Modified joint probabilistic data association with classification-aided for multitarget tracking

Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.

Rupture process of the 2011 Tohoku earthquake from the joint inversion of teleseismic and GPS data

Teleseismic and GPS data were jointly inverted for the rupture process of the 2011 Tohoku earthquake. The inversion results show that it is a bilateral rupture event with an average rupture velocity less than 2.0 km/s along the fault strike direction. The source rupture process consists of three sub-events, the first oc- curred near the hypocenter and the rest two ruptured along the up-dip direction and broke the sea bed, causing a maximum slip of about 30 m. The large-scale sea bed breakage may account for the tremendous tsunami disaster which resulted in most of the death and missing in this mega earthquake.

On the Joint Development of Tourism Economy and Culture in the Era of Big Data

This paper introduces the origin and development of tourism,the cultural connotation of tourism economy,the history of cultural tourism industry,and the strategic changes of business value and economic development in the era of big data.The strategy of economic and cultural joint development under the environment of ecological tourism is explored by developing the way of ethnic culture tourism and strengthening the interactive development of culture and economy.The competitive advantage of big data is analyzed and the importance of basic content and data collection is emphasized.In addition,the present situation of tourism market is evaluated and improved by constructing reasonable economic benefit analysis model.

3D Joint inversion of gravity and gravity tensor data

The processing and interpretation of gravity and gradient data plays an important role in geophysics.The cross gradient joint inversion is usually used for achieving structure coupling of multiple geophysical models. In order to realize the coupling of gravity and gravity tensor data,the authors analyzed each component.The results show that different types of data contain different direction information,and derived the joint inversion based on cross gradient function and applied it to model data. The theoretical model results show that the cross gradient method can reduce the multi solution and significantly improve the resolution of the inversion.The method was also applied to inverse the gravity tensor data in Vinton salt dome,showing that this method can get higher resolution results than the separate linear inversion,and be closer to the real density from drilling data.

A MATLAB-Based Numerical and GUI Implementation of Cross-Gradients Joint Inversion of Gravity and Magnetic Data

The cross-gradients joint inversion technique has been applied to multiple geophysical data with a significant improvement on compatibility, but its numerical implementation for practical use is rarely discussed in the literature. We present a MATLAB-based three-dimensional cross-gradients joint inversion program with application to gravity and magnetic data. The input and output information was examined with care to create a rational, independent design of a graphical user interface (GUI) and computing kernel. For 3D visualization and data file operations, UBC-GIF tools are invoked using a series of I/O functions. Some key issues regarding the iterative joint inversion algorithm are also discussed: for instance, the forward difference of cross gradients, and matrix pseudo inverse computation. A synthetic example is employed to illustrate the whole process. Joint and separate inversions can be performed flexibly by switching the inversion mode. The resulting density model and susceptibility model demonstrate the correctness of the proposed program.

Joint Variable Selection of Mean-Covariance Model for Longitudinal Data

In this paper we reparameterize covariance structures in longitudinal data analysis through the modified Cholesky decomposition of itself. Based on this modified Cholesky decomposition, the within-subject covariance matrix is decomposed into a unit lower triangular matrix involving moving average coefficients and a diagonal matrix involving innovation variances, which are modeled as linear functions of covariates. Then, we propose a penalized maximum likelihood method for variable selection in joint mean and covariance models based on this decomposition. Under certain regularity conditions, we establish the consistency and asymptotic normality of the penalized maximum likelihood estimators of parameters in the models. Simulation studies are undertaken to assess the finite sample performance of the proposed variable selection procedure.

2022年门源M_(S)6.9地震的同震滑动分布:联合InSAR、GPS和地表位错的贝叶斯建模

2022年1月8日青海省门源M_(S)6.9地震发生于托莱山断裂东段和冷龙岭断裂西段的交汇部位,其运动学特征关系到青藏高原北缘的动力学行为,同时也是区域地震危险性评估中的基础数据.本研究针对该地震,综合InSAR和GPS观测的同震位移场,以及野外地质调查的同震位错数据,采用贝叶斯反演方法,构建同震滑动分布,断层模型采用三角网格更好地刻画断层的不规则几何形态.结果显示,本次左旋走滑型地震的主要滑动发生在冷龙岭断裂西段,深度范围约2~6 km,计算的地震矩为0.95×10^(19)N·m,对应矩震级M_(W)6.65.利用多数据的联合反演解析出,沿走向存在两个滑动集中区,东侧的最大滑动达约4.8 m.震间亏损能量和库仑应力分析表明,托莱山断裂和冷龙岭断裂仍存在未来发震潜能;该地震造成的应力变化,对长期地震空区金强河—毛毛山段落有加载作用,因此,该段未来地震危险性值得关注.

