针对综合模块化航空电子系统(Integrated Modular Avionics,IMA)存在周期任务和非周期任务,以及任务间依赖关系,传统方法不能准确验证其实时任务可调度性的问题,本文提出了一种基于Stopwatch时间自动机的ARINC653实时任务可调度性验证方法,利用模型检验工具UPPAAL对IMA系统进行建模仿真,并结合统计模型检验(Statistical Model Checking,SMC)与符号模型检验(Symbolic Model Checking,MC)来验证其可调度性。实验结果表明,该方法不仅快速验证了IMA系统的可调度性,而且能够准确定位不可调度任务。 相似文献
Person re-identification plays important roles in many practical applications. Due to various human poses, complex backgrounds and similarity of person clothes, person re-identification is still a challenging task. In this paper, we mainly focus on the robust and discriminative appearance feature representation and proposed a novel multi-appearance method for person re-identification. First, we proposed a deep feature fusion method and get the multi-appearance feature by combining two Convolutional Neural Networks. Then, in order to further enhance the representation of the appearance feature, the multi-part model was constructed by combining the whole body and the six body parts. Additionally, we optimized the feature extraction process by adding a pooling layer. Comprehensive and comparative experiments with the state-of-the-art methods over publicly available datasets demonstrated that the proposed method can get promising results.
