Apparent power-law distributions in animal movements can arise from intraspecific interactions

Lévy flights have gained prominence for analysis of animal movement. In a Lévy flight, step-lengths are drawn from a heavy-tailed distribution such as a power law (PL), and a large number of empirical demonstrations have been published. Others, however, have suggested that animal movement is ill fit by PL distributions or contend a state-switching process better explains apparent Lévy flight movement patterns. We used a mix of direct behavioural observations and GPS tracking to understand step-length patterns in females of two related butterflies. We initially found movement in one species (Euphydryas editha taylori) was best fit by a bounded PL, evidence of a Lévy flight, while the other (Euphydryas phaeton) was best fit by an exponential distribution. Subsequent analyses introduced additional candidate models and used behavioural observations to sort steps based on intraspecific interactions (interactions were rare in E. phaeton but common in E. e. taylori). These analyses showed a mixed-exponential is favoured over the bounded PL for E. e. taylori and that when step-lengths were sorted into states based on the influence of harassing conspecific males, both states were best fit by simple exponential distributions. The direct behavioural observations allowed us to infer the underlying behavioural mechanism is a state-switching process driven by intraspecific interactions rather than a Lévy flight.     

基于RD算法的星载SAR斜视成像

本文研究了用距离一多普勒（ＲＤ）算法来实现星载 ＳＡＲ的斜视成像处理。给出了星载 ＳＡＲ斜视时的空间几何模型和回波信号模型，详细分析了地球自转和斜视产生的多普勒质心所引起的距离走动差异，及时域和频域校正对成像的影响，并研究了一种改进的ＲＤ算法进行距离走动的校正，此算法能适应大的斜视距离走动和地球自转距离走动。针对不同的距离走动校正进行了计算机仿真，理论分析和仿真结果表明：这种改进的ＲＤ算法是有效的。     

绝氧条件下β-Bi2Mo2O9晶相上丙烯氨氧化反应的Monte Carlo模拟研究

A random walk Monte Carlo （RWMC） simulation model of catalytic particle was established on the basis of the structures of bismuth molybdate catalysts and mechanisms of catalytic reactions with propylene selective oxidation and ammoxidation. The simulation results show that rationality of the RWMC model is proved on the basis of pulse experimental data. One of the most remarkable factors affecting catalytic behavior is the transfer of bulk lattice oxygen, which decides the rate of ammonia-consuming and propylene-consuming. The selectivity of main products reaches the maximum after the reduction of catalysts to a certain degree. It is inferred that catalytic performance improves greatly if the ratio of capacity for dehydrogenation from adsorbed propylene molecule on catalytically active site of molybdenum metal-imido group （Mo=NH） to that on catalytically active site of molybdenum metal-oxo group （Mo=O） becomes much higher.     

Monte Carlo simulation of radiation-induced solid state polymerization

A Monte Carlo method was used for a computer simulation of radiation-induced solid state polymerization. The propagation of polymer chains was simulated by means of self-avoiding random walks on a tetrahedral lattice. The initiation and termination of the chains were modelled by pseudorandom processes. The influence of conditions of the in-source process on the post-polymerization kinetics and on the degree of polymerization of the polymers was studied.     

基于随机游走模型的维基百科语义关系研究

运用随机游走模型提出了一种基于维基百科的语义相关度的计算方法。维基百科中包含了丰富的链接结构,这些链接结构一定程度上能够反应词条之间概念上的相关性,以内容链接和外部链接关系来计算基于维基百科的语义相关度,并在WS-353数据集上进行了实验,取得了较好的准确性。     

基于随机行走的海岛地下水流替代模型构建方法

地下水是海岛重要的淡水资源。为了解决海岛地下水管理实践中遇到的模型计算成本过高以及现有替代模型黑箱性问题,本文提出基于随机行走的海岛地下水流替代模型构建方法。通过GPU并行随机行走算法分别建立海岛的人工增储含水层、分层越流含水层、随机非均质含水层的替代模型,并与相应海岛含水层解析解或数值解进行对比,验证随机行走替代模型在不同海岛含水层模型中的适用性和可靠性,分析潮汐动态边界对海岛分层含水层的影响,最后评估行走元数量对替代模型误差及计算成本的影响。     

融合结构-属性交互二部图随机游走的社区搜索方法

属性图中的社区搜索是一种局部社区发现方法,本质是基于用户提供的查询节点返回包含查询节点且在结构内聚的同时属性与查询属性相似的个性化子图.该任务有助于用户更好地理解社区是如何形成的以及社区形成的原因.提出了一种融合结构-属性交互二部图随机游走机制,有效地支持属性图中的社区搜索.具体地,首先基于网络拓扑结构构建结构概率转移矩阵;其次探索结构与属性交互形成的二部图定义2阶段的节点-属性-节点概率转移矩阵,将其与结构概率转移矩阵有效融合得到属性图的概率转移矩阵;最后设计重启随机游走方法,基于融合结构和属性的并行电导值精准查询社区.在真实数据集和人工数据集上的实验表明了本文方法的有效性.     

基于信息传播节点集的CTDN节点分类算法

针对连续时间动态网络的节点分类问题,根据实际网络信息传播特点定义信息传播节点集,改进网络表示学习的节点序列采样策略,并设计基于信息传播节点集的连续时间动态网络节点分类算法,通过网络表示学习方法生成的节点低维向量以及OpenNE框架内的LogicRegression分类器,获得连续时间动态网络的节点分类结果。实验结果表明,与CTDNE和STWalk算法相比,该算法在实验条件相同的情况下,网络表示学习结果的二维可视化效果更优且最终的网络节点分类精度更高。     

混沌精英哈里斯鹰优化算法

针对哈里斯鹰优化（HHO）算法存在的收敛精度低、收敛速度慢、易于陷入局部最优的不足,提出了一种混沌精英哈里斯鹰优化（CEHHO）算法。首先,引入精英等级制度策略,以充分利用优势种群来增强种群多样性以及提升算法收敛速度和精度;其次,利用Tent混沌映射调整算法关键参数;然后,使用一种非线性能量因子调节策略来平衡算法的开发与探索;最后,使用高斯随机游走策略对最优个体施加扰动,并在算法停滞时,利用随机游走策略使算法有效跳出局部最优。通过对20个基准测试函数在不同维度下进行仿真实验,来评估算法的寻优能力。实验结果表明,改进算法的表现优于鲸鱼优化算法（WOA）、灰狼优化（GWO）算法、粒子群优化（PSO）算法和生物地理优化（BBO）算法,性能较原始HHO算法有明显提升,验证了改进算法的有效性。