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Record W1547044236 · doi:10.24908/pceea.v0i0.3097

Requirements to Properties- Iterative Problem Solving

2010· article· en· W1547044236 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2010
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsComputer scienceProcess (computing)Set (abstract data type)Iterative and incremental developmentFunctional requirementSystems engineeringSoftware engineeringEngineeringProgramming language

Abstract

fetched live from OpenAlex

Following papers by this author in recent CDEN conferences, the concept of a complete theory-based classification is presented for the properties of existing transformation processes TrfP, and of their existing driving technical systems TS. Requirements for future TrfP and TS must include requirements set by the designing and manufacturing organization(s), the first three life-cycle phases in the theory-based model. An engineering design process intends to translate these requirements in several stages to the desired properties of TrfP and TS, using conscious or sub-conscious procedures for creative and routine steps.
 For novel systems, this translation progresses via models of structures of TrfP, technologies, TS-internal and cross-boundary functions, organs and construc-tional parts. For redesign, mainly the more concrete structures are useful. Superimposed on this progress is a frequent cycle of problem-solving, including search for alternative solution proposals. Recent insights have shown that the requirements can be iteratively translated into properties. The difference between achieved (anticipated) properties and the relevant requirements dictated the necessary iteration behaviour, and drive the process of establishing the final proposed solution.
 Such a formalized experience of staged and iterative designing is a good methodical basis for novices, and for design applications in which the process must substantially depart from routine procedures. Some case studies are referenced to demonstrate the application of this systematic and methodical approach.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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