A Layer-Stripping Method for 3D Near-Surface Velocity Model Building Using Seismic First-Arrival Times

In order to improve the efficiency of 3D near-surface velocity model building, we develop a layer-stripping method using seismic first-arrival times. The velocity model within a Common Mid-Point (CMP) ...     

基于改进灰狼算法优化SVR的航天侦察装备效能评估

定量评估航天侦察装备效能是武器装备体系建设的重要环节之一, 对装备发展和作战应用具有重要的现实意义。针对评估样本数据少、效能在多指标因素影响下变化规律非线性等条件下的效能评估问题, 提出一种基于改进灰狼(improved grey wolf optimizer, IGWO)算法优化的支持向量回归机(support vector regression, SVR)评估方法(IGWO-SVR)。引入反向学习策略及余弦非线性收敛因子改进灰狼优化算法收敛性能及全局寻优能力, 并将其应用于基于支持SVR效能评估参数的优化。基于航天侦察装备特点, 构建评估指标体系及航天侦察装备效能评估模型。最后, 通过对一定作战想定背景下航天侦察装备效能进行仿真评估, 验证了所提方法的合理性及优化模型的有效性。     

An Economic Model-Based Matching Approach Between Buyers and Sellers Through a Broker in an Open E-Marketplace

A broker in an open e-marketplace enables buyers and sellers to do business with each other. Although a broker plays an important role in e-marketplaces, theory and guidelines for matching between buyers and sellers in multi-attribute exchanges are limited. Therefore, a challenge for a broker’s responsibility is how to maximize a buyer’s total satisfaction degree as its goals under the consideration of trade-off between a buyer’s buying quantity and price paid to a seller, and other attributes. To solve this challenge, this paper proposes an economic model-based matching approach between a buyer’s requirements and a seller’s offers. The major contributions of this paper are that (i) a broker can model a seller’s price policy as per a buyer’s buying quantity through communication between a broker and a seller; (ii) due to each buyer’s different quantity demand, a broker models a buyer’s satisfaction degree as per a buyer’s buying quantity based on communication between a broker and a buyer; and (iii) to carry out a broker’s matching processes, an objective function and a set of constraints are generated to help a broker to maximize a buyer’s total satisfaction degree. Experimental results demonstrate the good performance of the proposed approach.     

基于数据场联合PRI变换与聚类的雷达信号分选

基于脉冲描述字进行雷达信号分选时,传统聚类算法需要预先人工设定聚类中心和聚类数目。针对该问题,提出一种基于数据场理论联合脉冲重复间隔(pulse repetition interval,PRI)变换与聚类的雷达信号分选新方法。首先,依据数据场理论,基于势值大小实现干扰点剔除,而后利用PRI变换算法进行PRI估计,依据PRI估计值将归一化脉冲描述字数据预分类,进而以各类数据集中心间的欧氏距离小于辐射因子为准则进行类别合并,自动得到初始聚类中心和聚类数目,最后通过改进K-Means算法完成聚类分选。仿真实验表明:所提方法能够应对存在频率捷变,重频参差、抖动、参数交叠、局部脉冲丢失的复杂信号环境,分选正确率明显提升。     

Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.     

等候区手术患者家属的心理影响因素及干预措施

目的:探讨等候区手术患者家属的心理影响因素及其干预措施.方法:通过临床护理实践及查阅相关文献进行总结分析.结果:影响因素及其干预措施包括详解病情及手术风险性;对手术环境及术中情况的告知;完善急诊手术患者家属心理干预;根据不同文化水平进行健康宣教;尽量以病情为主,设计最经济有效的治疗方案;提高医护人员从业技能及道德品质.结论:对等候区手术患者家属进行积极有效的心理干预,可很大程度上减轻患者家属的焦虑程度,缓和医患关系,一定程度上提升了医疗质量.     

ICP-MS法测定黔产枳椇果梗、枳椇子中22种金属元素

建立微波消解-电感耦合等离子体质谱(ICP-MS)法同时分析枳椇果梗、枳椇子中Be、Mg、Al、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Sr、Mo、Ag、Cd、Sn、Sb、Ba、Tl、Pb等22种元素的含量。样品经微波消解后,利用ICP-MS测定上述22种元素,通过标准曲线计算其含量。实验结果表明,22种元素在其线性范围内线性关系良好,r值0.995;检出限为0.0007～1.0713μg/L;重复性的相对标准偏差(RSD)3%;精密度的相对标准偏差(RSD)7%;回收率为81.14%～112.91%。该方法灵敏度高,重复性好,分析速度快,适用于枳椇果梗、枳椇子中22种元素的含量测定。     

数字量子模拟已经应用到两费米子体系了（英文）

In a recent work,a group of researchers led by Gui-Lu Long of Tsinghua University proposed a digital quantum simulation algorithm for the dynamics of interacting quantum systems in real space.They experimentally implemented the algorithm to simulate the dynamics of two interacting fermions using a nuclear magnetic resonance(NMR)setup[1].     

中立型分数阶微分控制系统能控性

研究一类分数阶中立型微分控制系统的能控性问题,对系统状态方程的分析,利用拉普拉斯变换通过基本控制系统的基础解给出了控制系统通解的表达式,并且通过构造格拉姆矩阵,研究了控制系统能控性的充分必要条件;最后通过举出一个格拉姆矩阵的计算举例来进行验证。     

基于改进Faster R-CNN的农田残膜识别方法

为了实现农田残膜的精准捡拾,提高残膜回收机的回收率.将改进Faster R-CNN卷积神经网络运用到农田残膜的识别检测中,提出了一种农田残膜的识别方法.以11MS-1850残膜回收机工作后遗留在农田表面的残膜为研究对象,分别在晴天、阴天不同时间段采集图像共计1648幅.通过更改图像亮度、旋转等方式扩充数据集,最终得到4950幅残膜样本图像,按照7:2:1划分为训练集(3465幅)、验证集(990幅)、测试集(495幅);采用双阈值算法替代传统的单阈值算法,降低了阈值对模型性能的影响;通过对比试验,选取具有残差网络结构的ResNet50作为主干特征提取网络,准确率可达88.84％,召回率为87.70％,总体精度为88.27％;为了使检测模型对小目标更加灵敏,根据数据集中残膜尺寸大小,在原有锚点基础上增加322和642的尺度参数,准确率、召回率、总体精度分别提升了1.29％、0.67％、0.97％,单幅检测时间为284.13 ms,基本满足了识别残膜的要求.可为残膜回收机加装补收装置提供参考,为研制人工智能残膜回收机提供理论基础.