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Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures
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作者 Muhammad Qasim Khan Fazal Malik +1 位作者 Fahad Alturise Noor Rahman 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第1期123-153,共31页
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a... Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject. 展开更多
关键词 Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication
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Neural Network and GBSM Based Time-Varying and Stochastic Channel Modeling for 5G Millimeter Wave Communications 被引量:7
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作者 Xiongwen Zhao Fei Du +4 位作者 Suiyan Geng Ningyao Sun Yu Zhang Zihao Fu Guangjian Wang 《China Communications》 SCIE CSCD 2019年第6期80-90,共11页
In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN mod... In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall. 展开更多
关键词 TIME-VARYING CHANNEL NEURAL network CLUSTER CHANNEL modeling VIRTUAL array measurement 5G
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Comprehensive evaluation of 5G+smart distribution network based on combined weighting method-cloud model 被引量:5
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作者 Xiufan Ma Ying Wang +1 位作者 Zihao Liu Xiaoyu Feng 《Global Energy Interconnection》 EI CAS CSCD 2022年第6期675-691,共17页
With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distributi... With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks. 展开更多
关键词 5G+smart distribution network Comprehensive evaluation Improved FAHP Variance minimization Normal cloud model
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基于LeNet-5模型的太阳能电池板缺陷识别分类 被引量:12
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作者 吴涛 赖菲 《热力发电》 CAS 北大核心 2019年第3期120-125,共6页
太阳能电池板是光伏发电组件的核心部件,其质量的优劣直接关系安全发电和发电效率。因此,对太阳能电池板进行缺陷检测具有重要的实际价值。考虑到人工检测的低效性和高成本,本文提出利用在深度学习领域图像分类性能良好的卷积神经网络... 太阳能电池板是光伏发电组件的核心部件,其质量的优劣直接关系安全发电和发电效率。因此,对太阳能电池板进行缺陷检测具有重要的实际价值。考虑到人工检测的低效性和高成本,本文提出利用在深度学习领域图像分类性能良好的卷积神经网络对太阳能电池板图像进行自动识别分类。利用Tensorflow平台Tensorboard的可视化性能,对经典卷积神经网络Le Net-5模型进行结构改善和超参数的调整,并将改进LeNet-5模型与经典LeNet-5模型和支持向量机的分类结果互相对比,结果表明改进LeNet-5模型的分类效果最优。 展开更多
关键词 太阳能电池板 lenet-5模型 图像分类 卷积神经网络 超参数 Tensorboard
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基于改进LeNet-5模型的木材表面典型缺陷识别方法研究 被引量:5
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作者 张赛 王应彪 +1 位作者 杨谭 李明 《木材科学与技术》 北大核心 2021年第6期31-37,共7页
针对传统木材缺陷识别方法效率低、精度不高及泛化能力差等问题,对传统LeNet-5模型进行改进:通过分别增加卷积层和池化层的层数至4层,以增加网络深度;采用批量归一化算法,以解决内部协变量位移过拟合的问题;改用Leaky Relu函数作为激活... 针对传统木材缺陷识别方法效率低、精度不高及泛化能力差等问题,对传统LeNet-5模型进行改进:通过分别增加卷积层和池化层的层数至4层,以增加网络深度;采用批量归一化算法,以解决内部协变量位移过拟合的问题;改用Leaky Relu函数作为激活函数,并加入稀疏分类交叉熵作为损失函数,使用Adam作为优化器,来优化网络模型。应用改进LeNet-5模型对辐射松木材常见缺陷(结疤、裂痕)及无缺陷样本集进行识别试验,结果表明:相对于传统LeNet-5模型以及VGG19、AlexNet、ResNet-50三种经典模型,改进LeNet-5模型的训练集准确率最高为99.87%、验证集为99.43%,运算时间缩短,木材缺陷识别精度和效率提高。 展开更多
关键词 木材缺陷检测 改进lenet-5模型 深度学习 卷积神经网络
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基于LeNet-5模型的手写数字识别优化方法 被引量:11