即时绩效系统在石化销售行业中的应用与研究

文章介绍了即时绩效系统的整体建设思路、系统架构、技术路线、使用情况及提升方案等,围绕石化销售企业人力资源管理效能,着力解决加油站员工绩效指标纷繁复杂及激励质量参差不齐造成的导向不清、动力不足等问题。借助信息化手段,即时绩效系统依托加油卡及便利店系统实现了交易数据的实时获取与自动计算,助力员工通过移动端或管理后台实时查看所获的联量薪酬。

Simultaneous Structure-Coupled Joint Inversion of Gravity and Magnetic Data Based on a Damped Least-Squares Technique

The structure-coupled joint inversion method of gravity and magnetic data is a powerful tool for?developing improved physical property models with high resolution and compatible features;?however, the conventional procedure is inefficient due to the truncated singular values decomposition?(SVD) process at each iteration. To improve the algorithm, a technique using damped leastsquares?is adopted to calculate the structural term of model updates, instead of the truncated SVD. This?produces structural coupled density and magnetization images with high efficiency. A so-called?coupling factor is introduced to regulate the tuning of the desired final structural similarity level.?Synthetic examples show that the joint inversion results are internally consistent and achieve?higher?resolution than separated. The acceptable runtime performance of the damped least squares?technique used in joint inversion indicates that it is more suitable for practical use than the truncated SVD method.

一种动态双模态线阵相机的联合标定方法

在实际工业应用中,线阵相机在被测物体运动速度快、拍摄视场范围广以及精度要求高的场景下比面阵相机更具优势,并且将二维图像数据与三维点云数据相结合能使信息量更丰富,能更好地还原真实场景。为提高在工业应用场景下的双模态数据的结合精度,提出一种动态双模态线阵相机的联合标定方法,该方法能实现简便快捷的2D线扫相机与3D线扫相机之间的联合标定。实验结果表明,该算法能以较小计算量实现高精度双模态双线扫相机的联合标定。

本地差分隐私下的高维数据发布方法

从众多用户收集的高维数据可用性越来越高,庞大的高维数据涉及用户个人隐私,如何在使用高维数据的同时保护用户的隐私极具挑战性。文中主要关注本地差分隐私下的高维数据发布问题。现有的解决方案首先构建概率图模型,生成输入数据的一组带噪声的低维边缘分布,然后使用它们近似输入数据集的联合分布以生成合成数据集。然而,现有方法在计算大量属性对的边缘分布构建概率图模型,以及计算概率图模型中规模较大的属性子集的联合分布时存在局限性。基于此,提出了一种本地差分隐私下的高维数据发布方法PrivHDP(High-dimensional Data Publication Under Local Differential Privacy)。首先,该方法使用随机采样响应代替传统的隐私预算分割策略扰动用户数据,提出自适应边缘分布计算方法计算成对属性的边缘分布构建Markov网。其次,使用新的方法代替互信息度量成对属性间的相关性,引入了基于高通滤波的阈值过滤技术缩减概率图构建过程的搜索空间,结合充分三角化操作和联合树算法获得一组属性子集。最后,基于联合分布分解和冗余消除,计算属性子集上的联合分布。在4个真实数据集上进行实验,结果表明,PrivHDP算法在k-way查询和SVM分类精度方面优于同类算法,验证了所提方法的可用性与高效性。

多信息智能传感器融合技术在联合作战中的应用

基于传感器融合的相关概念介绍传感器的算法、方式、层次和数据类型。从实现多信息智能传感器的关键技术角度,将常见的关键技术按照战场要素感知、通信数据传输和数据管理及应用三方面展开介绍。以美国西格玛防务公司的应用案例为分析对象,介绍多信息融合智能传感器融合技术在战场环境下的应用,同时分析多信息智能传感器的基本架构及特点、工作流程以及能力要素。对多信息智能传感器融合技术的未来发展提出几点思考。

灸法治疗颞下颌关节紊乱综合征的取穴规律

目的探讨灸法治疗颞下颌关节紊乱综合征的取穴规律。方法搜集中国知网(CNKI)、万方数据库(Wanfang data)、中国生物医学文献数据库(sinomed)、维普(Vip data)自建库时至2023年4月1日有关灸法治疗颞下颌关节紊乱综合征的临床文献,建立数据库并进行数据分析。结果灸法治疗颞下颌关节紊乱综合征以温和灸和间接灸较为常用,治疗方法是温针灸为主,其次是单纯灸法。频次较高的穴位有下关穴、阿是穴、颊车和听宫;腧穴频数分布最多的经络是足阳明胃经;高频穴位多分布在面部。关联性最强的穴组为下关-颊车;聚类分析可将腧穴分为两大类。结论灸法治疗颞下颌关节紊乱综合征以温和灸、间接灸为主,常用的治疗方法为温针灸,同时灸法取穴重视循经选穴及局部取穴,其结果可以为灸法治疗颞下颌关节紊乱综合征的临床应用提供理论依据。

基于图神经网络的关系抽取研究综述

在关系抽取任务中,通常利用构建依赖树或句法树来获得更深层和丰富的结构信息.图神经网络作为一种强大的图结构数据表示学习方法,可以更好地对这种复杂数据结构进行建模.本文介绍了基于图神经网络的关系抽取方法,旨在深入理解该领域的最新研究进展和趋势.首先简要介绍了图神经网络的分类和结构,然后详细阐述了基于图神经网络的关系抽取方法的核心技术和应用场景,包括句子级和文档级方法,以及实体关系联合抽取方法.并分析和比较了各个方法的优缺点和性能表现,并探讨了未来可能的研究方向和挑战.

