下载Streaming电影的有效手段

上了宽带后,在网上欣赏电影是大家都想做的事。目前网上流行的Streaming Media有两大类,一是Real的.rm,另一个是Win-dows Media Player的.asf。基于安全原因,它们采用的都不是普通的HTTP协定,而是采用了rtsp://、mms://等通讯协定,用我们习惯的普通方法已无法下载。这次笔者就介绍一套专门用来下载Streaming Media的程序:StreamBox VCR。

电影疗法提升大学生生命意义感的团体心理辅导实践探索

目的:评估电影疗法在团体心理辅导中增强大学生生命意义感知的影响成效。方法:以电影《那山那人那狗》为教学素材,运用生命意义感理论、电影疗法、萨提亚模式和团体动力学等知识,涵盖观察学习、隐喻以及投射与认同等心理基础,探寻生命意义感团体心理辅导的作用机制。将自愿接受团体辅导的72名大二学生作为研究对象,其中36人作为对照组,36人作为干预组,运用扎根理论分析干预组生命意义感的三次访谈,以构成维度及发展机制。结果:大学生生命意义感的心理发展过程分为混沌期、觉察期和觉悟期等三个阶段,确定了生活质量、社会关系、价值观以及自我发展等四个维度,从而为生命意义感提供了兼具广度与纵深性的框评估架。结论:电影疗法在提升大学生生命意义的认知水平以及激发其探寻生命意义的动力方面发挥着积极作用,彰显出时代价值,为高校心理健康教育模式的创新提供了崭新的视角与范例,具有重要的应用推广价值。

The viscous strip approach to simplify the calculation of the surface acoustic wave generated streaming

In recent decades,the importance of surface acoustic waves,as a biocompatible tool to integrate with microfluidics,has been proven in various medical and biological applications.The numerical modeling of acoustic streaming caused by surface acoustic waves in microchannels requires the effect of viscosity to be considered in the equations which complicates the solution.In this paper,it is shown that the major contribution of viscosity and the horizontal component of actuation is concentrated in a narrow region alongside the actuation boundary.Since the inviscid equations are considerably easier to solve,a division into the viscous and inviscid domains would alleviate the computational load significantly.The particles'traces calculated by this approximation are excellently alongside their counterparts from the completely viscous model.It is also shown that the optimum thickness for the viscous strip is about 9-fold the acoustic boundary layer thickness for various flow patterns and amplitudes of actuation.

An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in Streaming Data

Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDC)model.The aim of the OSODLSDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed OS-ODLSDC model initially undergoes preprocessing step.Since streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling process.Besides,the OS-ODLSDC model employs bidirectional long short-term memory(Bi LSTM)for AD and classification.Finally,the root means square propagation(RMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM model.For ensuring the promising performance of the OS-ODLSDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.

Research on Current Situation and Legal Regulation of Cosmetics Live Streaming E-commerce in China

Analyze the compatibility between cosmetics and live streaming e-commerce from its own nature,marketing means and supply chain characteristics.According to the prominent problems,sort out the relationship between all parties in the cosmetics live e-commerce industry chain.Combined with the latest regulatory policies of live streaming e-commerce and cosmetics,the responsibilities of different subjects in cosmetics live streaming e-commerce are summarized,and relevant suggestions and countermeasures are put forward for the standardization and development of live streaming e-commerce.Cosmetics brand owners are the first responsible persons for product quality.Anchors,as a mixed identity between intermediary,advertising spokesperson and operator,should bear stricter joint and several liability when recommending products related to consumers’health.If anchors fail to clearly identify themselves in the recommendation process,thus causing consumers to mistake them for the operator of the cosmetics,they should assume the obligations of the operator.

Significance of Live Streaming in Shaping Business: A Critical Review and Analytical Study

With the rise of live streaming on social media, platforms like Facebook, Instagram, and YouTube have become powerful business tools. They enable users to share live videos, fostering direct connections between businesses and their customers. This critical literature review paper explores the impact of live streaming on businesses, focusing on its role in attracting and satisfying consumers by promoting products tailored to their needs and wants. It emphasizes live streaming’s crucial role in engaging customers, a key to business growth. The study also provides viable strategies for businesses to leverage live streaming for growth and customer engagement, underscoring its importance in the business landscape.

基于Spark Streaming的车辆电子围栏技术实现与应用

文章提出一种基于Spark Streaming实时数据流处理框架,使用Kafka作为车辆轨迹数据的消息队列服务,结合拓扑关系判断算法射线法的车辆电子围栏技术。应用表明,该技术能够处理高吞吐率、强实时性的车辆动态数据,满足车辆动态精细化监管需求。

A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

新女性·第一帧:FIRST青年电影展FIRST FRAME竞赛单元研究

FIRST FRAME作为FIRST青年电影展于2021年开设的特别策划竞赛单元,致力于关注多元女性形象,鼓励女性主题影像书写。于影展18周年成人礼之际,前缀“第一帧”正式变更为“她的一帧”,更为隐含地侧重在新世纪立足青年女性“她”立场上,透过华语新生代创作者的双眸,定格新女性影像。将目光投向竞赛单元的新生代“新女性”形象,于外梳理国内外女性影展史料,于内剖析入围影片所凸显的女性议题,并厘清身份认知、平权反抗、身份关系、主观能动等迭代变化的关键词流向,以期唤起每一位青年创作者对女性议题的勇敢捕捉与大胆表达之心。

