Birth of a norm champion: how South Africa came to support the NPT’s indefinite extension

In 1995, South Africa was in a special position. It was: a new party to the Treaty on the Non-Proliferation of Nuclear Weapons (NPT), the first country to voluntarily renounce nuclear weapons, led by a charismatic leader, and seen as a champion of disarmament principles. Yet South Africa’s new leaders were also interested in affirming their position within the Non-Aligned Movement, which was adamantly opposed to the NPT’s indefinite extension. Why, then, did South Africa decide to support the indefinite extension of the NPT in 1995? Existing scholarship has ascribed too much credit to pressure from the United States, overlooking domestic debates in South Africa and the bifurcation between professional diplomats and political elites. This article, building on new archival sources and in-depth oral-history interviews with major actors, demonstrates that South African diplomats opposed indefinite extension while South African policy elites allocated little attention to the topic until late in the game. The findings contribute to our understanding of South Africa’s norm entrepreneurship, as well as the politics of global nonproliferation.     

Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach

In this paper, we develop an iterative piecewise linear approximation approach with a novel initialization method to solve natural gas pipeline transmission problems with the nonuniform network elevation. Previous approaches, such as energy minimization methods, cannot be applied to solve problems with the nonuniform network elevation because they exclude pressure range constraints, and thus provide solutions far from optimum. We propose a new initialization model that considers pressure range constraints and improves the optimality of the solutions and the computational efficiency. Furthermore, we extend the energy minimization methods and provide the necessary conditions under which the extended methods operate in networks with the nonuniform elevation. We test the performances of the methods with previously reported pipeline networks from the literature, with the open data set GasLib, and with our industrial collaborator. The initialization approach is shown to be more efficient than the method with fixed initial breakpoints. The newly proposed initialization approach generates solutions with a higher accuracy than the extended energy minimization methods, especially in large‐size networks. The proposed method has been applied to natural gas transmission planning by the China National Petroleum Corporation and has brought a direct profit increase of 330 million U.S. dollars in 2015‐2017.     

三架固定翼无人机协同编队飞行避障策略

针对无人机编队执行空战任务过程中存在无人机之间以及无人机与障碍物发生碰撞的问题,提出单向网络连接结构的多无人机避障算法和基于人工势场的控制方法,同时应用于无人机编队避障控制。以三架无人机构成的正三角形编队作为控制体,同时以长机的运动轨迹作为期望路径,长机提供僚机飞行信息,僚机接受信息保持编队飞行。多无人机编队发现障碍物到避障完成的过程包括编队集结、松散队形、最终恢复集结正三角形编队。仿真实验结果表明,所提避障控制策略能够确保编队收敛于期望的队形和稳定飞行状态。     

复杂网络影响力极大化快速评估算法

分析复杂网络中影响力极大化问题,设计一种新的启发式算法框架。针对信息传递中节点的交互方式进行分析,给出节点在任意时刻处于信息接收态的概率。通过期望计算得到种子节点集传播影响力的近似估计,实现集群影响力快速计算,进而得到基于序列采样的影响力极大化快速评估算法。特别地,对于六个来自不同领域的真实网络上的影响力极大化问题进行了研究,仿真结果表明：该方法能够高效识别网络中具有重要传播影响力的节点集,在三种常见度量准则下的表现均明显优于三种影响力极大化问题基准算法。     

基于6LoWPAN与MQTT的无线传感网络设计

针对目前6LoWPAN无线传感网络设计与应用存在的可扩展性较差、与IPv4环境不兼容等问题,设计并实现了基于6LoWPAN与消息队列遥控传输(Message Queuing Telemetry Transport, MQTT)的无线传感网络。其中,无线传感网络节点作为MQTT客户端与MQTT服务器通信,边界路由器通过NAT64(Network Address Translation IPv6 to IPv4)实现无线传感网络节点与IPv4网络的通信。将所设计的无线传感网络应用到智能家居场景,评估了无线传感网络和边界路由器的性能,测试了系统功能的实现。结果表明,无线传感网络具有良好的连通性和稳定性,无线传感节点的数据上传与指令接收稳定可靠,边界路由器工作稳定,系统具有较好的性能。     

