MétaCan
Menu
Back to cohort
Record W2097156126 · doi:10.1109/vtcf.2006.543

Connectivity and Bit Error Rate Analysis of Mobile Ad Hoc Wireless Networks

2006· article· en· W2097156126 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Vehicular Technology Conference · 2006
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer networkComputer scienceWireless ad hoc networkMobile ad hoc networkRician fadingNode (physics)Mobility modelWireless networkBit error rateFadingWirelessTelecommunicationsNetwork packetChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

One- and two-dimensional ad hoc wireless networks with uniformly distributed (static) nodes and networks with nodes which move according to the random waypoint mobility model are considered. The inter-distance distributions between any two nodes within these networks are obtained. The network connectivity is considered and the minimum transmission range is derived. The bit error rate performance is then analytically evaluated in the connected regions of the networks taking into account the effect of path loss and Nakagami- <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> or Rician fading. It is shown that increasing the number of users increases the network connectivity, decreases the minimum transmission range, and improves the performance. It is also shown that node mobility enhances the network connectivity and performance.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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