新主流电影国家形象建构路径探析

如何构建和传播良好的国家形象已然成为中国所要面临的时代课题,而新主流电影的出现为这一时代课题给出了一些答案,其通过多样英雄人物塑造的路径实现了多元国家形象的建构。具而言之,新主流电影通过塑造革命英雄呈现着“穷且志坚”的国家形象,塑造战争英雄透视着“珍爱和平”的国家形象,塑造特战英雄表现着“担当有为”的国家形象,塑造凡人英雄展示着“欣欣向荣”的国家形象。通过新主流电影对国家形象的传播,在对内传播上具有提升国家认同感的价值,在对外传播上具有提升国际形象的价值。

国产神话题材动画电影的社会空间研究

神话题材动画电影的社会空间作为具有独特文化意义与美学价值的书写方式,其社会空间的运行逻辑与表达机制帮助人们推演出理解社会的一个新的知识体系。将列斐伏尔“空间三元辩证法”中的社会空间作为阐述神话题材动画电影的空间路径加以分析,可以发现,神话动画的社会空间是当代社会文化问题的表征与符码,也是凸显社会权力与社会关系的一种方式。

基于Spark Streaming的实时数据分析系统及其应用

为了实现对实时网络数据流的快速分析,设计一种分布式实时数据流分析系统(DRDAS),能有效解决并发访问数据流的收集、存储和实时分析问题,为大数据环境的网络安全检测提供了一种有效的数据分析平台;根据Spark Streaming运行的原理设计一种动态采样的K-Means并行算法,与DRDAS结合能实时有效地检测大数据环境下的各种分布式拒绝服务(DDo S)攻击。实验结果显示:DRDAS具有好的可扩展性、容错性和实时处理能力,与动态采样的K-Means并行算法结合能实时地检测各种DDo S攻击,缩短了攻击的检测时间。

面向直播HTTP Streaming系统的HTTP缓存服务器行为优化

HTTP缓存服务器是提高HTTP Streaming系统客户并发量的关键环节。但当前主流HTTP缓存服务器,如Nginx、Squid、Varnish等,在缓存资源更新期间的行为都存在不足,当被应用在面向直播的HTTP Streaming系统中时,会周期性地把大量客户端请求转发至源服务器,从而制约了HTTP Streaming系统的可伸缩性。提出一种优化的HTTP缓存服务器在缓存更新期间的行为,即缓存服务器仅向源服务器转发一路客户端请求,缓存更新期间,拒绝其他关于该资源的请求。优化策略在使用最为广泛的Nginx服务器的基础上进行了实现。实验证明,优化后系统的伸缩性得到了显著提高。

基于Spark Streaming流回归的煤矿瓦斯浓度实时预测

为了实时分析瓦斯监测流数据并对瓦斯浓度进行准确预测以实现瓦斯灾害实时预警,以实时流数据处理框架Spark Streaming构建基于流回归的瓦斯浓度实时预测系统。系统采用分布式流处理技术,可使基于回归算法的瓦斯浓度预测模型更新周期达到秒级,提高了瓦斯浓度预测精度,满足流式大数据处理的实时性要求。实验表明:应用Spark Streaming流回归预测系统在采样周期为5s的瓦斯监测数据流上进行实时预测时,预测平均均方根误差随模型更新周期的缩短而减小,模型更新周期可达15s,且更新周期为45s时预测总均方根误差最小,既能保证预测精度,又能提高瓦斯灾害预警时效。

使用Spark Streaming的自适应实时DDoS检测和防御技术

分布式拒绝服务(distributed denial of service,DDoS)攻击是重要的安全威胁,网络速度的不断提高给传统的检测方法带来了新的挑战。以Spark等为代表的大数据处理技术,给网络安全的高速检测带来了新的契机。提出了一种基于Spark Streaming框架的自适应实时DDoS检测防御技术,通过对滑动窗口内源簇进行分组,并根据与各分组内源簇比例的偏差统计,检测出DDoS攻击流量。通过感知合法的网络流量,实现了对DDoS攻击的自适应快速检测和有效响应。实验结果表明,该技术可极大地提升检测能力,为保障网络服务性能和安全检测的可扩展性提供了一种可行的解决方案。

基于Spark Streaming的实时能耗分项计量系统

能耗分项计量能够准确、及时、有效地发现能源使用问题,形成和实现最有效的节能措施。能耗分项计量系统需要对各项能源使用量在不同粒度上进行统计,既有实时性的需求,又需要涉及到聚合、去重、连接等较为复杂的统计需求。由于数据产生快、实时性强、数据量大,所以很难统一采集并入库存储后再作处理,这便导致传统的数据处理架构不能满足需求。为此,提出基于Spark Streaming大数据流式技术构建一个实时能耗分项计量系统,对实时能耗分项计量的系统架构和内部结构进行了详细介绍,并通过实验数据分析了系统的实时数据处理能力。与传统架构不同,实时能耗分项计量系统在数据流动的过程中实时地进行捕捉和处理,一方面把捕捉到的异常信息及时报警到前端,同时把分类分项统计处理的结果保存到数据库,以便进行离线分析和数据挖掘,能有效地解决上述数据处理过程中遇到的问题。

Darwin Streaming server的研究与应用

分析了Darwin streaming server(DSS)的架构和核心流程;讨论了Darwin streaming server的二次开发接口:module;最后给出了一个用户认证的二次开发模块。

基于Spark Streaming的视频/图像流处理与新的性能评估方法

智能视频监控技术在公共安全、交通管理、智慧城市等方面有着广泛的运用前景,需求日益增长。随着摄像头安装的数量越来越多,采集的图像数据量越来越大,靠单台计算机处理已经远远不能满足需求了。分布式计算的兴起与发展为解决大规模的数据处理问题提供了很好的途径。使用一种基于Spark Streaming的视频/图像流处理的测试平台,阐述了平台的构成和工作流程,深入研究各个参数对集群性能的影响,创新性地提出了CPU时间占用率作为性能评估指标,与总的处理时间结合,更为全面反映集群性能和资源利用率。