Asymptotic Properties of a Dynamic Neural System with Asymmetric Connection Weights

In this paper, based on new Lyapunov function, the asymptotic properties of the dynamic neural system with asymmetric connection weights are investigated. Since the dynamic neural system with asymmetric connection weights is more general than that with symmetric ones, the new results are significant in both theory and applications. Specially the new result can cover the asymptotic stability results of linear systems as special cases.

Stability of a Class of Neural Networks with Asymmetric Connection Weights

This paper derives some sufficient conditions for exponential stability for the equilibrium point by dividing the state variables of the system according to the characters of the neural networks. The new conditions are described by some blocks of the interconnection matrix. An example is given to demonstrate the effectiveness of the proposed theory.

Improvement of Bending Strength of Carbon Fiber/Thermoplastic Epoxy Composites <br/>—Effects of Molecular Weight of Epoxy on Carbon Fiber/Matrix Interfacial Strength and Connection of Cracks in Matrix

The bending strength of carbon?fiber/thermoplastic epoxy composites?(CF/TP-EP Compo.)?had?bi-linear increasewith increase of weight-average molecular weight (Mw) of matrix. The transition in the bending strength appeared at around 55k of Mw (“k”?means 103). SEM observation of fractured surface of CF/TP-EP Compo. showed that the fracture mode changed from interfacial failure to fiber breakage dominated failure. The smooth surface of carbon fibers appeared at lower Mw than 55k while some resin remained on the fibers indicating good adhesion between carbon fiber and matrix at higher Mw than 55k. The interfacial shear strength between carbon fiber and matrix bi-linearly increased with an increase of Mw similarly to the bending strength of the composite, measured by the micro droplet test. The dynamic loss tanδ?of the matrix measured at 2?Hz also showed a bi-linear relationship with respect to Mw having a knee point at Mw = 55k. The connection probability of two cracks introduced on?each side of specimens also confirmed that the interfacial strength between carbon fiber and matrix is the key for the mechanical performance of CF/TP-EP Compo. in bending.

Structural Robustness of Weighted Complex Networks Based on Natural Connectivity

Natural connectivity has been recently proposed to efficiently characterize the structural robustness of complex networks.The natural connectivity,interpreted as the Helmholtz free energy of a network,can be derived from the graph spectrum.We extend the concept of natural connectivity to weighted complex networks,in which the weight represents the number of multiple edges.We prove that the weighted natural connectivity changes monotonically when the weights are increased or decreased.We investigate the influence of weight on the network robustness within scenarios of weight changing and show that the weighted natural connectivity allows a precise quantitative analysis of the structural robustness for weighted complex networks.

Weighted Pseudo Almost Periodic Solutions for a Class of Hematopoiesis Model with Time-Varying Delay

In this paper, firstly, a notion of a class of generalized weighted pseudo al- most periodic function is introduced, then we investigate some basic and essential properties of the space that consists of these functions. Finally, we study the exis- tence of weighted pseudo almost periodic solutions to hematopoiesis model with time- varying delay.

Fragmental Weight-Conservation Combining Scheme for Statistical Signal Transmissions under Fast Time-Varying Channels

Statistical Signal Transmission(SST)is a technique based on orthogonal frequency-division multiplexing(OFDM)and adopts cyclostationary features,which can transmit extra information without additional bandwidth.However,the more complicated environment in 5G communication systems,especially the fast time-varying scenarios,will dramatically degrade the performance of the SST.In this paper,we propose a fragmental weight-conservation combining(FWCC)scheme for SST,to overcome its performance degradation under fast time-varying channels.The proposed FWCC scheme consists of three phases:1、incise the received OFDM stream into pieces;2、endue different weights for fine and contaminated pieces,respectively;3、combine cyclic autocorrelation function energies of all the pieces;and 4、compute the final feature and demodulate data of SST.Through these procedures above,the detection accuracy of SST will be theoretically refined under fast time-varying channels.Such an inference is confirmed through numerical results in this paper.It is demonstrated that the BER performance of proposed scheme outperforms that of the original scheme both in ideal channel estimation conditions and in imperfect channel estimation conditions.In addition,we also find the experiential optimal weight distribution strategy for the proposed FWCC scheme,which facilitates practical applications.

