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Record W2152677022 · doi:10.1109/iecon.2005.1569248

A novel system on a programmable chip design of a fastflex data controller

2005· article· en· W2152677022 on OpenAlexfundno aff
T.J. Coggins, Marcian Cirstea

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsnot available
FundersCanadian Institute of Steel Construction
KeywordsVHDLField-programmable gate arrayFlexibility (engineering)Computer scienceReuseEmbedded systemTime to marketController (irrigation)Hardware description languageProcess (computing)ASCIIComputer architectureProgrammable logic controllerSystem on a chipSoftware engineeringOperating systemEngineering

Abstract

fetched live from OpenAlex

Transmitton Ltd. is a competitive manufacturer of industrial control equipment in the UK. The company has embarked on a process of re-designing its products, using hardware description languages (HDLs) and targeting reprogrammable devices-field programmable gate arrays (FPGA's) for implementation. This paper presents a novel approach to the redesign of the existing discrete integrated circuits used in Transmitton's fastflex range of products, as system on a programmable chip. This marks the objective of ongoing research collaboration between the company and Anglia Polytechnic University, UK. The advantages of applying the HDL-based methodology consist of: i) using the same environment for modelling, design and implementation, ii) a computer platform independent model (VHDL files are ASCII files), iii) the ability to reuse components of the model in different data-processing applications (in combination with other models to form complex controller systems), iv) the prototyping via FPGA implementation, giving extra benefits. The new university led approach will bring important benefits to the company in terms of commercial competitiveness, intellectual property (IP) ownership, flexibility in the range of in-house developed systems and short time to market for new products.

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)0.002
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.093
GPT teacher head0.294
Teacher spread0.201 · 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 designSimulation or modeling
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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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