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Record W4253165422 · doi:10.2478/jok-2018-0004

The Use of Bluetooth Standard for Communication Between Vehicles Under Traffic

2018· article· en· W4253165422 on OpenAlexaff
Zbigniew Kasprzyk, Mariusz Rychlicki

Bibliographic record

VenueJournal of Konbin · 2018
Typearticle
Languageen
FieldComputer Science
TopicBluetooth and Wireless Communication Technologies
Canadian institutionsTransport Canada
Fundersnot available
KeywordsBluetoothTransmission (telecommunications)Computer scienceComputer networkWirelessWireless ad hoc networkData transmissionVehicular ad hoc networkTelecommunications

Abstract

fetched live from OpenAlex

Abstract Bluetooth is a type of wireless communication used to transmit voice and data at high speeds using radio waves. It is a standard protocol for short-range radio communications between many different types of devices, including mobile phones, computers and other electronics [1]. The use of this type of data transmission standard for voice communications at close range in the vehicle is commonly known. The trend of integrating new services in vehicles increases rapidly and Bluetooth is one of the emerging communication technologies for realizing ad-hoc networks. The paper presents the possibility of using Bluetooth to build ad-hoc network suitable for the transmission of sound, in particular voice data using the modulation GSFK. We analyzed the features or problems that Bluetooth offers for transmitting audio data in an ad-hoc network. Some initial results of simulations and real-life tests give an impression of the performance and efficiency this standard for the transmission of voice data in an ad-hoc networks [2].

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.088
GPT teacher head0.302
Teacher spread0.214 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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