THE DEVELOPMENT OF AERONAUTICAL SATELLITE COMMUNICATIONS (Ⅰ)

This paper presents an overview of the development of aeronautical satellite communi-cations over the past 30 years. The initial development of aeronautical satellite communications is de-scribed in the paper. The civil aviation growth and current unaccommodated communication systemsare discussed as well. The inherent shortcomings of present air-ground HF communications have hin-dered the development of civil aviation. but according to the Future Air Navigation Systems(FANS) concept aeronautical satellite communication-including Automatic Dependent Surveillance(ADS)-will be the key to eliminating the shortcomings of HF communication systems. Satellite-basedcommunication and surveillance will significantly improve air traffic control (ATC) over the oceanicand remote terrestrial airspace, and it will benefit civil aviation authorities, airlines as wel as passen-gers. This paper discusses the availability of system elements, and world wide trials, demonstrtionsand preoperational use of aeronautical satelli     

Analysis of radionuclide retention in water pools

An analysis is presented of the removal of aerosol particles and gaseous fission products from steam-noncondensable gas mixtures rising through water pools. The pool is divided into a gas injection zone, a bubble rise zone and a pool surface zone. The formulation of the governing conservation equations is relatively general with a quasi-steady one-dimensional formulation for the gas phase, and an unsteady, well stirred, formulation for the liquid phase. An associated computer code for performing the calculations, SUPRA, is described. Results of parametric calculations are given for conditions expected in a BWR severely degraded core accident sequence. Parameters studied include aerosol particle size and distribution, mass fraction of noncondensable gas, gas mass flow rate, quencher submergence depth, and pool water temperature.     

遥控履带小车视频监控系统设计

无线遥控履带小车系统的设计是多种专业知识的大融合,在军事、科研和工业中有较大的发展前景。小车上电池电压、光电、碰撞、电动机电流传感器、反碰撞系统和编码器的应用,保证了小车行走时的安全及运行状态各个参数的实时反馈。通过无线网络对履带小车进行实时控制与视频采集,上位机能够及时存储所得的视频及控制数据,便于以后对小车性能及目的地视频进行分析。在人无法进入的恶劣条件下,小车对目的地画面进行实时传送,为分析目的地的情况提供了可靠的依据。     

基于内容的海量监控视频的多层次检索系统

设计和实现了一种基于内容的海量监控视频的多层次检索系统。该系统首先从监控视频中提取关键帧图像,其次利用行人检测、人脸识别及车辆检测等算法将关键帧中的行人图像、人脸图像和车辆图像等感兴趣目标提取出来,然后提取这些图像的颜色、纹理等特征,利用改进的LIRe(Lucene Image Retrieval)建立分布式的特征库,最终形成了多层次的信息数据库。实验表明,该系统具有较高的检索准确率和较快的检索速率,并支持海量监控视频的检索。     

光伏专用电源模块的应用

本文主要介绍一款光伏专用模块电源在光伏监控系统上的应用。传统的光伏监控系统需要一个独立的供电电源系统给监控、控制的电路供电。该供电电源可能是蓄电池或市电电压,由于光伏发电站往往位置偏远,光伏电池占地面积宽广,使得供电系统布线困难,布线和维护成本都较高。光伏电源一改传统的供电方式,针对目前光伏阵列组直流输出电压一般为200VDC-1000VDC的高电压、超宽输入范围的特性,直接从光伏阵列组上取电为其后端负载电路供电,可以使设计电路更加简便,使用方式更加灵活。同时,自带的多重保护功能,可提升模块在电源工作出现异常的情况下电源及其负载的安全性能。     

SOINN-Based Abnormal Trajectory Detection for Efficient Video Condensation

With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the trajectory feature is the key to both goals, in this paper, a new method for feature extraction of moving object trajectory is proposed, and we use the SOINN (Self-Organizing Incremental Neural Network) method to accomplish a high accuracy abnormal detection. In the results, our method is able to shirk the video size to 10% storage size of the original video, and achieves 95% accuracy of abnormal event detection, which shows our method is useful and applicable to the surveillance industry.     

