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An Inductive Power Transfer System With Adjustable Compensation Network For Implantable Medical Devices

2019· article· en· W2999061804 on OpenAlexaff
Yilin Zhao, Xian Tang, Zhihua Wang, Wai Tung Ng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaximum power transfer theoremCompensation (psychology)Computer scienceElectrical engineeringPower (physics)Transfer (computing)Electronic engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

A reliable wireless power transfer (WPT) system with constant voltage output is necessary for power charging of implantable medical devices (IMDs). This paper proposes a single-loop WPT system with an adjustable compensation network in which the capacitor array can be altered. It can provide constant voltage supply without regulating circuit in the receiver, which benefits for IMDs. A prototype is built up and the measurement results validate the effectiveness of the proposed method. Typically, this system works properly at various values of load resistance and coupling coefficient. The measurement results show that when the coils' distance ranges from 32 mm to 40 mm and the load resistance varies from 100 Ω to 500 Ω, the capacitor array can be adjusted automatically to offer the load almost constant voltage at 3.4 V.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.700

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 head0.006
GPT teacher head0.201
Teacher spread0.194 · 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
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

Citations2
Published2019
Admission routes1
Has abstractyes

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