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Record W2089283333 · doi:10.1109/syscon.2013.6549932

Systems approach for the development of a Silent Wireless Communicator

2013· article· en· W2089283333 on OpenAlexaffabout
F. Stasi, R. Pennell, Sidney Givigi, Alain Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicHand Gesture Recognition Systems
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsEyewearWired gloveWirelessComputer scienceVisibilityOrientation (vector space)Human–computer interactionEngineeringComputer securityTelecommunicationsVirtual reality

Abstract

fetched live from OpenAlex

This paper discusses the design and implementation of the Silent Wireless Communicator. Night operations are becoming increasingly important in modern warfare. Section commanders that conduct missions rely on audio and visual signals in order to command their troops. The communication device is designed to provide a means to communicate commands in an environment which limits visibility and forbids audible commands. The signal data is collected via a glove worn by the commander. The glove captures the user's hand orientation and finger bend states. This data is fed to a Support Vector Machine algorithm that classifies it into standardized Canadian Forces hand signals in order to be disseminated to the rest of the team. The command is then transmitted wirelessly and displayed on a Heads-Up-Display (HUD) mounted to the ballistic eyewear in order for troops to execute.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.251
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2013
Admission routes2
Has abstractyes

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