基于有向图模型的多模态新闻图像检索研究

不同模态特征描述网络新闻数据各具优势。为充分利用不同模态特征的优点,提高网络新闻图像检索准确率,提出了一种基于有向图理论模型的多模态特征融合检索方法。首先对新闻图像进行预处理,提升新闻图像兴趣点对比度,之后对新闻文本提取关键词,然后对新闻图像进行场景辨别,结合图像人物特征,将文本、场景、人物特征依据有向图理论模型进行融合,形成基于有向图理论模型的多模态融合检索。在10万条新闻数据上测试,实验结果表明,本文提出的方法检索准确率达到了69%,查全率达到70%,效果提升了5%。     

基于知识图谱和图像描述的虚假新闻检测研究

针对传统虚假新闻检测方法主要采用图像统计学和图像分布式表示特征导致没有深层次挖掘图像所表达的文字含义的问题,设计了在融合知识图谱和图像描述的深度学习下的多模态虚假新闻检测模型.该模型一方面抽取出在新闻文本中的3元组形式知识图谱,另一方面生成图像对应的描述文本,同时采用Bert框架将原文本、3元组、图像描述文本加以集成.在基准汉语虚假新闻语料库上的实验结果表明:该模型显著优于传统的代表性方法.     

基于多任务多模态学习的谣言检测框架

谣言检测是对社交网络上传播的信息内容进行真实性鉴别的任务.一些研究表明融合多模态信息有助于谣言检测,而现有多模谣言检测方法具有以下问题：（1）只是将处于不同表示空间的单模态特征简单拼接形成多模态表示,没有考虑多模态之间的关系,难以提高模型的预测性能和泛化能力.（2）缺乏对社交网络数据组成结构的细致考虑,只能处理由文本-图像对的社交网络数据,无法处理由多幅图像组成的数据,且当其中一种模态（图像或文本）缺失时模型无法进行预测.针对上述问题,本文提出了一种多任务多模态谣言检测框架（MMRDF）,该框架由3个子网络组成：文本子网络、视觉子网络和融合子网络,通过从单模态数据中提取浅层至深层的单模特征表示,在不同的子空间中产生特征图,丰富模态内特征,并通过复合卷积结构融合生成联合多模态表示,以获得更好的预测性能.同时该框架可以灵活地处理所有类型的推文（纯文本、纯图像、文本-图像对和多图像文本）,并且没有引入造成额外时间延迟的传播结构、响应内容等数据作为输入,可以在推文发布后立即应用于谣言检测,减少辟谣的时间延迟.在两个真实数据集上的实验结果表明,所提框架明显优于目前最先进的方法,准确率上的提升分别...     

融合多模态的虚假新闻检测

在社交媒体高速发展方便信息交流的同时,虚假新闻也在网络上大量传播,对社会稳定造成了很大的影响.针对当前虚假新闻检测工作大多充分考虑虚假新闻中新闻文本内容而忽略图像内容的问题,提出了一种基于注意力的BiLSTM-CNN多模态虚假新闻检测模型.该模型首先使用双向长短期记忆神经记忆网络(BiLSTM)提取文本内容特征,使用卷积神经网络(CNN)提取图像语义特征,利用注意力机制(Attention)层对提取的内容特征信息分配相应的权重,再将两种特征融合以形成重新参数化的多模态特征作为输入进行虚假新闻检测.实验表明,该方法达到了98.3%的正确率.     

