Energy Efficiency Optimization for Heterogeneous Cellular Networks Modeled by Matérn Hard-Core Point Process

The Poisson point process(PPP) has been widely used in wireless network modeling and performance analysis due to the independence between its nodes. Therefore, it may not be a suitable model for many of the exclusive networks between the nodes. This paper analyzes the energy efficiency(EE) and optimizes the two-tier heterogeneous cellular networks(Het Nets). Considering the mutual exclusion between macro base stations(MBSs) distribution, the deployment of MBSs is modeled by the Matérn hard-core point process(MHCPP), and the deployment of pico base stations(PBSs) is modeled by the PPP. We adopt a simple approximation method to study the signal to interference ratio(SIR) distribution in two-tier MHCPP-PPP networks and then derive the coverage probabilities, the average data rates and the energy efficiency of Het Nets. Finally, an optimization algorithm is proposed to improve the EE of Het Nets by controlling the transmit power of PBSs. The simulation results show that the EE of a system can be effectively improved by selecting the appropriate transmit power for the PBSs. In addition, two-tier MHCPP-PPP Het Nets have higher energy efficiency than two-tier PPP-PPP Het Nets.

A k-Coverage Scheduling Scheme in Wireless Sensor Network Based on Hard-Core Process in Rayleigh Fading Channel

Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-coverage scheduling problem in dense WSNs,we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling(HCCS),in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling,HCCS allows coordination between sensors with little communication overhead.Moreover,due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs,we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors(RFDA),and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition,we analyze the influence factors,i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally,through Monte Carlo simulations,it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.

基于Point Transformer方法的鱼类三维点云模型分类

为实现对不同鱼类的精准分类,研究共采集110尾真实鱼类的三维模型,对获取的3D模型进行基于预处理、旋转增强和下采样等操作后,获取了1650尾实验样本。然后基于Point Transformer网络和2个三维分类的对比网络进行数据集的分类训练和验证。结果表明,利用本实验的目标方法Point Transformer获得了比2个对比网络更好的分类结果,整体的分类准确率能够达到91.9%。同时对所使用的三维分类网络进行有效性评估,3个模型对于5种真实鱼类模型的分类是有意义的,其中Point Transformer的模型ROC曲线准确率最高,AUC面积最大,对于三维鱼类数据集的分类最为有效。研究提供了一种可以实现对鱼类三维模型进行精准分类的方法,为以后的智能化渔业资源监测提供一种新的技术手段。

Joint asymptotic distribution of exceedances point process and partial sum of stationary Gaussian sequence

Let {Xi}i=1^∞ be a standardized stationary Gaussian sequence with covariance function τ（n） =EX1Xn＋1, Sn =∑i=1^nXi,and X^-n=Sn/n.And let Nn be the point process formed by the exceedances of random level （x/√2 log n＋√2 log n-log（4π log n）/2√log n） √1-τ（n） ＋ X^-n by X1,X2,…, Xn. Under some mild conditions, Nn and Sn are asymptotically independent, and Nn converges weakly to a Poisson process on （0,1].

Reliability Analysis of Repairable Systems Using Stochastic Point Processes

In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.

The SCUSUM Estimation of Variance Change Point in Linear Process

This paper considers the estimation problem of a variance change-point in linear process.Consistency of a SCUSUM type change-point estimator is proved and its rate of convergence is established.The mean-unknown case is also considered.

Model for Failure Point Process of a Repairable System and Application

A engineering system is usually repairable, and failure process of a repairable by a failure point process. The power law model is a commonly used approach to model syst the em is often described failure point process. This paper introduces the concept and model for the failure process of repairable system. The method of parameter estimation is developed, and failure observations are fitted into a power-law model by using the least square method. Two applications of the pressent model are discussed according to the practical failure data of the central cooling system of a nuclear power plant. One application is determining the optimal overhaul time, and the other is evaluating the quality of maintenance. This paper provides references for the overhaul decision making and maintenance quality evaluation in reality.

Aggregate Point Cloud Geometric Features for Processing

As 3D acquisition technology develops and 3D sensors become increasingly affordable,large quantities of 3D point cloud data are emerging.How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved.The point cloud geometric information is hidden in disordered,unstructured points,making point cloud analysis a very challenging problem.To address this problem,we propose a novel network framework,called Tree Graph Network(TGNet),which can sample,group,and aggregate local geometric features.Specifically,we construct a Tree Graph by explicit rules,which consists of curves extending in all directions in point cloud feature space,and then aggregate the features of the graph through a cross-attention mechanism.In this way,we incorporate more point cloud geometric structure information into the representation of local geometric features,which makes our network perform better.Our model performs well on several basic point clouds processing tasks such as classification,segmentation,and normal estimation,demonstrating the effectiveness and superiority of our network.Furthermore,we provide ablation experiments and visualizations to better understand our network.

A Modified Averaging Composite Implicit Iteration Process for Common Fixed Points of a Finite Family of k-Strictly Asymptotically Pseudocontractive Mappings

The composite implicit iteration process introduced by Su and Li [J. Math. Anal. Appl. 320 (2006) 882-891] is modified. A strong convergence theorem for approximation of common fixed points of finite family of k-strictly asymptotically pseudo-contractive mappings is proved in Banach spaces using the modified iteration process.

