Variations for the <Emphasis Type="Italic">Q</Emphasis>- and <Emphasis Type="Italic">H</Emphasis>-factors in the polar decomposition

In this paper, the variations of both subunitary polar factors and Hermitian positive semidefinite polar factors in the polar decomposition are studied. New perturbation bounds of both polar factors are given without the restriction that A and its perturbed matrix à have the same rank. These improve recent results.     

数据融合技术在消防车检测系统中的研究

文中主要研究消防车检测系统中温度工作状态参数,给出了基于DSP TMS320LF2407为核心的硬件构成,提出了基于多传感器数据检测与数据融合技术的温度采集方法。在多传感器采集数据基础上,采用分布图法去除疏失误差,同时采用自适应加权数据融合算法的方法对采集的数据进行融合。实测表明,采用这种方法可以提高温度采集的精度,同时有效地解决了由于传感器失效引起的误差和单点采集温度的不足。有效地保证了消防车检测系统的实时性和准确性。有一定良好的应用前景。     

基于风险因子的软件项目风险评价模型

以软件项目的启动过程、计划过程、执行过程、控制过程、收尾过程和项目综合管理能力作为六个风险因子,提出了一个风险评价模型,总结了78个风险指标,依据模型计算出各种风险对进度、成本、范围和质量的综合影响。     

Simulation of a liquid-liquid floating interface

The planar interface between two simple liquids interacting with 6-12 LJ potentials was simulated by molecular dynamics at a low temperature. The peculiar physical picture. the new breathing mode, the 2 x 2 matrix of the structure factorsS(k l, and the interfacial dynamic structure factor Slk. ), are reported.Paper presented at the Twelfth Symposium on Thermophysical Properties, June 19–24, 1994, Boulder, Colorado, U.S.A.     

材料加工用激光束质量初探

本文从激光材料加工的角度讨论了以M2参数作为光束质量评价标准的可能性。指出对穿透式的加工方式,M2参数可以表示光束的实用价值,但对表面加工方式,M2参数的大小并不能反映光束实际的实用价值。     

双重JPEG压缩图像篡改区域检测与定位

对JPEG(joint photographic experts group)图像实施篡改往往会产生双重JPEG(double JPEG,DJPE) 压缩痕迹,分析该痕迹有助于揭示图像压缩历史并实现篡改区域定位。现有算法在图像尺寸较小和质量因子(quality factor,QF) 较低的时候性能不佳,对两个QF的组合情况存在限制。本文提出了一种端到端的混合QF双重JPEG压缩图像取证网络,命名为DJPEGNet。首先,使用预处理层从图像头文件中提取表征压缩历史信息的量化表 (quantization table,Qtable) 特征,将图像从空域转换至DCT(discrete cosine transform)域构造统计直方图特征。然后,将两个特征输入到由深度可分离卷积和残差结构堆叠而成的主体结构,输出二分类结果。最后,使用滑动窗口算法自动定位篡改区域并绘制概率分布图。实验结果表明,在使用不同Qtable集生成的小尺寸数据集上,DJPEGNet所有指标均优于现有最先进的算法,其中ACC提高了1.78%,TPR提升了2.00%,TNR提升了1.60%。     

Ultra-Damping Composites Enhanced by Yolk–Shell Piezoelectric Damping Mechanism

High-performance damping materials are significant toward reducing vibration and maintaining stability for industrial applications. Herein, a yolk–shell piezoelectric damping mechanism is reported, which can enhance mechanical energy dissipation and improve damping capability. With the addition of yolk–shell particles and carbon nanotube (CNT) conductive network, damping properties of various resin matrices are enhanced with the energy dissipation path of mechanical to electrical to heat energy. Particularly, the peak loss factor of epoxy composites reaches 1.91 and tan δ area increases by 25.72% at 20 °C. The results prove the general applicability of yolk–shell piezoelectric damping mechanism. Besides, the novel damping materials also exhibit excellent flexibility, stretchability, and resilience, offering a promising application toward damping coating, indicating broad scope of application in transportation and sophisticated electronics, etc.     

High-Efficiency Organic Solar Cells Enabled by Chalcogen Containing Branched Chain Engineering: Balancing Short-Circuit Current and Open-Circuit Voltage,Enhancing Fill Factor

The elaborate balance between the open-circuit voltage (V_OC) and the short-circuit current density (J_SC) is critical to ensure efficient organic solar cells (OSCs). Herein, the chalcogen containing branched chain engineering is employed to address this dilemma. Three novel nonfullerene acceptors (NFAs), named BTP-2O , BTP-O-S , and BTP-2S , featuring different peripheral chalcogen containing branched chains are synthesized. Compared with symmetric BTP-2O and BTP-2S grafting two alkoxy or alkylthio branched chains, the asymmetric BTP-O-S grafting one alkoxy and one alkylthio branched chains shows mediate absorption range, applicable miscibility, and favorable crystallinity. Benefiting from the enhanced π–π stacking and charge transport, an optimal power conversion efficiency (PCE) of 17.3% is obtained for the PM6: BTP-O-S -based devices, with a good balance between V_OC (0.912 V) and J_SC (24.5 mA cm⁻²), and a high fill factor (FF) of 0.775, which is much higher than those of BTP-2O (16.1%) and BTP-2S -based (16.4%) devices. Such a result represents one of the highest efficiencies among the binary OSCs with V_OC surpassing 0.9 V. Moreover, the BTP-O-S -based devices fabricated by using green solvent yield a satisfactory PCE of 17.1%. This work highlights the synergistic effect of alkoxy and alkylthio branched chains for high-performance OSCs by alleviating voltage loss and enhancing FF.     

异质信息网络高阶层次化嵌入学习与推荐预测

异质信息网络是一种异质数据表示形式,如何融合异质数据复杂语义信息,是推荐系统面临的挑战之一.利用弱关系具有的丰富语义和信息传递能力,构建一种面向推荐系统的异质信息网络高阶嵌入学习框架,主要包括:初始化信息嵌入、高阶信息嵌入聚合与推荐预测3个模块.初始化信息嵌入模块首先采用基于弱关系的异质信息网络最佳信任路径筛选算法,有效地避免在全关系异质信息网络中,采样固定数量邻居造成的信息损失,其次利用新定义的基于多头图注意力的多任务共享特征重要性度量因子,筛选出节点的语义信息,并结合交互结构,有效地表征网络节点;高阶信息嵌入聚合模块通过融入弱关系及网络嵌入对知识良好的表征能力,实现高阶信息表达,并利用异质信息网络的层级传播机制,将被采样节点的特征聚合到待预测节点;推荐预测模块利用高阶信息的影响力推荐方法,实现了推荐任务.该框架具有嵌入节点类型丰富、融合共享属性和隐式交互信息等特点.最后,实验验证UI-HEHo学习框架可有效地改善评级预测的准确性,以及推荐生成的针对性、新颖性和多样性,尤其是在数据稀疏的应用场景中,具有良好的推荐效果.