Applications of sketches in network traffic measurement: A survey

Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions.     

电容式力感知牙周探针设计建模与实验研究

针对当前牙周探针在探诊力控制方面的不足,提出一种基于悬臂梁挠曲效应的差动电容式力感知牙周探针解决方案,设计了探针验证结构,建立了探诊力作用下具有不规则形状的探针工作尖的挠曲模型,导出了探诊力和差动电容之间的求解方程,并通过仿真和实验对模型与方程进行了验证。结果表明,所建立的探针工作尖挠曲模型与静应力仿真结果的最大相对误差不超过±4.5%,所设计的力感知牙周探针多次重复探诊力检测实验的标准差小于均值的0.1%,所导出的求解方程的计算值与实验数据之间趋向一致,以探诊力为拟合权重进行修正后全量程的平均偏差为2.49%,具备进一步产品开发的可行性。     

基于全U网络的混凝土路面裂缝检测算法

针对现有的混凝土裂缝检测算法在各种复杂环境中检测精度不够、鲁棒性不强的问题,根据深度学习理论和U-net模型,提出一种全U型网络的裂缝检测算法。首先,依照原U-net模型路线构建网络;然后,在每个池化层后都进行一次上采样,恢复其在池化层之前的特征图规格,并将其与池化之前的卷积层进行融合,将融合之后的特征图作为新的融合层与原U-net网络上采样之后的网络层进行融合;最后,为了验证算法的有效性,在测试集中进行实验。结果表明,所提算法的平均精确率可达到83.48%,召回率为85.08%,F1为84.11%,相较于原U-net分别提升了1.48%,4.68%和3.29%,在复杂环境中也能提取完整裂缝,保证了裂缝检测的鲁棒性。     

印刷电路板缺陷检测的实际应用

电路板在我们的日常生活中非常常见,这就使得印刷电路板的缺陷检测显得尤为重要。AOI作为新兴的检测PCB板缺陷的系统,在生产实际中正在被大家熟知并且应用。相较于传统的检测方式,AOI系统比较灵活,无论是在检测时间还是系统运算上,或者是对相关技术人员的要求相较于传统方式都比较有优势,本文就AOI系统在实际中的应用展开讨论,分析并且介绍了在实际应用中的具体细则。     

YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

新型无机内保温涂层的性能及应用

根据水泥烧成热耗的组成，降低高温设备表面散热是降低水泥烧成热耗的重要途径之一，而减少高温窑炉墙壁的热传导可有效降低设备的表面散热。本文在介绍无机内保温涂层隔热原理的基础上，对保温涂层的应用效果进行了对比研究，通过在传统耐火隔热材料的基础上增加新型无机内保温涂层，可有效降低高温设备外表面温度，减少水泥生产中的散热损失，达到节能降耗的目的。     

环境中污染源废气检测方法及影响因素分析

对污染源废气监测原理进行了简单分析,阐述了当前我国常用的环境中污染源废气检测方法,并对废气检测影响因素及质量控制进行了深入探究。     

新发展阶段中国水资源安全保障战略对策

进入新发展阶段，中国水资源安全保障需要以“节水优先、空间均衡、系统治理、两手发力”治水思路为指导，厘清问题、研判趋势、优化对策，支撑新阶段水利高质量发展。本文在全面分析我国水资源安全保障存在的突出问题与面临形势基础上，阐述了新发展阶段中国水资源安全保障的基本思路与战略路径，从保证资源安全、构建国家水网、强化供水保障、建设美丽河湖、改善水环境质量等方面提出了战略对策和需要进一步回答的重大问题，以期为完善新发展阶段中国水资源安全保障战略，全面提高国家水资源安全保障能力提供有力支撑。