用于非合作信号噪底估计的改进自回归算法

非合作接收中由于信道或接收机模拟器件的影响可能导致接收信号功率谱存在噪声基底不平坦现象，为便于划定检测门限需要先估计噪声基底再对原始功率谱进行修正。传统的非线性自回归滑动滤波算法采用固定阈值，仅适用于窄带单信号的噪底估计。改进算法通过增加调节系数实现对阈值的动态调节，并根据功率谱特征计算初始阈值和调节系数，提高了原算法的适应范围和工程实用性。仿真结果表明，改进算法对不同种类的信号具有普适性，能解决原算法无法适应的宽带多信号噪底估计。     

Enhancing claim classification with feature extraction from anomaly-detection-derived routine and peculiarity profiles

Usage-based insurance is becoming the new standard in vehicle insurance; it is therefore relevant to find efficient ways of using insureds' driving data. Applying anomaly detection (AD) to vehicles' trip summaries, we develop a method allowing to derive a “routine” and a “peculiarity” anomaly profile for each vehicle. To this end, AD algorithms are used to compute a routine and a peculiarity anomaly score for each trip a vehicle makes. The former measures the anomaly degree of the trip compared with the other trips made by the concerned vehicle, while the latter measures its anomaly degree compared with trips made by any vehicle. The resulting anomaly scores vectors are used as routine and peculiarity profiles. Features are then extracted from these profiles, for which we investigate the predictive power in the claim classification framework. Using real data, we find that features extracted from the vehicles' peculiarity profile improve the classification.     

连锁董事网络与中国上市公司违规

上市公司违规一直是困扰中国资本市场发展的顽疾，与当前高质量发展要求相违背。本文以2006—2017年沪深A股非金融类上市公司为研究样本，借鉴社会网络研究方法，构建上市公司的连锁董事网络，采用双变量概率单位估计方法，分别探究连锁董事网络与公司违规发生和稽查两过程的关系。研究发现公司的连锁董事网络中心度指标与公司违规后被稽查的概率显著负相关，与公司实施违规的倾向不存在显著关系。本文进行多种拓展性分析，考虑公司间的连锁董事网络构建的差异以及公司个体的财务特征，所得结论与基准回归一致。连锁董事网络作为公司间自发形成的一种组织形式，在预防和打击上市公司违规方面带来了负的外部性，本文间接地为上市公司和监管机构提供了治理和防范公司违规的线索。     

并行多尺度特征增强的小目标检测

由于小目标像素点少，本身携带的特征较少，大多数目标检测算法不能有效利用特征图中小目标的边缘信息和语义信息,导致小目标检测精度低，漏检、误检现象时有发生。为解决RetinaNet模型小目标信息特征不足的缺陷，在RetinaNet模型中引入一个并行辅助的多尺度特征增强模块MFEM(muti-scale feature enhancement model)，通过使用不同扩张率的空洞卷积，避免多次下采样造成信息损失的同时，有利于辅助浅层提取多尺度上下文信息。另外，采用一种专门针对目标检测任务而设计的主干网改进方案，可有效保存高层特征图的小目标信息。传统自上而下的金字塔结构侧重于将高层语义从顶层传递到底层，单向传递的信息流不利于小目标的检测。将辅助MFEM分支与RetinaNet相结合，构造一个包含双向特征金字塔结构的模型，它可有效地融合网络高层强语义信息和底层高分辨率信息。为证明文中算法FE-RetinaNet (Feature Enhancement RetinaNet)的有效性，在MS COCO公共数据集进行实验。与原RetinaNet相比，改进的RetinaNet在MS COCO数据集上检测精度（mAP）取得了1.8%的提升，COCO AP为36.2%；FE-RetinaNet在小目标上检测效果良好，APs提高了3.2%。     

