Detecting Periods of Significant Increased Communication Levels for Subgroups of Targeted Individuals

This paper investigates detecting significant increases in communication patterns and levels between small groups of individuals within a moderate‐size targeted group. Potential applications range from trying to establish emerging thought leaders within an organisation to the detection of the planning stages of a crime. The scan statistic is a popular choice for monitoring and detecting spatio‐temporal outbreaks, but it is difficult to apply to large‐scale target groups because of the computational effort required. When monitoring communication levels between thousands of people, the number of combinations of people whose communication may have increased is very high, and to scan through all of these to find which combinations have increased communications significantly is an enormous task. A successful surveillance plan will have early communication outbreak detection properties and good diagnostic capabilities for identifying individuals contributing to this outbreak. This paper proposes a new computationally feasible approach for detecting communication outbreaks based on exponentially weighted moving average smoothed communication counts between individuals within the network. We apply a cumulative sum of ordered signal‐to‐noise (SN) ratios for communication counts to flag significant departures from their respective median values. This plan is demonstrated to be efficient at detecting changes in communication levels for a small part of the network and diagnosing who is involved in the outbreak. Copyright © 2015 John Wiley & Sons, Ltd.     

提升交互过程时间体验的实验研究

目的通过设计手段来提升交互过程中的用户时间体验。方法以时间心理学为理论基础分析和总结影响人们时间体验的主要因素;以设计和心理学实验挖掘实验载体和进行效果测试。结果提出了设计提升时间体验的策略和原则并以交通灯红灯信号为对象建立假设和实验。基于时距估计的策略和人的时间信号读取习惯对红灯的2个变量——形状和速度进行考察,发现各样本2个变量的不同水平能够引起的时距估计和情绪状况变化。结论验证了时间信号的传达形式可以影响人的时距认知过程从而对提升时间体验具备实际的效果。     

RME:基于滑动窗口的实时人脸检测算法

研究了基于滑动窗口的视频实时人脸检测,提出了刚性运动估计(RME)算法.该算法以小尺度人脸瞬时刚性运动为假设,根据几何变换对窗口图像的运动进行描述,以光流代替运动矢量计算运动参数进而识别窗口图像的刚性、非刚性运动类型,通过排除非刚性窗口以提高人脸检测效率.对比实验与分析表明,该算法在准确率与时间效率方面具有优势.     

Structural damage diagnosis using incomplete static responses and LS-SVM

This paper presents novel approach to structural damage detection and estimation using incomplete static responses of a damaged structure and least squares support vector machine (LS-SVM). The presented method is based on the reduced stiffness matrix to formulate incomplete static responses as input parameters to the LS-SVM. The presented method is applied to a plane steel bridge, a four-span continuous beam and four-storey plane frame containing several damages. Also, the effect of the discrepancy in stiffness between the finite element model and the actual tested system has been investigated. The results show that the presented method is sensitive to the location and severity of the structural damage in spite of the incomplete noisy data and modelling errors.     

自适应聚类Hough变换及地震断层检测

针对现有基于Hough变换的地震断层检测方法只能检测单个断层,不能准确检测多个断层的不足,提出了一种基于自适应聚类Hough变换的地震断层检测方法。该方法首先对预处理后的地震相干图像进行边缘检测并对边缘图像进行Hough变换以检测出边缘图像中的线段,然后根据倾斜角和位置信息对线段进行自适应聚类以获得更完整的线段,最后根据初始地震图像对完整线段中的各点进行调整以获得准确、平滑的断层。为验证该方法的有效性,在实际地震图像上进行了对比实验。实验结果表明,该方法可正确检测地震图像中的多个断层,正确率达到90%以上,与现有方法相比,峰值信噪比提高了约10%。     

Distinguishable Detection of Ultraviolet,Visible, and Infrared Spectrum with High‐Responsivity Perovskite‐Based Flexible Photosensors

