MétaCan
Menu
Back to cohort
Record W4361276205 · doi:10.9734/bpi/rpst/v8/18489d

Policy for Reduction of Packet Loss with Gigabit SFP Module, San Switch and HBA Card: An Advanced Research

2023· book-chapter· en· W4361276205 on OpenAlexaboutno aff
Abdullah Yusuf Imam ., Prodip Kumar Biswas, Sonjoy Kumar Nath

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsGigabitAdapter (computing)Computer networkFibre ChannelBandwidth (computing)Network packetMulti-mode optical fiberPort (circuit theory)Computer scienceElectrical engineeringEngineeringComputer hardwareTelecommunicationsOptical fiber

Abstract

fetched live from OpenAlex

Three different single mode or multimode fiber cables are available: RC (Russia-Canada), LC (London-Canada), and SC (Singapore-Canada), all of which will be originated from the main optical fiber cable's TJ box (fiber joining box) and in general they can be at most 3456 core. The RC, LC, or SC cable will be connected to the Media converter and a UTP cable will be released from the Media converter and will be connected to any port of a switch to activate the network channel for passing bandwidth through the line. Now, our first concern is to reduce packet loss across the entire channel by using a switch with Gigabit SFP (Small Form-Factor Pluggable) module instead of using a media converter with or without SFP module, and our second concern is to reduce packet loss by using SAN (Storage area network) switch with HBA (Host bus adapter) card to delivery more than or equal100 MBPS bandwidth.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0230.016

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 head0.039
GPT teacher head0.309
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Optical Network TechnologiesFrench-language works237,207