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Record W2151421260 · doi:10.1109/ithet.2005.1560235

Virtual Versus Real Design Of A Traffic Light/Voice Controller

2005· article· en· W2151421260 on OpenAlexaff
Philip Daum, B. Fukuda, N. Jensen, G.C. Hancock, C. Ciubotariu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsUniversity of Calgary
FundersUniversity Grants Committee
KeywordsComplex programmable logic deviceController (irrigation)Computer scienceProgrammable logic deviceProcess (computing)Synchronization (alternating current)Programmable logic controllerInterface (matter)VisualizationComputer hardwareEmbedded systemVirtual realityMicroprocessorSet (abstract data type)Real-time computingArtificial intelligenceTelecommunicationsOperating systemChannel (broadcasting)

Abstract

fetched live from OpenAlex

The traffic light/voice controller is a sequential machine to be analyzed and programmed through a multi-step process. Both the hands-on and the virtual environments are described. The design projects of the four teams of fourth year students who developed the device involved: analysis of existing sequential machines in traffic light controllers, timing and synchronization, role and introduction of LEDs and of the push buttons for pedestrian walk requests and visual signals and various regimes of operation and flashing lights/voice synthesis sequence. The light system comprises a programmable ALTERA logic unit with a wired up set of LEDs and other electronic components. A low cost complex programmable logic device (CPLD) by ALTERA is used in the voice synthesis part of the traffic controller interface. The novelty of this digital design project is given by the systematic procedure set for the analysis of the controller operation and of the various circuits and digital elements involved. A CVI-based (computer visualization interface) simulation accompanies the real-time operation of the traffic light controller and time simulations of electric signals (shift registers for machine states) are also part of this teaching/learning tool. The students and other users can perform a virtual (remote) operation of the lights/voice sequence, test the electronic components and the programmable unit and check their results with the CVI simulation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.658

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)0.0010.000

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 head0.056
GPT teacher head0.338
Teacher spread0.282 · 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 designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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