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Record W2119116549 · doi:10.1109/mwc.2010.5416355

Bridge performance in a multitier wireless network for healthcare monitoring

2010· article· en· W2119116549 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 Wireless Communications · 2010
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceBody area networkComputer networkNetwork topologyBridging (networking)WirelessWireless networkWireless WANBridge (graph theory)Wireless sensor networkWi-Fi arrayTelecommunicationsMedicine

Abstract

fetched live from OpenAlex

Advances in computer and communication technology have enabled online healthcare monitoring using miniature sensing devices attached to a patient's body. Data collected in this manner is then delivered in real time, through one or more wireless hops, to the hospital network. In this article we discuss some design alternatives for the wireless portion of an integrated healthcare monitoring system, in particular issues related to its topology, the choice of wireless communication technology for tiers with well defined function, and the bridging between tiers. We also present some performance results for a two-tier topology with isolation of high-data-rate traffic from low-data-rate traffic, in which the patient's body area network is implemented using 802.15.4 low-data-rate WPAN technology, while connection in the next higher tier (i.e., from the body area network to a hospital ward network or home network) uses the ubiquitous 802.11 WLAN technology.

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 score0.643
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.283
Teacher spread0.248 · 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