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Record W2749785096 · doi:10.5539/mas.v11n9p92

Why Implement Distributed Systems in Municipal Music Schools in Colombia?

2017· article· en· W2749785096 on OpenAlexvenueno aff
Leidy D. Ariza, Carlos R. Orjuela

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceUploadNetwork packetPublicationPlan (archaeology)Order (exchange)Government (linguistics)Protocol (science)MultimediaTelecommunicationsWorld Wide WebComputer networkBusinessAdvertising

Abstract

fetched live from OpenAlex

In Colombia, since 2003, the public policy "National Plan of Music for citizen Coexistence" has been implemented as a government measure, which provides music courses in each one of the country's municipalities. This plan does not take into account the use of technologies to share the experiences of each one of the schools.Taking into account the above- mentioned points, this article focuses its attention on the search of technologies that can be used to share multimedia content such as Content Delivery Network (CDN), Learning Management System (LCMS) and Distributed Systems in order to indicate which technology is the most appropriate to fulfill this purpose.In that sense, through the Wireshark tool, network traffic is captured for each one of the tests performed: Upload, display and deletion of videos for each configured technology (CDN, LCMS and Distributed Systems), having as comparison parameters the following aspects: Real-time Traffic, Total Traffic Vs Packet Loss, Communication Exchange and Protocol Hierarchies. After doing that, we proceed to take statistics to be analyzed and obtain the comparative results that are needed for this research.Finally, one can conclude the comparison of the results of each technology: that it is appropriate that the municipal schools of music use distributed systems because the size of the packets sent is smaller than that one that is sent by CDN and CML technologies. There are no multiple communication jumps. No prior approval is required to publish the content and there is no limitation on the size of the content to be published.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.895
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.282
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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