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Record W92127656 · doi:10.3233/jid-2004-8404

ENVIRONMENT-BASED FORMULATION OF DESIGN PROBLEM

2004· article· en· W92127656 on OpenAlexaff
Yong Zeng

Bibliographic record

VenueJournal of Integrated Design and Process Science · 2004
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceMathematical optimizationBiochemical engineeringMathematicsEngineering

Abstract

fetched live from OpenAlex

This paper proposes a formal definition of design problem using the axiomatic theory of design modeling. Based on the concept of product system and an informal description of design problem, a design problem is formulated into three parts: environment, structural requirements, as well as performance requirements. On the basis of this formulation, both structural requirements and performance requirements are related to product environment, which is divided into natural, built, and human environments. As a result, product environment is identified as the source of product requirements. An environment-based formulation of design problem is thus developed. This formulation implies that both design problem and design solutions are included in a product system. The design governing equation is formulated to capture the interdependence relation between product problem and product descriptions along the design process. An example of rivet setting tool design is used to illustrate the mathematical formulations throughout the paper.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.025
GPT teacher head0.264
Teacher spread0.239 · 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 designTheoretical or conceptual
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

Citations96
Published2004
Admission routes1
Has abstractyes

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