A Mobile Localization Strategy for Wireless Sensor Network in NLOS Conditions

The problem of mobile localization for wireless sensor network has attracted considerable attention in recent years. The localization accuracy will drastically grade in non-line of sight(NLOS) conditions. In this paper, we propose a mobile localization strategy based on Kalman filter. The key technologies for the proposed method are the NLOS identification and mitigation. The proposed method does not need the prior knowledge of the NLOS error and it is independent of the physical measurement ways. Simulation results show that the proposed method owns the higher localization accuracy when compared with other methods.

Overview of Distribution Network Fault Location

According to the existing research, the fault section location and fault location of passive distribution network and active distribution network are reviewed. Among them, fault location of passive distribution network mainly introduces fault segment location based on transient state and steady state quantity and fault location based on transient quantity. The active distribution network mainly introduces the fault segment location based on the current amount and the switching capacity based on the distribution network topology. On this basis, the difficulties of fault location in the distribution network at present are analyzed, and the future development is prospected.

Meteorological applications of precipitable water vapor measurements retrieved by the national GNSS network of China

In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.

Research on Link Duration for Mobile Multihop Communication Networks

Mobile multihop communication network is an important branch of modern mobile communication system, and is an important technical support for ubiquitous communication. The random movement of the nodes makes the networking be more flexible, but the frequently changing topology will decrease the link duration between nodes significantly, which will increase the packets loss probability and affect the network communication performance. Aiming at the problem of declining link duration caused by nomadic characteristics in mobile multihop communication network, four link duration models for possible moving states are established based on different features in real networking process in this paper, which will provide reliable criterion for the optimal routing selection. Model analysis and simulation results show that the reliable route established by the proposed model will effectively extend the link duration, and can enhance the global stability of the mobile multihop information transmission, so as to provide new option to transmission reliability improvement for the mobile communication network.

Ten Reflections on 5G

5G takes the concept of service-oriented architecture to replace the priority principle of network efficiency in the Internet to meet requirements of the industrial Internet and smart cities,such as high reliability and low latency.On the other hand,in order to adapt to the uncertainty of future business,5G features the openness of services and the Internet protocols,different from the closeness of traditional telecommunication networks.Although 5G tries to have the advantages of both the Internet and telecommunication network,its realization still faces many challenges.In this paper,ten major issues concerning 5G networking and service offering are discussed.

Analysis of Negative Correlation Learning

This paper describes negative correlation learning for designing neural network ensembles. Negative correlation learning has been firstly analysed in terms of minimising mutual information on a regression task. By minimising the mutual information between variables extracted by two neural networks, they are forced to convey different information a-bout some features of their input. Based on the decision boundaries and correct response sets, negative correlation learning has been further studied on two pattern classification problems. The purpose of examining the decision boundaries and the correct response sets is not only to illustrate the learning behavior of negative correlation learning, but also to cast light on how to design more effective neural network ensembles. The experimental results showed the decision boundary of the trained neural network ensemble by negative correlation learning is almost as good as the optimum decision boundary.

基于特征相似性和特征规范化的注意力模块

近年来,注意力机制在图像分类、目标检测和语义分割等领域取得了巨大成功,但现有的注意力机制大多只能在通道或空间维度上实现特征融合,这极大限制了其在通道和空间维度上变化的灵活性,导致无法充分利用特征信息。为此,文中提出一种基于特征相似性和特征规范化的、可同时利用特征图各维度信息的卷积神经网络注意力模块FSNAM。该模块由特征相似性模块(FSM)和特征规范化模块(FNM)两部分组成,FSM利用输入特征图的通道特征信息和局部空间特征信息生成一个二维的特征相似性权重图;FNM利用输入特征图的全局空间特征信息生成一个三维的特征规范化权重图;两个模块生成的权重图融合在一起,生成一个三维的注意力权重图,以此实现通道特征信息和空间特征信息的融合。为证明FSNAM的可行性和有效性,进行了消融实验,结果表明:在图像分类任务方面,FSNAM模块对分类网络在CIFAR数据集上的性能提升明显优于其他主流注意力模块;在目标检测任务方面,使用FSNAM模块的目标检测网络对VOC数据集中的小目标和中等大小目标的检测准确率分别提高了3.9和1.2个百分点;在语义分割任务方面,使用FSNAM模块可以提高HRNet模型的性能,在SBD数据集上模型的平均像素准确率提高了0.58个百分点。

