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Record W2088514628 · doi:10.1177/1063293x11420176

Developing a Dynamic Wheelchair Using the Design Structure Matrix Method

2011· article· en· W2088514628 on OpenAlexaff
Mohammed Othman, Nadia Bhuiyan, Linghua Kong

Bibliographic record

VenueConcurrent Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsConcordia University
Fundersnot available
KeywordsWheelchairProcess (computing)Manual wheelchairEngineeringComputer scienceDesign processHuman–computer interactionSimulationOperations managementWork in process

Abstract

fetched live from OpenAlex

Involuntary extensor thrusts, experienced by wheelchair users with cerebral palsy, can cause injuries due to unexpected impacts with the wheelchair. Consequently, these unexpected motions can hurt the human body, damage the wheelchair, and change the correct position of the user’s pelvis. Many of the existing wheelchairs do not address all the needs of disabled people. The goal of this article is to develop an instrumented, dynamic seating system for people with extensor thrust using the Design Structure Matrix (DSM) tool in order to provide an efficient development sequence of the design tasks for three subsystems of the seat: the seat back, seat bottom, and footrest. This article provides a detailed application of the use of the DSM. It reveals that the design process of the three main systems can be executed concurrently with different teams having different specializations and proposes a method to minimize total design time.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.079
GPT teacher head0.329
Teacher spread0.250 · 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 designBench or experimental
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

Citations4
Published2011
Admission routes1
Has abstractyes

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