Real-time Audio &Video Transmission System Based on Visible Light Communication

With the increasing popularity of solid sate lighting devices, Visible Light Communication (VLC) is globally recognized as an advanced and promising technology to realize short-range, high speed as well as large capacity wireless data transmission. In this paper, we propose a prototype of real-time audio and video broadcast system using inexpensive commercially available light emitting diode (LED) lamps. Experimental results show that real-time high quality audio and video with the maximum distance of 3 m can be achieved through proper layout of LED sources and improvement of concentration effects. Lighting model within room environment is designed and simulated which indicates close relationship between layout of light sources and distribution of illuminance.

Real-time 3-D space numerical shake prediction for earthquake early warning

In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake pre- diction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.

Real-time numerical shake prediction and updating for earthquake early warning

Ground motion prediction is important for earthquake early warning systems, because the region＇s peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and pre- cisely with limited station wave records, we propose a real- time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 Ms8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.

Adaptive Learning Video Streaming with QoE in Multi-Home Heterogeneous Networks

In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.

生殖医学教学视频的拍摄与应用

随着辅助生殖技术的发展、三孩政策开放及人口出生率的下降,生殖中心在全国各大医院中发挥着越来越重要的作用。然而,目前无论是临床医学生还是广大的不孕症患者对生殖医学相关知识的了解依旧是凤毛麟角。一方面,生殖医学的知识在五年制甚至八年制的医学教材中的占比很小,学生们通过课本的知识只能了解到生殖领域中的冰山一角。另一方面,随着不孕症患者的上涨,亟须向他们科普更多的生殖医学相关知识。文章从辅助生殖技术的相关视频拍摄及其应用两方面进行详细阐述,借此将辅助生殖技术更好地展现在临床医学生们及不孕症患者面前,增加医学生对生殖医学专业的兴趣,以培养更多的医学人才、解决不孕这个社会难题,同时让非生殖医学专业的医师们加强生育力保护的理念。

一种基于HTTP/3传输特性的加密视频识别方法

视频流量逐渐在网络中占据主导地位,且视频平台大多对其进行加密传输。虽然加密传输视频可以有效保护用户隐私,但是也增加了监管有害视频传播的难度.现有的加密视频识别方法基于TCP(Transmission Control Protocol)传输协议头部信息和HTTP/1.1(HypertextTransferProtocol Version1.1)的传输模式,提取应用层音视频数据单元传输长度序列来实现视频识别.但是随着基于UDP(UserDatagramProtocol)的QUIC(QuickUDP Internet Connections)协议及基于QUIC实现的HTTP/3(HypertextTransferProtocol Version 3)协议应用于视频传输,已有方法不再适用.HTTP/3协议缺少类似TCP的头部信息,且使用了多路复用机制,并对几乎所有数据进行了加密,此外,视频平台开始使用多片段合并分发技术,这给从网络流量中精准识别加密视频带来了巨大挑战。本文基于HTTP/3协议中的控制信息特征,提出了从HTTP/3加密视频流中提取数据传输特征并进行修正的方法,最大程度复原出应用层音视频长度特征.面向多片段合并分发导致的海量匹配问题,本文基于明文指纹库设计了键值数据库来实现视频的快速识别.实验结果表明,本文提出的基于HTTP/3传输特性的加密视频识别方法能够在包含36万个真实视频指纹的YouTube大规模指纹库中达到接近99%的准确率,100%的精确率以及99.32%的F1得分,对传输过程中加人了填充顿的Facebook平台,在包含28万个真实视频指纹的大规模指纹库中达到95%的准确率、100%的精确率以及96.45%的F1得分,在具有同样特性的Instagram平台中,最高可达到97.57%的F1得分,且本方法在所有指纹库中的平均视频识别时间均低于0.4秒.本文的方法首次解决了使用HTTP/3传输的加密视频在大规模指纹库场景中的识别问题,具有很强的实用性和通用性.

