A3钢表面有机膦合钼聚多酸盐转化膜的研究

由Ｎａ２ＭｏＯ４·２Ｈ２Ｏ和Ｎａ２ＨＥＤＰ·５Ｈ２Ｏ合成了有机膦合钼聚多酸盐Ｎａ８［（ＨＥＤＰ）２Ｍｏ５Ｏ２１］·５Ｈ２Ｏ。用Ｎａ８［（ＨＥＤＰ）２Ｍｏ５Ｏ２１］·５Ｈ２Ｏ的溶液处理Ａ３钢，获得了具有一定耐蚀性的黄色转化膜，适宜的工艺条件为：浓度１６ｇ·Ｌ－１，ｐＨ３．５，温度５０℃，时间８０ｓ。本文还报告了膜层的ＸＰＳ和ＡＥＳ分析结果。     

基于K-shell位置和两阶邻居的复杂网络节点重要性评估方法

K-shell分解法能快速识别复杂网络中的关键节点,但是无法辨别同壳层内节点重要性的差异,并且低估了处于网络边缘位置的高度值节点的重要性。针对这两个问题,提出一种基于K-shell位置和两阶邻居的节点重要性评估方法。该方法根据K-shell分解过程中节点移除的顺序细化节点的全局位置信息,然后综合考虑节点的局部拓扑结构信息和全局位置信息,利用两步长内邻居节点的K-shell位置信息度量节点的重要性。在八个真实网络上用传染病模型进行仿真实验,结果表明,所提方法与其他五种相关方法相比能更准确有效地评估并区分节点的重要性。     

融合语义差别和流型学习的偏标记学习方法

偏标记学习是一种重要的弱监督学习框架。在偏标记学习中,每个实例与一组候选标记相关联,它的真实标记隐藏在候选标记集合中,且在学习过程中不可获知。为了消除候选标记对学习过程的影响,提出了一种融合实例语义差别最大化和流型学习的偏标记学习方法(partial label learning by semantic difference and manifold learning, PL-SDML)。该方法是一个两阶段的方法：在训练阶段,基于实例的语义差别最大化准则和流型学习方法为训练实例生成标记置信度;在预测阶段,使用基于最近邻投票的方法为未知实例预测标记类别。在四组人工改造的UCI数据集中,在平均70%的情况下优于其他对比算法。在四组真实偏标记数据集中,相比其他对比算法,取得了0.3%～13.8%的性能提升。     

Clustering research fields for macro-strategic analysis: A comparative specialization approach

The goal of this article is to show that it is possible to construct an index to measure a country's relative specialization in different scientific fields in a way which is both reliable and relevant for macro-strategic analysis. We will call this index a Revealed Scientific Advantages Index. The technical problem to be discussed is one of aggregation: how can we be sure that an index calculated for a small number of relatively large fields does not mask significant policy needs synthetic measures which are easy to interpret. We will show that the Revealed Scientific Advantages approach offers the possibility of building them. The study itself is based on figures obtained through an exploitation of the INIST/CNRS PASCAL database classification of science. 107 sub-fields of this classification were initially used to determine the areas of specialization for 11 countries (revealed national advantages). Clustering techniques were then used to aggregate this data and 13 specific fields were identified. The science policy information produced during the study concerned these 13 fields. It proved to be both easily understandable and relevant for macro-strategic analysis.     

Ageing characteristics of dendritic and non-dendritic (stir-cast) Zn-Al alloy (ZA-27)

The dimensional changes of dendritic and non-dendritic (stir-cast) Zn-Al alloy (ZA-27) were investigated during ageing at temperatures in the range 20–245 °C. The linear expansion of both dendritic and non-dendritic samples increased rapidly with ageing time after about 24 h at 95 °C. An initial normalization treatment led to a large initial growth of the alloy which increased further after prolonged ageing times ( 10⁴h). Accelerated ageing tests in the range 75–250 °C showed that increasing the ageing temperature decreased the long term linear expansion of the alloy. In comparing the behaviour of the two materials, the stir-cast material grew less than the dendritic alloy. Extensive SEM and TEM done on as-stir-cast and aged samples showed that the main changes during ageing occurred in the (FCC) lamellae of the +(Zn) eutectoid, the phase at the primary _particles/_eutectoid interface and in the interparticle areas. In the lamellae and at the interface, zinc precipitated whilst the phase precipitated in the interparticle areas. It is considered that the occurrence of this latter phase, rich in copper, is responsible for the growth of stir-cast material during ageing.     

Capture device identification from digital images using Kullback-Leibler divergence

Multimedia Tools and Applications - It is proposed a forensic method for the capture device identification from digital images, which requires two elements: i) a digital image subject to...     

Faceless identification based on temporal strips

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)² and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.

     

Study of UAV tracking based on CNN in noisy environment

Multimedia Tools and Applications - Recently, there are lots of tracking methods proposed to improve the performance of visual tracking in videos with challenging situations, such as background...     

基于多次散射目标模型的雷达成像研究

合成孔径雷达（Synthetic Aperture Radar, SAR）作为一种主动微波传感器,被广泛应用于遥感对地观测。然而,传统上的雷达散射模型是基于几何光学近似的,忽略了地物目标之间的相互作用,即多次散射效应。为了充分挖掘和利用毫米波雷达影像中目标电磁散射特性信息,亟需对典型目标的多次散射效应进行建模仿真和验证。基于矩量法（Method of Moments, MoM）分析了球体、二面角等目标表面等效电流分布与分段成像结果的对应关系,并利用后向投影（Back-Projection, BP）算法进行电磁仿真成像,总结了单/双基地雷达模式对成像中散射机制的影响。结果表明：目标表面等效电流分布以及分段等效合成孔径张角会随入射角度发生改变,其中分段等效合成孔径张角会影响方位向分辨率;双基地雷达成像结果中包含更丰富的电磁散射信息。本研究可为SAR系统设计和验证、典型目标回波特性数据收集以及如何基于高解析度SAR影像进行目标识别等研究提供借鉴与参考。