Streaming Technology Research Articles

Future Hybrid Technology for Pay TV Platform

The main objective of this study is to analyze the potentiality of new technology of TV broadcasting and video distribution systems and how to adapt to the new trend of video viewing experience and design a future generation TV for the Bangladesh Pay TV industry. This research is based on Bangladesh and the interest of Bangladesh's Pay-TV industry delves into a novel approach aimed at mitigating these challenges by harnessing terrestrial or mobile networks for video broadcasting, thereby upgrading the old-fashioned broadcasting system or diminishing reliance on conventional internet-based streaming for mobile. This study adapts to the latest practice and implementation of ATSC 3.0 Terrestrial broadcasting and video streaming technology enhancement and business success along with emerging 5G network feasibility. ATSC 3.0 terrestrial broadcasting for mobile users has a significant impact on view experience, and seamless video transmission without the usage of internet data, especially in rural areas of the country where the 4G network is very limited. Local Gateway Node will receive ATSC 3.0 live TV and locally added offline video or streaming apps injected through API to deliver household through private CDN. This study offers a comprehensive technical feasibility, benefits, and implications of this innovative approach, upgradation of terrestrial broadcasting system highlighting its potential to revolutionize video delivery to mobile users. This study analyzes the technology evolution and adaptability with the recent trend of video content viewing experience, the importance of this study is significant for Bangladesh's pay-TV market to secure the future business.

VIDEO STREAMING PLATFORMS FOR LEARNING ENGLISH – CASE STUDY: NETFLIX

We live in an age of technology when people increasingly give up on television and turn to online streaming sources to entertain. These services provide an alternative to cable and satellite on-demand service, sometimes at a lower cost. Due to its intense development over the last few years, video streaming technology has attracted academic attention as a valuable tool for learning or improving English. Thus, this study discusses the practicality of video streaming use in foreign language higher education. It starts with a brief review of the literature on the use of video for language learning, focusing on the main benefits for learners. Then, the study presents the video as a learning tool underlying its advantages over the other previous physical technologies. To highlight the value of video streaming to language education, benefits and problems are explained, and Netflix is outlined as an example of a streaming video platform that may be used within English language teaching. General vocabulary items will be acquired, and listening skills will be improved. However, the interest in studying and approaching new topics focusing on specialized vocabulary will be recognized as an advantage when utilizing video streaming platforms. Next, specific strategies for using video streaming platforms will be outlined. The first was that short documentaries could be watched along with multiple-choice questions to promote general vocabulary building. The second is that Netflix’s series or movies can be utilized to find specific themes to help explain particular grammar or vocabulary points while improving the specialized business vocabulary.

Traffic spills the beans: A robust video identification attack against YouTube

Traffic-based video identification attack is a side-channel attack that allows an attacker to identify transmitted online videos from encrypted network traffic. Existing attacks face two types of challenges: 1) YouTube's improved streaming technology renders them invalid or impacted; 2) real-world diverse traffic makes them underperform. In this paper, we provide the first study of YouTube's technical improvements and reveal its three key features: i) the mechanism that replaces the MPD file, ii) variable combined segments, and iii) various buffering processes. Based on the above analysis, we propose a Robust and easily scalable Video Identification Attack against YouTube called RoVIA. RoVIA extracts video fingerprints from video file headers and reference sequences from video traffic. RoVIA uses the reference sequence to generate candidate sequences in the pre-built video fingerprint library and achieves video identification by measuring sequence similarity. Experimental results show that RoVIA achieves open-world accuracy of 0.967, 0.924, and 0.863 in open-world, fixed-quality, and poor network experiments. Furthermore, RoVIA's scalability allows the target classes to be adjusted by updating the fingerprint library without collecting new samples and retraining parameters. This study aims to demonstrate the vulnerabilities of YouTube streaming technology and the potential consequences of its malicious use. We also propose two YouTube-friendly countermeasures to help developers build effective defenses.