面向摄像头视频监控的泥石流发生场景智能识别方法

摄像头视频监控在泥石流防灾减灾中的应用较为广泛,但现有的视频检测技术功能有限,无法自动判断出泥石流灾害事件的发生。针对这一问题,本文基于迁移学习策略,改进一种基于卷积神经网络的视频分类方法。首先,借助TSN模型框架,将底层网络架构更改为ResNet-50,用于运动特征提取和泥石流场景识别。然后,通过ImageNet和Kinet-ics-400数据集预训练该模型,使模型具备较强的泛化能力。最后,结合经过预处理的地质灾害视频数据集对模型进行训练和微调,使其能够精准地识别出泥石流事件。通过大量的运动场景视频对该模型进行检验,实验结果表明,该方法对泥石流运动场景视频的识别准确率可达87.73%。因此,本文的研究成果可充分发挥视频监控在泥石流监测预警中的作用。

RTP payload format for H.264/SVC scalable video coding

The scalable extension of H.264/AVC, known as scalable video coding or SVC, is currently the main focus of the Joint Video Team’s work. In its present working draft, the higher level syntax of SVC follows the design principles of H.264/AVC. Self-contained network abstraction layer units (NAL units) form natural entities for packetization. The SVC specification is by no means finalized yet, but nevertheless the work towards an optimized RTP payload format has already started. RFC 3984, the RTP payload specification for H.264/AVC has been taken as a starting point, but it became quickly clear that the scalable features of SVC require adaptation in at least the areas of capability/operation point signaling and documentation of the extended NAL unit header. This paper first gives an overview of the history of scalable video coding, and then reviews the video coding layer (VCL) and NAL of the latest SVC draft specification. Finally, it discusses different aspects of the draft SVC RTP payload format, in- cluding the design criteria, use cases, signaling and payload structure.

Influence of longitudinal magnetic field on metal transfer in MIG arc welding

Metal transfer is an important phenomenon in metal inert gas （MIG） arc welding with longitudinal alternating magnetic field. It is of great significance to observe the metal transfer modes under different excitatory currents and frequencies. However, it is very difficult to view the metal transfer process directly during welding, due to the strong interference from the arc light. To obtain the relationship between the metal transfer modes and the different magnetic fields, a high-speed video camera was used to acquire the images of globules. Different metal transfer modes under the conditions of different magnetic fields and welding parameters were studied. The experiment shows clear images of droplet transfer as well as influence of longitudinal magnetic field on both metal transfer and globule shape.

Delphi中基于VideocapX ActiveX控件的视频采集系统的实现

以WindowsXP作为开发平台,Delphi2005作为开发工具,采用VideocapX ActiveX控件,实现了视频的采集和传输。实验结果表明:在开发视频采集和传输系统的过程中使用ActiveX视频控件是很容易实现的。

On the QoS Assessment of Video Sessions in Heterogeneous 3G-WLAN Networks with Seamless and Secure Mobility Support

Real-time video data transmission is currently emerging as a popular application among mobile users but it is very sensitive to QoS degradation due to packet losses in wireless networks.In order to achieve service continuity and integrity upon handoffs among heterogeneous networks,provisioning of seamless and secure mobility is required.However,in order to reduce the delay and packet losses during vertical handovers we need to employ supportive protocols like context transfer.In this paper we evaluate the QoS of video transmission over a heterogeneous 3G-WLAN network.The aggregate video data traffic is represented by a dynamic two-dimensional Markov chain model,which has been evaluated against real video data measurement.Upon the vertical handover, appropriate AAA handshaking and enhanced mobility management using context transfer have been considered.Perceived QoS evaluation of video streams was performed based on peak signal-noise ratio(PSNR) measurements,while we analyticallyestimated the number of packet losses during handovers.The results show that both packet loss within the converged network and loss occurrence affecting the perceived video quality is reduced. Moreover,the proposed context transfer scheme minimizes handover delay and the number of lost packet up to 3 times compared to standard AAA handshaking.

