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Record W2476341172 · doi:10.5539/mas.v10n8p56

Reliable Wireless Sensor Protocol Based Health Monitoring System

2016· article· en· W2476341172 on OpenAlexvenueno aff
Munther Naif Thiyab

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceUploadNode (physics)Focus (optics)Protocol (science)Sensor nodeWireless sensor networkSIGNAL (programming language)Process (computing)WirelessNetwork packetComputer networkReal-time computingEmbedded systemComputer hardwareWireless networkKey distribution in wireless sensor networksTelecommunicationsMedicineEngineeringOperating system

Abstract

fetched live from OpenAlex

The patient monitoring during normal activity is getting more and more significant as a standard method to prevent craniology process for detection of transient ischemiaperiod ,cardiac arrhythmias as well as silent myocardium ischemic. In this paper, we mainly focus on the structureand the composition of awireless (600m) synchronizationarrhythmias invigilator as well as a alarming device for patients. To realize the corresponding functions, a Wireless Transducer Protocol (WTP) based on Time Divisibility Double (TDD) is what we require, the implemented system is totally composed of four main nodes includingthe Core (dominant) node which is a personal computer-based Graphic user system. It works at anstable frequency of 915MHz. The passive node is a digital signal processor-based board connected with the patients whichcould receive two channels of full-spectrum ECG signal at the same time, and uploads processed data at a specificperiod to the core node. The MPC8260 communications and the computeris composed of the dominant nodedesigned to receive data, decompress, and analyze the latest data baggage. The SRWF-501F915 completednoderealize the data communication.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.621
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.314
Teacher spread0.284 · 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 designBench or experimental
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

Citations0
Published2016
Admission routes1
Has abstractyes

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