Robust Beamforming Under Channel Prediction Errors for Time-Varying MIMO System

The accuracy of acquired channel state information(CSI)for beamforming design is essential for achievable performance in multiple-input multiple-output(MIMO)systems.However,in a high-speed moving scene with time-division duplex(TDD)mode,the acquired CSI depending on the channel reciprocity is inevitably outdated,leading to outdated beamforming design and then performance degradation.In this paper,a robust beamforming design under channel prediction errors is proposed for a time-varying MIMO system to combat the degradation further,based on the channel prediction technique.Specifically,the statistical characteristics of historical channel prediction errors are exploited and modeled.Moreover,to deal with random error terms,deterministic equivalents are adopted to further explore potential beamforming gain through the statistical information and ultimately derive the robust design aiming at maximizing weighted sum-rate performance.Simulation results show that the proposed beamforming design can maintain outperformance during the downlink transmission time even when channels vary fast,compared with the traditional beamforming design.

6种代谢产物与特应性皮炎的因果关联:双向双样本孟德尔随机化研究

目的采用双向双样本孟德尔随机化(MR)分析来研究代谢产物与特应性皮炎(AD)之间的因果关系。方法从全基因组关联研究(GWAS)的汇总数据中提取与代谢产物相关的单核苷酸多态性(SNP)位点作为工具变量(IV)。使用R软件中的TwoSampleMR包对6种代谢物与AD之间的因果关联进行分析。所采用的主要方法包括逆方差加权法(IVW)、MR Egger和加权中位数法。使用Cochran’Q统计量进行异质性检验,MR Egger截距检验水平多效性,使用“留一法”进行敏感性分析。结果IVW分析结果显示,抗坏血酸(OR=0.861,95%CI:0.751~0.987)、花生四烯酸(OR=0.363,95%CI:0.193~0.683)、可的松(OR=0.447,95%CI:0.221~0.906)与AD的发生呈负相关;尿苷(OR=3.473,95%CI:1.043~11.562)、5-羟色胺(OR=1.896,95%CI:1.007~3.571)及2-羟基戊二酸(OR=2.158,95%CI:1.186~3.924)与AD的发生呈正相关,差异均具有统计学意义。结论遗传学预测的代谢产物与AD风险增加具有因果关联,但尚无显著证据支持AD与上述6种代谢产物之间的因果关系。

DTN中适用于节点环境状态的拥塞控制管理策略

针对容迟网络中节点存储空间有限从而出现大量丢包情况的问题,本文提出了一种适用于节点环境状态的拥塞控制管理策略(congestion control management strategy suitable for the state of the node environment,NEMS):该策略由节点间位置差异相关的控制保留策略和节点自差异相关的丢包策略构成.首先根据节点剩余缓存空间的大小判断节点是处于忙碌状态(BS)还是崩溃状态(CS),当节点处于BS状态时,节点间位置差异相关的控制保留策略结合门限度和连接活跃值的概念分析是否留存新消息.节点自差异相关的丢包策略利用熵权法动态计算各个节点中不同消息属性权重,得到消息丢弃优先级.当拥塞发生,优先删除丢弃优先级大的消息.同时,引入ACK反馈机制,消除网络中已成功投递的冗余消息.仿真结果表明,与无缓存管理的路由策略相比,加入NEMS后使得消息成功投递率增加了约100.93%~200.67%,网络负载降低了约76.05%~81.42%.

面向对象高分影像归纳式图神经网络分类法

传统面向对象分类多采用遥感影像的光谱特征,忽略了影像对象之间的空间特征。本文提出了一种采用改进归纳式图神经网络的高分遥感影像面向对象分类方法,实现了光谱-空间复合节点相似度的融合系数自适应调节,以及邻域节点采样最佳数量的自动确定。首先,改进KNN图构建方法,采用标准差信息量评价法确定用于构建光谱特征和空间特征的复合节点相似度的融合系数;然后,利用反馈曲线法确定最佳的采样邻域节点数量,使用GraphSAGE节点嵌入完成特征表达;最后,依托Softmax函数预测节点类别。以GID和BDCI2017数据集为试验数据,本文的构图方法相较于改进前的构图方法在分类精度上有所提升。本文分类方法的平均Kappa系数和总体精度分别优于CART分类树算法、GCN算法、GAT算法、LANet算法、CCTNet算法和SLCNet算法0.31、0.14、0.13、0.12、0.08、0.02和42.31%、7.4%、6.73%、8.69%、6.03%、1.52%,并且在植被和建设用地提取上具有较好的稳健性。本文方法为高分遥感影像土地覆盖分类提供了有效的工具。

