预应力锚固技术在龙滩水电站高边坡工程中的应用

龙滩水电站进水口高边坡最大坡高达420m，为保证高边坡的稳定，采用预应力锚索技术。预应力锚索的加固作用非常明显，不仅为边坡的稳定提供了经济、有效的手段，而且为按期截流创造了条件。     

液晶分子附着能和盒间隙对响应时间的影响

通过理论分析和实验研究液晶分子附着能和液晶盒间隙对响应时间(τ0)的影响。用液晶盒有效间隙法和表面动力学方程法两种方法推出分析公式,由这两种方法推出的结果是一致的。实验数据与简化方程τ0-dx基本拟合(其中d是液晶盒的间隙,x是指数)。在两种极端的(极大或极小)附着能极限下,指数x分别接近2和1。这个结论有助于优化液晶显示器件的应用。     

Intelligent tool wear monitoring based on parallel residual and stacked bidirectional long short-term memory network

Effective tool wear monitoring (TWM) is essential for accurately assessing the degree of tool wear and for timely preventive maintenance. Existing data-driven monitoring methods mainly rely on complex feature engineering, which reduces the monitoring efficiency. This paper proposes a novel TWM model based on a parallel residual and stacked bidirectional long short-term memory (PRes–SBiLSTM) network. First, a parallel residual network (PResNet) is used to extract the multi-scale local features of sensor signals adaptively. Subsequently, a stacked bidirectional long short-term memory (SBiLSTM) network is used to obtain the time-series features related to the tool wear characteristics. Finally, the predicted tool wear value is outputted through a fully connected network. A smoothing correction method is applied to improve the prediction accuracy. The proposed model is experimentally verified to have a high prediction accuracy without sacrificing its generalization ability. A TWM system framework based on the PRes–SBiLSTM network is proposed, which has a certain reference value for TWM in actual industrial environments.     

胺烷基化聚羟基酸酰胺类超分散剂的研制及应用

对胺烷基化聚羟基酸酰胺的合成方法进行研究，确立了反应条件与制得的聚羟基酸酯特征之间的一些相互关系。并为获得适当长度的聚酯链选择了最佳合成条件。同时扼要论述了这类超分散剂的结构特性，以及对于颜料粒子表面吸附作用、分散体系的稳定作用以及对涂料、油墨生产的重要意义。     

Context-aware adaptive IP mobility anchoring

The novel distributed mobility management trend is a promising direction to cope with the increasing mobile data traffic and flatten network architectures. Most of the novel mobility approaches distribute the mobility anchors through the access level, as opposed to the centralized mobility anchoring model. Other recent approaches argue that mobility anchors closer to the content servers may be the solution to optimize the mobility performance. However, none of the mobility anchoring models is ideal for all scenarios, since it depends on the user, the session and the network. Hence, we propose an IP mobility approach driven by the context of the user, sessions and the network, where the mobility anchors for IP address allocation and for routing/forwarding are distributed through the network nodes, while the mobility context is managed by the mobile devices. Although each session is properly anchored in the establishment phase, the routing/forwarding is adapted over time, according to the user, the session and the network context: the proposed approach is able to signal different mobility anchors to optimize the routing path to new and ongoing sessions of the user. The outcome of the evaluation shows that the proposed approach overall reduces the data cost, the data delay, the tunneled packets and the tunnel length, when compared with other anchoring models.     

Macromolecular anchoring layers for polymer grafting: comparative study

Comparative study of efficiency of macromolecular anchoring layers in the grafting of end-functionalized polymers to a surface was conducted. Poly(glycidyl methacrylate) (PGMA) and epoxydized polybutadienes (EPB) were utilized as the primary anchoring films. Amount of the epoxy moieties introduced to the surface was varied via thickness of the modifying polymer layer or amount of epoxy groups in the polymer backbone. Comparison between the grafting of polystyrene and poly(ethylene glycol) to the various macromolecular anchoring layers indicated that grafting ability of a layer was mostly governed by thickness of the interpenetration zone between the two polymers (anchoring and being grafted). In case of low level of the interpenetration, only functional groups at the periphery of the primary polymer layer were available for the grafting. Then, amount of grafted polymer did not increase with total number of epoxy groups in the anchoring film. However, as the thickness of the interpenetration zone increased, higher amount of the functional groups become available for the grafting.     

基于ViLBERT与BiLSTM的图像描述算法

传统图像描述算法存在提取图像特征利用不足、缺少上下文信息学习和训练参数过多的问题,提出基于ViLBERT和双层长短期记忆网络(BiLSTM)结合的图像描述算法.使用ViLBERT作为编码器,ViLBERT模型能将图片特征和描述文本信息通过联合注意力的方式进行结合,输出图像和文本的联合特征向量.解码器使用结合注意力机制的BiLSTM来生成图像描述.该算法在MSCOCO2014数据集进行训练和测试,实验评价标准BLEU-4和BLEU得分分别达到36.9和125.2,优于基于传统图像特征提取结合注意力机制图像描述算法.通过生成文本描述对比可看出,该算法生成的图像描述能够更细致地表述图片信息.     

基于动态行为和机器学习的恶意代码检测方法

目前恶意代码出现频繁且抗识别性加强,现有基于签名的恶意代码检测方法无法识别未知与隐藏的恶意代码。提出一种结合动态行为和机器学习的恶意代码检测方法。搭建自动化分析Cuckoo沙箱记录恶意代码的行为信息和网络流量,结合Cuckoo沙箱与改进DynamoRIO系统作为虚拟环境,提取并融合恶意代码样本API调用序列及网络行为特征。在此基础上,基于双向门循环单元（BGRU）建立恶意代码检测模型,并在含有12 170个恶意代码样本和5 983个良性应用程序样本的数据集上对模型效果进行验证。实验结果表明,该方法能全面获得恶意代码的行为信息,其所用BGRU模型的检测效果较LSTM、BLSTM等模型更好,精确率和F1值分别达到97.84%和98.07%,训练速度为BLSTM模型的1.26倍。     

结合Bi-2DPCA与CNN的美式手语识别

针对现有美式手语（ASL）识别算法准确率低和模型训练时间长的问题,提出一种结合双向二维主成分分析（Bi-2DPCA）与卷积神经网络（CNN）并基于贝叶斯优化的识别算法。利用Bi-2DPCA算法对原始图像做数据降维处理,提取行、列方向的特征图,使用卷积神经网络对特征图进行训练分类,同时采用贝叶斯优化算法对模型超参数进行自动调参。在24分类ASL数据集上的实验结果表明,该算法的识别准确率达到99.15%,训练时间相比传统CNN算法减少90.3%。     

GFRP抗浮锚杆在基础底板中的锚固性能现场试验研究

通过现场拉拔破坏性试验,测得不同直径的GFRP抗浮锚杆在基础底板内的极限承载力和滑移量,并与实际工程中不同形式的钢筋抗浮锚杆作比较,分析其承载性能和粘结特性。研究表明,在相同的混凝土强度与养护条件下,相同直径的GFRP抗浮锚杆的极限承载力、平均粘结强度与钢筋抗浮锚杆相比较高,且GFRP抗浮锚杆的变形能够满足实际工程需求,充分验证了GFRP材料用作抗浮锚杆的先进性与合理性。基于试验结果与理论分析,给出了GFRP抗浮锚杆与基础底板的最佳锚固面积,并提出了计算公式。