基于多模态医学图像的Alzheimer病分类方法

多模态医学影像信息已经在计算机辅助检测和诊断中被广泛地应用。在对Alzheimer病(Alzheimer's disease, AD)的分类与诊断中,结合多个模态医学影像的特征信息能够更加准确且全面地对同一AD主题进行分类与诊断。该文提出了一种基于卷积神经网络的模型结构,分别对AD病患的磁共振图像(MRI)和正电子发射型计算机断层显像(PET)图像进行3D卷积操作来提取各自模态的特征信息,并应用模型融合方法对模态特征信息加以融合,从而得到包含更加丰富的多模态特征信息。最后用全连接神经网络将上述提取的多模态特征信息进行分类预测。通过在AD神经影像学倡议(Alzheimer's disease neuroimaging initiative, ADNI)公开数据集上的实验结果表明:该文所提出的模型在准确率(accuracy, ACC)和曲线下面积(area under the curve, AUC)的性能评价中都取得了更加优越的结果。     

基于多模态特征融合的无人驾驶系统车辆检测

针对无人驾驶系统环境感知中的车辆检测精度低的问题,本文提出一种基于多模态特征融合的三维车辆检测算法.该算法通过毫米波雷达与摄像机联合标定,匹配2个传感器间的坐标关系并减小采样误差;采用统计滤波剔除毫米波雷达数据冗余点,减少离群点干扰;构造多模态特征融合模块,利用逐像素平均融合点云与图像信息;加入特征金字塔提取融合后的高...     

基于改进MGR融合算法的视频信息融合框架

针对视频信息具有的多模态性质,提出了融合视音频多种模态特征信息的视频融合分析框架,用以提高视频检索的正确率和效率.该框架根据从视频底层提取出的多种图像特征、音频特征,采用基于图嵌入框架的降维算法MFA降维,根据降维后得到的各种特征向量,训练SVM分类器进行分类,并用改进后的MGR融合算法对SVM分类器输出的序号矩阵进行融合分析.实验结果表明该融合框架融合多种特征提高了分类识别的效率,采用了改进的融合算法降低了计算复杂度,提高了系统的整体性能.     

档案管理中文本数据的增量多模态聚类方法

随着现代档案管理数据量的不断增长，有效地对档案文本进行聚类划分能够提升档案分类和检索的效率。文中提出2种增量多模态文本数据聚类方法，通过对文本内容进行多视角分析，融合挖掘文本的潜在主题特征，提升文本聚类的准确性。此外，设计文本聚类多模态增量学习模型，提升海量、动态文本划分的效率。在文本数据集上的实验结果表明，文中提出的增量多模态文本聚类方法优于单模态和多模态聚类算法，能够对文本数据进行有效划分。     

基于文本指导的层级自适应融合的多模态情感分析

提出了一种基于文本模态指导的多模态层级自适应融合方法,以文本模态信息为指导实现多模态信息的层级自适应筛选及融合。首先,基于跨模态注意力机制实现两两模态之间的重要性信息表征;然后通过多模态自适应门控机制实现基于多模态重要信息的层级自适应融合;最后综合多模态特征和模态重要性信息实现多模态情感分析。在公共数据集MOSI和MOSEI上的实验结果表明：对比基线模型,本文所提方法在准确率与F₁值方面分别提升了0.76%和0.7%。     

基于情感信息辅助的多模态情绪识别

不同于纯文本的情绪分析, 本文面向多模态数据(文本和语音)进行情绪识别研究。为了同时考虑多模态数据特征, 提出一种新颖的联合学习框架, 将多模态情绪分类作为主任务, 多模态情感分类作为辅助任务, 通过情感信息来辅助提升情绪识别任务的性能。首先, 通过私有网络层对主任务中的文本和语音模态信息分别进行编码, 以学习单个模态内部的情绪独立特征表示。接着, 通过辅助任务中的共享网络层来获取主任务的辅助情绪表示以及辅助任务的单模态完整情感表示。在得到主任务的文本和语音辅助情绪表示之后, 分别与主任务中的单模态独立特征表示相结合, 得到主任务中单模态情绪信息的完整表示。最后, 通过自注意力机制捕捉每个任务上的多模态交互特征, 得到最终的多模态情绪表示和情感表示。实验结果表明, 本文方法在多模态情感分析数据集上可以通过情感辅助信息大幅度地提升情绪分类任务的性能, 同时情感分类任务的性能也得到一定程度的提升。     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Lower Paleozoic oil relationships within Williston Basin, Canada

