模糊综合评价方法在桥型多方案选择中的应用

为了解决现阶段桥型多方案选择中过多依赖设计者经验,而不可避免的带来主观性与片面性的问题.针对桥型方案选择的多因素与模糊性特征,提出了模糊综合评价方法在桥型多方案选择中的应用,确定了影响桥梁选型的指标体系,介绍了该方法的应用模型与步骤,并结合实例详细介绍了这种方法的应用过程.结果验证了这一方法的简明性和实用性.有利于减少桥梁型式选择的失误,提高其客观性与合理性,以得出最佳方案.     

尿液喷浆造粒--生产复合肥的一种新工艺

简述了在团粒法工艺的基础上，用尿素熔融尿液或尿素车间二段蒸发器的尿液进行喷浆造粒生产复合肥的改造方案、改造内容、改造效果和投资情况。     

以888-JH为催化剂Na_2CO_3为碱源的脱硫技术

本文着重介绍以888-JH为催化剂,Na2CO3为碱源焦炉煤气(COG)湿式氧化法脱硫工艺的脱硫原理、影响因素,并介绍了现场试验结果。认定单独使用888-JH可以替代PDS+RTS获得脱硫效率99%以上和出口H2S含量小于5mg/m3的较佳脱硫效果。     

Factors influencing magnetic polymer microspheres prepared by dispersion polymerization

Magnetic iron oxide (Fe₃O₄) was prepared by a coprecipitation method. Core–shell composite magnetic polymer microspheres with carboxyl groups were synthesized by the dispersion polymerization of styrene and acrylic acid in the presence of magnetic oxide, and dibenzoyl peroxide was used as an initiator. The synthesized magnetic polymer microspheres were characterized with X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, and so forth. The results indicated that the product was single‐phase Fe₃O₄, and its average size was about 10 nm. The configuration of the microspheres, which contained carboxyl groups, was spherical, and the average size was about 2 μm. The results of vibrating sample magnetometry tests showed that the magnetic powders produced by different surfactants had different saturation magnetizations. When poly(ethylene glycol) with a weight‐average molecular weight of 4000 was used as a surfactant, the saturation magnetization of the samples reached 69.2 emu/g. The factors that affected the shape, magnetism, size, and distribution of the microspheres were also studied. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

基于显著性的遥感图像舰船目标检测

舰船作为海洋信息感知中的重要目标,其检测在军舰探测、精确制导等军用领域以及海面搜救、渔船监测等民用领域具有极其重要的战略意义.海洋遥感图像受云雾、风浪、海杂波和光照等干扰使得舰船检测具有挑战性.根据可见光遥感图像舰船目标检测特点提出粗检测和细鉴别相结合的技术路线.先基于视觉显著性的谱残差法对图像进行增强以提取目标候选区域,后根据舰船与干扰因素差异采用舰船方向梯度直方图特征对目标候选区域进行鉴别,提取真正的舰船目标.实验结果表明,上述算法舰船检测率高,对光照、海杂波干扰具有一定程度的鲁棒性,且能有效剔除碎云岛屿等干扰物,显著降低虚警率.     

An improved K-means algorithm for underwater image background segmentation

Conventional algorithms fail to obtain satisfactory background segmentation results for underwater images. In this study, an improved K-means algorithm was developed for underwater image background segmentation to address the issue of improper K value determination and minimize the impact of initial centroid position of grayscale image during the gray level quantization of the conventional K-means algorithm. A total of 100 underwater images taken by an underwater robot were sampled to test the aforementioned algorithm in respect of background segmentation validity and time cost. The K value and initial centroid position of grayscale image were optimized. The results were compared to the other three existing algorithms, including the conventional K-means algorithm, the improved Otsu algorithm, and the Canny operator edge extraction method. The experimental results showed that the improved K-means underwater background segmentation algorithm could effectively segment the background of underwater images with a low color cast, low contrast, and blurred edges. Although its cost in time was higher than that of the other three algorithms, it none the less proved more efficient than the time-consuming manual segmentation method. The algorithm proposed in this paper could potentially be used in underwater environments for underwater background segmentation.

     

基于持久性内存的单向移动B^+树

由新型非易失存储介质构成的持久性内存(persistent memory,PM)具有扩展性强、按字节访问与静态能耗低等特性,为未来主存与辅存融合提供了强大的契机.然而由于LLC(last level cache)具有易失性且与主存交互粒度通常为64B,而PM的原子持久化操作粒度为8B.因此,数据从LLC更新到PM的过程中,若发生故障,则可能破坏更新操作的失败原子性,进而影响原始数据的完整性.为了保证更新操作的失败原子性,目前研究主要采用显式调用持久化指令与内存屏障指令,将数据有序地持久化到PM上,但该操作会造成显著的开销,在索引更新中尤为明显.在对索引进行更新时,往往会涉及到索引结构的变化,该变化需要大量的有序持久化开销.研究旨在减少基于PM的B+树在更新过程中为保证失败原子性而引入的持久化开销.通过分析B+树节点利用率、不同更新模式下持久化开销以及更新操作之间的关系,提出了一种基于节点内数据真实分布的数据单向移动算法.通过原地删除的方式,减少删除带来的持久化开销.利用删除操作在节点内留下的空位,减少后续插入操作造成的数据移动,进而减少数据持久化开销.基于上述算法,对B+树的重均衡操作进行优化.最后通过实验证明,相较于最新基于PM的B+树,提出的单向移动B+树能够显著提高单一负载与混合负载性能.     

基于国产处理器增量式实时交通流预测算法及实现

针对城市交通难以处理大量数据且实时性差等问题,提出了根据增量式城市交通流数据预测拥堵情况的一种基于国产处理器的L-BFGS(limited-memory BFGS)算法。该算法通过存储向量序列计算Hessian矩阵,改进Two-Loop算法求下降方向,在Spark集群中并行处理时收敛速度快,适用于实时性要求强的城市交通场景。实验结果证明,L-BFGS预测算法完全可以在国产平台上对大规模的实时交通数据流进行快速建模、预测,在改善城市交通管理水平提供有效支撑的同时也丰富了国产芯片的应用领域。     

采用长短期记忆网络的深度学习方法进行网页正文提取

针对复杂网页上主题信息被过多地与主题无关的广告、导航、版权等噪声信息隐藏的问题,提出一种基于长短期记忆的深度学习正文提取方法(LTE).首先,设计一种根据超文本标记语言(HTML)中标签信息的数据划分策略:通过遍历HTML代码的文档对象模型(DOM)树来根据DOM树结构划分每一个具有文本信息的文本块;然后,通过预训练模型对每一个内容块的从属关系进行表征;最后,这些标签会被输入到用这种格式的数据预先训练好的长短期记忆(LSTM)网络模型进行主要内容正文判别.实验结果证明,模型能够有效拟合已标记的数据集,在训练集中的F1分数能稳定在0.96以上;对于不存在于训练集中的网页格式,对其正文的预测准确度也比两个传统正文抽取工具Readability和Newspaper3k的分别高47.54、19.02个百分点.由实验结果可知,LTE能够有效提取出网页中的正文内容.