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Record W2312189361 · doi:10.7210/jrsj.32.550

Saddle Type Human Body Motion Interface for Personal Mobility Vehicle

2014· article· en· W2312189361 on OpenAlex
Sho Yokota, Hiroshi Hashimoto, Daisuke Chugo, Kuniaki Kawabata

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

VenueJournal of the Robotics Society of Japan · 2014
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsInterface (matter)Personal mobilitySimulationUsabilityMotion (physics)SaddleComputer scienceEngineeringHuman–computer interactionComputer visionMechanical engineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper proposes the human body motion interface for personal mobility vehicle including the user's twisting motion. First, saddle is attached on the personal mobility vehicle using the seat post which has the universal joints at the attachment portion. The universal joints have three rotational joints where the potentio meters are attached on each. By hip motion, the joints are moved. The potentio meters detect these rotations. Next, we introduced the sigmoid function to connect the motion of hip and the velocity of the personal mobility vehicle. Finally, the experiment was conducted to confirm the usability. In the experiment, the control interface was prepared which doesn't use the twisting motion of the hip. The subjects drive the personal mobility vehicle on the figure 8 course layout by using proposed interface and control interface. The lap times were measured in both interface and compared. After driving the vehicle, the paired preference test was conducted. The lap time using proposed interface was shorter than the control interface, and the paired preference test showed the proposed interface is intuitive.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.024
GPT teacher head0.279
Teacher spread0.254 · 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