高比例风电接入下次同步振荡监测系统次同步相量监测装置多阶段优化配置方法

随着风电等新能源大规模接入,未来次同步振荡问题将更为突出,亟需建立新型次同步振荡监测系统。中国学者已针对次同步振荡监测装置——次同步相量监测装置(subsynchronous phasor measurement unit, SPMU)开展了相关研究。在此基础上,如何经济高效地制定SPMU配置方案成为了构建次同步振荡监测系统的首要问题。基于风电机组频率耦合阻抗模型提出计及评价指标之间重要程度差异、振荡工况发生概率的监测关键度评价体系;考虑到SPMU实际安装配置中常存在多阶段安装的情况,建立计及节点监测关键度的SPMU多阶段优化配置模型;最后利用整数线性规划求解多阶段优化配置方案。采用美国得克萨斯州ERCOT系统、改进的New England 39节点系统,验证了所提指标及算法的准确性和经济性。     

“互联网+政务”信息安全管理的问题与策略研究

随着信息化技术的发展,数字政府的信息化进程也随之加快。“互联网+政务”的实施,使互联网技术越来越多地被运用于政务工作中。“互联网+政务”是利用网络技术对政府部门进行行政审批的一种新的技术,它将政府的行政工作与网络技术相结合,使行政工作与服务更加智能化,从而使政府的政务更加公开化。     

Magnetic Large-Mesoporous Nanoreactors Enable Enzymatically Regulated Background-Free and Persistently Signalling Diseases Diagnosis

Diverse diseases and increasing prevalence pose a serious threat to public health. Point-of-care testing (POCT) techniques have imposed superior requirements over sensitivity, selectivity, robustness, affordability, and high-throughput. However, transient signal, complex sample pretreatment, and low signal-to-noise ratio make POCT severely limited in detection accuracy, efficiency, and sensitivity. Here, an enzyme-assisted magnetic large-mesoporous nanoreactor (FS) is constructed for achieving persistent-chemiluminescence signal output and eliminating matrix interference in disease diagnosis. The core-shell structured FS synthesized via an interface coassembly method exhibits uniform size, large and open mesopores (≈22 nm), and intrinsic magnetic separability. Such unique FS acts as efficient nanoreactor for confined cascade reactions enable efficient persistent-chemiluminescence (pCL) signal transduction and high-SNR chromogenic analysis of diverse biomarkers. The developed pCL assays facilitate high-sensitive determination of chronic disease biomarkers glucose and uric acid with detection limits (DL) of 5.4 mg L⁻¹ and 151.2 ng L⁻¹, respectively. The proposed chromogenic immunoassay enables an ultrasensitive and visual determination of alpha-fetoprotein with a DL of 1.2 ng L⁻¹, which is superior to previously published immunoassays. The feasibility of the developed methods for real-world applications are demonstrated in 159 clinical serum samples, and the determination results agree well with the clinical data. The proposed technique is expected to promote highly sensitive disease diagnosis in primary medical institutions and resource-limited areas since not relying on expensive automatic sampling and testing instruments. The good flexibility of the customizable nanoreactor makes it a powerful tool for developing various POCT techniques for rapid, sensitive, and accurate diseases diagnosis.     

Photo-Driven Hydrogen Production from Methanol and Water using Plasmonic Cu Nanoparticles Derived from Layered Double Hydroxides

Methanol steam reforming (MSR) is viewed as an important technology in the growth of a future hydrogen economy, with methanol serving as an easily transportable and storable liquid hydrogen carrier. However, the thermocatalytic MSR reaction is energy intensive as it requires high temperatures. Herein, a novel L-Cu catalyst is successfully fabricated for photo-driven MSR through reduction of CuAl layered double hydroxide (CuAl-LDH) nanosheets. L-Cu offers outstanding activity for the photothermal conversion of methanol and water to hydrogen (160.5 µmol g_cat⁻¹ s⁻¹) under ultraviolet-visible irradiation, with this rate being much higher than that achieved for L-Cu at the same temperature in the dark. Characterization studies using X-ray diffraction, X-ray photoelectron spectroscopy, X-ray absorption spectroscopy, and high-resolution transmission electron microscopy determine that L-Cu catalyst comprise Cu nanoparticles on an amorphous alumina support. Computational calculations reveale that Cu localized surface plasmon resonance effects promote the activation of H₂O, thereby underpinning the remarkable hydrogen production rates achieved during photo-driven MSR. This study introduces a novel photothermal strategy for hydrogen generation from methanol, demonstrating the enormous potential of photothermal catalysis in the chemical and energy sectors.     