Detecting insurance fraud using supervised and unsupervised machine learning

Fraud is a significant issue for insurance companies, generating much interest in machine learning solutions. Although supervised learning for insurance fraud detection has long been a research focus, unsupervised learning has rarely been studied in this context, and there remains insufficient evidence to guide the choice between these branches of machine learning for insurance fraud detection. Accordingly, this study evaluates supervised and unsupervised learning using proprietary insurance claim data. Furthermore, we conduct a field experiment in cooperation with an insurance company to investigate the performance of each approach in terms of identifying new fraudulent claims. We derive several important findings. Unsupervised learning, especially isolation forests, can successfully detect insurance fraud. Supervised learning also performs strongly, despite few labeled fraud cases. Interestingly, unsupervised and supervised learning detect new fraudulent claims based on different input information. Therefore, for implementation, we suggest understanding supervised and unsupervised methods as complements rather than substitutes.     

基于DSP的电机断条故障在线检测系统设计

针对传统以单片机为核心的电机断条故障在线检测系统计算能力有限,不能实时、有效地进行高速数据处理的缺点,结合数字信号处理器DSP的高精度、高速率的特点,研制了以TMS320F2812为核心的电机断条故障在线检测系统,该系统可以实时采集电机的电流、电压、转速等参数,实时处理采集到的电机数据,在线监测电机状态,系统通过细化包络算法诊断电机断条故障,当有故障出现时发出报警信号,并以自动短信方式通知值班人员,从而保证电机正常运行。     

层状全空间介质中重叠回线的瞬变电磁响应

采用第一类修正贝塞尔函数积分对回线源的瞬变电磁场进行求解，应用法拉第电磁感应原理得到柱坐标系下的瞬态值，研究一维全空间介质的层状递推公式和均匀全空间瞬变电磁场的扩散规律，分析不同回线尺寸大小、经典模型的全空间响应特征，并应用于实测数据。结果表明，回线源产生的瞬变电磁场在空间上具有一定的方向性；回线尺寸增加不影响早期的响应强度，但延后了响应对应的延时时间。均匀全空间层状解的相对误差小于4%，具有较高的精确度；回线半径小于层厚时，低阻层的畸变表现基本在同一时刻，反之则增加。半径减小，使得晚期响应强度明显降低，但扩大了晚期应用范围，增强了纵向分辨率。补充了重叠回线瞬变电磁的理论内容，为矿井全空间观测的工作参数提供参考。     

中国城市轨道交通轮轨力检测技术研究综述

对中国城市轨道交通轮轨力的检测技术进行了系统性的介绍。地面测试方法包括连续测试法和非连续测试法，连续测试法能够对车辆运行状态、车轮多边形等病害进行检测。车载测试方法包括直接测量法和间接测量法，其中连续测力轮对法是目前最常用的测试方法。轮轨力采集系统具有快速、高效、稳定等优势，在地铁动态验收及运维过程中的轮轨力检测中发挥了重要作用。     

Anti-money laundering and financial fraud detection: A systematic literature review

Money laundering has affected the global economy for many years, and there are several methods of solving it presented in the literature. However, when tackling money laundering and financial fraud together there are few methods for solving them. Thus, this study aims to identify methods for anti-money laundering (AML) and financial fraud detection (FFD). A systematic literature review was performed for analysis and research of the methods used, utilizing the SCOPUS and Web of Science databases. Of the 48 articles that aligned with the research theme, 20 used quantitative methods for AML and FFD solution, 13 were literature reviews, 7 used qualitative methods, and 8 used mixed methods. This study contributes by presenting a systematic literature review that fills two research gaps: lack of studies on AML and FFD, and the methods used to solve them. This will assist researchers in identifying gaps and related research.     

油气站场运行异常全息管控平台的建立与应用

为全面保障集气处理站人员和设备安全,提升油气站场智能化水平,基于信息化和物联网技术设计并实现了油气站场运行异常全息管控系统.利用过程安全管理和完整性管理技术建立风险识别管控机制,并构建状态监测、火气监测、腐蚀监测、位移监测、工艺监测和视频监控等多个功能模块,再结合三维全息技术,建立全场景的三维全息数字场站.结果显示,系...