增强型飞行数据管理单元 (EFDMU) 是一种高度可配置的航空电子单元,旨在以 ARINC 600 外形尺寸承载 FDAU、DMU、QAR 和 FOQA/FDM 功能。输入接口选项包括所有主要航空电子总线系列和所有主要模拟传感器/变送器类型(请参阅“可用接口”部分了解当前选项)。然后可以将获取的数据传送到符合 ED-112 标准的 FDR 系统,记录到可移动快速访问 CompactFlash ® 存储卡或通过网络设备传输(例如无线快速访问收发器)。
病毒是通过食物传播的常见病原体。乙型肝炎和诺沃克样病毒(Novovirus)是最重要的病毒性食物传播病原体。这些病毒具有高度感染力,可能导致广泛的爆发。疾病只需要少数几个病毒颗粒。大量的病毒颗粒通过感染者的粪便进一步传播(每克粪便最多1011个颗粒。特定的内膜细胞对于病毒复制是必需的。因此,它们不能在食物或水中繁殖。食物传播病毒相对稳定,宿主细胞外的酸性耐酸
To ensure reliable environmental perception in the realm of autonomous driving, precise and robust multi- object tracking proves imperative.This study proposes an innovative approach to multi-object tracking by combining YOLOv9's sophisticated detection capabilities with an enhanced DeepSORT tracking algorithm, enriched through the integration of optical flow.In the proposed method, the YOLOv9 detector acutely identifies objects in input images, and these detected entities are subsequently transmitted to the optimized DeepSORT tracking algorithm.The principal contribution of this study lies in improving the Kalman filter measurement model within DeepSORT by incorporating robust local optical flow, thus adding a velocity dimension to the filter's update vector.这种新颖的方法可显着提高遮挡,快速运动和外观变化的追踪弹性。Evaluations on MOT17 and KITTI show substantial improvement gains of 2.42%, 2.85%, and 1.84% for HOTA, MOTA, and IDF1, respectively, on MOT17, and 1.94% in MOTA and 2.09% in HOTA on KITTI.The proposed method particularly excels in managing scenarios involving dense traffic and light variations, which are recurrent problems in dynamic urban environments.This enhanced performance positions the proposed solution as an essential component of future perception architectures for autonomous vehicles, promising safer and more efficient navigation in the complex real world.
