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Record W2150606304 · doi:10.1109/te.2008.919690

A Laboratory Setup and Teaching Methodology for Wireless and Mobile Embedded Systems

2008· article· en· W2150606304 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.

Bibliographic record

VenueIEEE Transactions on Education · 2008
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsMcGill University
Fundersnot available
KeywordsWirelessComputer scienceDigital electronicsSoftwareWireless networkArchitectureEmbedded systemSoftware engineeringMultimediaMobile deviceSystems engineeringEngineering managementElectronic circuitComputer architectureEngineeringTelecommunicationsElectrical engineeringOperating system

Abstract

fetched live from OpenAlex

Increasingly, electrical and computer engineers are making their careers in designing wireless embedded systems. This paper presents a teaching methodology and the associated laboratory setup designed to meet the needs in teaching wireless embedded systems. The courses allow the students not only to apply their previous knowledge of digital system design, computer architecture, electronic circuits, wireless networking, and software engineering, but experience actual systems engineering by designing and implementing a large-scale team project within a semester. A flexible hardware platform was developed and was accompanied by teaching methodologies that allow quick completion of ambitious course projects in this area.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.508

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 head0.020
GPT teacher head0.281
Teacher spread0.261 · 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