Experimental and numerical study on compressive performance of perforated brick masonry after fire exposure

This paper discusses the compressive performance of perforated brick masonry after fire exposure. Compressive strength tests of the mortar, clay perforated brick, and perforated brick masonry specimens were performed in accordance with ISO834 fire tests of different durations. The temperature distribution of the masonry materials and specimens was simulated using the finite element software ABAQUS, with the thermal parameters of masonry materials recommended by European standard Eurocode 6 and related literature. The compressive strength reduction factors of mortar and clay perforated brick exposed to different fire durations were calculated via the layered method suggested by European standard Eurocode 1. In addition, the compressive strength reduction factors after cooldown were obtained from the experimental data of the masonry materials, and by considering further reductions in the compressive strength after cooling from high temperatures. Experimental data of the masonry specimens were compared with the numerical results obtained using the reduction factors proposed in this work. The comparison revealed an overall acceptable approximation. Thus, the method presented in this paper can be used to evaluate the residual capacity of masonry structures after fire.     

Graph-based video fingerprinting using double optimal projection

A double optimal projection method that involves projections for intra-cluster and inter-cluster dimensionality reduction are proposed for video fingerprinting. The video is initially set as a graph with frames as its vertices in a high-dimensional space. A similarity measure that can compute the weights of the edges is then proposed. Subsequently, the video frames are partitioned into different clusters based on the graph model. Double optimal projection is used to explore the optimal mapping points in a low-dimensional space to reduce the video dimensions. The statistics and geometrical fingerprints are generated to determine whether a query video is copied from one of the videos in the database. During matching, the video can be roughly matched by utilizing the statistics fingerprint. Further matching is thereafter performed in the corresponding group using geometrical fingerprints. Experimental results show the good performance of the proposed video fingerprinting method in robustness and discrimination.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Size-controlled synthesis of Mo powders via hydrogen reduction of MoO2 powders with the assistance of Mo nuclei

The size-controlled preparation of Mo powders is always a challenge and important task in the molybdenum metallurgy. In the current study, Mo powders with controllable sizes are synthesized by hydrogen reduction of MoO₂ powders with the assistance of Mo nuclei in the range of 900–1100 °C. The influences of the particle sizes of Mo nuclei, the additive amount as well as reaction temperature on the morphology and particle sizes of the final products are studied. For the hydrogen reduction of MoO₂ without any additive, the obtained Mo powders always have large particle sizes. However, the addition of small amounts of nuclei in MoO₂ can help Mo nucleate dispersedly, and the growth of Mo could be also controlled by adjusting the sizes of added nuclei, amount of addition and the reaction temperature. With the addition of Mo nuclei, the different sizes of Mo powders with the good dispersity can be prepared. As adding commercial Mo powders with the particle size of about 2.03 μm, the micron-sized Mo powders ranged from 2.11 μm to 3.25 μm could be prepared. While for the case of adding ultrafine Mo nuclei of about 170 nm, Mo powders from 0.28 μm to 0.88 μm can be obtained. Moreover, the more the amounts of nuclei added and the lower the reaction temperature (in the range of 900–1100 °C) is, the smaller the particle size of the prepared Mo powder will be. The current method is a facile and feasible method, and is potential to be used for industrial production of Mo powder with controllable particle sizes.     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

IDS告警融合与关联模型的研究

入侵检测是保障网络安全的重要手段,针对现有入侵检测系统中告警数量多、协调性差等问题,论文提出了一种具有告警融合与关联功能的告警处理系统模型,该模型冗余告警量少、整体检测能力强,并能进行攻击企图的预测,能有效提高入侵检测的效率,有助于进一步增强网络的健壮性。     

数据融合在经纬仪引导中的应用

介绍一种用于经纬仪引导数据的处理方法。该方法利用参数估计法对引导数据进行融合，弥补了常规方法的不足。对经纬仪引导数据进行处理，结果表明，该方法可显著提高经纬仪的引导精度，引导误差小于0．50m。     

林达大型低压甲醇合成塔在内蒙天野20万吨/年装置上的应用

简要介绍了林达均温型甲醇塔在内蒙天野20万t/a甲醇装置开车及初步运行情况。运行情况验证了该反应器的先进性,其催化剂床层测温点多、温度分布均匀、运行稳定。     

相关条件下基于N-P准则的分布式检测理论研究

本文针对并行网络、二元局部判决的情况,研究了在相关条件下基于N-P准则的分布式检测融合算法,给出了在联合概率密度已知和未知两种情况下的最优融合规则的理论推导及相应的解决方案,并在实验仿真的基础上,得到了部分有益的结论。     

基于粗糙集信息观的决策表属性约简方法

粗糙集理论是近年来发展起来的一种有效的处理不精确、不确定、含糊信息的数学理论方法，它被广泛应用于相容和不相容决策表的属性约简和核属性计算。利用反例指出目前基于粗糙集信息观[2、6]的决策表属性约简和核属性计算方法的局限性。对决策表的性质作了深入的研究，研究发现文献[2、6]方法的不足原因是：它们没有考虑U／ind（C）中等价类的相客性。给出了基于U／ind（C）中等价类相客性的属性约简定义和核属性定义，并给出了一种新的基于粗糙集信息观的决策表属性约简和核属性计算方法。讨论了该方法同文献[2、6]方法的区别。最后用相同实例验证了该方法的有效性。