Structural and optical properties of AIN sputtering deposited on sapphire substrates with various orientations

AIN thin films were deposited on c-,a-and r-plane sapphire substrates by the magnetron sputtering technique.The in-fluence of high-temperature thermal annealing (HTTA) on the structural,optical properties as well as surface stoichiometry were comprehensively investigated.The significant narrowing of the (0002) diffraction peak to as low as 68 arcsec of AIN after HTTA implies a reduction of tilt component inside the AIN thin films,and consequently much-reduced dislocation densities.This is also supported by the appearance of E2(high) Raman peak and better Al-N stoichiometry after HTTA.Furthermore,the in-creased absorption edge after HTTA suggests a reduction of point defects acting as the absorption centers.It is concluded that HTTA is a universal post-treatment technique in improving the crystalline quality of sputtered AIN regardless of sapphire orienta-tion.     

An SPH-based mass transfer model for simulating hydraulic characteristics and mass transfer process of dammed rivers

Engineering with Computers - Aerated flow characterized by complex mass transfer processes with multiple hydraulic properties is a common enviro-hydraulics phenomenon, which have a variety of...     

聚类分割的交互式遥感热红外图像模糊增强北大核心CSCD

交互式遥感热红外图像在边缘区域的像素呈现较强交互干扰,缺少必要区分过程,导致增强后的交互式遥感热红外图像视觉效果差、抗噪性能差、增强效率低。提出基于聚类分割的交互式遥感热红外图像模糊增强方法,采用模糊C均值聚类算法,对交互式遥感热红外图像聚类分割处理,对边缘区域特殊及弱小交互目标分割,进一步区分交互区域的干扰,缩短后期增强所用的时间。采用中值滤波方法去除交互式遥感热红外图像中存在的噪声,结合Sobel算子和二阶微分算子的拉普拉斯算子对去噪后的交互式遥感热红外图像进行锐化处理,通过图像去噪和图像锐化实现交互式遥感热红外图像的模糊增强。仿真实验可知,所提方法进行交互式遥感热红外图像模糊增强所获取的图像清晰度较高、抗噪性能较佳、增强效率较高。     

静电喷印技术在太赫兹超表面制备中的应用

近年来,太赫兹技术快速发展,基于超表面的太赫兹器件受到广泛关注,并已应用于太赫兹成像、光谱和生物传感等诸多领域。但太赫兹超表面器件的制备复杂且成本高,而静电喷印技术无需掩模版,成本低、精度高且易于在异形曲面上制作。基于静电喷印技术设计和制备了太赫兹吸波器,并利用太赫兹时域光谱系统（THz-TDS）对样品进行了性能测试,实验与仿真结果基本相符,在0.098~0.353 THz频段内吸收大于90%。此外,还设计了太赫兹线极化转换器,在0.167~0.355 THz频段内的极化转换大于95%,相对带宽约72%,并分析了所设计样品的制备工艺条件,验证了静电喷印技术对于制备太赫兹极化转换器的可行性。研究成果表明,静电喷印技术在太赫兹超表面器件的制备中具有广泛的应用前景。     

一种改进的水声正交频分复用稀疏信道时延估计算法

水声正交频分复用(OFDM)系统中,采用传统正交匹配追踪(OMP)方法估计离网格(off-grid)时延时,需要很高的过采样因子和高昂的计算开销.针对传统OMP方法估计离网格时延计算复杂度高的问题,该文借鉴多元线性拟合思想引入路径补偿的概念,提出了一种基于路径补偿的改进OMP时延估计算法,用以补偿从离网格路径向其周围网格位置泄漏的能量,并用补偿距离这一参数来解释路径补偿效果.该算法无需增加过采样因子,仅利用恰当的补偿距离即可实现较好的估计效果,且能在提高估计性能的同时降低计算复杂度.仿真分析与海试结果验证了该方法的优越性.     

