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社交媒体谣言检测是当前研究的热点问题,现有方法多数通过获取大量用户属性学习用户特征,但不适用于谣言的早期检测,忽略了用户之间的潜在关系对信息传播的影响。提出一种基于多传递影响力的谣言检测方法,根据源微博及其对应转发(评论)之间的关系构建文本信息传播图,并通过图卷积神经网络来捕获、学习文本信息的传播特征。利用文本信息和用户传播过程中的影响力,丰富可用于谣言检测早期的检测信息。将存在转发关系的用户构成用户影响力传播图,构建一种用户节点影响力学习方法,获取用户节点影响力,以增强用户特征信息。在此基础上,将文本特征与用户特征融合以进行谣言检测,从而提升检测效果。在3个真实社交媒体数据集上的实验结果表明,该方法在谣言自动检测以及早期检测的效果都有显著提升,与目前最好的基准方法相比,在微博、Twitter15、Twitter16数据集上的正确率分别提高了2.8%、6.9%和3.4%。  相似文献   
3.
Cyberbullying (CB) is a challenging issue in social media and it becomes important to effectively identify the occurrence of CB. The recently developed deep learning (DL) models pave the way to design CB classifier models with maximum performance. At the same time, optimal hyperparameter tuning process plays a vital role to enhance overall results. This study introduces a Teacher Learning Genetic Optimization with Deep Learning Enabled Cyberbullying Classification (TLGODL-CBC) model in Social Media. The proposed TLGODL-CBC model intends to identify the existence and non-existence of CB in social media context. Initially, the input data is cleaned and pre-processed to make it compatible for further processing. Followed by, independent recurrent autoencoder (IRAE) model is utilized for the recognition and classification of CBs. Finally, the TLGO algorithm is used to optimally adjust the parameters related to the IRAE model and shows the novelty of the work. To assuring the improved outcomes of the TLGODL-CBC approach, a wide range of simulations are executed and the outcomes are investigated under several aspects. The simulation outcomes make sure the improvements of the TLGODL-CBC model over recent approaches.  相似文献   
4.
The statistical analysis methods based on differential pressure signals of two-phase flow are employed in the present study to identify the flow patterns in packed porous bed. The typical flow pattern images of two-phase flow in the packed porous beds are recognized and the corresponding differential pressure signals are recorded based on the visualization experiments. Then the statistical analysis methods, including probability density function (PDF), power spectral density (PSD), and wavelet energy spectrum (WES), are employed to extract the features of differential pressure signals in the time domain, frequency domain, and time-frequency domain respectively. The dimensionless parameters are proposed as the evaluation index to quantify the differences among flow patterns. The results show that the PDF, PSD, and WES methods can effectively characterize different flow patterns in the time, frequency, and time-frequency domain, respectively. The comprehensive recognition efficiency is about 88.5% using the introduced dimensionless parameters.  相似文献   
5.
孔隙率是选择性催化还原(SCR)脱硝催化剂结构的重要指标,对催化剂的脱硝效率有重要影响。根据工程依据范围创建微观孔隙尺度的SCR脱硝催化剂多孔介质模型,采用随机配置的方法,构造出8种不同孔隙率。采用格子Boltzmann方法模拟SCR催化剂表面流动及传质耦合化学反应过程,在特定烟气流速和NO原始浓度工况条件下获得多孔介质中烟气流动的速度分布和伴随流动过程发生催化还原反应的NO浓度分布,研究孔隙率对流动和脱硝效率的影响。研究结果表明:随孔隙率的增加,全场平均孔隙流速逐渐减小,出口NO平均浓度逐渐增大,脱硝率逐渐降低;孔隙率为0.748时,出口NO平均浓度最低,脱硝效率最高,此孔隙率为最佳孔隙结构。  相似文献   
6.
