Deep Neural Network–based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions

Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual apps spanning from on-demand movies and 360° videos to video-conferencing and live streaming. However, robustly delivering visual content under fluctuating networking conditions on devices of diverse capabilities remains an open problem. In recent years, advances in the field of deep learning on tasks such as super-resolution and image enhancement have led to unprecedented performance in generating high-quality images from low-quality ones, a process we refer to as neural enhancement. In this article, we survey state-of-the-art content delivery systems that employ neural enhancement as a key component in achieving both fast response time and high visual quality. We first present the components and architecture of existing content delivery systems, highlighting their challenges and motivating the use of neural enhancement models as a countermeasure. We then cover the deployment challenges of these models and analyze existing systems and their design decisions in efficiently overcoming these technical challenges. Additionally, we underline the key trends and common approaches across systems that target diverse use-cases. Finally, we present promising future directions based on the latest insights from deep learning research to further boost the quality of experience of content delivery systems.

Technical analysis of content placement algorithms for content delivery network in cloud

<p>Content placement algorithm is an integral part of the cloud-based content de-livery network. They are responsible for selecting a precise content to be re-posited over the surrogate servers distributed over a geographical region. Although various works are being already carried out in this sector, there are loopholes connected to most of the work, which doesn't have much disclosure. It is already known that quality of service, quality of experience, and the cost is always an essential objective targeting to be improved in existing work. Still, there are various other aspects and underlying reasons which are equally important from the design aspect. Therefore, this paper contributes towards reviewing the existing approaches of content placement algorithm over cloud-based content delivery network targeting to explore open-end re-search issues.</p>

Enhancing innovative delivery in schools using design thinking

The pandemic has created challenges in all sectors of the economy and education. Traditional teaching approaches seem futile in the new context, thus the need to constantly reinvent the delivery to meet the fast-paced changes in the education domain. Hence, Design Thinking (DT) is an alternative approach that might be useful in the given context. DT is known to be a human-centric approach to innovative problem-solving processes. DT could be employed in the delivery process to develop twenty-first-century skills and enhance creativity and innovation, in an attempt to identify alternative solutions. The study explores the role of design thinking (DT) in the form of empathy, thinking process, gamified lessons and curriculum enhancement, which leads to innovative delivery among teachers. It enhances and facilitates innovative content delivery by leveraging creativity. The study targeted 131 teachers, whereby 61 are primary school teachers and 70 are secondary school teachers. A questionnaire constituting of 23 close-ended questions using the 5-point Likert scale was used to collect data. Data was analyzed using SmartPLS to establish relationships between DT and Innovative Delivery in schools. The data was further analyzed to seek co-relations between the DT steps and the successful transformation of content delivery by teachers. The study established a framework for the application of design thinking for teachers as the primary support in developing activities for their students. It shows that thinking process, gamifying lessons and curriculum enhancement have positive significance in innovative delivery, whereas empathy did not show a significant positive relationship. The outcome of this study will help fill the gap towards creating an interesting method of delivery in schools and constantly innovating the method to suit the evolving generation. This insight is crucial for the Ministry of Education and policymakers to enhance teachers’ ability to innovatively deliver content to students.

EnTraP: A factorial randomised controlled trial embedded within world hip trauma evaluation eight COPAL investigating the effect of an enhanced trainee principal investigator package and digital nudge on recruitment rates

