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Record W4206414825 · doi:10.18280/rces.080401

Real-Life Survey of Assistive Technologies Developed for the Visually Impaired

2021· article· en· W4206414825 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of Computer Engineering Studies · 2021
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsVisually impairedArduinoRaspberry piAssistive technologyHuman–computer interactionComputer scienceMultimediaApplied psychologyEngineeringSimulationEmbedded systemPsychologyInternet of Things

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate the problems that the visually impaired are facing by depicting the outcome of real-life research conducted with the participation of around 100 people in a Blinds’ Institute, Khulna, Bangladesh. It represents the performance of assistive technologies developed for safe and comfortable navigation to help visually impaired people. To execute this research, an extensive objective and subjective experimental evaluation have been done with the help of Raspberry-Pi and Arduino Uno-based systems and the students at the blinds’ institute. The accuracy of the Raspberry-Pi-based system is 64% and the Arduino-based system is only 36%. These findings might help the researchers to understand and detect the most significant devices and highlight the performance to design and implement devices that would ensure proper safety, convenience, and independent mobility to the visually impaired.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.512
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.116
GPT teacher head0.368
Teacher spread0.252 · 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