While experimental designs developed in recent decades have contributed to research on dynamic nonequilibrium effects in transient two-phase flow in porous media, this problem has been seldom investigated using direct numerical simulation (DNS). Only a few studies have sought to numerically solve Navier–Stokes equations with level-set (LS) or volume-of-fluid (VoF) methods, each of which has constraints in terms of meniscus dynamics for various flow velocities in the control volume (CV) domain. The Shan–Chen multiphase multicomponent lattice Boltzmann method (SC-LBM) has a fundamental mechanism to separate immiscible fluid phases in the density domain without these limitations. Therefore, this study applied it to explore two-phase displacement in a single representative elementary volume (REV) of two-dimensional (2D) porous media. As a continuation of a previous investigation into one-step inflow/outflow in 2D porous media, this work seeks to identify dynamic nonequilibrium effects on capillary pressure–saturation relationship (PcS) for quasi-steady-state flow and multistep inflow/outflow under various pressure boundary conditions. The simulation outcomes show that Pc, S and specific interfacial area (anw) had multistep-wise dynamic effects corresponding to the multistep-wise pressure boundary conditions. With finer adjustments to the increase in pressure over more steps, dynamic nonequilibrium effects were significantly alleviated and even finally disappeared to achieve quasi-steady-state inflow/outflow conditions. Furthermore, triangular wave-formed pressure boundary conditions were applied in different periods to investigate dynamic nonequilibrium effects for hysteretical PcS. The results showed overshoot and undershoot of Pc to S in loops of the nonequilibrium hysteresis. In addition, the flow regimes of multistep-wise dynamic effects were analyzed in terms of Reynolds and capillary numbers (Re and Ca). The analysis of REV-scale flow regimes showed higher Re (1 < Re < 10) for more significant dynamic nonequilibrium effects. This indicates that inertia is critical for transient two-phase flow in porous media under dynamic nonequilibrium conditions.  相似文献   
7.
In this article, pre-assembly hot-press pressure and thermal expansion effects in gas-diffusion layers (GDLs) are addressed to explore the practicalities of the constitutive model reported in the companion article. A facile technique is proposed to include deformation history dependent residual strain effects. The model is implemented in the numerical environment and compared with widely followed conventional models such as isotropic and orthotropic material models. With the normal and accelerated thermal expansion effects no significant variation in stresses or strains is reported with the compressible GDL model in contrast to the conventional incompressible form of the GDL model. The present work identifies the critical differences with advanced and extended variants of the model along with conventional GDL material models in terms of planar stress/strain distribution and the membrane response. Finally, the model is simulated for micro-cyclic stress loads of varying amplitudes that imitate the real working conditions of fuel cell. The inelastic energy dissipation in GDLs is predicted using the proposed model, which is utilized further to distinguish the safe (elastic) and unsafe (inelastic shakedown) operating limits. The inelastic collapse of GDLs is shown to be a active function of high amplitude micro-cyclic load with high initial clamping load.  相似文献   
8.
Renewable electricity-powered hydrogen production is an attractive alternative to unsustainable industrial processes, but the large-scale implantation of such sustainable technology still requires efficient and noble-metal-free electrocatalysts for driving cathodic hydrogen evolution reaction (HER), especially under alkaline conditions. In this paper, CoP nanowire array was in-situ developed on porous graphite felt (CoP/GF) as a new 3D electrocatalyst in facilitating hydrogen evolution electrocatalysis. This CoP/GF presents outstanding HER activity, requiring a low overpotential of 130 mV to deliver a current density of 20 mA cm?2 as tested in 1.0 M KOH. Furthermore, this free-standing catalyst exhibits impressive long-term durability of up to 50 h under working conditions.  相似文献   
9.
越南语网络评论的情感分类是越南语事件观点分析的基础。越南语资源匮乏,标注困难,可借助中文标注语料进行跨语言情感分类,实现越南语评论的情感极性预测。但现有的跨语言情感分类模型忽略了主题信息对加强情感表征学习、减小语言差异的作用。为此,该文提出了一种融入主题特征的中越跨语言情感分类模型。将中文和越南语的主题词分布作为外部知识引入模型,利用门控机制将主题表征与语义表征进行融合编码,并通过对抗过程使模型学习到语言分布差异最小的表征,最终完成情感分类任务。实验结果表明,该模型能更快拟合出语言分布差异,其宏F1值较多个基线模型均有明显提高。  相似文献   
10.
现有的大多数虚假新闻检测方法将视觉和文本特征串联拼接,导致模态信息冗余并且忽略了不同模态信息之间的相关性。为了解决上述问题,提出一种基于矩阵分解双线性池化的多模态融合虚假新闻检测算法。首先,该算法将多模态特征提取器捕捉的文本和视觉特征利用矩阵分解双线性池化方法进行有效融合,然后与虚假新闻检测器合作鉴别虚假新闻;此外,在训练阶段加入了事件分类器来预测事件标签并去除事件相关的依赖。在Twitter和微博两个多模态谣言数据集上进行了对比实验,证明了该算法的有效性。实验结果表明提出的模型能够有效地融合多模态数据,缩小模态间的异质性差异,从而提高虚假新闻检测的准确性。  相似文献   
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