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Record W2003502346 · doi:10.1115/detc2002/cie-34461

A Distributed Multidisciplinary Design Optimization Framework Based on Web and Agents

2002· article· en· W2003502346 on OpenAlex
Weiming Shen, Hamada Ghenniwa

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

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsWestern UniversityNational Research Council Canada
Fundersnot available
KeywordsComputer scienceWeb modelingWeb serviceThe InternetWeb developmentServerWeb serverWorld Wide Web

Abstract

fetched live from OpenAlex

Web technology is playing an increasingly important role in collaborative product development systems. However, most Web-based applications were developed using client/server architecture for information sharing. This paper presents some results of an on-going research project on developing a distributed multidisciplinary design optimization (MDO) framework based on Web and agents. The primary objective is to develop an architectural framework for implementing MDO environments by integrating intelligent agents and Internet/Web based technologies. The principle is to leverage the right technology for the appropriate purpose. Agent-based negotiation is used for computing resource management or load balancing. Web-based interfaces are developed for users to access the MDO software environment and collaborate with each other. Active Web servers provide a way to integrate legacy systems separated by firewalls. The paper describes the proposed framework; presents a prototype environment for blow molded automotive parts design; and addresses some key issues in system implementation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.243
Teacher spread0.211 · 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

Quick stats

Citations12
Published2002
Admission routes1
Has abstractyes

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