity by suppressing the formation of solid compounds.