基于SPA的涂料企业重大危险源安全风险评价

提出了一种针对涂料企业重大危险源安全风险等级的评价模型,从固有危险因子和危险抵消因子两个方面,构建了重大危险源评价指标体系,采用组合赋权判断各级指标权重,通过集对分析法(SPA)建立联系数函数,求出各指标单项联系数和整体联系数,以此为依据判定重大危险源的安全风险等级。结果表明:此模型可有效地解决评价中存在的重大危险源定量困难的难题,评价结果既能对企业安全状况作出分析,又能对企业未来的安全趋势作出合理的预测,可以为重大危险源的安全监管和事故预防工作提供理论支持。

Composition operators on weighted Bergman spaces induced by doubling weights

Given a doubling weightωon the unit disk D,let A_(ω)^(p) be the space of all the holomorphic functions f,where∥f∥A_(ω)^(p):=(∫_(D)|f(z)|_(p)ω(z)dA(z))^(1/p)<∞.We completely characterize the topological connectedness of the set of composition operators on A_(ω)^(p).As an application,we construct an interesting example which reveals that two composition operators on A_(α)^(p) in the same path component may fail to have a compact difference and give a negative answer to the Shapiro-Sundberg question in the(standard)weighted Bergman space.In addition,we completely describe the central compactness of any finite linear combinations of composition operators on A_(ω)^(p) in three terms:a Julia-Carathéodory-type function-theoretic characterization,a power-type characterization,and a Carleson-type measure-theoretic characterization.

耦合耕地综合质量和空间连通性的基本农田划定研究

保护集中连片的优质耕地对于保障国家粮食安全具有重要意义。本文以江西省兴国县为例,从耕地的自然质量、立地条件、生态条件3个层面系统构建耕地综合质量评价指标体系;基于TOPSIS(Technique for order preference by similarity to an ideal solution)综合评价法对耕地综合质量进行评价,引入耕地连片度、耕地空间连通格局分析了耕地空间集聚特征,综合耕地质量及其连通特征划定永久基本农田。结果表明:从耕地综合质量来看,兴国县耕地质量由高到低划分为4个质量等级,面积分别为6 204.95、16 031.72、19 321.79、3 573.76 hm^(2),占总耕地面积的13.75%、35.52%、42.81%、7.92%。总体来看,兴国县中等质量耕地居多,占比为78.33%。从耕地连通性来看,兴国县耕地连片程度由高到低划分为5个等级,其中一级~五级连片耕地面积分别为24 731.44、6 199.73、3 131.54、7 397.71、3 671.80 hm^(2),分别占耕地总面积的54.80%、13.73%、6.94%、16.39%、8.14%,耕地存在不同程度破碎化。将耕地质量三等以上、连片程度四级以上耕地划入基本农田,面积为37 029.62 hm^(2),占耕地总面积的82.05%,与原有划定基本农田相比,实现了划定后永久基本农田“总体稳定、布局优化、质量有提升”的目标。

基于AHP-熵权法的鄞西平原河网水环境改善效果综合评价

随着城市化的发展,河流间原有的联系被打断,水动力条件变差,继而引发水质污染、水生态功能衰退等问题。以鄞西平原为例,提出一种基于层次分析-熵权法的水环境改善效果评估方法,在水动力、水质参数的基础上,综合考虑经济效益和感官参数,全面评估水环境改善方案的效果。量化比选研究区提升效果,最终确定方案3为研究区改善效果最优方案。研究表明,基于层次分析法和熵权法的综合评价方法相较于传统仅考虑水动力、水质或其他单一因素的评价方法,能够克服定性数据和主观赋权对评价结果的影响,更加全面地评价不同连通方案的提升效果,实现了方案综合评价与优选。