A Visual Sensitivity Aware ABR Algorithm for DASH via Deep Reinforcement Learning

In order to cope with the fluctuation of network bandwidth and provide smooth video services, adaptive video streaming technology is proposed. In particular, the adaptive bitrate (ABR) algorithm is widely used in dynamic adaptive streaming over HTTP (DASH) to improve quality of experience (QoE). However, existing ABR algorithms still ignore the inherent visual sensitivity of human visual system (HVS). As the final receiver of video, HVS has different sensitivity to the quality distortion of different video content, and video content with high visual sensitivity needs to allocate more bitrate resources. Therefore, existing ABR algorithms still have limitations in reasonably allocating bitrate and maximizing QoE. To solve this problem, this paper designs an adaptive bitrate strategy from the perspective of user vision, studies the modeling of visual sensitivity, and proposes a visual sensitivity aware ABR algorithm. We extract a set of content features and attribute features from the video, and consider the simulation of HVS to establish a total masking effect model that reflects the visual sensitivity more accurately. Further, the network status, buffer occupancy, and visual sensitivity are comprehensively considered under a deep reinforcement learning framework to select the appropriate bitrate for maximizing QoE. We implement the proposed algorithm over a realistic trace-driven evaluation and compare its performance with several latest algorithms. Experimental results show that our algorithm can align ABR strategy with visual sensitivity to achieve better QoE in high visual sensitivity content, and improves the average perceptual video quality and overall user QoE by 18.3% and 22.8%, respectively. Additionally, we prove the feasibility of our algorithm through subjective evaluation in the real environment.

Interactive mixed reality live streaming technology in manufacturing

This paper presents the first field-tested application of interactive mixed reality live streaming technology in a manufacturing setting and elaborates on its implications for practitioners and scholars. A proof-of-concept of a mixed reality live streaming device that uses 360° video calls for remote presence is developed and applied in a field test during a tool changeover at a Stanley Black & Decker factory. This study documents that interactive mixed reality live streaming for shop-floor environments has passed Technology Readiness Level 6, representing a radical new way of organizing remote shop-floor tours, inspections, audits, and training.

Structural testing and numerical modelling of a glass fibre-reinforced composite demonstrator for turbine blades

Tidal energy, a clean, predictable and reliable renewable energy source, can play an important role in creating a carbon-free energy system in Europe. The cumulative tidal stream technology deployed in Europe was 27.9 MW in 2020, which contributes to 77% of the global total tidal energy device installations. Under a high growth scenario, about 2388 MW of tidal energy capacities will be deployed in Europe by 2030. The structural performance of a tidal turbine blade is vital as it guarantees the safe operation of a turbine within its lifespan in marine environments. Experimental testing is a reliable way of investigating the structural performance of a tidal turbine blade. In this research, the structural performance of a composite demonstrator is carried out. The 5-m long demonstrator represents a tidal current turbine’s spar cap, the strongest region of a typical rotor blade. The demonstrator consists of two spar cap and two webs, which are manufactured with glass-fibre reinforced composite materials. Steel inserts are drilled into the root of the spar cap to connect to the support frame. A hydraulic actuator is used to apply loading to the tip region of the demonstrator to simulate the operation loading. Instrumentations, including strain gauges, accelerometers and displacement transducers, are installed to monitor the demonstrator responses. Besides testing the demonstrator, the mechanical properties of the glass-fibre reinforced composite material are also obtained through coupon tests. The test results are utilised to develop a finite element model, which will be used in the blade design and optimisation case study in the future.

Developing STREAM (Science, Technology, Religiosity, Engineering, Art, and Mathematics) Based Tiktok Video on Buffer Solution Lesson

Developing STREAM (Science, Technology, Religiosity, Engineering, Art, and Mathematics) Based Tiktok Video on Buffer Solution Lesson

Design of Virtual Anchor Based on 3Dmax

With the rapid development of virtual reality and live streaming technologies, virtual anchors have become increasingly popular in recent years. In this paper, we propose a design method of virtual anchors based on 3DMAX. Through the use of modeling, rigging, and animation techniques, virtual anchors with realistic appearances and human-like movements can be created. We also explore the application of machine learning technologies in improving the interaction between virtual anchors and users. In addition, we provide a case study on the design and implementation of a virtual anchor for a popular live streaming platform. Our results show that the use of 3DMAX in virtual anchor design can greatly enhance user engagement and improve the overall user experience.Virtual anchor design technology based on 3DMAX is a highly complex design work, which requires designers to have a variety of skills and creative capabilities, and needs to fully consider the needs of the audience and the development trend of the industry. Designers should also have certain cultural accumulation and creative ability, and be able to design an attractive and valuable virtual anchor image from the perspective of the audience.This paper analyzes the production and design of the current virtual anchors, in order to provide some reference significance for the production, operation and commercial realization of the virtual anchors in the future.

