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Record W2596608889 · doi:10.18260/1-2--10608

Use Of The Ms Flight Simulator In The Teaching Of The Introduction To Avionics Course

2020· article· en· W2596608889 on OpenAlexaffabout
Ruxandra Mihaela Botez, Iulian Cotoi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAvionicsAerospaceAeronauticsCourse (navigation)Presentation (obstetrics)Class (philosophy)Session (web analytics)EngineeringCockpitInstrumentation (computer programming)Integrated modular avionicsComputer scienceSystems engineeringMultimediaEmbedded systemSimulationOperating systemAerospace engineeringArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Main Menu Session 1928 Use of the MS Flight Simulator in the teaching of the Introduction to avionics course Iulian Cotoi, Ruxandra Mihaela Botez Ecole de technologie supérieure Département de génie de la production automatisée 1100 Notre Dame Ouest Montréal, Qué., Canada, H3C 1K3 Introduction The course Introduction to avionics GPA-745 is an optional course in the Aerospace program given in the Department of Automated Production Engineering at École de technologie supérieure in Montreal, Canada. The main objectif of this course is the study of electronic avionics instrumentation installed in aircraft. In this course, the following chapters are presented : History of avionics, Methods of navigation and orientation, Pilot cockpit and board instrumentation, Communication systems, Radio-navigation systems, Landing systems, Engine signalization instruments, Central alarm systems, Maintenance systems and Warning systems. The presentation of the course in the class to the students is shown on PowerPoint slides and videos on modern aircraft such as Airbus and Boeing. Also, regarding the pilot induced oscillations a video film is provided from Bombardier Aerospace. However, the presentation of the course in the class may be improved and become more efficient grace to the use of MS Flight Simulator. The main idea of this paper is to show how the participation of the students in the class will be increased by use of the MS Flight Simulator. The use of the systems and the electronic board instrumentation will be shown with the help of the new flight simulations modules realized within the MS Flight Simulator. For each instrument, one module will be created and presented in the class, which will result in a more interesting course presentation, stimulating and dynamical from pedagogical point of view, than the theory of the course by use of PowerPoint. In these modules, the use of : - Flight instruments for the aircraft control - Radio-navigation systems for landing such as ILS and MLS - Board instrumentation and radio-navigation systems such as VOR and ADF will be analyzed for the flight main phases : take-off, climb, horizontal flight, descent, landing, and turns. Main Menu

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.427

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1280.052

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

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Citations1
Published2020
Admission routes2
Has abstractyes

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