View Direction Adaptive 360 Degree Video Streaming System Based on Projected Area

360 video streaming services over the network are becoming popular. In particular, it is easy to experience 360 video through the already popular smartphone. However, due to the nature of 360 video, it is difficult to provide stable streaming service in general network environment because the size of data to send is larger than that of conventional video. Also, the real user's viewing area is very small compared to the sending amount. In this paper, we propose a system that can provide high quality 360 video streaming services to the users more efficiently in the cloud. In particular, we propose a streaming system focused on using a head mount display (HMD).

YOLOv5-Based Seabed Sediment Recognition Method for Side-Scan Sonar Imagery

Seabed sediment recognition is vital for the exploitation of marine resources.Side-scan sonar(SSS)is an excellent tool for acquiring the imagery of seafloor topography.Combined with ocean surface sampling,it provides detailed and accurate images of marine substrate features.Most of the processing of SSS imagery works around limited sampling stations and requires manual interpretation to complete the classification of seabed sediment imagery.In complex sea areas,with manual interpretation,small targets are often lost due to a large amount of information.To date,studies related to the automatic recognition of seabed sediments are still few.This paper proposes a seabed sediment recognition method based on You Only Look Once version 5 and SSS imagery to perform real-time sedi-ment classification and localization for accuracy,particularly on small targets and faster speeds.We used methods such as changing the dataset size,epoch,and optimizer and adding multiscale training to overcome the challenges of having a small sample and a low accuracy.With these methods,we improved the results on mean average precision by 8.98%and F1 score by 11.12%compared with the original method.In addition,the detection speed was approximately 100 frames per second,which is faster than that of previous methods.This speed enabled us to achieve real-time seabed sediment recognition from SSS imagery.

微视频结合Teach-back健康教育模式在体外受精-胚胎移植患者中的应用

目的分析微视频结合Teach-back健康教育模式在体外受精-胚胎移植患者中的应用价值。方法选取2021年6月至2022年6月赣州市妇幼保健院收治的100例体外受精-胚胎移植患者作为研究对象,按照随机数字表法将其分为观察组(50例)与对照组(50例)。对照组患者采用常规健康教育方式,观察组患者采用微视频结合Teach-back健康教育模式。比较两组患者的辅助技术知识水平掌握程度评分、焦虑自评量表评分、护理满意度评分以及临床妊娠率。结果观察组患者护理后的辅助技术知识水平掌握程度评分高于对照组,差异有统计学意义(P<0.05);观察组患者护理后的焦虑自评量表评分低于对照组,差异有统计学意义(P<0.05);观察组患者护理后的护理满意度评分高于对照组,差异有统计学意义(P<0.05);观察组患者护理后的临床妊娠率高于对照组,差异有统计学意义(P<0.05)。结论体外受精-胚胎移植患者采取微视频结合Teach-back健康教育模式能够提高护理效果,改善患者的负面情绪,提升临床妊娠率。

Performance Analysis of Hybrid RR Algorithm for Anomaly Detection in Streaming Data

Automated live video stream analytics has been extensively researched in recent times.Most of the traditional methods for video anomaly detection is supervised and use a single classifier to identify an anomaly in a frame.We propose a 3-stage ensemble-based unsupervised deep reinforcement algorithm with an underlying Long Short Term Memory(LSTM)based Recurrent Neural Network(RNN).In the first stage,an ensemble of LSTM-RNNs are deployed to generate the anomaly score.The second stage uses the least square method for optimal anomaly score generation.The third stage adopts award-based reinforcement learning to update the model.The proposed Hybrid Ensemble RR Model was tested on standard pedestrian datasets UCSDPed1,USDPed2.The data set has 70 videos in UCSD Ped1 and 28 videos in UCSD Ped2 with a total of 18560 frames.Since a real-time stream has strict memory constraints and storage issues,a simple computing machine does not suffice in performing analytics with stream data.Hence the proposed research is designed to work on a GPU(Graphics Processing Unit),TPU(Tensor Processing Unit)supported framework.As shown in the experimental results section,recorded observations on framelevel EER(Equal Error Rate)and AUC(Area Under Curve)showed a 9%reduction in EER in UCSD Ped1,a 13%reduction in ERR in UCSD Ped2 and a 4%improvement in accuracy in both datasets.