Intelligent Video Streaming at Network Edge: An Attention-Based Multiagent Reinforcement Learning Solution

Video viewing is currently the primary form of entertainment for modern people due to the rapid development of mobile devices and 5G networks. The combination of pervasive edge devices and adaptive bitrate streaming technologies can lessen the effects of network changes, boosting user quality of experience (QoE). Even while edge servers can offer near-end services to local users, it is challenging to accommodate a high number of mobile users in a dynamic environment due to their restricted capacity to maximize user long-term QoE. We are motivated to integrate user allocation and bitrate adaptation into one optimization objective and propose a multiagent reinforcement learning method combined with an attention mechanism to solve the problem of multiedge servers cooperatively serving users. Through comparative experiments, we demonstrate the superiority of our proposed solution in various network configurations. To tackle the edge user allocation problem, we proposed a method called attention-based multiagent reinforcement learning (AMARL), which optimized the problem in two directions, i.e., maximizing the QoE of users and minimizing the number of leased edge servers. The performance of AMARL is proved by experiments.

Features of Using the mBlock Program in the Scratch Environment in Teaching with STREAM Technology in High School

In the leading countries of the world, learning through STEM, STEAM and STREAM is included in the curriculum of secondary schools. While STEM is about strengthening the role of science, technology, engineering, and mathematics in education, STREAM is about building systematic thinking skills by adding reading and art to the role of science, technology, engineering, and mathematics in education. In STREAM development, you can use the mBlock programming environment based on Scratch+Arduino. In secondary schools of the Republic of Kazakhstan, robotics is often used in the teaching of computer science using STEM technology. As a result of studying informatics, students have not developed the knowledge, skills, and abilities to create digital products using art, mathematics, and engineering. Therefore, there is a need to develop STREAM technology in teaching computer science using STEM technology in high school. In this regard, the purpose of the research work “Determining the specificity of the STREAM teaching method in secondary school” was set. To achieve this goal, firstly, the state of teaching STREAM teaching methods in secondary schools in the republic was determined and the results were analyzed. Secondly, an educational program was developed that combines engineering and mathematics sciences and teaches how to create a project that builds students’ ability to think systematically in the mBlock environment, built on the basis of Scratch+Arduino hardware-programming. The effectiveness of the STREAM teaching method was determined by conducting an optional lesson of the IT class according to the compiled curriculum. The experience of the research was carried out at R. Koshkarbayev secondary school No. 1 and IT school-lyceum of the city of Koschy. The teaching of the Scratch+Arduino hardware programming framework, which took place in computer science optional classes, was defined with mBlock code and ways of practical implementation were introduced. The curriculum of the optional lesson for 8th grade includes a total of 36 hours. In addition to the proposed training course program, digital educational resources were compiled, the teaching methodology was used in the educational process, and the effectiveness of the proposed teaching methods was determined as a result of the experiment. In the future, the training course program and digital educational resources of the course “mBlock Programming based on Scratch+Arduino” can be used in STEM classrooms or in elective computer science classes in any schools in the country.

An Active Service Recommendation Model for Multi-Source Remote Sensing Information Using Fusion of Attention and Multi-Perspective

With the development and popularization of remote sensing earth observation technology and the remote sensing satellite system, the problems of insufficient proactiveness, relevance and timeliness of large-scale remote sensing supporting services are increasingly prominent, which seriously restricts the application of remote sensing resources in multi-domain and cross-disciplinary. It is urgent to help terminal users make appropriate decisions according to real-time network environment and domain requirements, and obtain the optimal resources efficiently from the massive remote sensing resources. In this paper, we propose a recommendation algorithm using fusion of attention and multi-perspective (MRS_AMRA). Based on MRS_AMRA, we further implement an active service recommendation model (MRS_ASRM) for massive multi-source remote sensing resources by combining streaming pushing technology. Firstly, we construct value evaluation functions from multi-perspective in terms of remote sensing users, data and services to enable the adaptive provision of remote sensing resources. Then, we define multi-perspective heuristic policies to support resource discovery, and fusion these policies through the attention network, to achieve the accurate pushing of remote sensing resources. Finally, we implement comparative experiments to simulate accurate recommendation scenarios, compared with state-of-the-art algorithms, such as DIN and Geoportal. Furthermore, MRS_AMRA achieves an average improvement of 10.5% in the recommendation accuracy NDCG@K, and in addition, we developed a prototype system to verify the effectiveness and timeliness of MRS_ASRM.

