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Record W7046317456

Design and Development of Ground Segment Software and Hardware for Nanosatellie Space Missions

2013· dissertation· en· W7046317456 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typedissertation
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsSoftwareVisualizationKey (lock)Space explorationProcess (computing)SatelliteScheduling (production processes)Development (topology)Software developmentGround segment
DOInot available

Abstract

fetched live from OpenAlex

Contributions to two nanosatellite missions are discussed. First, the design and development of a test system for an advanced nanosatellite power board is discussed. Details of software and hardware design process involved in the implementation of automated test procedures are presented. The system has been deployed for unit-level testing of power boards for several nanosatellite missions, significantly reducing testing cost and time. Next, a Mission Planning and Scheduling Software platform is proposed for Earth Observation missions. The motivation is described for the development of a stand-alone application enabling satellite operations teams to identify suitable observation scenario parameters. Attitude and orbital trajectory estimation algorithms constituting the computational model are integrated and implemented within a graphical visualization environment to allow interaction with the user in an efficient and intuitive manner. Key results of major component-level testing are presented, showing the behaviour and accuracy of analytical components satisfy mission requirements.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score1.000

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 head0.152
Teacher spread0.146 · 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.

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
Published2013
Admission routes1
Has abstractyes

Explore more

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