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作者 汪雅琴 夏春蕾 戴曙光 《计算机与数字工程》 2019年第12期3177-3181,共5页
作为深度前馈人工神经网络的一种,卷积神经网络在图像识别领域得到了成功应用。其中,最经典的卷积神经网络模型就是LeNet-5模型。在MNIST字符库上运用该模型,通过优化卷积层的样本训练方式,即将原来以每批固定输入样本数量、固定迭代次... 作为深度前馈人工神经网络的一种,卷积神经网络在图像识别领域得到了成功应用。其中,最经典的卷积神经网络模型就是LeNet-5模型。在MNIST字符库上运用该模型,通过优化卷积层的样本训练方式,即将原来以每批固定输入样本数量、固定迭代次数的训练方式,优化为以每批不同输入样本数量、不同迭代次数的混合训练样本方式。优化后的训练方式能够减少预处理工作量,加快识别速度。实验结果表明:在保证样本训练时间相等的前提下,优化后的混合样本输入方式可以得到更高的识别率。 展开更多
关键词 图像识别 卷积神经网络 lenet-5模型 MNIST字符库 手写数字识别
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基于改进LeNet-5模型的手写数字识别 被引量:19
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作者 邓长银 张杰 《信息通信》 2018年第1期109-112,共4页
在卷积神经网络的基础上改进了LeNet-5模型,建立了更适合于手写数字识别的神经网络模型,并对改进后的模型及网络训练识别过程进行了详细介绍。将改进后的模型用MNIST字符数据库进行验证,分析了不同卷积层特征图数量、每批次训练数等参... 在卷积神经网络的基础上改进了LeNet-5模型,建立了更适合于手写数字识别的神经网络模型,并对改进后的模型及网络训练识别过程进行了详细介绍。将改进后的模型用MNIST字符数据库进行验证,分析了不同卷积层特征图数量、每批次训练数等参数对最终识别性能的影响,并与几种常用识别方法进行比对。通过结果可看出,改进后的新型网络结构简单,识别度高,识别速度快,具有鲁棒性好,泛化能力强等优点。说明改进后的神经网络模型对手手写数字具有很好的识别性能,能满足实际应用需求。 展开更多
关键词 深度学习 卷积神经网络 lenet-5模型 手写数字 识别性能
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A Game Theoretic Approach for Hierarchical Caching Resource Sharing in 5G Networks with Virtualization 被引量:3
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作者 Renchao Xie Jun Wu +1 位作者 Rui Wang Tao Huang 《China Communications》 SCIE CSCD 2019年第7期32-48,共17页
Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into ... Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme. 展开更多
关键词 HIERARCHICAL CACHING resource sharing GAME theory OLIGOPOLY market model 5G networkS
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Projected change in precipitation forms in the Chinese Tianshan Mountains based on the Back Propagation Neural Network Model 被引量:1
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作者 REN Rui LI Xue-mei +2 位作者 LI Zhen LI Lan-hai HUANG Yi-yu 《Journal of Mountain Science》 SCIE CSCD 2022年第3期689-703,共15页
In the context of global warming,precipitation forms are likely to transform from snowfall to rainfall with a more pronounced trend.The change in precipitation forms will inevitably affect the processes of regional ru... In the context of global warming,precipitation forms are likely to transform from snowfall to rainfall with a more pronounced trend.The change in precipitation forms will inevitably affect the processes of regional runoff generation and confluence as well as the annual distribution of runoff.Most researchers used precipitation data from the CMIP5 model directly to study future precipitation trends without distinguishing between snowfall and rainfall.CMIP5 models have been proven to have better performance in simulating temperature but poorer performance in simulating precipitation.To overcome the above limitations,this paper used a Back Propagation Neural Network(BNN)to predict the rainfall-to-precipitation ratio(RPR)in months experiencing freezing-thawing transitions(FTTs).We utilized the