图像超分辨率卷积神经网络加速算法

为了实现模型的实时和嵌入式运行,提出了一种轻量级的卷积神经网络结构。通过采用较小的滤波器尺寸和引入深度可分离卷积,可大量减少模型参数,提高模型非线性表达能力;在网络末端引入子像素卷积层,直接从原始低分辨率图像学习到高分辨率图像的映射,计算成本为原来的1/k²(k为放大因子)。在Set5数据集上的实验表明,所提模型的速度较经典的图像超分辨率重建算法速度提高了25.8倍,能够在通用GPU上实时运行,峰值信噪比平均提高了0.17 dB,并且参数只有它的35%。     

基于新型非易失内存的远程零拷贝文件系统

为提升物联网与边缘计算应用中前端节点间的数据访问效率,提出了一种新型远程零拷贝文件系统。该文件系统无须借助特殊硬件,可直接基于通用网卡设备实现零拷贝的数据传输框架;充分利用新型非易失内存的随机访问特性,尽可能减少数据缓存和拷贝,提高数据访问的吞吐量。建立缓冲区池,精简并融合传统网络栈和存储栈,从而缩短文件访问路径,减少软件冗余,降低数据访问延迟。最终提供高带宽、低延迟的远程数据访问性能。测试结果表明,远程零拷贝文件系统比传统网络文件系统减少了42.26%～99.19%的读写延迟,细粒度访问下的吞吐量最高可提升1297倍,显著降低了处理器开销和缓存失效次数。     

非奇异快速终端滑模及动态面控制的轨迹跟踪制导律

针对飞行器跟踪预设轨迹的问题,提出非奇异快速终端滑模和角度约束的轨迹跟踪制导律。通过引入虚拟目标点,提出参考轨迹曲率半径的期望视线角约束条件,建立带有视线角约束并考虑自动驾驶仪动态特性的轨迹跟踪数学模型。为了保证在有限时间内跟踪预设轨迹并避免出现奇异问题,采用快速非奇异终端滑模和动态面控制方法进行制导律设计。推导出视线角误差和轨迹跟踪误差之间的数学关系,并利用Lyapunov稳定性准则证明轨迹跟踪误差最终有界任意小。与弹道成型轨迹跟踪制导律进行仿真对比,仿真结果表明所提出的制导律具有良好的跟踪性能及鲁棒性。     

基于深度森林的网络流量分类方法

随着网络应用的迅猛发展,流量分类在网络资源分配、流量调度和网络安全等诸多研究领域受到广泛关注。现有的机器学习流量分类方法对流量数据特征的选取和分布要求苛刻,导致在实际应用中的复杂流量场景下分类精确度和稳定度难以提高。为了解决样本特征属性的复杂性给分类性能带来的不利影响,引入了基于深度森林的流量分类方法。该算法通过级联森林和多粒度扫描机制,能够在样本数量规模和特征属性选取规模有限的情况下,有效地提高流量整体分类性能。通过网络流量公开数据集Moore对支持向量机、随机森林和深度森林机器学习算法进行训练和测试,结果表明基于深度森林的网络流量分类器的分类准确率能够达到96. 36%,性能优于其他机器学习模型。     

基于多通道卷积神经网络的磁性舰船目标运动参数估计

传统磁性目标运动估计效果依赖于目标的初始状态信息,为克服这一缺陷,建立磁性运动目标三分量投影模型,并据此生成磁性舰船运动目标在运动速度、航向、信噪比等参数变化情况下的10类目标的训练数据集、验证数据集以及测试数据集。设计多通道卷积神经网络,对目标的正横距离和运动速度进行估计,并比较和分析了不同的学习方式和激活函数对网络性能的影响。结果表明:Adam+tanh组合方式的估计性能要优于其他组合方式,而且对磁性目标运动参数的估计效果比较精确,此方法相较于卡尔曼滤波、粒子滤波等估计算法的优越性在于运算复杂度低以及参数估计不需要目标初始状态信息。