Cell structure of microcellular combustible object foamed by supercritical carbon dioxide

In order to solve the issue that the combustible objects for cased telescoped ammunition (CTA) didn't burn completely during the combustion process, the microcellular combustible objects were foamed with numerous cells in the micron order to improve the combustion performance by the supercritical carbon dioxide (SCCO₂) foaming technology. As the cell structure determined the combustion properties of microcellular combustible objects, the solubility of SCCO₂ dissolved into the combustible objects was obtained from the gravimetric method, and scanning electron microscope (SEM) was applied to characterize the cell structure under various process conditions of solubility, foaming temperature and foaming time. SEM images indicate that the cell diameter of microcellular combustible objects is in the level of 1 μm and the cell density is about 10¹¹ cell⋅cm⁻³. The microcellular combustible objects fabricated by the SCCO₂ foaming technology are smooth and uniform, and the high specific surface area of cell structure can lead to the significant combustion performance of microcellular combustible object for CTA in the future.     

消防责任事故罪构成要件探讨

消防责任事故罪包括客体、客观要件、主体、主观要件等若干构成要件,其客体为“国家的消防监督制度”,其客观要件是“经消防监督机构通知采取改正措施而拒绝执行”,其主体为特殊主体“直接责任人员”,其主观要件应限于过于轻信的过失。     

基于粗集的神经网络在目标类型识别中的研究

为克服传统的目标类型识别方法的不足,提出将粗集和神经网络紧耦合建立新的识别模型,即经过识别信息预处理、样本数据粗集方法简化、神经网络学习训练及待识信息网络识别等步骤,充分融合了粗集强大的规则提取能力和神经网络优良的分类能力。实验表明,该模型减少了识别的主观因素,简化了神经网络结构,提高了运算速度。     

UML在装备虚拟维修训练系统设计中的应用

介绍了通用装备虚拟维修训练系统的功能需求和面向对象的统一建模语言(UML),结合构造虚拟维修训练系统的软件技术,以某型雷达装备为例,将雷达模型与UML视图相结合,阐述如何用UML语言对虚拟装备进行系统建模,从而完成仿真功能。     

融合神经网络与超像素的候选区域优化算法

为解决目标检测中候选区域召回率低的问题,提出融合神经网络与超像素的目标候选区域算法。该算法利用神经网络提取更能清楚表达目标边界的特征,并使用聚类、相似性等策略,计算每个滑动窗口所含有的边缘信息量;将待测图像使用简单线性迭代聚类算法分割成若干个超像素,并利用超像素的空间位置、完整性、相邻超像素间的对比度信息,计算各个超像素的显著性得分及每个滑动窗口的显著性得分;根据每个滑动窗口的边缘信息及显著性得分筛选滑动窗口。在PASCAL VOC 2007测试集上进行对比实验,其实验结果表明:所述算法能够快速产生定位质量高的候选区域。     

Visual SLAM in dynamic environments based on object detection

A great number of visual simultaneous localization and mapping (VSLAM) systems need to assume static features in the environment. However, moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption. To cope with this challenging topic, a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed. To reduce the influence of dynamic content, we incorporate the deep-learning-based object detection method in the visual odometry, then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system. Experiment with both on the TUM and KITTI benchmark dataset, as well as in a real-world environment, the results clarify that our method can significantly reduce the tracking error or drift, enhance the robustness, accuracy and stability of the VSLAM system in dynamic scenes.     

面向对象的反舰导弹航路规划

针对反舰导弹航路规划的任务特点,提出了一种面向对象的反舰导弹航路规划方法.在全面分析了反舰导弹航路规划中可能用到的类的基础上,建立了对各种类的描述,使得不同算法和不同任务要求的航路规划可以通过对类的继承和对成员函数的重载实现.最后,在VC 平台下,对这种面向对象的反舰导弹航路规划方法进行了编程实验.     

某型舰炮火控系统建模与仿真

简要介绍了某型舰炮火控仿真系统的训练、教学和和科研功能设计方案,硬件组成和必需的软件模块.在对一批空中目标拦截的战术设定情况下,给出了作战仿真流程图,列出了我舰及目标运动状态和姿态、噪声仿真、系统解命中、射击效果在线评估等数学模型.最后指出在建立数学模型时新的跟踪机制、解命中体制和滤波外推算法是三个技术难点,而在仿真过程中必须注意分布式、可视化和时钟统一等关键技术.     

从艺术客体的选择看中国古代戏剧家表现社会生活内容的广阔性

中国古代戏剧家在戏剧人物艺术客体的选择上,同古希腊悲喜剧和印度梵剧迥然不同,表现出别具一格的建树和开拓性,初步形成了具有中国作风和中国气派的戏剧文化,并在这种戏剧文化中体现了中国古代剧作家们主体精神的独立不羁的自由品格和表现社会生活内容的无限广阔性。     

基于HLA的防区外空面导弹攻防对抗仿真

针对HLA/RTI在接口规范、对象模型模板等关键技术建立分布式仿真平台的复杂性,提出了利用数字武器开发平台进行开发的方法,构建防区外空面导弹攻防对抗系统体系结构,实现了该体系结构联邦成员划分、设计联邦/仿真对象模型表等HLA仿真关键技术,并采用面向对象建模与仿真技术建立了各联邦成员的数学模型.该仿真结果表明,各联邦成员的数学模型与底层支撑环境能够相互分离,仿真模型具有良好的交互性和互操作性,可通过添加或删除联邦成员仿真不同的复杂战场想定,并可作为验证不同算例的仿真平台.