基于深度学习的ViSAR多运动目标检测

视频合成孔径雷达(ViSAR)在地面动目标检测和感兴趣区域(ROI)的动态监测方面具有巨大的潜力。对地面运动目标的检测与跟踪一直是ViSAR的研究热点。针对现有基于深度学习的ViSAR动目标检测方法存在的依赖预训练模型,模型迁移难等问题,本文提出了一种基于深度学习与多目标跟踪(MOT)算法的ViSAR动目标阴影检测方法。该方法首先设计了一种从零开始深度学习的网络模型,实现动目标阴影的单帧检测。为了提高检测性能的鲁棒性,采用了基于卡尔曼滤波和逐帧数据关联的多目标跟踪算法跟踪动目标。实测数据处理结果表明该方法具有良好的检测性能。     

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。     

In Situ Management of Ions Migration to Control Hysteresis Effect for Planar Heterojunction Perovskite Solar Cells

As one of the most promising photovoltaic materials, the efficiency of inorganic–organic hybrid halide perovskite solar cells (PSCs) has reached 25.5% in 2020. However, the stability and hysteresis remain primary challenges before it can become a commercial photovoltaic technology. Therefore, those issues have drawn significant attention for photovoltaic applications. In this work, a study of the PSCs hysteresis improvement is presented based on a combination of first-principles simulations, scanning electron microscopy images, and time-dependent photocurrent measurements. It indicates the hysteresis led by the ion migration and accumulation is mainly localized at the two interfaces: one is between electron transport layer and active layer, and the other is between active layer and hole transport layer. Considering the massive defects at the grain boundaries (GBs), they lower the potential barriers significantly. The defect density at GBs is therefore reduced via the in situ passivation of PbI₂ crystals. The hysteresis index is decreased from 22.43% down to 1.04%, and results in an improvement in efficiency from 17.12% up to 20.10%. Following the understanding of defect-induced hysteresis, an approach to improve the hysteresis is provided, which can be integrated into the fabrication process and widely applied to enhance the performance of PSCs.     

Epitaxial growth of large-area and highly crystalline anisotropic ReSe<Subscript>2</Subscript> atomic layer

The anisotropic two-dimensional (2D) layered material rhenium disulfide (ReSe2) has attracted considerable attention because of its unusual properties and promising applications in electronic and optoelectronic devices.However,because of its low lattice symmetry and interlayer decoupling,anisotropic growth and out-of-plane growth occur easily,yielding thick flakes,dendritic structure,or flower-like structure.In this study,we demonstrated a bottom-up method for the controlled and scalable synthesis of ReSe2 by van der Waals epitaxy.To achieve controllable growth,a micro-reactor with a confined reaction space was constructed by stacking two mica substrates in the chemical vapor deposition system.Within the confined reaction space,the nucleation density and growth rate of ReSe2 were significantly reduced,favoring the large-area synthesis of ReSe2 with a uniform monolayer thickness.The morphological evolution of ReSe2 with growth temperature indicated that the anisotropic growth was suppressed at a low growth temperature (＜600 ℃).Field-effect transistors employing the grown ReSe2 exhibited p-type conduction with a current ON/OFF ratio up to 10s and a hole carrier mobility of 0.98 cm2/(V.s).Furthermore,the ReSe2 device exhibited an outstanding photoresponse to near-infrared light,with responsivity up to 8.4 and 5.1 A/W for 850-and 940-nm light,respectively.This work not only promotes the large-scale application of ReSe2 in high-performance electronic devices but also clarifies the growth mechanism of low-lattice symmetry 2D materials.     

Mo2NiB2基金属陶瓷的研究进展

在金属陶瓷领域中,三元硼化物的研究已经取得了一系列的成果,但是对Mo_2NiB_2基金属陶瓷涂层的研究还比较少。主要论述了Mo_2NiB_2晶体结构、显微组织、Mo_2NiB_2基金属陶瓷的性能、Mo_2NiB_2基金属陶瓷的合金化、Mo_2NiB_2基金属陶瓷涂层研究进展,并且对Mo_2NiB_2基金属陶瓷的研究进行了展望。     

Optimal Locality Regularized Least Squares Support Vector Machine via Alternating Optimization

The least squares support vector machine (LSSVM), like standard support vector machine (SVM) which is based on structural risk minimization, can be obtained by solving a simpler optimization problem than that in SVM. However, local structure information of data samples, especially intrinsic manifold structure, is not taken full consideration in LSSVM. To address this problem and inspired by manifold learning technique, we propose a novel iterative least squares classifier, coined optimal locality preserving least squares support vector machine (OLP-LSSVM). The idea is to combine structural risk minimization and locality preserving criterion in a unified framework to take advantage of the manifold structure of data samples to enhance LSSVM. Furthermore, inspired by the recent development of simultaneous optimization technique, adjacent graph of locality preserving criterion is optimized simultaneously to give rise to improved discriminative performance. The resulting model can be solved by alternating optimization method. The experimental results on several publicly available benchmark data sets show the feasibility and effectiveness of the proposed method.     

翻车机控制系统的设计及应用研究

在介绍翻车机卸车线组成结构的基础上,针对使用过程中靠车板出现无法同步动作、检测装置故障率高等问题,研究并设计了基于MTS磁致伸缩传感器的靠车板控制系统。对于定位车定位精度差的问题,提出了基于最小二乘法和绝对值编码器的动态定位车定位控制方法。应用大型PLC系统、SINAUT通信系统、ACS800多传动系统及总线技术等先进技术,所设计的翻车机控制系统翻车效率可达到116 s/循环。经实验表明,该系统设备工作稳定可靠。     

基于正则化技术的对支持向量机特征选择算法

对支持向量机(twin support vector machine,TWSVM)的优化思想源于基于广义特征值近似支持向量机(proxi mal SVMbased on generalized eigenvalues,GEPSVM),问题解归结为求解两个SVM型问题,因此,计算开销缩减到标准SVM的1/4.除了保留了GEPSVM优势外,在分类性能上TWSVM远优于GEPSVM,但仍需求解凸规划问题,并且,目前尚无有效的TWSVM的特征提取算法提出.首先,向TWSVM模型中引入正则项,提出了正则化TWSVM(RTWSVM).与TWSVM不同,RTWSVM保证了该问题为一个强凸规划问题.在此基础上,构造了TWSVM的特征提取算法(FRTWSVM).该分类器只需求解一个线性方程系统,无需任何凸规划软件包.在保证得到与TWSVM相当的分类性能以及较快的计算速度上,此方式还减少了输入空间的特征数.对于非线性问题,FRTWSVM可以减少核函数数目.     

Pricing and inventory management in a system with multiple competing retailers under (r, Q) policies

We consider a multi-retailer system operated on an infinite horizon, in which each retailer faces stochastic demand following a Poisson process and adopts a continuous-review (r, Q) policy for replenishing inventory to satisfy customer demand. The system involves decisions of pricing and inventory management with the goal of maximizing profit, which equals the sales revenue minus the purchase and inventory costs. Taking Cournot competition into account, models are formulated to optimize simultaneously the expected sales volumes and (r, Q) policies of all retailers. An efficient approach is proposed to calculate the approximate inventory cost. Based on this approach, solution methods for centralized and decentralized scenarios are developed. A great number of numerical computations are provided to evaluate the efficiency of the solution methods, and their performance in the two scenarios. Moreover, system performance under sequential decisions (first pricing and then inventory management) is also investigated.