基于深度学习的视频跟踪研究进展综述

近年来深度学习迅猛发展，颠覆了语音识别、图像分类、文本理解等领域的算法设计思路。深度学习因其具备强大的特征提取能力，在图像识别领域的成绩尤为突出。然而深度学习与视频监控领域的结合并不多，由于深度模型具有多层网络结构，算法复杂度大，训练和更新模型时比较耗时，很难满足实时性要求。回顾了深度学习的发展史，介绍了最近10年来国内外深度学习主要模型，论述了基于深度学习的目标跟踪算法，指出了各算法的优缺点，最后对当前该领域存在的问题和发展前景进行了总结和展望。     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

影响煤层气开发效果的地质因素再认识

地质特征认识对煤层气开发效果起着重要作用。在资源特征相差不大的情况下,发现煤层气相邻井的产量差异仍较大。排除工程因素后,通过选取8类地质参数,细致比对了保德区块低产井与邻井的参数特征,筛查出其关键因素为煤层微幅构造与顶板封盖条件,其中以微幅构造为主。据此,重新认识并划分出区块新的次生褶皱背斜单元、向斜单元和斜坡单元,获得了不同次生褶皱构造单元的开发特征。结果表明,高、低产井分布与次生褶皱背斜、向斜相关性高达92%。其中:高产井主要分布在次生褶皱背斜变化较缓、呈隆起状的“平台”,且煤层顶板以泥岩、碳质泥岩为主,封盖性较好;低产井主要分布在次生褶皱向斜,同一井台各井开发效果差异表现为从向斜条带轴部—向斜条带内—向斜条带外的煤层气井平均单井产量不断增加,到向斜轴部的距离大于向斜曲率半径73.5%的范围为主力产气区,小于向斜曲率半径40.0%范围为产水主力区。这对煤层气新井部署、生产管理、开发调整等,具有一定的指导意义。     

Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.     

空气预热器实时监控系统堵塞可视化性能研究

针对电站锅炉回转式空气预热器运行时上下表面不可见的问题，本文提出了一种视频监控与故障分析系统，可直接监测转子表面情况。该系统通过视频监控获取图像，结合改进的Retinex算法对其进行处理，实现了以下2个功能:1）能分析积灰程度以判断转子堵塞 情况；2）与温度场融合实时显示转子表面热点分布以预防二次燃烧。该系统已应用于某600 MW机组，实现了在热态环境下对空气预热器转子积灰程度、热点分布、堵塞程度的估算与可视化，大大提高了空气预热器运行的可靠性。     

Cross-Layer Optimization of Dynamic Packet Assignment for Video Transmission Over IEEE 802.11e Networks

Video transmission over IEEE 802.11e wireless networks still shows poor performance for large bandwidth demand and frequently changed environments. Thus, several enhancements of IEEE 802.11e were proposed. On the other hand, big frames and simultaneous sending of adjacent frames always cause packet dropping for buffer overflow. In the past, we proposed an IEEE 802.11e enhancement named DFAA and a content aware mechanism to solve the above problems. The motivation of this paper is to find a proper way to integrate these two mechanisms. A DFAA enhancement (DFAA-E) is proposed to make up the insufficiency of content aware mechanism. Experiments results show that the combination of DFAA-E and content aware mechanism improves the video decoded quality greatly. And its performance can be further enhanced by selecting the suitable settings of certain parameters.