基于联合神经网络的用户窃电行为识别模型

针对窃电行为识别准确率低的问题,提出了基于联合神经网络的窃电行为识别模型。首先,对获取的用户用电数据进行处理,利用格拉姆角场方法对用户用电数据进行二维化处理。然后,针对不同维度的用电数据,提出了基于联合神经网络的用户窃电行为识别模型,利用卷积神经网络(CNN)和双向长短期记忆(BiLSTM)神经网络提取一维用电数据和二维用电数据特征。通过实例分析表明,提出的联合神经网络模型对窃电行为识别准确率达到90%以上,证明所建立的评估模型为解决窃电问题提供了一种切实可行的方案。

基于地震和InSAR联合反演2018年M_(L)5.7兴文地震破裂过程

2018年12月16日发生的M_(L)5.7兴文地震很可能是由页岩气水力压裂所诱发,确定此类震级较大的诱发地震的震源破裂过程具有重要意义。文中利用近震数据和InSAR数据联合反演,获得了兴文地震的破裂过程。与单独使用地震数据或InSAR数据进行反演相比,联合反演得到的地震破裂过程可同时拟合2种类型数据,因此具有更高的时空分辨率。联合反演结果显示该地震为典型的单侧破裂,破裂方向近N向。破裂过程的持续时间为6s,能量释放主要集中在前5s,呈分段式破裂。主震破裂过程分为2个阶段:沿着断裂的走向,紧挨着震中的0~5km范围内为破裂的第1阶段(1~3s);距震中6~8km处为破裂的第2阶段(3~5s)。同震滑移主要集中在5km以浅的区域,峰值滑移约为0.27m,这可以解释为何M_(L)5.7兴文地震造成了较为严重的破坏。结合前震和余震分布可以看出,前震主要集中在滑移区的东部,说明该区域在主震发生之前就已发生破裂,意味着该区域可能存在注入的流体。余震主要分布在滑移区周围,是由主震破裂后的余滑引起的。对比单独反演结果,联合反演克服了台站分布不均匀的影响,提高了破裂分布的分辨率,所得结果更加符合真实物理过程。文中联合反演得到的破裂模型为进一步研究诱发地震机理、地震灾害评估和震后防灾减灾奠定了基础。

基于朴素贝叶斯的配电终端数据联合分层加密

为完善配电终端数据密文模板,缩短配电终端数据加密耗时,提出了基于朴素贝叶斯的配电终端数据联合分层加密算法。根据朴素贝叶斯模型建立决策树组织,联合已输出的配电终端数据求解挖掘深度指标的具体数值,完成对配电终端数据的处理。按照数据分层标准,创建密钥文本模板,再通过计算加密系数的方式,实现基于朴素贝叶斯的配电终端数据联合分层加密。对比实验结果表明,在朴素贝叶斯模型的作用下,配电终端数据输出量达到9×109MB时,所需加密时长仅为27.3 ms,利用该方法定义密文模板的完善程度明显更高,加密耗时较短。

基于源体生长思想的全张量重力梯度数据联合反演

基于源体生长思想的三维反演是一种使用系统搜索的反演方法。和正则化反演相比,该方法计算量小,运算速度快。源体生长的判断准则是其核心,影响着结果质量。本文提出了一种全张量重力梯度数据源体生长反演方法,旨在提高纵向的反演效果。首先,在判断准则中引入深度加权函数,优化对不同深度上源体生长的判断;其次,根据单分量梯度数据反演结果,调整不同类型数据的权重,建立联合反演方法;最后,利用矩阵压缩减少内存占用,提高反演计算效率。通过模型数据与文顿盐丘地区实测数据试验,证明了提出的方法能够有效地引导源体生长,对深部目标具有更高的分辨能力,适用于较复杂形态目标的反演,且具有较高的计算效率和抗噪性。

三维激光扫描仪与RTK技术在矿山综合测绘及数据集成中的联合应用

该文详细探讨三维激光扫描仪与RTK技术在矿山测绘和数据集成中的联合应用。分析当前矿山测绘的现状和挑战,以及现有的测绘方法和技术的优点及局限性。详细介绍三维激光扫描仪和RTK技术的工作原理,以及它们在矿山测绘中的应用实例和优点。探讨这2种技术的联合应用,包括其理论基础、实际案例和可能出现的问题。讨论这2种技术在数据集成中的作用,以及数据集成的实际案例和效果评估。