MétaCan
Menu
Back to cohort
Record W2384636886 · doi:10.1145/2834119

A System-Level Modeling and Design for Cyber-Physical-Social Systems

2016· article· en· W2384636886 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

VenueACM Transactions on Embedded Computing Systems · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsComputer scienceCyber-physical systemPetri netField (mathematics)Distributed computingCyberspaceDesign flowSystems designRepresentation (politics)Human–computer interactionThe InternetSoftware engineeringEmbedded system

Abstract

fetched live from OpenAlex

The design of cyber-physical-social systems (CPSS) is a novel and challenging research field due that it emphasizes the deep fusion of cyberspace, physical space, and social space. In this article, we extend our previously proposed system-level design framework [Zeng et al. 2015] to tailor it to the needs of social scenario of multiple users. A hierarchical Petri net-based model and social flow are presented to extend the control flow and formally describe the social interactions of multiple users, respectively. By using the extended model, the system-level optimization for CPSS can be achieved by the improved design flow. Specifically, object emplacement and user satisfaction are further extended into the social environment. Also maximal power estimation algorithm is improved, leveraging the extended intermediate representation model. Finally, we use a smart office case to demonstrate the feasibility and effectiveness of our improved design approach for multiple users.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.211
GPT teacher head0.396
Teacher spread0.186 · 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