区域求和表算法的改进

查找表技术可以使纹理过滤变得容易处理,其计算精度不再依赖于纹理的密度.目前常用的有Mipmap技术和区域求和表技术.区域求和表技术使用一张预先计算的表格,该表格的每一个值代表由纹理图像左下角和当前点所确定的长方形区域的纹理值之和,它在相同性能的情况下能提供比mipmap过滤算法更好的视觉效果.由于该算法需要更多的内存空间和内存读写次数,本文对算法进行了改进,使之更适合于硬件实现.     

多星侦察移动目标：一种基于潜在区域的求解策略

针对面向移动目标侦察的多星联合调度,提出了一种新颖的求解策略:将移动目标问题转变为区域目标问题,即在多星联合侦察的框架内利用电子侦察引导信息构建移动目标的潜在区域,基于约束满足问题(CSP)描述方法以最大覆盖率为目标建立了面向潜在区域目标的多星联合调度模型,并提出了相应的禁忌搜索算法。通过基于潜在区域的求解策略,可以优化星载遥感器的侦察方案,指导移动目标侦察任务的执行。     

基于图像建模的多视图模型合并

通过基于单幅图像的建模方法或者基于立体像对的建模方法,可以重建图像序列中每一幅图像或者立体图像对对应的模型。但所得的是局部模型,并非物体的完整模型。针对这一问题,提出了一种基于序列图像建模的多视图模型合并方法。基于已重建出的同一物体不同角度的三角形网格模型,在统一坐标系下,对相邻角度下的三角形网格模型求取其重合区域,记录刚好包围重合区域的原始网格区域,对该区域重新进行网格划分,最后得到物体完整的三角网格模型。实验结果表明,该方法是可行的、有效的。     

Collaborative writing in multiple discourse contexts

Research in computer-supported writing has traditionally compared electronic communication with oral, face-to-face communication to identify the benefits and weaknesses of each, as if they entailed dichotomous choices. In this article, we challenge that view and argue instead that any form of communication and its educational usefulness is shaped by the situation in which it is used, the backgrounds and goals of the participants, the institutional and technological setup, and the intended purpose of the medium. Three modes of communication in one graduate course are examined — oral discussion, synchronous written discussion on a local area network, and asynchronous written postings on an email list set up for the class. It was found that patterns of participation, topic introduction, and topic development differed across the three communication modes, but that the three were interwoven with each other and embedded within the larger classroom context and forms of knowledge creation in the class. Thus, rather than examining different communication media separately, researchers interested in understanding computer-supported collaborative writing need to look at how different media are used to create a meta-medium, which is established by the discourse community involved.     

Study on Recognition Method of Similar Weather Scenes in Terminal Area

Weather is a key factor affecting the control of air traffic. Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air traffic flow management. Current researches mostly use traditional machine learning methods to extract features of weather scenes, and clustering algorithms to divide similar scenes. Inspired by the excellent performance of deep learning in image recognition, this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering (IDCEC), which uses the combination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image, retaining useful information to the greatest extent, and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area. Finally, terminal area of Guangzhou Airport is selected as the research object, the method proposed in this article is used to classify historical weather data in similar scenes, and the performance is compared with other state-of-the-art methods. The experimental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather; at the same time, compared with the actual flight volume in the Guangzhou terminal area, IDCEC's recognition results of similar weather scenes are consistent with the recognition of experts in the field.     

基于计算机视觉的高速路面状态检测方法

路面状态检测技术是辅助高速公路监管部门及时发现结冰、积雪等不良路况的重要手段。针对传统基于硬件设备的路面状态检测技术存在成本较高、检测范围受局限等问题,提出了一种基于计算机视觉的高速路面状态检测方法。该方法首先将融合了空间注意力机制和通道注意力机制的Attention模块与具有高分割精度的U-Net网络相结合,对路面区域图像进行分割提取;之后实现了一种基于循环生成对抗网络的路面阴影消除算法,对已经提取的路面图像进行阴影消除;最后基于残差结构构建了路面状态分类器,实现高准确率的路面状态检测。实验结果表明,采用该方法可以消除路面状态检测过程中高速公路两侧景物和路面阴影对状态检测带来的干扰,实现了对路面干燥、积雪、积水和结冰4类状态的准确识别。基于高速公路监控视频进行测试时,识别率可达97.9%。     

地铁站场景下的可行驶区域检测

在室内环境下的机器人视觉导航任务中,可行驶区域检测是不可或缺的一部分,这是保证自动驾驶任务实现的基础.目前较多的解决方法是对数据集中出现过的障碍物进行识别来检测可行驶区域,缺乏灵活性,因此本文提出了一种针对地铁站等室内平坦地面的可行驶区域检测方法,提高实用性.本文采用经典的MobileNetV3网络对采集到的前方图像进行分类,判断是否为地面区域.由于室内地面的地标、箭头等贴纸的影响,因此需要对非地面区域进一步判断,与常规的立体障碍物进行区分.本文利用连续帧之间的特征点匹配获得相机移动距离,并利用直线拟合计算斜率的方法达到区分立体障碍物与平面地标的目的.实验表明,本文提出的方法能较好地检测机器人前方可行驶区域,具有较高的实用价值.     

矿井作业区域环境安全评价系统的设计与实现

分析了现有煤矿安全监控系统的状况,在安全监测的基础上建立了作业区域危险程度分级判定的评价模型,设计了一个矿井作业区域环境安全评价系统,详细介绍了该系统的设计思想、系统结构原理及主要功能。该系统可对煤矿井下主要作业区域生产安全的环境参数的变化进行动态分析和综合评价,并以不同的颜色给出该作业区域的危险等级,为保证井下作业人员的环境安全提供参考依据。该评价系统可独立运行,也可作为安全监控系统的功能组件运行。     

矿井采空区无线传感器网络路由协议研究

研究和设计了一种适用于煤矿采空区的无线传感器网络路由机制。首先对LEACH协议的簇头选举机制进行了改进,在计算阀值时添加剩余能量参数,然后采用改进后的协议和多径路由机制设计了煤矿采空区无线传感器网络路由算法,最后通过NS-2仿真平台进行了实验。实验结果表明,改进后的协议与原协议相比,提高了网络中节点的能量有效性,延长了网络的生命周期。     

基于LAN的转台机动控制虚拟动态测试分析系统设计

针对卫星姿态机动控制地面物理仿真监测实验,设计了卫星姿态机动控制性能动态测试分析系统;测试系统采用码盘作为测角传感器、数字I/O接口卡、测试目标为飞行器仿真气浮单轴实验转台,Labview和Access为开发软件;运用了动态测试技术、Lab-view与SQL连接的ADO技术,设计了库结构,利用Datasocket技术实现了实验数据的网络通讯,并介绍了系统硬件设计方法和软件系统设计方法,该系统实现了角度动态数据采集、数据自动存储、数据自动分析、数据管理及数据自动打印等实验功能,分析结果包括机动范围、姿控精度、控制误差及机动响应时间等数据项,还实现了局域网内PC机在线实验观测和实验数据备份功能;经实验验证,达到预期的实验测试任务要求。