RATE OF CONVERGENCE FOR MULTIPLE CHANGEPOINTS ESTIMATION OF MOVING-AVERAGE PROCESSES

In this paper, the least square estimator in the problem of multiple change points estimation is studied. Here, the moving-average processes of ALNQD sequence in the mean shifts are discussed. When the number of change points is known, the rate of convergence of change-points estimation is derived. The result is also true for p-mixing, φ-mixing, a-mixing, associated and negatively associated sequences under suitable conditions.

Computer Processing of the Intersection of Two Cones with Their Axes Intersecting and a Method to Get the Special Points

The analytic expression of the special points on the intersection of two cones with their axes intersecting(ITCTAI) is given. It also presents a method to construct the special points graphically according to the analytic expression of them. Finally, with computer programming language, it gives a program to generate the intersection in several different cases.

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.

Point Cloud Processing Methods for 3D Point Cloud Detection Tasks

Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.

Standby Redundancy Allocation for a Coherent System under Its Signature Point Process Representation

Willing to work in reliability theory in a general set up, under stochastically dependence conditions, we intend to characterize a not identically spare standby redundancy operation through compensator transform under a complete information level, the physic approach, that is, observing its component lifetime. We intend to optimize system reliability under standby redundancy allocation of its components, particularly, under minimal standby redundancy. To get results, we will use a coherent system representation through a signature point process.

Comparison of Results of Different GPS Post-processing Software

In order to obtain high-precision GPS control point results and provide high-precision known points for various projects,this study uses a variety of mature GPS post-processing software to process the observation data of the GPS control network of Guanyinge Reservoir,and compares the results obtained by several kinds of software.According to the test results,the reasons for the accuracy differences between different software are analyzed,and the optimal results are obtained in the analysis and comparison.The purpose of this paper is to provide useful reference for GPS software users to process data.

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

Pre-process algorithm for satellite laser ranging data based on curve recognition from points cloud

The satellite laser ranging （SLR） data quality from the COMPASS was analyzed, and the difference between curve recognition in computer vision and pre-process of SLR data finally proposed a new algorithm for SLR was discussed data based on curve recognition from points cloud is proposed. The results obtained by the new algorithm are 85 % （or even higher） consistent with that of the screen displaying method, furthermore, the new method can process SLR data automatically, which makes it possible to be used in the development of the COMPASS navigation system.

基于点云维度转换的双优化层手眼标定方法

为提高点云相机与机器人坐标转换精度,提出一种双层Levenberg-Marquardt优化(D-LM)算法标定点云视觉系统和机器人的手眼关系。根据点云成像特点提出采用同心圆标记物代替棋盘格标定板,推导出2D-3D维度转换的标记物中心提取算法。利用欧拉角变换正交化手眼矩阵旋转矩阵。此外,构建双层LM优化模型对手眼矩阵进行优化。通过自主搭建的机器人平台验证提出的手眼标定算法,并与传统Tsai-LM标定方法对比。实验结果是采用提出的D-LM方法标定出的手眼矩阵平均误差为0.89 mm,优于Tsai-LM(平均误差3.55 mm),表明D-LM方法能减少系统随机误差对标定结果影响,提升工业领域视觉机器人工作精度。

基于视觉传感的铆焊点处焊缝识别方法

针对组合件自动焊接时铆焊点对焊缝识别造成严重的干扰问题,提出一种基于视觉传感的薄板焊缝识别方法。首先利用CCD工业相机采集带有激光条带的焊缝图像,再用中值滤波平滑噪声,OTSU自适应阈值分割图像,骨架提取细化激光条纹,概率Hough变换拟合直线,采用基于二值矩阵的方法在ROI区域去除铆焊点对焊缝识别的干扰,最后利用直线拟合得到的端点坐标找到焊缝中心点。试验结果表明,该方法误差小于0.6 mm,能够快速提取焊缝特征点,满足焊接要求。

多分支加权的Transformer霍克斯过程

时序点过程作为一种异步事件序列建模的重要方法,目前已经在地震、医疗等领域得到了广泛的应用。Transformer等深度学习模型的引入使得模型的预测性能得到了突破性进步,为了解决基于Transformer的霍克斯过程模型在对事件序列建模时出现的学习偏差问题,提出了多分支加权的Transformer霍克斯过程模型(multi-branch weighted transformer Hawkes process,MWTHP)。基于多分支的思想,通过为不同角度下学习到的依赖关系赋予差异化的重要性,提高模型对事件序列的建模能力;为了应对基于Transformer的霍克斯过程模型的局部感知能力较差问题,构建了一种基于因果卷积的局部感知增强网络,改善了模型对事件序列局部上下文信息的关注能力。通过在多个合成数据集和真实世界数据集上进行实验,采用对数似然值、时间均方根误差、事件类型准确率等指标进行综合评价。实验结果验证了所提模型的性能优于其他基准模型;通过消融实验,证明了局部感知增强网络的有效性。