meteorological(air pressure,air temperature,evaporation,relative humidity,wind speed,sunshine hours,surface temperature),topographic(altitude,slope,aspect)and geographic(longitude,latitude)data from 28 meteorological stations in the Chinese Tianshan Mountains region(CTMR)from 1961 to 2018 to calculate the RPR and constructed an index system of impact factors.Based on the BNN,decision-making trial and evaluation laboratory method(BP-DEMATEL),the key factors driving the transformation of the RPR in the CTMR were identified.We found that temperature was the only key factor affecting the transformation of the RPR in the BP-DEMATEL model.Considering the relationship between temperature and the RPR,the future temperature under different representative concentration pathways(RCPs)(RCP2.6/RCP4.5/RCP8.5)provided by 21 CMIP5 models and the meteorological factors from meteorological stations were input into the BNN model to acquire the future RPR from 2011 to 2100.The results showed that under the three scenarios,the RPR in the number of months experiencing FTTs during 2011-2100 will be higher than that in the historical period(1981-2010)in the CTMR.Furthermore,in terms of spatial variation,the RPR values on the south slope will be larger than those on the north slope under the three emission scenarios.Moreover,the RPR values exhibited different variation characteristics under different emission scenarios.Under the low-emission scenario(RCP2.6),as time passed,the RPR values changed slightly at more stations.Under the mediumemission scenario(RCP4.5),the RPR increased in the whole CTMR and stabilized on the north slope by the end of this century.Under the high-emission scenario(RCP8.5),the RPR values increased significantly through the 21 st century in the whole CTMR.This study may help to provide a scientific management basis for agricultural production and hydrology. 展开更多
关键词 Global warming Tianshan Mountains region Precipitation forms CMIP5 models Back Propagation Neural network model
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基于改进LeNet-5的压印字符识别 被引量:1
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作者 汪志成 何坚强 +1 位作者 翁嘉鑫 苗荣 《计算机仿真》 北大核心 2022年第2期441-446,共6页
针对传统的图像识别算法在压印字符识别领域存在识别精度低、速度较慢的问题,提出了一种基于LeNet-5压印字符识别方法。与传统的LeNet-5不同,在文中网络各卷积层中采用小尺寸卷积核,以提取更多的特征并加快模型的训练速度;使用Inceptio... 针对传统的图像识别算法在压印字符识别领域存在识别精度低、速度较慢的问题,提出了一种基于LeNet-5压印字符识别方法。与传统的LeNet-5不同,在文中网络各卷积层中采用小尺寸卷积核,以提取更多的特征并加快模型的训练速度;使用InceptionV2卷积模块取代C5全连接层,可加深网络宽度,从而提高网络的识别精度;放弃全连接层F6,改用全局平均池化层,并且选用性能优越的Relu函数作为激活函数,以便减少训练参数,提高网络的训练速度。通过实验发现,文中模型的识别精度达到98.57%,与传统LeNet-5模型以及BP神经网络相比识别精度分别提高3%和4%,证明文中模型在压印字符的识别上拥有更大的优势。 展开更多
关键词 压印字符识别 改进模型 卷积神经网络 识别精度 收敛速度
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基于改进LeNet-5模型的手写体中文识别 被引量:5
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作者 何凯 黄婉蓉 +1 位作者 刘坤 高圣楠 《天津大学学报(自然科学与工程技术版)》 EI CSCD 北大核心 2020年第8期847-853,共7页