‘I am not a number’: Conceptualising identity in digital surveillance

Surveillance, now a commonplace phenomenon in everyday life, has been explored from various disciplines over three decades. Today's surveillance practices depend primarily upon many software technologies that collect, store and process personal data for the purposes of influence, management, protection or detection. The identification and categorisation of data have thus emerged as the technical signature of surveillance. An individual has many identities belonging to different contexts of his/her life, but in this paper, we explore the relationship between surveillance and identity in virtual contexts only. We argue that an understanding of identity purely as data is fundamental to understanding surveillance. We propose abstract general definitions of surveillance and identity that together create a conceptual framework, capturing key features common to many disparate surveillance situations. Our work concludes that the essence of surveillance is that of a surveillance context, which is precisely and solely defined by the availability of data about the behaviour and identity of its entities. The data that distinguishes the entities of the context we call identifiers; we explore the creation, provenance, comparison and transformation of identifiers. Abstractly, surveillance is a process that tests for properties of data, and sorts identifiers into categories.     

Background foreground boundary aware efficient motion search for surveillance videos

The huge amount of data in surveillance video coding demands high compression rates with lower computational requirements for efficient storage and archival. The motion estimation is a very time-consuming process in the traditional video coding framework, and hence reducing computational complexity is a pressing task, especially for surveillance videos. The presence of significant background proportion in surveillance videos makes its special case for coding. The existing surveillance video coding methods propose separate search mechanisms for background and foreground regions. However, they still suffer from misclassification and inefficient search strategies since it does not consider the inherent motion characteristics of the foreground regions. In this paper, a background-foreground-boundary aware block matching algorithm is proposed to exploit special characteristics of the surveillance videos. A novel three-step framework is proposed for boundary aware block matching process. For this, firstly, the blocks are categorized into three classes, namely, background, foreground, and boundary blocks. Secondly, the motion search is performed by employing different search strategies for each class. The zero-motion vector-based search is employed for background blocks. Whereas, to exploit fast and directional motion characteristics of the boundary and foreground blocks, the eight rotating uni-wing diamond search patterns are proposed. Thirdly, the speed-up is achieved through the novel region-based sub-sampled structure. The experimental results demonstrate that two to four times speed-up over existing methods can be achieved through this scheme while maintaining better matching accuracy.     

A regional distance regression network for monocular object distance estimation

Monocular pipelines are convenient and cost-effective solutions for object distance estimation in 3D vision. Current methods for monocular object distance estimation either perform inaccurately or require heavy work on data collection. In this paper, we propose a network with R-CNN based structure to implement object detection and distance estimation simultaneously. We append an efficient branch to integrate the information of camera extrinsic parameters with RGB data in our network. Further, optimized multi-scale feature is utilized to enrich the representation power of deep feature, hence to enhance the estimation accuracy. Finally, several regression methods are explored to improve distance estimation results. We train and validate our network on KITTI object dataset, and compare with other methods to show that our method is accurate and easy to train. To prove the generality of our method under other scenarios, we construct a dataset of surveillance scenes, and conduct similar experiments on this dataset.     

2019年江苏省部分地区儿童腹泻沙门氏菌的感染率及耐药状况研究

目的 了解江苏省部分地区2019年5岁以下食源性腹泻儿童中沙门氏菌感染的流行病学特征、血清分布及耐药性。方法 从江苏省各设区市哨点医院肠道门诊采集食源性腹泻患儿粪便标本,按照江苏省食源性疾病监测方案进行细菌的分离与鉴定、血清分型,用微量肉汤稀释法进行药敏试验。结果共收集3582份腹泻儿童粪便,沙门氏菌的检出率为2.9％,1～2岁患儿居多。全年均有检出,夏季高发。共有24种血清型的沙门氏菌,优势血清型为鼠伤寒沙门氏菌和肠炎沙门氏菌,分别占41.9％和18.1％。耐药检测结果显示,沙门氏菌对红霉素的耐药率最高,达96.1%。其次为氨苄西林、氨苄西林/ 舒巴坦、萘啶酸和四环素,分别为67.5%、56.6%、53.5%和51.3%;对甲氧苄氨嘧啶/磺胺甲噁唑、氯霉素和环丙沙星呈现中度耐药,耐药率分别为33.3％,31.6％和26.8％;对一、二、三代头孢类抗生素的耐药率有显著性差异。对阿奇霉素和亚胺培南的耐药率较低,为7.5％和2.6％。多重耐药率达72.4％。结论 江苏省部分地区腹泻儿童沙门氏菌感染以1～2岁高发,男孩多于女孩。主要血清型是鼠伤寒沙门氏菌和肠炎沙门氏菌,多重耐药现象严重,在临床用药时应选择较为敏感的药物。