基于负荷介数的配电网电气连通性检测试验研究

在10 kV以上的高压配电网电气连通性检测中,负荷介数有较好的指标意义,并且介入性较小。通过运算高压配电网内各节点的加权介数与节点结构关键度,获得各节点的负荷介数,依据各节点负荷介数辨识出配电网内的关键节点;通过对配电网网络拓扑图的描述数据结构实施更改,设计针对拓扑图的连通性算法,采用此算法检测负荷介数,辨识出高压配电网内关键节点的电气连通性。试验研究结果表明,该方法可辨识出高压配电网内关键节点,且辨识结果准确可靠,能够针对辨识出的关键节点实施连通性检测,且具有较高的检测速度与精度,检测性能优越。

国外城市建成环境与共享单车研究评述与展望

文章对国外城市建成环境与共享单车的研究主题、研究方法、研究趋势展开了综述。首先阐述了交通路网、社会经济因素、土地利用、绿化空间四类建成环境与共享单车的联系;其次,对比了传统与新兴的研究方法,并分析各类研究方法的适用性以及不足;最后,总结了国外共享单车的研究现状,并对未来的研究重点进行了探究与展望。

变权-混合决策评估的复合功能并网逆变器多目标协同优化控制方法

复合功能并网逆变器(multi-functional grid-connected inverter,MFGCI)在完成功率输出的同时,具备解决配电网中多种电能质量问题的能力,但该能力往往受其可用于电能质量治理的补偿容量的限制。以MFGCI的控制结构为基础,给出了无锁相环补偿指令电流及并网跟踪电流指令,提出了基于变权-混合决策评估的多目标协同优化方法,以更好适用于因新能源不确定性及非线性负荷接入导致的电能质量指标波动问题。构建了以电能质量补偿效果最佳和所需补偿容量最小的多目标函数,采用基于多目标人工蜂鸟算法(multi-objective artificial hummingbird algorithm,MOAHA)更新机制的优化算法,求解补偿各电能质量问题的最优容量分配系数,并通过多种场景下仿真,验证了所提方法的正确性和有效性。

非正则赋权有向图A_(α)谱半径的上界

Let D be a weighted digraph with n vertices in which each arc has been assigned a positive number.Let A(D)be the adjacency matrix of D and W(D)=diag(w_(1)^(+),w_(2)^(+),...,w_(n)^(+)).In this paper,we study the matrix A_(α)(D),which is defined as Aα(D)=αW(D)+(1−α)A(D),0≤α≤1.The spectral radius of A_(α)(D)is called the Aαspectral radius of D,denoted byλα(D).We obtain some upper bounds on the Aαspectral radius of strongly connected irregular weighted digraphs.

改进YOLOV7的跌倒人员检测

随着人口老龄化的到来,老年人在跌倒后能否及时被发现并得到救治显得越来越重要。采用YOLOV7可以通过图像识别老年人跌倒,为提高原始YOLOV7的检测精度和速度,本研究对YOLOV7进行了一系列改进,并提出了一种新型YOLOV7结构——YOLOV7-CMJ。首先对收集到的图片进行处理,对部分图片进行了旋转、亮度等预处理,并对其进行标定以获取样本数据集;其次引入CBAM注意力机制,增强了通道注意力和空间注意力,从而提升模型的准确性;最后,将YOLOV7中原有的PANet特征融合改为MJPANet,即多跳动征融合结构,并将之前的Concat采用加权的方式进行替换,从而得到改进YOLOV7-CMJ结构。通过与原始YOLOV7进行实验对比可知,改进后的算法精度提高了7.4%、召回率提高了7.1%、平均精度提高了7.1%,证明了改进算法的有效性,更好地满足了摔倒检测要求。

基于二维混沌映射正余弦算法的智能变电站虚回路自动连接技术

提出一种基于二维混沌正余弦算法的虚回路自动连接技术,首先采用Jaro-Winkler距离构建了涉及距离权重向量的虚端子匹配模型,然后在虚连接历史数据的基础上利用二维混沌正余弦算法求解最优距离权重向量,最后以蒙东某66 kV变电站为例,采用所提方法进行虚端子匹配。结果表明:相比现有技术该方法所得虚端子连接结果更准确且匹配效率更高。