手写体中文的自动识别是中文文档数字化的前提和基础,由于中文字符数目繁多、相似性强、字体种类繁多、书写随意、缺乏统一规范等原因,一直是计算机视觉领域中一个具有挑战性的问题.为解决这一难题,提出了一种基于卷积神经网络的手写体... 手写体中文的自动识别是中文文档数字化的前提和基础,由于中文字符数目繁多、相似性强、字体种类繁多、书写随意、缺乏统一规范等原因,一直是计算机视觉领域中一个具有挑战性的问题.为解决这一难题,提出了一种基于卷积神经网络的手写体中文识别方法.在经典LeNet-5网络模型的基础上进行改进,提出了一种LeNet-Ⅱ模型.利用改进的Inception模块和空洞卷积,设计了一种并行的双路卷积神经网络结构;两路分支可分别提取手写中文图像中不同尺度的特征,获得多个尺度的特征图像;通过对其进行特征融合,可以达到丰富特征图像多样性、提升识别准确率的目的;最后经过全连接层进行分类.利用经典手写体中文数据集进行训练,利用该模型实现了3755类手写体中文字符及相关文本的自动识别.实验结果表明,基于改进LeNet-5模型的手写体中文识别方法,在同一训练数据集上的收敛速度和识别准确率明显优于经典LeNet-5模型,对经典数据集的识别准确率可以达到95.21%,也高于其他传统算法;此外,对4幅手写体中文文本的平均识别准确率达到97.30%,超出了人类表现,取得了理想的实际效果. 展开更多
关键词 手写体中文识别 卷积神经网络 lenet-5模型 Inception模块
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New Directions of 5G for the Development of Blended Learning Models
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作者 Li Xinya Jiang Bo 《Psychology Research》 2022年第10期802-807,共6页
To improve the quality of education,the application of various forms of teaching and learning tools supported by technology is becoming increasingly widespread in education.Especially the internet communication and te... To improve the quality of education,the application of various forms of teaching and learning tools supported by technology is becoming increasingly widespread in education.Especially the internet communication and technology are changing the education era swiftly with the advent of fifth-generation technology.Research about blended learning(BL)based on 5G networks is emerging.However,few studies have explained how 5G network technology helps the BL teaching model be better applied to teaching.Therefore,this paper tries to sort out the development process of BL teaching mode,summarize the challenges of BL learning in teaching,and explore how the development of the 5G era will positively impact BL teaching mode. 展开更多
关键词 blended learning 5G network technology teaching model online learning
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基于FRBPSO-RBF神经网络的污水BOD5软测量方法 被引量:1
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作者 班慧琳 李中志 +1 位作者 李斌勇 王远 《成都信息工程大学学报》 2024年第4期416-421,共6页
污水处理过程中污水BOD5难以实时准确测量,故软测量方法逐渐被用于污水BOD5的预测,其中RBF神经网络软测量方法应用广泛,但存在训练过程易陷入局部极值等问题。为提高RBF神经网络的预测精度,提出了基于适应度排名的粒子群算法(fitness ra... 污水处理过程中污水BOD5难以实时准确测量,故软测量方法逐渐被用于污水BOD5的预测,其中RBF神经网络软测量方法应用广泛,但存在训练过程易陷入局部极值等问题。为提高RBF神经网络的预测精度,提出了基于适应度排名的粒子群算法(fitness ranking based particle swarm optimization,FRBPSO),根据适应度排名与迭代次数确定惯性权重的大小,并根据粒子个体历史最优值的排名与迭代次数确定自我学习因子与社会学习因子的大小,并将FRBPSO算法引入RBF神经网络的参数训练中。基于13个基准测试函数与其他3个粒子群优化算法对比,实验结果显示FRBPSO算法的寻优能力相对较强。再将基于FRBPSO算法的RBF神经网络用于构建污水BOD5软测量模型,仿真结果表明,在测试数据中,FRBPSO-RBF软测量模型的平均绝对误差比PSO-RBF软测量模型、DAIW-RBF软测量模型、SCVPSO-RBF软测量模型分别降低了0.7178、0.2402、0.5851,平均绝对百分比误差分别降低了0.47%、0.15%、0.33%,均方根误差分别降低了0.0034、0.0015、0.0039。与其他3个基于PSO算法的BOD5软测量模型相比,FRBPSO-RBF模型具有较高的BOD5预测精度。 展开更多
关键词 RBF神经网络 PSO算法 软测量模型 BOD5软测量 污水水质预测
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基于增强LetNet-5的非霍奇金淋巴瘤辅助诊断 被引量:6
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作者 张剑飞 崔文升 +1 位作者 王真 杜晓昕 《科学技术与工程》 北大核心 2020年第16期6527-6531,共5页
