Evidence map›Paper›PMID 35125927›Full record

ArticleMultimedia tools and applications2022

An enhanced algorithm for improving real-time video transmission for tele-training education.

Pooja Maharjan, Abeer Alsadoon, P W C Prasad, Ahmad B Al-Khalil, Oday D Jerew, Ghossoon Alsadoon, Binod Chapagain

Open access · bronzeAbstract read
In one paragraph

Article in Multimedia tools and applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 3 countries.

Pooja MaharjanSchool of Computing Mathematics and Engineering, Charles Sturt University (CSU), Sydney, Australia.
Abeer AlsadoonSchool of Computing Mathematics and Engineering, Charles Sturt University (CSU), Sydney, Australia.ORCID 0000-0002-2309-3540
P W C PrasadSchool of Computing Mathematics and Engineering, Charles Sturt University (CSU), Sydney, Australia.
Ahmad B Al-KhalilCollege of Science, Department of Computer Science, The University of Duhok, Duhok, KRG Iraq.
Oday D JerewAsia Pacific International College (APIC), Sydney, Australia.
Ghossoon AlsadoonBusiness Informatics Department, AMA International University Bahrain (AMAIUB), Salmabad, Bahrain.
Binod ChapagainSchool of Computing Mathematics and Engineering, Charles Sturt University (CSU), Sydney, Australia.
Charles Sturt University · AUAMA International University · BHUniversity of Duhok · IQ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tele-training in surgical education has not been effectively implemented. There is a stringent need for a high transmission rate, reliability, throughput, and reduced distortion for high-quality video transmission in the real-time network. This work aims to propose a system that improves video quality during real-time surgical tele-training. The proposed approach aims to minimise the video frame's total distortion, ensuring better flow rate allocation and enhancing the video frames' reliability. The proposed system consists of a proposed algorithm for Enhancing Video Quality, Distorting Minimization, Bandwidth efficiency, and Reliability Maximization called (EVQDMBRM) algorithm. The proposed algorithm reduces the video frame's total distortion. In addition, it enhances the video quality in a real-time network by dynamically allocating the flow rate at the video source and maximizing the transmission reliability of the video frames. The result shows that the proposed EVQDMBRM algorithm improves the video quality with the minimized total distortion. Therefore, it improves the Peak Signal to Noise Ratio (PSNR) average by 51.13 dB against 47.28 dB in the existing systems. Furthermore, it reduces the video frames processing time average by 58.2 milliseconds (ms) against 76.1, and the end-to-end delay average by 114.57 ms against 133.58 ms comparing to the traditional methods. The proposed system concentrates on minimizing video distortion and improving the surgical video transmission quality by using an EVQDMBRM algorithm. It provides the mechanism to allocate the video rate at the source dynamically. Besides that, it minimizes the packet loss ratio and probing status, which estimates the available bandwidth.

Indexed as

Distortion minimizationHeterogeneous wireless networksReliabilitySurgical tele-trainingVideo quality

Identifiers

PMID35125927
PMCPMC8809212
OpenAlexW4210625418

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.