Augmented virtual environment: fusion of real-time video and 3D models in the digital earth system

An Augmented virtual environment(AVE)is concerned with the fusion of real-time video with 3D models or scenes so as to augment the virtual environment.In this paper,a new approach to establish an AVE with a wide field of view is proposed,including real-time video projection,multiple video texture fusion and 3D visualization of moving objects.A new diagonally weighted algorithm is proposed to smooth the apparent gaps within the overlapping area between the two adjacent videos.A visualization method for the location and trajectory of a moving virtual object is proposed to display the moving object and its trajectory in the 3D virtual environment.The experimental results showed that the proposed set of algorithms are able to fuse multiple real-time videos with 3D models efficiently,and the experiment runs a 3D scene containing two million triangles and six real-time videos at around 55 frames per second on a laptop with 1GB of graphics card memory.In addition,a realistic AVE with a wide field of view was created based on the Digital Earth Science Platform by fusing three videos with a complex indoor virtual scene,visualizing a moving object and drawing its trajectory in the real time.

音视频传输技术探讨

随着信息技术的发展,音视频应用场景越来越多,传输需求越来越大。针对音视频传输技术现状进行总结,分析各种技术的优缺点和应用场景,列举音视频技术发展面临的问题,并针对这些问题提出一些建议,为相关从业人员提供参考。

Supporting multi-user real-time VBR video service using dynamic bandwidth management based on prediction

Real-time variable bit rate（VBR） video is expected to take a significant portion of multimedia applications.However,plentiful challenges to VBR video service provision have been raised for its characteristic of high traffic abruptness.To support multi-user real-time VBR video transmission with high bandwidth utilization and satisfied quality of service（QoS）,this article proposes a practical dynamic bandwidth management scheme.This scheme forecasts future media rate of VBR video by employing time-domain adaptive linear predictor and using media delivery index（MDI） as both QoS measurement and complementary management reference.In addition,to support multi-user application,an adjustment priorities classified strategy is also put forward.Finally,a test-bed based on this management scheme is established.The experimental results demonstrate that the scheme proposed in this article is efficient with bandwidth utilization increased by 20%-60% compared to a fixed service rate and QoS guaranteed.

Real-time ultra-wideband video streaming in long-reach passive optical networks with wireless radiation in the 10 and 60 GHz bands

Real-time video streaming using ultra-wideband(UWB) technology is experimentally demonstrated along long-reach passive optical networks(LR-PONs) with different wired and wireless reaches. Experimental tests using external and direct modulation with UWB wireless radiation in the 10- and 60-GHz bands are performed. An ultra-bendable fiber is also considered for a last-mile distribution. The video quality at the output of the optical fiber infrastructure of the LR-PON is assessed using the error vector magnitude(EVM), and the link quality indicator(LQI) is used as a figure of merit after wireless radiation. An EVM below –17 dB is achieved for both externally and directly modulated LR-PONs comprising up to 125 km of optical fiber. EVM improvement is observed for longer LR-PONs when directly modulated lasers(DMLs) are used because of the amplitude gain provided by the combined effect of dispersion and DML's chirp. Compared with optical back-to-back operation, the LQI level degrades to the maximum around 20% for LR-PONs ranging between 75 and 125 km of fiber reach and with a wireless coverage of 2 m in the 10-GHz UWB band. The same level of LQI degradation is observed using the 60-GHz UWB band with a LR-PON integrating 101 km of access network, a last-mile distribution using ultra-bendable fiber, and a 5.2-m wireless link.

南水北调东线一期工程泵站群视频监视系统中的算法分析及应用研究

南水北调东线一期工程有14个现地站建立了视频监视与分析系统,通过建设智能化的现场管控视频平台,采用智能化深度学习的算法,分析特定目标检测和移动目标侦测,对突发事件进行及时预警。现地站的系统在报警后,会将现地站报警前的视频发送至监控中心服务器存储,然后在省公司调度中心通过云服务平台的视频报警服务系统采集现地站的所有视频,并存储推送报警信息及报警图像。