A State-of-the-Art Review of Structural Testing of Tidal Turbine Blades

Over the last two decades, the tidal energy industry has laid the groundwork for creating commercially viable tidal power generation projects to strengthen sustainable energy policies around the world. At the end of 2021, the cumulative installation of tidal stream technology that has been deployed in Europe reached 30.2 MW, where the majority of the installations are by small and medium-sized companies. Due to a growing demand among investors related to the global tidal energy industry, the reliability and safety of operational-stage tidal energy systems’ components are becoming increasingly important. In this context, companies, universities and research institutes are focusing on conducting large- and small-scale tests of tidal turbine elements to validate their projected design life, and major attention is being given to assessing the structural integrity of turbine blades. This review paper focuses on structural tests that have been reported for axial flow tidal turbine blades manufactured using composite materials around the world, highlighting the testing standards, equipment and instrumentation required. Overall, this review article discusses the state of the art in the structural testing of tidal turbine blades. In addition, it highlights the global concerns and research gaps to ensure the long-term sustainability of axial flow tidal turbine blades. In addition, the information contained in this article will be useful for formulating a smooth and reliable mechanism to enhance the evaluation process of the structural properties of tidal turbine blades in the future.

New generation commerce: The rise of live commerce (L-commerce)

Live commerce (L-commerce) is an emerging distribution channel that has transformed consumer shopping preferences. Owing to the COVID-19 pandemic, consumers’ need for non-face-to-face (NFTF) commerce increased rapidly. However, unlike face-to-face (FTF) commerce, NFTF commerce has disadvantages. It lacks interactivity. The newly emerged L-commerce addresses this deficiency using real-time streaming technology. It is positively evaluated in various business segments. This study investigated the structural relationships between the characteristics of L-commerce, customer satisfaction, repurchase intention, and customer loyalty to L-commerce. The moderating effects of security and privacy (SP) and the perceived price advantage (PPA) were further examined. The findings represent a priori research that empirically proves the effectiveness of L-commerce.

CLOUD GAMING

Cloud gaming, sometimes referred to as gaming-as-a-service, is a form of online gaming that allows users to access video games without having to install them on their own computers. It leverages the power of cloud computing to enable users to access games from remote locations, either on dedicated cloud gaming servers or through peer-to-peer networks. This paper examines the advantages and disadvantages of cloud gaming, its current state of development, and the potential opportunities and challenges it presents. KEYWORDS Cloud Gaming, Gaming-as-a-Service, Cloud Computing, Stream Technology.

Wearable point-of-view live streaming technology in a virtual airway management workshop for medical students

Background: Trauma resuscitation skills are an essential part of medical training. Airway management skills are often learned via simulation-based training, but physical distancing restrictions have forced medical schools to transition their preclinical curricula to a virtual format. A wearable, point-of-view (POV), live streaming tool was piloted in a virtual airway management workshop to preclinical medical students to address limitations in the standard online curriculum. Methods: An anesthesiologist instructor donned a chest-mounted smartphone that captured POV video as it was connected to a Zoom video conference call. Simultaneously, a second camera view from a different angle was streamed from a laptop webcam. Preclinical medical student attendees watched the facilitator demonstrate airway management and resuscitation skills on a simulation mannequin. Student perceptions of the workshop were assessed via standardised course evaluations administered through the online student portal and a questionnaire distributed by the course representative. Results: Qualitative and quantitative course evaluation data showed that although this platform may not completely substitute in-person learning, students appreciated the alternative teaching style, particularly the use of POV video and multiple camera views. Generally, students believed that the learning objectives were achieved. Camera stability, camera positioning, and the distracting nature of the virtual student-instructor interactions were identified as areas for improvement. Conclusions: Moving forward, this innovative workshop format can act as a valuable framework for other institutions that wish to bridge gaps in current virtual education methods and enhance technical skills training in medical learners.

Parental experiences of live video streaming technology in neonatal care in England: a qualitative study

BackgroundThe use of bedside cameras in neonatal units facilitates livestreaming of infants to support parental and family bonding when they are unable to be physically present with their baby. This study aimed to explore the experiences of parents of infants previously admitted for neonatal care and who used live video streaming to view their baby in real-time.MethodsQualitative semi-structured interviews were conducted after discharge with parents of infants admitted for neonatal care on a tertiary level neonatal unit in the UK in 2021. Interviews were conducted virtually, transcribed verbatim and uploaded into NVivo V12 to facilitate analysis. Thematic analysis by two independent researchers was undertaken to identify themes representing the data.ResultsSeventeen participants took part in sixteen interviews. Thematic analysis identified 8 basic themes which were grouped into 3 organizational themes: (1) family integration of the baby including parent-infant, sibling-infant, and wider family-infant attachment facilitated through livestreaming, (2) implementation of the livestreaming service including communication, initial set up of the livestreaming service, and areas for improvement, and (3) parental control including emotional, and situational control.ConclusionsThe use of livestreaming technology can provide parents with opportunities to integrate their baby into their wider family and friendship community and gain a sense of control over their baby’s admission for neonatal care. On-going parental education around how to use, and what to expect from, livestreaming technology is required to minimise any potential distress from viewing their baby online.