针对主流网络模型在医学辅助诊断适用性低的问题,在现有LetNet-5模型的基础上,给出了增强LetNet-5模型用于非霍奇金淋巴瘤的智能辅助诊断方案。首先将获取到的数据集进行图像切分和归一化等预处理操作,然后使用深度学习框架KERAS搭建增... 针对主流网络模型在医学辅助诊断适用性低的问题,在现有LetNet-5模型的基础上,给出了增强LetNet-5模型用于非霍奇金淋巴瘤的智能辅助诊断方案。首先将获取到的数据集进行图像切分和归一化等预处理操作,然后使用深度学习框架KERAS搭建增强前后的LetNet-5模型,接着对增强前后的网络模型进行训练、预测和评估,最后对模型的泛化能力和稳定性进行验证。实验表明,增强LetNet-5模型相对于原始LetNet-5模型具有更高的识别精度、更好的稳定性和更快的模型收敛速度,为非霍奇金淋巴瘤的诊断提供科学性的指导并具有重要的临床价值。 展开更多
关键词 深度学习 卷积神经网络 LetNet-5模型 计算机辅助诊断
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IEC60870-5-101在配电自动化无线公网通信中的应用 被引量:4
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作者 李克文 莫凤芝 +4 位作者 吴丽芳 高立克 俞小勇 吴智丁 祝文姬 《电力系统通信》 2012年第10期39-43,共5页
文章介绍了IEC60870-5-101通信规约(101规约)的特点、规约构架、正常通信过程及异常通信过程的处理;分析了TCP、UDP网络协议的利弊,阐述了配电自动化无线公网通信中网络协议的选择。结合目前配电自动化试点过程中无线公网通信方面存在... 文章介绍了IEC60870-5-101通信规约(101规约)的特点、规约构架、正常通信过程及异常通信过程的处理;分析了TCP、UDP网络协议的利弊,阐述了配电自动化无线公网通信中网络协议的选择。结合目前配电自动化试点过程中无线公网通信方面存在的问题,提出了一些有益的建议。 展开更多
关键词 IEC60870—5-101规约 平衡模式 网络协议 无线公网通信
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大蒜素对不同年龄组小鼠血清神经递质5-羟色胺和β-内啡肽的影响 被引量:4
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作者 吕亚囡 董群 《中国临床药理学与治疗学》 CAS CSCD 2012年第8期884-887,共4页
目的:探讨大蒜素对不同年龄组小鼠神经递质5-羟色胺(5-HT)和β-内啡肽(β-EP)的影响。方法:健康ICR小鼠60只,随机分为青年组和老年组;各组又分设对照组和实验组。老年组鼠是用D-半乳糖制备衰老模型。实验组喂食大蒜素14d,对照组灌服同... 目的:探讨大蒜素对不同年龄组小鼠神经递质5-羟色胺(5-HT)和β-内啡肽(β-EP)的影响。方法:健康ICR小鼠60只,随机分为青年组和老年组;各组又分设对照组和实验组。老年组鼠是用D-半乳糖制备衰老模型。实验组喂食大蒜素14d,对照组灌服同体积生理盐水。采用ELISA法测各组小鼠血清5-HT和β-EP含量。结果:老年组鼠的β-EP明显低于青年组(P<0.05),而老年组鼠和青年组鼠5-HT无统计学差异(P>0.05)。青年实验组鼠较青年对照组鼠的5-HT,β-EP水平明显增加(P<0.05);老年实验组较老年对照组的β-EP水平明显增加(P<0.05),而5-HT仅有增加趋势,但差异无统计学意义(P>0.05)。结论:大蒜素对β-EP的表达有明显的上调作用,对5-HT的上调作用青年组较老年组明显。 展开更多
关键词 大蒜素 衰老模型 5-羟色胺 Β-内啡肽 神经内分泌免疫调节网络(NEI)
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基于水力模型的管网破损率与污水厂进水BOD_(5)浓度之间的关系 被引量:2
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作者 陈城 李智 +2 位作者 王昊 唐颖 宋利祥 《净水技术》 CAS 2022年第2期63-67,74,共6页
随着城市建设的发展与城市化进程加快,城市排水管网作为城市地下的重要“脉络”,是人们安全生产生活的重要保障,而排放标准越来越严格,污水厂的处理成本逐渐升高。研究污水厂进水BOD_(5)浓度与管网破损率的关系,制定合理的管网修复方案... 随着城市建设的发展与城市化进程加快,城市排水管网作为城市地下的重要“脉络”,是人们安全生产生活的重要保障,而排放标准越来越严格,污水厂的处理成本逐渐升高。研究污水厂进水BOD_(5)浓度与管网破损率的关系,制定合理的管网修复方案,是保证各项污染物指标稳定达标的重要一环。本文运用水力模型(SWMM)建立昭通市中心城区污水管网模型,计算在不同管网破损率下污水处理厂的进水量和进水BOD_(5)浓度并分析其相关性。结果表明:在不同管网破损率下污水处理厂的进水量和进水BOD_(5)浓度存在明显差异,随着管网破损率上升,污水处理厂的进水量呈现上升趋势,进水BOD_(5)浓度呈现下降趋势,得到的管网破损率与污水处理厂进水BOD_(5)浓度关系图可支撑管网修复工作。 展开更多
关键词 水力模型 排水管道 BOD_(5) 浓度 破损率 渗流 管网修复
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基于社会网络分析的长株潭“3+5”城市群经济网络结构研究
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作者 刘晓玲 谭三友 《湖南工程学院学报(社会科学版)》 2022年第2期34-40,共7页
长株潭“3+5”城市群是湖南省经济上紧密联系、功能上分工合作的城市聚合体。为了更好地构建区域经济格局,更为全面而清晰地把握单个城市之间、单个城市在城市群中以及城市群整体网络的真实关系,运用社会网络分析法和城市引力模型,对长... 长株潭“3+5”城市群是湖南省经济上紧密联系、功能上分工合作的城市聚合体。为了更好地构建区域经济格局,更为全面而清晰地把握单个城市之间、单个城市在城市群中以及城市群整体网络的真实关系,运用社会网络分析法和城市引力模型,对长株潭“3+5”城市群的经济联系强度、网络密度、网络中心度、核心-边缘结构等指标进行定量化实证研究。研究结果表明:长株潭“3+5”城市群整体网络密度高,8个城市间经济联系非常紧密;网络中心度较高,城市群网络化结构明显;整个城市群处于非均衡发展状态,具有明显的核心-边缘结构特征;凝聚子群之间处于较弱连接状态。鉴于此,亟须进一步大力推进长株潭三市一体化建设、推动区域性中心城市建设。提高城市群内部主体关联度和建立良好的信息共享机制是优化长株潭“3+5”城市经济网络结构的有效途径。 展开更多
关键词 长株潭区域一体化 长株潭“3+5”城市群 社会网络分析 经济网络结构 城市引力模型