The Williston Basin is a significant petroleum province, containing oil production zones that include the Middle Cambrian to Lower Ordovician, Upper Ordovician, Middle Devonian, Upper Devonian and Mississippian and within the Jurassic and Cretaceous. The oils of the Williston Basin exhibit a wide range of geochemical characteristics defined as "oil families", although the geochemical signature of the Cambrian Deadwood Formation and Lower Ordovician Winnipeg reservoired oils does not match any "oil family". Despite their close stratigraphic proximity, it is evident that the oils of the Lower Palaeozoic within the Williston Basin are distinct. This suggests the presence of a new "oil family" within the Williston Basin. Diagnostic geochemical signatures occur in the gasoline range chromatograms, within saturate fraction gas chromatograms and biomarker fingerprints. However, some of the established criteria and cross-plots that are currently used to segregate oils into distinct genetic families within the basin do not always meet with success, particularly when applied to the Lower Palaeozoic oils of the Deadwood and Winnipeg Formation.     

An Analysis of Catherine＇s Character——Wuthering Heights

Wuthering Heights, Emily Bronte＇s only novel, was published in December of 1847 under the pseudonym Ellis Bell. The book did not gain immediate success, but it is now thought one of the finest novels in the English language. Catherine is the key character of this masterpiece, because everybody and everything center on her though she had a short life. We can understand this masterpiece better if we know Catherine well.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

Design and analysis of generic LBS application developing platform

Location based services is promising due to its novel working style and contents.A software platform is proposed to provide application programs of typical location based services and support new applications developing efficiently. The analysis shows that this scheme is easy implemented, low cost and adapt to all kinds of mobile nework system.     

橡胶颗粒沥青混合料低温抗裂性试验研究

以AC-13级配为基础,将橡胶颗粒代替部分集料掺入混合料中,以低温弯曲试验为评价方法对不同橡胶颗粒掺量下沥青混合料的低温抗裂性进行研究,并引入应变能密度值对混合料的低温抗裂性进行综合评价.试验结果表明:橡胶颗粒沥青混合料试件的破坏微应变均超过2 300,满足冬寒区的技术指标;无论是否掺加橡胶颗粒,随着温度的下降,沥青混合料破坏时的最大弯拉强度增大,弯拉应变降低,劲度模量增大;弯曲应变能密度在胶粒掺量为1%左右时具有较大的弯曲应变能密度值,此时橡胶颗粒沥青混合料具有较好的低温抗裂性.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

Quantitative trait loci （QTLs） for quality traits related to protein and starch in wheat

Quality traits in wheat （Triticum aestirum L.） were studied by quantitative trait locus （QTL） analysis in a recombinant inbred line （RIL） population, a set of 131 lines derived from Chuan 35050 × Shannong 483 cross （ChSh）. Grains from RILs were assayed for 21 quality traits related to protein and starch. A total of 35 putative QTLs for 19 traits with a single QTL explaining 7.99-40.52% of phenotypic variations were detected on 10 chromosomes, 1D, 2A, 2D, 3B, 3D, 5A, 6A, 6B, 6D, and 7B. The additive effects of 30 QTLs were positive, contributed by Chuan 35050, the remaining 5 QTLs were negative with the additive effect contributed by Shannong 483. For protein traits, 15 QTLs were obtained and most of them were located on chromosomes 1 D, 3B and 6D, while 20 QTLs for starch traits were detected and most of them were located on chromosomes 3D, 6B and 7B. Only 7 QTLs for protein and starch traits were co-located in three regions on chromosomes 1D, 2A and 2D. These protein and starch trait QTLs showed a distinct distribution pattern in certain regions and chromosomes. Twenty-two QTLs were clustered in 6 regions of 5 chromosomes. Two QTL clusters for protein traits were located on chromosomes 1D and 3B, respectively, three clusters for starch traits on chromosomes 3D, 6B and 7B, and one cluster including protein and starch traits on chromosome 1D.