OpenStackDP: a scalable network security framework for SDN-based OpenStack cloud infrastructure

Network Intrusion Detection Systems (NIDS) and firewalls are the de facto solutions in the modern cloud to detect cyberattacks and minimize potential hazards for tenant networks. Most of the existing firewalls, perimeter security, and middlebox solutions are built on static rules/signatures or simple rule matching, making them inflexible, susceptible to bugs, and difficult to introduce new services. This paper aims to improve network management in OpenStack Clouds by taking advantage of the combination of software-defined networking (SDN), Network Function Virtualization (NFV), and machine learning/artificial intelligence (ML/AI) and for making networks more predictable, reliable, and secure. Artificial intelligence is being used to monitor the behavior of the virtual machines and applications running in the OpenStack SDN cloud so that when any issues or degradations are noticed, the decision can be quickly made on how to handle that issue, being able to analyze data in motion, starting at the edge. The OpenStackDP framework comprises lightweight monitoring, anomaly-detecting intelligent sensors embedded in the data plane, a threat analytics engine based on ML/AI algorithms running inside switch hardware/network co-processor, and defensive actions deployed as virtual network functions (VNFs). This network data plane-based architecture makes high-speed threat detection and rapid response possible and enables a much higher degree of security. We have built the framework with advanced streaming analytics technologies, algorithms, and machine learning to draw knowledge from this data that is in motion before the malicious traffic goes to the tenant compute nodes or long-term data store. Cloud providers and users will benefit from improved Quality-of-Services (QoS) and faster recovery from cyber-attacks and compromised switches. The multi-phase collaborative anomaly detection scheme demonstrates an accuracy of 99.81%, average latencies of 0.27 ms, and response speed within 9 s. The simulations and analysis show that the OpenStackDP network analytics framework substantially secures and outperforms prior SDN-based OpenStack solutions for Cloud architectures.

Awaiting Tiresias: A Livestream Performance for the Digital Research in the Humanities and Arts Conference Context:

Awaiting Tiresias is a livestream performative autoethnography that uses film and streaming technology to take audience members into the liminal space of a medical exam room in which the performer is left blindfolded and in the dark to contemplate their fate. The piece draws upon Greek mythology, common attitudes towards blindness and disability, and modern conceptions of gender in its multi-layered analysis of identity and diagnosis. Awaiting Tiresias examines tensions between liminality and diagnosis, sight and insight, and inter and independence. The performance relies upon film’s ability to carefully construct perspective and interiority as a means of generating empathy and awareness. At the same time, Awaiting Tiresias embraces the way that the mixture of film with liveness can destabilize theatrical expectations to create a space where new perspectives are possible. The creative team behind Awaiting Tiresias utilize the individualized experiences of audience members who witness the performance from their personal electronic devices to challenge the ocular-centric focus of film and theatre. In order to best experience the performance, audiences are encouraged to use headphones, turn out lights, and minimize distractions.

Deep Reinforcement Learning-based Bitrate Adaptations in Dynamic Adaptive Streaming over HTTP

Dynamic adaptive streaming over HTTP (DASH) has been a superior video streaming technology in recent years. Bitrate adaptation function at video player plays a vital role in guaranteeing a high quality-of-experience for the users. This work evaluates the performance of several advanced deep reinforcement learning algorithms, i.e., deep Q-learning, actor-critic, and proximal policy optimization, applied in bitrate adaptations and compares them with other rate adaptation methods with real-trace datasets.

Technological affordances of video streaming platforms: Why people prefer video streaming platforms over television

This article investigates to what extent technological affordances are associated with people's preference for video streaming platforms over traditional television services. Such affordances refer to properties of these platforms (including personalized recommendations and easy-to-navigate interfaces) that provoke certain uses of the technology and satisfy social and psychological needs. Based on a quantitative study of 25–50-year-olds in Belgium ( N = 596) and a hierarchical regression analysis, the study builds further on the conceptualization of technological affordances as presented in the MAIN model, which suggests that four affordances (Modality, Agency, Interactivity and Navigability) are central to digital media technology. As such, the study presents an affordance-based measure of video streaming platforms, and helps to understand how video streaming technology shapes new patterns of audiovisual consumption and enhances the viewing experience beyond that of traditional television. Whereas most research attention has focused on user-oriented gratifications of video streaming platforms, this study addresses a gap in the literature by dealing with platform-oriented gratifications of video streaming platforms.