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Record W2110578625 · doi:10.1109/ccece.2004.1347584

A tool converting finite state machine to VHDL

2004· article· en· W2110578625 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsFinite-state machineVHDLComputer scienceHardware description languageProgramming languageComponent (thermodynamics)Representation (politics)Code (set theory)Transformation (genetics)State (computer science)Computer architectureTheoretical computer scienceComputer engineeringComputer hardwareEmbedded systemField-programmable gate array

Abstract

fetched live from OpenAlex

Finite state machines (FSM) are a basic component in hardware design; they represent the transformation between inputs and outputs for sequential designs. FSMs can be represented graphically, which would help the designer to visualize and design in a more efficient way; on the other hand the designer requires a fast direct way to convert the visualized design to hardware description language (HDL) code directly in order to simulate and implement it for synthesis and analysis. In this paper, we present a tool which, starting from a graphical FSM representation, produces a behavioral HDL code which can be directly analyzed and synthesized.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score0.558

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 science0.0010.000
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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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

Quick stats

Citations28
Published2004
Admission routes1
Has abstractyes

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