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Development and Analysis of Electronic and Electrical Experiment Simulation Technology

2021· article· en· W3131305594 on OpenAlexaboutno aff
Liuning Zhu, Chuanwu Liu

Bibliographic record

VenueJournal of Physics Conference Series · 2021
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsElectronic circuit designElectronicsComputer scienceWorkbenchElectronic circuit simulationSoftwareElectronic componentCircuit diagramElectronic circuitDigital electronicsCircuit designReliability (semiconductor)Simulation softwareElectrical engineeringEmbedded systemEngineeringVisualizationArtificial intelligence

Abstract

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Abstract The development of electronic and electrical technology is based on the tedious experiment of electronic and electrical engineering, which is operated by electronic working platform. EWB (electronic workbench) is a kind of electronic circuit simulation software developed by Canadian interactive image technology company in 1988. The software design function is perfect, the operation interface is friendly, the image is very easy to master. The software core of EWB is Spice3f5, which enhances its simulation ability in digital and analog mixed signals. The development of EWB not only solves the problem of time-consuming, laborious and expensive in electronic circuit design, but also brings great convenience and benefits to electronic product designers. They can use computer-aided design to carry out circuit simulation, which can effectively save development time and cost. Only through continuous experiments can we verify the reliability of the circuit and improve the circuit design, but in the specific experimental operation, some factors often lead to the failure of the experiment, which not only increases the cost of the electronic and electrical experiment, but also destroys the original equipment, and also has certain risks. Therefore, to solve this problem, the simulation technology has been widely used in the electronic and electrical experiment. Moreover, the convenient operation mode of EWB, the intuitive circuit diagram and the display form of simulation analysis results are also very suitable for the auxiliary teaching of electronic course, which is conducive to improving students' understanding and mastery of theoretical knowledge and cultivating students' innovation ability. Therefore, many universities in the world have brought EWB into the teaching of electronic courses. This paper mainly describes the application value and specific application mode of simulation technology in electronic and electrical experiment, in order to further expand the application scope of simulation technology in electronic and electrical experiment. The component library of EWB provides thousands of circuit components, including passive components and active components, analog components and digital components, discrete components and integrated components, as well as new or expanded existing component libraries. EWB also provides a complete set of virtual instruments, such as oscilloscope, signal generator, multimeter, baud chart instrument, spectrum analyzer and logic analyzer. Using these components and instruments to simulate electronic circuits is just like doing experiments in a laboratory. It is very real. Moreover, it is not necessary to worry about damaging the instruments and components, or to be at a loss for outdated instruments and insufficient measurement accuracy. This paper first analyzes the advantages of simulation technology in the application of electronic and electrical experiment teaching, and then analyzes the experimental means and application practice of simulation technology in detail[1].

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.009
GPT teacher head0.239
Teacher spread0.229 · 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 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".

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Citations3
Published2021
Admission routes1
Has abstractyes

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