Distinguishable detection of the ultraviolet, visible, and infrared spectrum is promising and significant for the super visual system of artificial intelligences. However, it is challenging to provide a photosensor with such broad spectral response ability. In this work, the ultraviolet, visible, and infrared spectrum is distinguished by developing serial photosensors based on perovskite/carbon nanotube hybrids. Oraganolead halide perovskites (CH₃NH₃PbX₃) possess remarkable optoelectronic properties and tunable optical band gaps by changing the halogens, and integration with single‐walled carbon nanotubes can further improve their photoresponsivities. The CH₃NH₃PbCl₃‐based photosensor shows a responsivity up to 10⁵ A W^?1 to ultraviolet and no obvious response to visible light, which is superior to that of most ultraviolet sensors. The CH₃NH₃PbBr₃‐based photosensor exhibits a high responsivity to visible light. Serial devices of the two hybrid photosensors with comparable electric and sensory performances can distinguish the spectrum of ultraviolet, visible, and infrared even with varying light intensities. The photosensors also demonstrate excellent mechanical flexibility and bending stability. By taking full advantages of the oraganolead halide perovskites, this work provides flexible high‐responsivity photosensors specialized for ultraviolet, and gives a simple strategy for distinguishable detection of ultraviolet, visible, and infrared spectrum based on the serial flexible photosensors.     

Recent Advances in Passive Digital Image Security Forensics: A Brief Review

With the development of sophisticated image editing and manipulation tools, the originality and authenticity of a digital image is usually hard to determine visually. In order to detect digital image forgeries, various kinds of digital image forensics techniques have been proposed in the last decade. Compared with active forensics approaches that require embedding additional information, passive forensics approaches are more popular due to their wider application scenario, and have attracted increasing academic and industrial research interests. Generally speaking, passive digital image forensics detects image forgeries based on the fact that there are certain intrinsic patterns in the original image left during image acquisition or storage, or specific patterns in image forgeries left during the image storage or editing. By analyzing the above patterns, the originality of an image can be authenticated. In this paper, a brief review on passive digital image forensic methods is presented in order to provide a comprehensive introduction on recent advances in this rapidly developing research area. These forensics approaches are divided into three categories based on the various kinds of traces they can be used to track—that is, traces left in image acquisition, traces left in image storage, and traces left in image editing. For each category, the forensics scenario, the underlying rationale, and state-of-the-art methodologies are elaborated. Moreover, the major limitations of the current image forensics approaches are discussed in order to point out some possible research directions or focuses in these areas.     

基于XMC4500的汽车CAN网络检测卡设计

CAN总线作为车用网络的主要应用总线技术,通过CAN总线获得汽车运行时的实时数据成为汽车电子系统研发、维修及故障分析的主要手段;在对传统CAN总线检测卡分析及研究的基础上,为了使移动PC更加便捷地分析及记录汽车CAN网络中的数据,使基于串口通讯的系统及应用软件能够方便地继承使用,设计了基于XMC4500单片机的汽车CAN网络检测卡;实现了将汽车CAN网络中的数据通过USB端口虚拟的高速串口传输至上位机、实时备份相关数据到Micro SD卡中的功能;实验数据显示在最高1 000kb/s的传输速率下,能够100%正确接收及存储相关数据,满足对该卡实时性和可靠性的要求。     

基于YOLOV4的工件表面质量在线检测方法研究

目的 提升自动化产线上工件表面微小缺陷的检测精度和检测速度。方法 首先,在预处理阶段提出采用CutMix的数据增强方法,增加训练样本的多样性,提高模型的鲁棒性和泛化能力,避免训练模型产生过拟合;使用K–means++聚类算法生成边界候选框,以适应不同尺寸的缺陷,并较早地筛选出更精细的特征。其次,借助CSP Darknet53网络及SPP模块提取输入原始图像的特征,通过训练获得针对工件表面质量的在线检测模型,提升YOLOV4缺陷位置检测及识别的精度。结果 实验结果表明,文中所提出的基于YOLOV4的工件表面质量在线监测方法的预测精度达到97.5%,检测速度达到32.8帧/s,均优于同类的深度学习算法。以贵州某航空工业产品的自动化产线作为实验平台验证了所提方法的可行性和有效性。结论 该方法具备结构简单清晰、自适应性强等优点,检测精度和速度均满足工业场景需求,可以将其用于产品表面质量的在线检测。