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Record W4389521567 · doi:10.23977/acss.2023.071010

The basic principles and application areas of embedded systems

2023· article· en· W4389521567 on OpenAlexvenueno aff
Jia Ai

Bibliographic record

VenueAdvances in Computer Signals and Systems · 2023
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsnot available
Fundersnot available
KeywordsAutomotive industryField (mathematics)Systems engineeringElectronicsComputer scienceDomain (mathematical analysis)Embedded systemManufacturing engineeringEngineeringElectrical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

This paper discusses the fundamental principles and widespread application areas of embedded systems. Embedded systems represent an interdisciplinary field of computer science and electronic engineering, known for their compact, efficient, and domain-specific characteristics. The paper begins by introducing the concept and components of embedded systems, followed by a detailed examination of their applications in domains such as healthcare, automotive, industrial control, and consumer electronics. Subsequently, design principles and challenges of embedded systems are discussed. Finally, by analyzing current technological trends and future prospects, the paper summarizes the opportunities and challenges that embedded systems face as they continue to evolve and expand.

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)0.001
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: none
Teacher disagreement score0.587
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.240
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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