Background Randomised controlled trials (RCTs) often struggle with various aspects of participant recruitment, including engaging clinicians to recruit effectively, and subsequently fail to reach their target sample size. Studies evaluating interventions to improve recruitment aimed specifically at recruiters to the trial are limited in number. The RCTs embedded into the World Hip Trauma Evaluation (WHiTE) cohort study use Trainee Principal Investigators (TPIs) to help manage and drive recruitment at trial sites. No formalised training or support is provided by central trials units to the TPIs. Additionally, trial recruiters receive a generic automated email confirming randomisation to the trial with no other communication to influence or incentivise their behaviour to further recruit. The primary aim of this factorial trial was to evaluate the effectiveness of an educational intervention to TPIs and a positive reinforcement intervention via an email (digital) nudge on increasing recruitment. Secondary aims included feasibility of implementing the interventions and surveying TPIs on the educational package quality of content, delivery and ongoing support. Design This was a multicentre, open, cluster, 2x2 factorial RCT embedded in the WHiTE 8 COPAL RCT, in which research sites were randomised 1:1:1:1 to receive the enhanced TPI package, the digital nudge intervention, both, or neither. Results 1215 patients were recruited to the WHiTE 8 COPAL trial across 20 sites during the SWAT between August 2018 and March 2019. There was a statistically significant interaction between the interventions (IRR 2.09, 95% CI 1.64 to 2.68, p < 0.001). There was a statistically significant benefit on recruitment (IRR 1.23 95% 1.09 to 1.40, p=0.001) from utilizing an enhanced TPI education intervention. The digital nudge intervention had no significant impact on recruitment (IRR 0.89 95% CI 0.79 to 1.01, p=0.07). Within enhanced TPI package sites, the digital nudge had a beneficial effect, while in the standard practice TPI sites it had a detrimental effect. Feasibility analysis showed the median time to site digital nudge and enhanced TPI set up were one day and 17 days, respectively. 353 digital nudges were created taking an average of 12 min to construct, log the activity and then disseminate to recruiters. Median induction time for enhanced TPI was 32 min and 100% of the groups were extremely satisfied with the induction content, delivery and ongoing support. Discussion An education and support programme targeted at surgical TPIs involving a digital education package, 1:1 telephone induction and subsequent support package was effective in increasing recruitment in the first 6 months of trial commencement. There was no evidence for the effectiveness of the digital nudge intervention in isolation, although our results show that when combined with an education programme, it leads to enhanced effectiveness of that programme.

Preparing Teachers for the Post-COVID Era

This chapter examines the impact of the COVID-19 pandemic on existing learning spaces and emerging learning spaces. The authors address the need to restructure teacher education programs to prepare teachers for flexible teaching in various modalities. Throughout this book chapter, the authors anchor their positions using research-based literature, highlighting the need for new and emerging spaces to ensure the learner's diversity about content delivery, student experience, and the management of these learning spaces. Additionally, the authors provide a critical overview of the need to redesign learning spaces to accommodate learning as learning and knowledge assessments. The chapter concludes by providing readers with a framework anchored on the teacher enterprise domain designed to evaluate and examine new and emerging learning spaces within the context of teacher, structure, content, and learners.

Students Experience of Hybrid- Education Model at The University of Baghdad College of Pharmacy

The impact of COVID-19 pandemic on education models was mainly through the expansion of technology use in the different educational programs. Earlier impact of COVID-19 was manifested in the complete and sudden transition to distance education regardless of institution preparedness status. Gradually, many institutions are moving back to on-campus face-to-face education. However, others including all higher education institutions in Iraq are adopting the hybrid education model. This report presents part of the end of semester evaluation survey conducted at the University of Baghdad College of Pharmacy for the Spring 2021 semester. The survey aims to address points of strength and weakness associated with the hybrid education model and specifically the virtual content delivery aspect of hybrid education. The outcomes of the end of semester evaluation will shape a better experience for upcoming years and guide distance education implantation in the program.

Video Pre-Caching Joint Hand-Off and Content Delivery in Multi-Access Edge Computing Based EONs

Multi-access Edge Computing (MEC) performs as a feasible solution when it comes to content delivery, for it can bring contents much closer to users. However, the hand-off (HO) and latency that occur in user movement reduce the users’ quality of service. In this work, we consider the problem of high mobility handoff and content delivery of video streaming in the MEC based EONs. We propose a video pre-caching algorithm considering handoff and content delivery. The algorithm firstly selects the content delivery method and chunks the video accordingly using a preset threshold. Secondly, the algorithm chooses the shortest transmission path and calculates the latency time using Dijkstra method. Simulation results show that our algorithm significantly reduces the latency time and balances the server load compared to the other two baselines.