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Modeling oblique load carrying capacity of batter pile groups using neural network,random forest regression and M5 model tree 被引量:3
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作者 Tanvi SINGH Mahesh PAL V.K.ARORA 《Frontiers of Structural and Civil Engineering》 SCIE EI CSCD 2019年第3期674-685,共12页
M5 model tree,random forest regression(RF)and neural network(NN)based modelling approaches were used to predict oblique load carrying capacity of batter pile groups using 247 laboratory experiments with smooth and rou... M5 model tree,random forest regression(RF)and neural network(NN)based modelling approaches were used to predict oblique load carrying capacity of batter pile groups using 247 laboratory experiments with smooth and rough pile groups.Pile length(L),angle of oblique load(a),sand density(ρ),number of batter piles(B),and number of vertical piles(V)as input and oblique load(Q)as output was used.Results suggest improved performance by RF regression for both pile groups.M5 model tree provides simple linear relation which can be used for the prediction of oblique load for field data also.Model developed using RF regression approach with smooth pile group data was found to be in good agreement for rough piles data.NN based approach was found performing equally well with both smooth and rough piles.Sensitivity analysis using all three modelling approaches suggest angle of oblique load(a)and number of batter pile(B)affect the oblique load capacity for both smooth and rough pile groups. 展开更多
关键词 BATTER PILES OBLIQUE load test NEURAL network M5 model TREE random FOREST regression ANOVA
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The 5C Model of Linguistic Creativity:Construction Grammar as a Cognitive Theory of Verbal Creativity
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作者 Thomas HOFFMANN 《Journal of Foreign Languages and Cultures》 2024年第1期139-154,共16页
Creativity is a design feature of human language.This paper presents a cognitive model of verbal creativity that draws on insights from the psychological research into creativity-particularly Glaveanu's 5A model t... Creativity is a design feature of human language.This paper presents a cognitive model of verbal creativity that draws on insights from the psychological research into creativity-particularly Glaveanu's 5A model that distinguishes five crucial perspectives on a creative act(actors,audience,artefacts,actions and affordances).The paper will outline a linguistic version of this model that adopts Construction Grammar as its theoretical foundation.The resulting"5C model of constructional creativity"argues that the central elements of linguistic creativity are constructors,co-constructors,constructs,constructional blending and the constructional network. 展开更多
关键词 CREATIVITY construction grammar cognitive linguistics BLENDING 5C model of constructional creativity COGNITION constructional networks
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