The key-value store can provide flexibility of data types because it does not need to specify the data types to be stored in advance and can store any types of data as the value of the key-value pair.Various types of ...The key-value store can provide flexibility of data types because it does not need to specify the data types to be stored in advance and can store any types of data as the value of the key-value pair.Various types of studies have been conducted to improve the performance of the key-value store while maintaining its flexibility.However,the research efforts storing the large-scale values such as multimedia data files(e.g.,images or videos)in the key-value store were limited.In this study,we propose a new key-value store,WR-Store++aiming to store the large-scale values stably.Specifically,it provides a new design of separating data and index by working with the built-in data structure of the Windows operating system and the file system.The utilization of the built-in data structure of the Windows operating system achieves the efficiency of the key-value store and that of the file system extends the limited space of the storage significantly.We also present chunk-based memory management and parallel processing of WR-Store++to further improve its performance in the GET operation.Through the experiments,we show that WR-Store++can store at least 32.74 times larger datasets than the existing baseline key-value store,WR-Store,which has the limitation in storing large-scale data sets.Furthermore,in terms of processing efficiency,we show that WR-Store++outperforms not only WR-Store but also the other state-ofthe-art key-value stores,LevelDB,RocksDB,and BerkeleyDB,for individual key-value operations and mixed workloads.展开更多
针对内埋舱武器性能鉴定试飞中机弹分离相对位姿测量需求,提出了一种基于高速影像的内埋舱武器分离位姿测量方法。通过加装带有弯管镜头的高速摄像机阵列,实现内埋弹舱狭小空间内弹体分离全过程高速影像数据的分段获取;采用结合机载空...针对内埋舱武器性能鉴定试飞中机弹分离相对位姿测量需求,提出了一种基于高速影像的内埋舱武器分离位姿测量方法。通过加装带有弯管镜头的高速摄像机阵列,实现内埋弹舱狭小空间内弹体分离全过程高速影像数据的分段获取;采用结合机载空间参考点不确定性的相机外参解算、基于You Only Look Once version 8(YOLOv8)的标志点智能检测、基于边缘灰度梯度正交迭代的十字标中心坐标自动提取、直线约束下的多视角非交叠影像测量等方法,实现机载高速摄像机分布快速标定、小视场成像条件下弹体表面标志点亚像素坐标自动提取、机载高速摄像机抖动下的外参动态修正以及武器分离相对位姿分段测量等功能。经地面试验验证,该方法位置解算均方根误差不大于2 mm,满足飞行试验测试精度要求。展开更多
文摘The key-value store can provide flexibility of data types because it does not need to specify the data types to be stored in advance and can store any types of data as the value of the key-value pair.Various types of studies have been conducted to improve the performance of the key-value store while maintaining its flexibility.However,the research efforts storing the large-scale values such as multimedia data files(e.g.,images or videos)in the key-value store were limited.In this study,we propose a new key-value store,WR-Store++aiming to store the large-scale values stably.Specifically,it provides a new design of separating data and index by working with the built-in data structure of the Windows operating system and the file system.The utilization of the built-in data structure of the Windows operating system achieves the efficiency of the key-value store and that of the file system extends the limited space of the storage significantly.We also present chunk-based memory management and parallel processing of WR-Store++to further improve its performance in the GET operation.Through the experiments,we show that WR-Store++can store at least 32.74 times larger datasets than the existing baseline key-value store,WR-Store,which has the limitation in storing large-scale data sets.Furthermore,in terms of processing efficiency,we show that WR-Store++outperforms not only WR-Store but also the other state-ofthe-art key-value stores,LevelDB,RocksDB,and BerkeleyDB,for individual key-value operations and mixed workloads.
文摘针对内埋舱武器性能鉴定试飞中机弹分离相对位姿测量需求,提出了一种基于高速影像的内埋舱武器分离位姿测量方法。通过加装带有弯管镜头的高速摄像机阵列,实现内埋弹舱狭小空间内弹体分离全过程高速影像数据的分段获取;采用结合机载空间参考点不确定性的相机外参解算、基于You Only Look Once version 8(YOLOv8)的标志点智能检测、基于边缘灰度梯度正交迭代的十字标中心坐标自动提取、直线约束下的多视角非交叠影像测量等方法,实现机载高速摄像机分布快速标定、小视场成像条件下弹体表面标志点亚像素坐标自动提取、机载高速摄像机抖动下的外参动态修正以及武器分离相对位姿分段测量等功能。经地面试验验证,该方法位置解算均方根误差不大于2 mm,满足飞行试验测试精度要求。
