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Record W4295789121 · doi:10.1109/jmass.2022.3206713

Flight Software Development for a CubeSat Application

2022· article· en· W4295789121 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Journal on Miniaturization for Air and Space Systems · 2022
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsUniversité de Moncton
FundersNew Brunswick Innovation FoundationUniversité de MonctonCanadian Space AgencyUniversity of New Brunswick
KeywordsCubeSatSoftwareComputer scienceSTM32Operating systemEmbedded systemSoftware developmentSatelliteEngineeringTelecommunicationsAerospace engineering

Abstract

fetched live from OpenAlex

This article presents a development of a CubeSat mission software running on an STM32-based on-board computer (OBC). This was conducted under the Canadian CubeSat Project, initiated by the Canadian Space Agency in 2018 to support the development of 15 CubeSats across Canada. The proposed mission software has a multilayered architecture and is divided into five layers from a low layer dedicated to the peripherals to the top layer dedicated to the Mission Applications. The CubeSat protocol (CSP) is used at the communication layer for easing connectivity between subsystems and to communicate with the ground segment. The mission software running on the OBC is built to meet many requirements defined for this satellite, such as version control, classifications, margins, etc. The CubeSat will be able to accomplish two scientific missions related to the study of space weather once the satellite is put into orbit from the International Space Station. An overview of the software running on the OBC is presented, written in C Language, and includes the implementation of the CSP. FreeRTOS used as an operating system for the OBC is also presented. A Command Line Interface was designed for testing purposes to ensure software efficiency and some results are discussed in this article. The flight software consists of three main tasks and subtasks. Of the 1024 kB of flash memory, only 240 kB was used which represents less than 20% of the total memory. The CPU load is 34% for normal, manual, and maintenance modes and 16% for failure modes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.526

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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