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Record W4396620760 · doi:10.36950/2024.3ciss009

Design and build of a portable apparatus for measuring lace tension

2024· article· en· W4396620760 on OpenAlexaff
K. Lockwood, Tzu-Ting Hsu, Colin Dunne, John-Allan Ellingson

Bibliographic record

VenueCurrent Issues in Sport Science (CISS) · 2024
Typearticle
Languageen
FieldComputer Science
TopicWeb Applications and Data Management
Canadian institutionsGeorge Brown CollegeBrock University
Fundersnot available
KeywordsTension (geology)Engineering drawingComputer scienceEngineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Laces have traditionally been used to secure the foot, limit slippage, enhance fit, and prevent injury across different types of footwear. Quantitatively assessing the merits and effectiveness of laces is technically challenging due to the lack of portable instrumentation that can measure lace tension reliably. Therefore, the purpose of the study was to design and build a portable apparatus to quantify lace tension to be used on footwear in both laboratory and real-world environments. The apparatus was designed to meet three major design criteria: (i) portable, (ii) able to accommodate different types of footwear, lace materials, and lacing patterns, and (iii) able to measure lace tension while the footwear is secured on the foot. As a result of the design process, the apparatus consisted of a base, fabricated from High Density Polyethylene (HDPE), and a frame, made from aluminum and 3D printed Acrylonitrile Butadiene Styrene (ABS). A measurement system was affixed to the frame and consisted of a lever, a non-deformable cable with a hook, a load cell, a caliper, and a microcontroller to measure the force and change in length of laces when a force was applied. The total height and weight of the apparatus was 25.5 cm and 6.35 kg, respectively. A reliability analysis was conducted using three different types of laces (waxed, non-waxed, and carbon fiber blend) and revealed a high internal consistency within lace types with alpha values of 0.95, 0.81, 0.91, respectively. The interclass reliability coefficient across lace types revealed an alpha value of 0.84. As a result of the design, build, and reliability analysis, the apparatus was able to provide reliable measurements of lace tension while satisfying the design criteria. It is envisioned that the apparatus can be used for ongoing investigations across different types of footwear and different types of laces.

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)0.002
metaresearch head score (Gemma)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.057
GPT teacher head0.336
Teacher spread0.279 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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