基于碳汇潜力的碳排放空间关联网络结构特征及影响因素——以长江中游城市群为例

考虑碳汇潜力的碳排放空间关联是促进城市群协同减排的重要基础,更是实现碳中和的有力抓手。以长江中游城市群为研究区,对传统引力模型进行修正,构建兼具碳汇潜力的碳排放空间关联网络,采用社会网络分析(SNA)和二次指派程序方法(QAP)探究长江中游城市群碳排放空间关联网络的时空特征与影响因素。结果表明:①研究期间长江中游城市群碳排放网络关联关系数、网络密度和网络关联度呈增长趋势,网络效率和网络等级度不断下降,且网络等级度在2010年后始终为0,表明碳排放空间关联网络日益稠密、网络通达性较强,存在多重叠加的溢出渠道,但等级结构并不森严。基于碳汇潜力的长江中游城市群碳排放空间关联网络从“双核化”向“多极化、多线程”网络形态发展,核心城市的扩散作用不断增强。此外,以抚州、宜昌、鹰潭、上饶和吉安等为代表的高碳生态承载力地区,在碳排放空间关联网络中的受益关联性大于溢出关联性。②2020年,长江中游城市群碳排放空间关联网络形成四大板块,相较于板块内部成员间的碳排放空间关联效应,板块间的碳排放空间关联效应更为明显,即板块间的“碳排放转移”效应较为普遍。净溢出板块主要分布在武汉都市圈、宜荆荆都市圈和长株潭城市群外围城市,处于网络核心圈层位置;净受益板块主要分布在环鄱阳湖城市群东部,“碳排放避难所”效应显著。经纪人板块集中在环鄱阳湖城市群西部,板块间表现出“净溢出板块→经纪人板块→净受益板块”的碳排放传递路径,呈现出明显的“梯度转移”特征。双向溢出板块主要位于长江中游城市群西部,对净溢出和净受益板块都存在碳排放的空间溢出。研究期内,净溢出板块的成员虽然有所变化但总数保持不变,经纪人板块的成员有所增加,而净受益和双向溢出板块的成员均减少,环鄱阳湖城市群的“碳排放避难所”效应有所弱化。③地理邻近关系能够促进城市间碳排放关联关系的建立,而城市间的经济集聚程度、土地利用强度和经济发展水平上的互补性,促使碳排放空间关联网络随着城市间分工与协作的加强而呈现出千里“碳缘”一线牵的特点。

Opportunistic spectrum sharing in software defined wireless network

Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.

Some Features of Neural Networks as Nonlinearly Parameterized Models of Unknown Systems Using an Online Learning Algorithm

This paper deals with deriving the properties of updated neural network model that is exploited to identify an unknown nonlinear system via the standard gradient learning algorithm. The convergence of this algorithm for online training the three-layer neural networks in stochastic environment is studied. A special case where an unknown nonlinearity can exactly be approximated by some neural network with a nonlinear activation function for its output layer is considered. To analyze the asymptotic behavior of the learning processes, the so-called Lyapunov-like approach is utilized. As the Lyapunov function, the expected value of the square of approximation error depending on network parameters is chosen. Within this approach, sufficient conditions guaranteeing the convergence of learning algorithm with probability 1 are derived. Simulation results are presented to support the theoretical analysis.

社交网络用户反馈数据的个性化推荐算法仿真

社交网络通常涉及大量的用户和内容,使得对所有用户和所有内容进行个性化推荐的计算复杂度非常高,导致推荐系统难以捕捉到用户的偏好和兴趣。因此,提出一种社交网络用户反馈数据的个性化推荐算法。通过用户时间和空间范围的相似度计算方法,结合用户之间的信任关系,准确地捕捉目标用户的个性化信息。采用全局相似度计算方法,结合用户邻居和项目邻居的相似度计算,建立全局相似度计算矩阵分解模型,采用聚类算法按用户聚类特征个性化推荐,通过构建兴趣图谱和计算用户与聚类主题之间的参与关系,计算个性化向量的相互距离和差异性指数,实现精准的个性化推荐。实验结果表明,所提方法在困惑度和平均余弦相似性指标上表现好,说明上述方法在同等的用户反馈数据个性化兴趣推荐条件下能够提供精准和与用户兴趣相似的推荐结果。

