To solve the problems such as large number of parameters and high computational complexity of the high-resolution human pose estimation networks， a lightweight Sandglass Coordinate Attention Network （SCANet） based on High-Resolution Network （HRNet） was proposed for human pose estimation. The Sandglass module and the Coordinate Attention （CoordAttention） module were first introduced； then two lightweight modules， the Sandglass Coordinate Attention bottleneck （SCAneck） module and the Sandglass Coordinate Attention basicblock （SCAblock） module， were built on this basis to obtain the long-range dependence and accurate position information of the spatial direction of the feature map while reducing the amount of model parameters and computational complexity. Experimental results show that with the same image resolution and environmental configuration， SCANet model reduces the number of parameters by 52.6% and the computational complexity by 60.6% compared with HRNet model on Common Objects in COntext （COCO） validation set； the number of parameters and computational complexity of SCANet model are reduced by 52.6% and 61.1% respectively compared with those of HRNet model on Max Planck Institute for Informatics （MPII） validation set； compared with common human pose estimation networks such as Stacked Hourglass Network （Hourglass）， Cascaded Pyramid Network （CPN） and SimpleBaseline， SCANet model can still achieve high-precision prediction of key points of the human body with fewer parameters and lower computational complexity.

为了克服传统密度估计方法受限于算法配置工作量高、高等级密度样本数量有限等因素无法大规模应用的缺点,提出一种基于监控视频的全景密度估计方法。首先,通过自动构建场景的权重图消除成像过程中射影畸变造成的影响,该过程针对不同的场景自动鲁棒地学习出对应的权值图,从而有效降低算法配置工作量;其次,利用仿真模拟方法通过低密度等级样本构建大量高密度等级样本;最后,提取训练样本的面积、周长等特征用于训练支持向量回归机(SVR)来预测每个场景的密度等级。在测试过程中,还通过二维图像与全景地理信息系统(GIS)地图的映射,实时展示全景密度分布情况。在北京北站广场地区的深度应用结果表明,所提全景密度估计方法可以准确、快速、有效地估计复杂场景中人群密度动态变化。

In view of maintenance difficulties and high cost in large-scale development of Wireless Local Access Network (WLAN), the Control and Provisioning of Wireless Access Points (CAPWAP) protocol that applied to communication between Access Controller (AC) and Wireless Terminator Point (WTP) was researched and implemented. In Linux environment, main features were realized, such as state machine management, and WTP centralized configuration. A platform of WLAN centralized management system based on local Medium Access Control (MAC) framework was built up. Wireshark capture tool, Chariot and Iperf were used to test the platform. The capture test results verify the feasibility of the framework, and the results of throughput and User Datagram Protocol (UDP) test also show that network performance is efficient and stable.

In order to solve the semantic conflict of emergency cases understanding in Case-Based Reasoning (CBR), an emergency case ontology model based on CBR was defined on the basis of the extended ABC ontology model according to the analysis of emergency cases, and the key elements of the model were described in detail, such as concepts, relations, axioms and instances. Finally, the model was validated by the analysis on the case of the nuclear crises of the first nuclear power station in Fukushima.

According to the characteristics of wireless single-hop broadcast networks, a network coding scheme based on sliding windows named NCBSW was proposed. The scheme designed a coding window which slid in a chronological order in the matrix of data packets waiting for retransmission, and the data packets used to encode were chosen from the sliding window. Meanwhile, the scheme ensured the solvability of coded packets. The simulation results show that the proposed scheme has a better performance as compared to the retransmission approach in wireless broadcasting based on network coding (NCWBR) in terms of the number of retransmission, delay, network overhead and energy consumption.

Multiprocessor scheduling algorithm is the key in the embedded real-time systems. According to the multiprocessor features, a new dynamic parallel scheduling algorithm of real-time multiprocessor, named Split-Parallel (SPara), was proposed. The algorithm solved the problem that the previous algorithms, such as Myopic, EDPF, only judge by the deadline to schedule the tasks, and it was also developed by adding the restriction of the urgency and an effective method as the task with long execution time and tight deadline. Furthermore, the multiprocessor scheduling algorithm which combined the theory of high-level coloured time Petri net was analyzed by modeling, and according to the model, an example of SPara algothrim was simulated and tested. The experimental results show that SPara performances are much better than the other algorithms like Myopic in processor utilization and scheduling success ratio.