Image sequence-based risk behavior detection of power operation inspection personnel

A novel image sequence-based risk behavior detection method to achieve high-precision risk behavior detection for power maintenance personnel is proposed in this paper. In this method, the original image sequence data is first separated from the foreground and background. Then, the free anchor frame detection method is used in the foreground image to detect the personnel and correct their direction. Finally, human posture nodes are extracted from each frame of the image sequence, which are then used to identify the abnormal behavior of the human. Simulation experiment results demonstrate that the proposed algorithm has significant advantages in terms of the accuracy of human posture node detection and risk behavior identification.     

基于BIM超高层密集布筋区埋入式型钢混凝土柱脚施工技术

以漳州市某超高层项目为例,针对超高层密集布筋区埋入式型钢柱脚与钢筋的深化设计、地脚螺栓的定位预埋、型钢柱脚支撑体系设计、节点钢筋穿插连接施工、埋入式型钢柱脚安装等方面,提出切实可行的施工方法,解决了埋入式型钢混凝土柱脚的地脚螺栓精准预埋、与底板密集钢筋穿插连接施工、悬空支撑稳定等一系列施工技术难题,既满足了设计方案的要求,又可为类似工程提供借鉴。     

基于双层修正无迹卡尔曼的水下节点定位算法* .txt

摘要：针对水下无线传感网络中运动节点定位精度低的问题，提出了一种新的基于双层修正无迹卡尔曼的水下节点定位算法(DLMUKF)。该算法利用下层无迹卡尔曼滤波算法对节点状态进行预测，根据各信标节点的测距传播时延对预测的节点状态进行修正。运用上层无迹卡尔曼滤波算法对修正后的状态进行新的预测与修正。仿真实验中，DLMUKF算法的平均定位误差约为传统多边定位算法的15%，约为基于无迹卡尔曼滤波（UKF）定位算法的16%，受节点运动时间与速度的影响最小。通过实验证明DLMUKF算法能更充分利用实际距离值，可以有效减小运动节点的定位误差。 .txt     

一种外LET柔顺半铰的动力学建模与分析

对一种外LET柔顺半铰进行建模与动力学特性分析。采用斜率不连续的绝对节点坐标法（ANCF）建立了该柔顺半铰系统动力学方程；对外力作用下半铰中心线和外轮廓的运动变形进行仿真，与实验结果对比，证明了绝对节点坐标法对柔顺半铰动力学建模的有效性；进一步分析了半铰外形尺寸变化对其变形规律的影响。     

考虑节点过载的碳排放空间关联系统级联失效模型

为提高突发事件级联失效对现实碳排放关联系统破坏程度的评估可信性，在传统复杂网络的"负载-容量"级联失效模型基础上，考虑个体成员对负载的冗余能力，提出一种过载失效概率，构建了考虑节点过载状态的级联失效模型，并基于节点特性提出了6种过载节点负载分配策略。仿真结果表明：在过载节点负载分配策略中，综合分配策略整体上较优，能够有效控制级联失效的规模，增加网络鲁棒性；在一定范围内提升过载参数有助于降低级联失效的影响，但提升到一定程度时改善效果不明显；在不同负载分配策略下，剩余系数存在一个最优值，容量可调参数存在最优区间，可以使碳排放关联网络保持较好鲁棒性的同时，花费较小的构建成本，其中紧密度分配策略对应的网络构建成本较高。     

基于联合节点行为策略的WSN覆盖控制算法

针对无线传感器网络在对移动目标节点覆盖过程中出现网络能量快速消耗问题，提出了一种基于联合节点行为策略的覆盖算法。根据网络模型建立传感器节点与目标节点从属关系，确定覆盖关联模型；利用概率理论求解邻居节点冗余覆盖度，确定最少传感器节点数量；给出了邻居节点覆盖期望值的求解方法；仿真实验表明，该算法与其他算法在网络覆盖率和网络生存周期两个性能指标上均提升了12.39%和15.01%，从而验证了算法的有效性。     

Evaluation across and within collaborative manufacturing networks: a comparison of manufacturers’ interactions and attributes

Evaluation on collaborative manufacturing network (CMN) structure characteristics has important implications for network operations such as production decision-making, product recovery, creating consensus. Several recent studies suggest that augmenting network structure with nodes’ attributes can provide a more fine-grained understanding of the network. However, there have been few studies to provide a systematic understanding of these effects in a CMN at scale. This gap is bridged using an industrial printing machinery CMN data-set collected on a web-based producing and outsourcing service platform. Novel phenomena with respect to both interaction and attribute metrics across and within the CMNs are observed. Moreover, although many studies employ either interaction or attribute data to study the relative roles of manufacturers in a CMN, relatively little is known about the relationship between these two types of data. This study explores this relationship by comparing two defined metrics (i.e. relational capability and node capability), which evaluate the manufacturers’ interactions and attributes, respectively. We examine to what extent the two metrics of manufacturers correlate with each other, and how possible dissimilarities and similarities can be explained based on the collected industrial CMN data-set. The insights thereby provide a better basis for efficient operations decision-making in CMN.     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

工业无线传感器网络攻击源定位任务分配优化算法

针对工业无线传感器网络中参与攻击源节点定位的任务分配问题,构建和求解多目标优化定位任务分配模型,任务分配模型中设定参考节点组合总能量消耗、距离平均标准偏差目标函数,以及空间约束和剩余能量约束条件;采用循环拥挤排序将非支配排序遗传算法(NSGA-Ⅱ)进行改进后加入基于稀疏度局部搜索的混合优化算法联合求解任务分配模型,将稀疏度最小的解作为稀疏解,再采用极限优化策略在稀疏解周围进行局部搜索使得解拥有更好的分布特性.Matlab仿真结果表明该改进的混合优化算法可以提高算法收敛速度以及降低算法复杂度,在较快的时间内选择出合适的参考节点组合,减少了定位误差,提高了定位精度.     

基于改进正弦余弦算法的无线传感器节点部署优化

为了提高无线传感器网络（WSN）的性能，提出了一种基于改进正弦余弦算法（ESCA）的节点部署优化方法。首先，引入双曲正弦调节因子和动态余弦波权重系数，以平衡算法的全局探索与局部开发能力；然后，提出了一种基于拉普拉斯和高斯分布的变异策略，避免算法陷入局部最优。对于基准函数的优化实验结果表明，ESCA相比引力搜索算法、鲸鱼优化算法、基本正弦余弦算法（SCA）及其改进算法具有更高的收敛精度和收敛速度。最后，将ESCA应用于WSN节点部署优化，结果表明其优化覆盖率相比改进粒子群优化算法、外推人工蜂群算法、改进灰狼优化算法和自适应混沌量子粒子群算法分别提高了1.55个百分点、7.72个百分点、2.99个百分点和7.63个百分点，用更少节点便可达到相同目标精度。