Simultaneous CO2 and H2O Activation via Integrated Cu Single Atom and N Vacancy Dual-Site for Enhanced CO Photo-Production

Photocatalytic conversion of CO₂ into fuels using pure water as the proton source is of immense potential in simultaneously addressing the climate-change crisis and realizing a carbon-neutral economy. Single-atom photocatalysts with tunable local atomic configurations and unique electronic properties have exhibited outstanding catalytic performance in the past decade. However, given their single-site features they are usually only amenable to activations involving single molecules. For CO₂ photoreduction entailing complex activation and dissociation process, designing multiple active sites on a photocatalyst for both CO₂ reduction and H₂O dissociation simultaneously is still a daunting challenge. Herein, it is precisely construct Cu single-atom centers and two-coordinated N vacancies as dual active sites on CN (Cu₁/N_2CV-CN). Experimental and theoretical results show that Cu single-atom centers promote CO₂ chemisorption and activation via accumulating photogenerated electrons, and the N_2CV sites enhance the dissociation of H₂O, thereby facilitating the conversion from COO* to COOH*. Benefiting from the dual-functional sites, the Cu₁/N_2CV-CN exhibits a high selectivity (98.50%) and decent CO production rate of 11.12 µmol g⁻¹ h⁻¹. An ingenious atomic-level design provides a platform for precisely integrating the modified catalyst with the deterministic identification of the electronic property during CO₂ photoreduction process.     

BERT蒙古文词向量学习

以Word2Vec为代表的静态蒙古文词向量学习方法,将处于不同语境的多种语义词汇综合表示成一个词向量,这种上下文无关的文本表示方法对后续任务的提升非常有限。通过二次训练多语言BERT预训练模型与CRF相结合,并采用两种子词融合方式,提出一种新的蒙古文动态词向量学习方法。为验证方法的有效性,在内蒙古师范大学蒙古文硕博论文的教育领域、文学领域数据集上用不同的模型进行了同义词对比实验,并利用K-means聚类算法对蒙古文词语进行聚类分析,最后在嵌入式主题词挖掘任务中进行了验证。实验结果表明,BERT学出的词向量质量高于Word2Vec,相近词的向量在向量空间中的距离非常近,不相近词的向量较远,在主题词挖掘任务中获取的主题词有密切的关联。     

结合Transformer与非对称学习策略的图像检索

目的 图像检索是计算机视觉领域的一项基础任务,大多采用卷积神经网络和对称式学习策略,导致所需训练数据量大、模型训练时间长、监督信息利用不充分。针对上述问题,本文提出一种Transformer与非对称学习策略相结合的图像检索方法。方法 对于查询图像,使用Transformer生成图像的哈希表示,利用哈希损失学习哈希函数,使图像的哈希表示更加真实。对于待检索图像,采用非对称式学习策略,直接得到图像的哈希表示,并将哈希损失与分类损失相结合,充分利用监督信息,提高训练速度。在哈希空间通过计算汉明距离实现相似图像的快速检索。结果 在CIFAR-10和NUS-WIDE两个数据集上,将本文方法与主流的5种对称式方法和性能最优的两种非对称式方法进行比较,本文方法的mAP(mean average precision)比当前最优方法分别提升了5.06%和4.17%。结论 本文方法利用Transformer提取图像特征,并将哈希损失与分类损失相结合,在不增加训练数据量的前提下,减少了模型训练时间。所提方法性能优于当前同类方法,能够有效完成图像检索任务。     

虚拟惯量控制响应延时对控制效果的影响分析

电力电子接口电源通过虚拟惯量控制模拟同步机惯量响应,但控制过程存在响应延时。全面分析了延时对虚拟惯量控制效果的影响,发现延时并非越小越好。虚拟惯量控制可以降低频率变化率和最大频差两个指标。响应延时增大,扰动后短时间内平均频率变化率变大,但是,最大频差先下降后上升,并在某个延时取值处获得最优值。而且延时增大时调频功率峰值和能量峰值均降低,控制成本更小。虚拟惯量控制的目标不同时,对延时的要求不同。分析结论有助于更加全面地认识虚拟惯量控制的效果并指导实际应用。     

基于多CCD同步耦合的动态燃烧场三维辐射测温（特邀）

为满足燃烧场温度参量时空演化特征诊断的需求,提出了基于多CCD同步耦合的动态三维辐射测温方法。在多视线方向测量基础上,通过代数重建技术对燃烧场进行体素分割,根据Plank辐射定律采用标准黑体辐射源对光电信号的映射关系进行标定,利用比色法实现三维温度场表征。进一步在时间序列上控制多CCD相机来同步获取燃烧场不同视线方向的辐射信息,基于R、G通道内的灰度信息,对实验室蜡烛火焰与外场某型号固体火箭发动机试验器尾喷焰的瞬态燃烧场温度参量进行了测试。结果表明,在实验室内,蜡烛火焰温度分布范围为805.4~1280.8 K,使用热电偶进行时空点位验证,平均误差为3.8%,最大误差为4.36%;固体火箭发动机试验器尾喷焰最高温度为2125.7 K,经近红外测温仪验证,测试误差在8%以内。该研究能够在保证时间、空间分辨率的条件下对燃烧场的三维温度参量进行特征诊断,在航天测试领域,对固体火箭发动机的温度参量测量提供了一种有效的方法。     

Evaluation Method of Classroom Teaching Effect Under Intelligent Teaching Mode

Mobile Networks and Applications - In order to improve the accuracy and performance of classroom teaching effect evaluation, an intelligent teaching mode classroom teaching effect evaluation method...