基于双层聚类信息的极光亚暴自动检测

极光亚暴与太阳风和地球磁场的耦合过程有着紧密的联系,对其发生和发展机制的研究,有助于深入地分析行星际磁场、地球磁层和地球电离层的相互作用,了解太阳风携带的大量能量在地球空间的输运过程,对地球空间环境预警具有重要的意义。Polar卫星搭载的紫外极光图像成像仪能够全天候地获取紫外极光图像,在紫外极光图像中可以完整地展示出极区极光的亮度和尺度变化,尤其是可以清晰地展示出亚暴膨胀相的极光点亮和亮斑膨胀现象。现有的极光亚暴事件检测方法通常需要人工设计特征和相关规则库,耗时耗力。本文利用紫外极光图像提出了基于双层聚类信息的亚暴事件检测方法,实现了紫外极光图像数据中的亚暴事件自动检测。同时,针对极光亚暴事件检测依赖手工设计特征,设计了子空间聚类指导的三维卷积特征自动提取网络;针对极光图像帧间存在成像角度差异,利用地磁纬度和磁地方时信息对极光序列中图像的空间位置进行校正;针对卫星成像位置变化导致的成像噪声,利用极光图像级聚类保留极光亮斑区域和剔除未成像或噪声区域。主观和客观实验结果表明,本算法提升了亚暴事件检测的查全率。

政策视角下我国档案利用服务中部门合作结构与演进

厘清档案利用服务中的部门合作结构与演进特征,有助于促进部门协同机制建设,并提升档案利用服务水平。本文以中央层级档案利用服务相关政策为研究对象,将我国档案利用服务政策演进分为政策初创阶段、政策深化阶段、政策体系化阶段与政策转型阶段,这四个阶段呈现参与政策制定的部门逐渐增多,“高位推动”转向国务院部委为主的变化。运用关联网络分析方法探讨档案利用服务中部门合作结构及其演进特征,分析发现:部门合作不断扩大及趋于集中,并形成了多元化的共同体;部门合作整体构型由“松散型”转向“中心边缘型”;部门合作局部构型则由“二元组”演变为“三元交互”。为促进跨部门政策协同,针对当前档案利用服务中部门合作规模较小、稳定性较弱,且整体连通性不强的特点,提出应充分利用全国档案查询利用服务平台,并建立档案利用服务联席会议制度的建议。

地铁线网性能分析及最小化韧性损失恢复策略

为更好地分析地铁线网性能,优化其在扰动状态下的恢复策略,采用基于复杂网络的地铁线网性能分析方法,并提出最小化韧性损失恢复策略.鉴于地铁线网复杂网络特征,采用Space L拓扑方法处理地铁线网,并运用复杂网络理论计算线网内各站点的基本参数,包括线网的度、平均路径和线网效率等.其次根据韧性理论以线网效率作为性能指标求解各站点韧性损失,采用遗传算法求解站点恢复序列.最后,以福州市为例,分析其地铁线网的复杂网络特征并进行扰动仿真,比较在多站点失效情况下的最小化韧性损失恢复策略与随机恢复策略的恢复效果.研究结果表明:在多个地铁站点受到扰动失效,采用最小化韧性损失恢复策略能够令地铁线网性能在恢复期间仍处于较优水平,恢复效果明显优于具有不确定性的随机恢复策略.

无线传感节点中频域传输信号解调与控制方法

为提高无线传感网络节点中的频域传输信号抗噪能力,优化前端镜像与噪声信号处理能力,以无线传感节点中的频域传输信号为研究对象,提出一种新的信号控制与解调方法。将无线传感信号输入设计的滤波器中,通过电容器、电阻、运算放大器相互协作完成信号滤波。引入前馈补偿通路组建两级节点信号解调线路,当输出传感信号功率超过标准,便可根据超出值,以前馈补偿的方式调节增益带宽积实现解调。在传感节点中外接一个校正电路,以校正电容调节码的方式,控制传感信号频域传输特性满足正常运行标准。仿真结果表明:在1 V的电源电压下,此滤波器中心频率为2 MHz,邻近信号抑制为55 dB,镜像信号抑制为33 dB,带内纹波为0.1 dB,通带电压增益为18 dB,工作电流为382μA。验证了所提方法具有较高的频域传输信号深度处理能力,且有助于实现无线传感网络高质量通信。