Unraveling the Charge Storage and Activity-Enhancing Mechanisms of Zn-Doping Perovskite Fluorides and Engineering the Electrodes and Electrolytes for Wide-Temperature Aqueous Supercabatteries

Herein, a trimetallic Ni–Co–Zn perovskite fluoride (ABF₃) (denoted as KNCZF) electrode material is explored for advanced aqueous supercabatteries (ASCBs), with KNCZF and activated carbon–FeBiCu@reduced graphene oxides (AC–FeBiCu@rGO) as cathode and anode, respectively, which outperform aqueous supercapacitors (ASCs) and batteries (ABs) with AC and FeBiCu@rGO anodes because of the synergistic effect of pseudocapacitive (KNCZF), capacitive (AC), and faradaic (FeBiCu@rGO) responses. One of the important findings is that the KNCZF shows a typical bulk phase conversion mechanism for charge storage in the alkaline media with the transition of ABF₃ perovskite nanocrystals into amorphous metal oxides/(oxy)hydroxides nanosheets, showing the redox-active and redox-inert roles for the Ni/Co and Zn species, respectively, which can be deduced by various ex-situ techniques. Another interesting finding is that the redox-inert Zn species largely enhance the activity of Ni/Co redox-active species in the ABF₃ materials, mainly owing to the promotion of surface electroactive sites, adsorption of OH^?, and charge transfer of surface Ni/Co atoms by Zn-doping, which can be proved by ex-situ characterizations and theoretical calculations. Overall, this study reveals the structure–activity relationship and charge storage mechanisms of Zn-doping ABF₃ materials for advanced ASCBs, showing a great impact on developing advanced electrochemical energy storage.     

基于生成对抗网络的知识蒸馏数据增强

在图像分类和工业视觉检测过程中,缺陷样本量少导致神经网络分类器训练效率低及检测精度差,直接采用原始的离散标签又无法使网络分类器学习到不同类别间的相似度信息。针对上述问题,在区域丢弃算法的基础上,提出一种基于生成对抗网络的知识蒸馏数据增强算法。使用补丁对丢弃区域进行填补,减少区域丢弃产生的非信息噪声。在补丁生成网络中,保留生成对抗网络的编码器-解码器结构,利用编码器卷积层提取特征,通过解码器对特征图上采样生成补丁。在样本标签生成过程中,采用知识蒸馏算法中的教师-学生训练模式,按照交叉检验方式训练教师模型,根据教师模型生成的软标签对学生模型的训练进行指导,提高学生模型对特征的学习能力。实验结果表明,与区域丢弃算法相比,该算法在CIFAR-100、CIFAR-10数据集图像分类任务上的Top-1 Err、Top-5 Err分别降低3.1、0.8、0.5、0.6个百分点,在汽车转向器轴承数据集语义分割任务上的平均交并比和识别准确率分别提高2.8、2.3个百分点。     

基于改进多嵌入空间的实时语义数据流推理

将语义数据流处理引擎与知识图谱嵌入表示学习相结合,可以有效提高实时数据流推理查询性能,但是现有的知识表示学习模型更多关注静态知识图谱嵌入,忽略了知识图谱的动态特性,导致难以应用于实时动态语义数据流推理任务。为了使知识表示学习模型适应知识图谱的在线更新并能够应用于语义数据流引擎,建立一种基于改进多嵌入空间的动态知识图谱嵌入模型PUKALE。针对传递闭包等复杂推理场景,提出3种嵌入空间生成算法。为了在进行增量更新时更合理地选择嵌入空间,设计2种嵌入空间选择算法。基于上述算法实现PUKALE模型,并将其嵌入数据流推理引擎CSPARQL-engine中,以实现实时语义数据流推理查询。实验结果表明,与传统的CSPARQL和KALE推理相比,PUKALE模型的推理查询时间分别约降低85%和93%,其在支持动态图谱嵌入的同时能够提升实时语义数据流推理准确率。