A Study of an IT-Assisted Higher Education Model Based on Distributed Hardware-Assisted Tracking Intervention.
This paper presents an in-depth study and analysis of the model of higher education using distributed hardware tracking intervention of information technology. The MEC-based dynamic adaptive video stream caching technology model is proposed. The model dynamically adjusts the bit rate by referring to...
| Publicado en: | Occupational Therapy International pp. 1 - 13 |
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| Autor principal: | |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
4/8/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156201729&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156201729 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09667903 GPF jtl: Occupational Therapy International issn: 09667903 maglogo: Y pubinfo: dt: 4/8/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 156201729 156201729 156201729 10.1155/2022/8862716 156201729 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Study of an IT-Assisted Higher Education Model Based on Distributed Hardware-Assisted Tracking Intervention. aug: au: Liu, Haijun affil: School of Teacher Education, Shangqiu Normal University, Shangqiu Henan 476000, China sug: subj: Models, Educational Evaluation Information Technology Educational Technology Computer Hardware Videorecording Computer-Assisted Instruction Systems Design Human Simulations Computer Memory Communication Protocols Motivation Faculty Role User-Computer Interface Algorithms Learning Environment Cloud Computing Data Mining Item Analysis Validation Studies Factor Analysis ab: This paper presents an in-depth study and analysis of the model of higher education using distributed hardware tracking intervention of information technology. The MEC-based dynamic adaptive video stream caching technology model is proposed. The model dynamically adjusts the bit rate by referring to the broadband estimation and cache occupancy data to ensure users have a smooth experience effect. Simulation results show that the model has fewer transcoding times and generates lower latency than the traditional model, which is suitable for dual-teacher classroom scenarios and further improves the quality of the user's video viewing experience. The model uses an edge cloud collaborative architecture to migrate the rendering technology to an edge server closer to the user side, enabling real-time interaction, computation, and rendering, reducing the time of data transmission as well as computation time. According to the blended learning-based adaptive intervention model, three rounds of teaching practice are conducted to validate the effectiveness of the intervention model in terms of both student process performance and outcome performance, thereby improving learning adaptability and improving learning effect. Teachers' teaching has a significant impact on learning motivation (β = 0.311 , p < 0.01), which in turn affects learning adaptability. Teachers use scientific teaching methods to stimulate students' learning motivation, mobilize enthusiasm, and improve learning adaptability. Under the communication topology of the system as a directed graph, a multi-intelligent system dynamic model with grouping is established; i.e., the intragroup intelligence has the same dynamics but is different between groups, and all system dynamics are unknown. The proposed novel policy iterative algorithm is used to learn the optimal control protocol and achieve optimal consistency control. The effectiveness of the algorithm is demonstrated by the simulation experimental results. The simulation results show that the model has lower latency and energy consumption compared to the cloud rendering model, which is suitable for the safety education classroom scenario and solves the outstanding problems of network connection rate and cloud service latency. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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