Effects of Different Short-Term UV-B Radiation Intensities on Metabolic Characteristics of Porphyra haitanensis

The effects of ultraviolet (UV) radiation, particularly UV-B on algae, have become an important issue as human-caused depletion of the protecting ozone layer has been reported. In this study, the effects of different short-term UV-B radiation on the growth, physiology, and metabolism of Porphyra haitanensis were examined. The growth of P. haitanensis decreased, and the bleaching phenomenon occurred in the thalli. The contents of total amino acids, soluble sugar, total protein, and mycosporine-like amino acids (MAAs) increased under different UV-B radiation intensities. The metabolic profiles of P. haitanensis differed between the control and UV-B radiation-treated groups. Most of the differential metabolites in P. haitanensis were significantly upregulated under UV-B exposure. Short-term enhanced UV-B irradiation significantly affected amino acid metabolism, carbohydrate metabolism, glutathione metabolism, and phenylpropane biosynthesis. The contents of phenylalanine, tyrosine, threonine, and serine were increased, suggesting that amino acid metabolism can promote the synthesis of UV-absorbing substances (such as phenols and MAAs) by providing precursor substances. The contents of sucrose, D-glucose-6-phosphate, and beta-D-fructose-6-phosphate were increased, suggesting that carbohydrate metabolism contributes to maintain energy supply for metabolic activity in response to UV-B exposure. Meanwhile, dehydroascorbic acid (DHA) was also significantly upregulated, denoting effective activation of the antioxidant system. To some extent, these results provide metabolic insights into the adaptive response mechanism of P. haitanensis to short-term enhanced UV-B radiation.     

基于层次分析法的叶用甜菜种质资源观赏性评价

根据叶用甜菜品种的观赏特性,运用层次分析法初步建立叶用甜菜品种观赏价值的评价模型,包含叶梗、叶片和整体感3个方面共11个评价因子。结果表明:叶梗是评价叶用甜菜观赏价值的核心要素;叶梗色、叶梗厚、叶丛型是重要因子,分别以红、粉红、粉白叶梗,叶梗厚度厚和直立型叶丛为优良性状。利用该评价模型对8个甜菜品种进行观赏价值综合评价,筛选出‘Clnx-blush2018'、'Clnx-fen2018’和‘荷兰必久'3个观赏价值高、适于市场推广叶品种。     

基于NR-Transformer的集群作业运行时间预测

高性能集群的作业调度通常使用作业调度系统来实现，准确填写作业运行时间能在很大程度上提升作业调度效率。现有的研究通常使用机器学习的预测方式，在预测精度和实用性上还存在一定的提升空间。为了进一步提高集群作业运行时间预测的准确率，考虑先对集群作业日志进行聚类，将作业类别信息添加到作业特征中，再使用基于注意力机制的NR-Transformer网络对作业日志数据建模和预测。在数据处理上，根据与预测目标的相关性、特征的完整性和数据的有效性，从历史日志数据集中筛选出7维特征，并按作业运行时间的长度将其划分为多个作业集，再对各作业集分别进行训练和预测。实验结果表明，相比于传统机器学习和BP神经网络，时序神经网络结构有更好的预测性能，其中NR-Transformer在各作业集上都有较好的性能。     

基于自适应LS-SVM的柴油机废气再循环冷却控制系统设计

针对当前柴油机废气再循环冷却控制系统受到时滞问题影响,导致系统开度走势与设定走势不一致、废气再循环效果差的问题,提出基于自适应LS-SVM的柴油机废气再循环冷却控制系统;以AT89C51单片机40针作为电控单元核心部件,利用位置传感器向系统发送负载信号,利用温度传感器来传输信号并反馈至D/A转换器;在D/A转换器中,反馈信号以串行或并行方式进入寄存器,并在转换后输出电流电压,控制系统阀门在排气再循环时的开启;伺服泵采用冷却系统,为系统提供液压动力源;利用自适应LS-SVM原理计算柴油机废气再循环冷却控制目标边界值,在最小二乘支持向量机基础上,利用求解线性方程组进行优化,消除了控制误差;根据控制差的大小,调整控制系统的输出值;由试验结果可知,该系统开度走势与设定开度走势一致,且与设定开度误差为1开度,说明使用该系统具有良好稳态特性,有效克服了系统中时滞问题,废气再循环效果较好。     

基于人脸卡口数据的行人共现关系图谱构建

随着人脸识别技术的不断进步以及人脸卡口的大范围且密集的部署, 本文针对团伙犯罪案件侦察这一应用场景, 对人脸卡口数据进行深入挖掘, 探究其中行人间的共现关系, 获取所关注的嫌疑人的现实社交网络, 锁定团伙其余人员. 经过实验比对和论证, 本文使用Chinese Whispers聚类算法对行人节点进行识别, 通过Faiss加速邻接边的构建, 加速图的初始化步骤, 解决其聚类效率低下的问题. 在此基础上, 使用共现频次和Apriori算法中的置信度挖掘行人间的共现关系, 构建行人共现关系图谱.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

针对细微特征进行K-means聚类的电台分选识别技术

现代战场中的无线通信设备日益增多，精准获取个体信息已成为研究热点，但也是难点。针对通信电台，提出了一种分选识别技术。该技术从电台物理层特性出发，对其辐射信号的细微特征进行K-means聚类以实现分选，分选的同时提取各个个体的特征属性值，未知信号通过与特征属性值相关运算实现个体识别。该技术无需先验知识，无需训练运算，通过实验验证，其可行、高效，易于工程实现。