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Record W2542420464 · doi:10.1109/acssc.2010.5757531

A scheme of bandwidth allocation for the transmission of medical data

2010· article· en· W2542420464 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceBandwidth (computing)Bandwidth allocationScheme (mathematics)Computer networkData transmissionDynamic bandwidth allocationTransmission (telecommunications)Real-time computingTelecommunications

Abstract

fetched live from OpenAlex

In this paper, a bandwidth allocation scheme for the transmission of medical data in the IEEE 802.11n based WLAN is proposed. The main idea is to transmit medical data on the subcarriers for realtime traffic when these subcarriers are available and, otherwise, to store these medical data in patient devices; this is a tradeoff between the traffic load in the WLAN and the memory size of patient devices. In addition, based on the patient status, the medical data are classified into normal data and abnormal data, and the delay requirement of the transmission of abnormal medical data is taken into account. Based on this scheme as well as the requirements of various types of traffic, the method for optimal bandwidth allocation to minimize the number of subcarriers is obtained by solving a dynamic programming problem.

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 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 score0.962
Threshold uncertainty score0.245

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)0.0000.000

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 head0.022
GPT teacher head0.268
Teacher spread0.246 · 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

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

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