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Record W2118405758 · doi:10.1145/1066677.1066902

Pocket PC beacons

2005· article· en· W2118405758 on OpenAlexaff
Ankit Arora, Alexander Ferworn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWheelchairBeaconComputer scienceEmbedded systemRemote controlServerHuman–computer interactionReal-time computingComputer hardwareComputer network

Abstract

fetched live from OpenAlex

The Network-Centric Applied Research Team (N-CART) is continuing its work on an ambitious project known as the Network-Enabled Powered Wheelchair Adaptor Kit (NEPWAK) [25]. It introduces techniques for modifying and using powered wheelchairs as mobile platforms enabling communication and remote control. The wheelchair runs a PC104 based embedded server allowing both PC and PocketPC clients to connect in either infrastructure or ad-hoc mode. The clients receive audio, video and other sensory feedback from the wheelchair and can send control data for maneuvering the wheelchair. In this paper we present our preliminary work on a novel, inexpensive and coarse 'Human Tracking and Following' system for NEPWAK. Our approach uses a custom built highly directional steerable Wi-Fi antenna on the wheelchair that scans the Wi-Fi signal strength of its peer. This can be used to track and follow a person carrying a Wi-Fi enabled pocketPC.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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 designNot applicable
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

Citations7
Published2005
Admission routes1
Has abstractyes

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