MétaCan
Menu
Back to cohort
Record W3040950080 · doi:10.21608/ijisd.2020.101620

Design Methodology Framework for Cyber-Physical Products

2020· article· en· W3040950080 on OpenAlexaff
Haider Al-Fedhly, Waguih ElMaraghy

Bibliographic record

VenueInternational Journal of Industry and Sustainable Development · 2020
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceCyber-physical systemBlueprintVariety (cybernetics)Systems designComplex systemContext (archaeology)Systems engineeringPhysical systemHuman–computer interactionDistributed computingSoftware engineeringArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Dealing with complex systems often involves a layering (e.g.: hierarchical) representation that isprevalent throughout engineering. This layering appears in various disciplines in a variety of forms. Concurrentdesign refers to a generalized methodology for mapping from the functional requirements and conceptual modelto blueprints in various domains. Cyber-Physical, hence complex, system include mechanical, electrical,sensors, computer, data, user interface, and external factors. The system is capable of acquiring historical data,receiving real-time sensory status, adapt accordingly while interacting with the environment. The purpose of thispaper is to introduce a novel design methodology approach for smart complex systems such as cyber-physicalproducts and machines. The potential impact of this methodology is to provide a common design approach forany smart system. It can also be used to calculate system complexity in the context of the coupling index.Additionally, it can reduce the compatibility issues at the early system design level.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.073
GPT teacher head0.302
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 designNot applicable
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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Industry and Sustainable DevelopmentSame topicDigital Transformation in IndustryFrench-language works237,207