基于控制点的分层双向动态规划立体匹配算法

提出一种基于控制点的分层双向动态规划立体匹配算法．首先，利用改进Volumetric迭代算法获取具有高可靠度的控制点，将其作为具有正确视差的匹配点．其次，在高可靠度控制点的指导下，利用分层双向动态规划算法在DSI（disparity-space image）视差空间图中进行初匹配，进而在Delta DSI（delta disparity-space image）视差变化空间图中进行精匹配，从而获取高密度视差图．实验结果表明，该算法不仅可以改善传统直接动态规划立体匹配算法产生的带状条纹瑕疵，而且计算速度较快，匹配结果也优于传统动态规划的匹配结果．     

A new instrument for passive remote sensing: 2. Measurement of leaf and canopy reflectance changes at 531 nm and their relationship with photosynthesis and chlorophyll fluorescence

A previously described passive remote sensing fluorimeter (see companion paper) was modified to detect changes in the reflectance of vegetation. The utility of this remote sensing technique to measure the Physiological Reflectance Index (PRI) is shown at both leaf level under laboratory conditions and at the canopy level in the field. PRI, defined as the relative changes in reflectance at 531 nm with respect to those at 570 nm (PRI=R531−R570/R531+R570), is related to xanthophyll-related, dynamic changes of non-photochemical quenching of chlorophyll fluorescence. The robustness of this relationship by simultaneous remote sensing of PRI and chlorophyll fluorescence is strengthened. At the leaf level, the existence of two kinetically distinct components of PRI is shown. A fast (within seconds) component that is partly attributed to ΔpH induced chloroplast shrinkage, and a slow (within minutes), main component that is related to xanthophyll de-epoxidation, as demonstrated by its disappearance in the presence of DTT. Overall, PRI correlated better with non-photochemical quenching of chlorophyll fluorescence (NPQ) than with any other measured parameter, including the photochemical efficiency of PSII. Finally, at the canopy level and under field conditions, it is shown that PRI can be a useful tool for remote sensing of water stress in grapevines.     

双向加载情况下工字形SRC柱抗震性能数值分析

为了研究工字形SRC柱在双向水平加载下的抗震性能,采用纤维模型对已有试验进行数值模拟,验证了纤维模型的适用性。基于此模型,考察了轴压比、配钢率、型钢强度等参数对工字形SRC柱在双向水平加载下的承载力、耗能及延性的影响,并与单向水平加载下的情况进行了对比。结果表明:轴压比对工字形SRC柱的抗震性能影响显著,随着轴压比的增大,柱子承载力先增大后减小,而滞回耗能和延性则随轴压比的增大逐步降低;配钢率对工字形SRC柱的抗震性能有一定影响,随配钢率的增大,柱的承载力、耗能及延性均有明显增长;承载力、耗能及延性均随型钢强度的增加而得到一定改善,但增幅较小。此外,双向加载下SRC柱的承载力、耗能及延性均较单向水平加载的低。     

428XL光缆交叉线的工作原理及故障检修方法

428XL光缆交叉线是428XL仪器的重要组成部分,它的问世有效提高了采集数据的传输速度,满足了随着野外采集道数的增加采集数据的数据量越来越大的数传要求。本文从428XL光缆交叉线的基本组成入手,详细剖析了428XL光缆交叉线的传输原理,并介绍了光缆交叉线应用于428XL仪器施工时的工作流程及其在施工中可能出现的故障和相应的检修方法。     

Deep Scalogram Representations for Acoustic Scene Classification

Spectrogram representations of acoustic scenes have achieved competitive performance for acoustic scene classification. Yet, the spectrogram alone does not take into account a substantial amount of time-frequency information. In this study, we present an approach for exploring the benefits of deep scalogram representations, extracted in segments from an audio stream. The approach presented firstly transforms the segmented acoustic scenes into bump and morse scalograms, as well as spectrograms; secondly, the spectrograms or scalograms are sent into pre-trained convolutional neural networks; thirdly, the features extracted from a subsequent fully connected layer are fed into (bidirectional) gated recurrent neural networks, which are followed by a single highway layer and a softmax layer; finally, predictions from these three systems are fused by a margin sampling value strategy. We then evaluate the proposed approach using the acoustic scene classification data set of 2017 IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE). On the evaluation set, an accuracy of 64.0% from bidirectional gated recurrent neural networks is obtained when fusing the spectrogram and the bump scalogram, which is an improvement on the 61.0% baseline result provided by the DCASE 2017 organisers. This result shows that extracted bump scalograms are capable of improving the classification accuracy, when fusing with a spectrogram-based system.      

基于BERT-Att-biLSTM模型的医学信息分类研究

目前,对互联网上虚假健康信息的研究多集中于谣言识别,而对医学信息自动分类的研究较少。采用基于双向编码的语言表征模型和注意力增强的双向长短时记忆模型(BERT-Att-BiLSTM模型),对健康信息文本进行分类,实现自动识别虚假健康信息。实验结果表明,BERT-Att-BiLSTM模型可以高效地对医学信息进行分类,其中BERT模型相较于BiLSTM模型,性能提升明显;与融合Word2Vec的BiLSTM模型相比,BERT-Att-BiLSTM模型效果更佳。     

基于注意力机制的双向长短时记忆网络模型突发事件演化关系抽取

针对现有突发事件关系抽取研究多集中于因果关系抽取而忽略了其他演化关系的问题，为了提高应急决策中信息抽取的完备性，应用一种基于注意力机制的双向长短时记忆（LSTM）网络模型进行突发事件演化关系抽取。首先，结合突发事件演化关系的概念，构建演化关系模型并进行形式化定义，依据模型对突发事件语料进行标注；其次，搭建双向LSTM网络结构，并引入注意力机制计算注意力概率以突出关键词汇在文本中的重要程度；最终，使用搭建的网络模型进行演化关系抽取得到结果。在演化关系抽取实验中，相对于现有因果关系抽取方法，所提方法不仅抽取出更加充分的演化关系，为突发事件应急决策提供了更完善的信息；同时，在正确率、召回率和F1分数上分别平均提升了7.3%、6.7%和7.0%，有效提高了突发事件演化关系抽取的准确性。     

一种应用于双向DC/DC变换器的新型耦合电感的设计

本文提出的"I王I"形耦合电感器通过增加磁路气隙的数量,使磁路的磁压分布更加均匀,与传统铁心电感器相比显著减小了磁路的电磁损耗、电磁干扰和线圈的涡流损耗,且增大了窗口面积。通过分析耦合电感器的磁通分布,建立磁路模型,给出了耦合电感器的设计方法,并对所提出的耦合电感器进行仿真,结合双向DC/DC变换器的实验验证了"I王I"形耦合电感器结构的可行性。