基于注意力时间卷积网络的加密流量分类

针对目前大多数加密流量分类方法忽略了流量的时序特性和所用模型的效率等问题,提出了一种基于注意力时间卷积网络(attention temporal convolutional network,ATCN)的高效分类方法。该方法首先将流量的内容信息与时序信息共同嵌入模型,增强加密流量的表征;然后利用时间卷积网络并行捕获有效特征以增加训练速度;最后引入注意力机制建立动态特征汇聚,实现模型参数的优化。实验结果表明,该方法在设定的两项分类任务上的性能都优于基准模型,其准确率分别为99.4%和99.8%,且模型参数量最多可降低至基准模型的15%,充分证明了本文方法的先进性。最后,本文在ATCN上引入了一种基于迁移学习的微调方式,为流量分类中零日流量的处理提供了一种新颖的思路。

基于柔性互联装备主动控制的配电网故障定位方法

Sen变压器可实现配电网的柔性互联,但其接入后故障电流的双向流动导致原配电网故障定位方案不再适用。针对该问题,提出一种基于Sen变压器主动控制的柔性互联配电网相间短路故障定位方法。该方法通过Sen变压器的主动调相控制调节其等效变比,利用波形相似度提取Sen变压器调相控制前、后电流波形的相位差异,并构造自相关系数比值判据,从而实现配电网故障区段的准确定位。所提方法无需电压信息,兼容分布式馈线自动化系统,对通信要求低且无需数据同步,提高了配电网故障区段定位的准确性。基于PSCAD/EMTDC仿真平台验证了所提方法的正确性和可行性。

基于能量均衡的非均匀分簇调度算法

针对无线传感器网络节点能量有限且不可充电的问题,本文提出基于能量均衡的非均匀分簇调度算法(EBNC_CHES)延长网络寿命。EBNC_CHES在麻雀搜索算法的基础上,引入时间竞争机制减少冗余信息获取和能耗传递的同时,采取K-means非均匀分簇均衡簇间网络能量消耗,引入改进的麻雀搜索在簇头选举中均衡簇内能耗。仿真结果表明:该算法与LEACH、EECHS_ISSADE和EESSTBRP相比,冗余信息降低了81%、80%、55%,能耗利用率提高了133%、50%、11.4%,寿命延长了52.8%、43.5%、12.2%。此算法能减少冗余信息,降低网络能耗、延长网络寿命。

基于光纤传感的铁路牵引网故障自动识别技术

由于现有的铁路牵引网故障识别方法在识别过程中易受到周围环境影响,故障识别准确率较低,因此,提出基于分布式光纤传感的铁路牵引网故障自动识别方法。构建3种牵引网故障自动识别规则,通过自动识别规则,使用分布式光纤传感对故障特征进行提取;使用变量分析对故障损伤数据进行处理,筛选符合传输的故障损伤数据进行传输,计算故障损伤数据,运用网络拓扑结构对故障特征信息进行传输;通过融合层次的诊断,进行数据的融合,得到诊断结果,实现基于分布式光纤传感的铁路牵引网故障自动识别。

川渝地区天然气管网特征及新建管道项目技术经济评价需求

四川盆地是中国陆上第三大含油气盆地,常规气、页岩气资源量均居全国之首。川渝地区拥有天然气资源禀赋优势,具有巨大的行业发展潜力和空间。为了加快四川盆地天然气产业的发展,对川渝地区天然气管网现状进行调研,以新建管道项目技术经济评价需求为研究对象,提出了川渝管网新建管道经济评价主要影响因素和技术经济特性。研究结果表明:(1)川渝地区天然气管网系统的历史成因有以下3点,即天然气资源分布及开发建设顺序、油气田一体化管理模式的推动及市场的辅助作用;(2)川渝管网的优势有以下4点,即开拓和培育市场、促进利用多元化和产业集群、提高供应安全保障和形成完整发达的产业链;(3)川渝管网新建管道经济评价主要影响因素有以下2点,即蛛网式管网结构是塑造新建管道多元功能的关键因素,投资主体多元化是经济评价反映管道多元功能的主要推手;(4)川渝管网新建管道布局时,应综合考虑企业效益和社会效益,可通过由运输成本决定的用气企业区位论和由投资成本决定的供气点区位论两种方法进行测算。