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Novel Low Power System Design for Aviation Industrial Data Logger

2023· article· en· W4397000122 on OpenAlexaff
Esteve Hassan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsMohawk College
Fundersnot available
KeywordsData loggerProcess (computing)Data acquisitionEngineeringComputer scienceAutomotive engineeringEmbedded systemSystems engineeringComputer hardwareReal-time computing

Abstract

fetched live from OpenAlex

This paper is intended to describe the design process, planning, and development of a new Data Logger System (DLS) that can be potentially used in acquiring sensor signals in the landing gear of aircraft. The developed data logger system is capable of simultaneously recording 32 channels of incoming data provided by conditioned sensors. The data recorder system is meant to be an integrated tool to supplement landing gear studies at Safran Landing Systems. The main module of the product will house the vital DLS electronics which include, but are not limited to, a data logger system control board, power management system, and sensors/data interfaces. The developed work presents the concept and development process of the DLS that employs a novel low-power pulse mode circuit structure. It outlines the overview of the sensor acquisition system and manufacturing of the DLS housing to fit the industrial partner's requirements. The conducted work is broken down into several phases, these include conceptual design, development, production, and testing.

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: none
Teacher disagreement score0.995
Threshold uncertainty score0.459

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 head0.106
GPT teacher head0.266
Teacher spread0.160 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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