遥感卫星随遇接入互联网星座和在轨智能处理

低轨互联网星座是当前全球研究和发展的热点,互联网星座支持随遇接入遥感卫星和信息在轨直接处理的应用前景备受期待,但由于轨道高度不同会产生双向高动态异构星座的接入互联问题。首先,通过设定低轨卫星互联网星座在不同轨道特性、不同卫星数量情况下的随遇接入仿真场景,重点探讨了时空非连续可视性和多普勒频移问题对遥感卫星接入性能的影响;其次,基于遥感卫星随遇接入互联网星座场景的特点,分析了不同时延性在轨处理任务的流程及其星地功能分配;最后,对当前在轨智能处理算法存在的问题和未来研究重点进行阐述,为未来低轨互联网星座及遥感卫星的发展和联合组网应用提供可靠的理论支撑。     

Diluted chemical bath deposition of CdZnS as prospective buffer layer in CIGS solar cell

In this study, dilute chemical bath deposition technique has been used to deposit CdZnS thin films on soda-lime glass substrates. The structural, morphological, optoelectronic properties of as-grown films have been investigated as a function of different Zn²⁺ precursor concentrations. The X-ray diffractogram of CdS thin-film reveals a peak corresponding to (002) plane with wurtzite structure, and the peak shift has been observed with the increase of the Zn²⁺ concentration upon formation of CdZnS thin film. From morphological studies, it has been revealed that the diluted chemical bath deposition technique provides homogeneous distribution of film on the substrate even at a lower concentration of Zn²⁺. Optical characterization has shown that the transparency of the film is influenced by Zn²⁺ concentration and when the Zn²⁺ concentration is varied from 0 M to 0.0256 M, bandgap values of resulting films range from 2.42 eV to 3.90 eV while. Furthermore, electrical properties have shown that with increasing zinc concentration the resistivity of the film increases. Finally, numerical simulation validates and suggests that CdZnS buffer layer with composition of 0.0032 M Zn²⁺ concentration would be a promising candidate in CIGS solar cell.     

Modeling of Ignition and Combustion of a Coflowing Hydrogen Jet in a Supersonic Air Flow

Combustion, Explosion, and Shock Waves - Results of a numerical study of mixing, ignition, and combustion of a cold hydrogen jet propagating along the lower wall of a channel parallel to a...     

Low light enhancement algorithm for color images using intuitionistic fuzzy sets with histogram equalization

Multimedia Tools and Applications - In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light color images. A generalization of a fuzzy set known as an...     

基于滚动摩擦作用下玉米颗粒在模拟筒仓卸料中的力链分析（网络首发、推荐阅读）

针对颗粒滚动摩擦作用对筒仓中玉米颗粒的力链空间分布进行研究，通过EDEM离散元软件建立筒仓模型与仿真玉米颗粒模型进行卸粮仿真模拟，并与筒仓卸料实验作流态对比，验证模型与仿真结果的准确性。通过对模拟仓进行切片观察和数据处理，对比分析了不同摩擦情况下力链的细观参数随时间演化规律。模拟结果表明：颗粒间摩擦系数越大，卸粮完成的最终时间越长；颗粒间滚动摩擦系数越小，颗粒由整体流转变为管状流的时间越早。对于有漏斗的筒仓来说，减小颗粒间摩擦会改变整体流和管状流之间的极限，从而增加产生管状流的面积。标准滚动摩擦系数下玉米颗粒在卸料过程中会出现起拱-塌陷效应；减小滚动摩擦，玉米颗粒卸料较稳定，未出现起拱的应力突增、以及拱塌陷的应力衰减；增大颗粒间滚动摩擦不但会增加拱效应，且出现成拱高度距离漏斗口更高。     

Three dimensional reconstruction of brain tumor along with space occupying in lesions

Multimedia Tools and Applications - The three-dimensional models of brain tumors serve as diagnostic assistance for physicians, surgeons, and radiologists. The proposed system establishes an...     

小型饮料瓶盖颜色识别系统设计与实现

目的：解决当前饮料瓶盖检测系统功能单一、体积偏大、颜色识别率低的问题。方法：提出一种基于ARM处理器的小型饮料瓶盖颜色识别系统设计方案，通过仿真软件HyperLynx的LineSim工具设计四层PCB板，设置传输线参数并进行阻抗匹配仿真分析；利用编译软件Jupyter Notebook实现阈值设置、目标轮廓检测、目标框出等功能。结果：在强、弱光条件下，识别系统对红、绿、蓝3种颜色瓶盖的识别率达到92.7%。结论：与傅里叶描述子相比，该识别系统识别准确率和精度更高，同时系统也具有人脸识别功能，适用于各种智能应用场景。     

Low Temperature Characteristics of the Metal–Superconductor NIS Tunneling Thermometer

We discuss the temperature dependence of a common low temperature local thermometer, a tunnel junction between a superconductor and a normal metal (NIS junction). Towards the lowest temperatures its characteristics tend to saturate, which is usually attributed to selfheating effects. In this technical note, we reanalyze this saturation and show that the temperature independent subgap current of the junction alone explains in some cases the low temperature behavior quantitatively.

     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.