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Record W2784273521 · doi:10.24843/mite.2017.v16i03p05

RANCANG BANGUN PEMANDU TUNA NETRA MENGGUNAKAN SENSOR ULTRASONIK BERBASIS MIKROKONTROLER

2017· article· id· W2784273521 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.

Bibliographic record

VenueMajalah Ilmiah Teknologi Elektro · 2017
Typearticle
Languageid
FieldComputer Science
TopicIoT-based Control Systems
Canadian institutionsArbutus Biopharma (Canada)
Fundersnot available
KeywordsPhysicsOperating systemHumanitiesComputer scienceArt

Abstract

fetched live from OpenAlex

Penyandang tuna netra memiliki kondisi fisik yang terbatas. Kondisi fisik ini membuat penyandang menggunakan tongkat sebagai alat pemandu dalam kegiatan sehari-hari. Kemajuan teknologi membantu penyandang mengganti tongkat dengan alat pemandu menggunakan sensor ultrasonik sehingga lebih leluasa bergerak. Sensor ultrasonik bekerja dengan memanfaatkan gelombang ultrasonik sebagai pemancar dan menghitung jarak dengan perbedaan selisih waktu. Kepekaan sensor ultrasonik dari 2 cm sampai 200 cm. Pengolah data yang digunakan adalah mikrokontroler arduino dan keluaran berupa motor getar. Alat pemandu tuna netra menggunakan sabuk sebagai desain utama. Sensor diletakkan pada sisi kiri, depan, dan kanan sabuk untuk mendeteksi benda yang berada pada jarak pantulan sensor. Motor getar diletakkan pada samping sensor untuk memberikan getaran ketika sensor ultrasonik aktif. Alat pemandu tuna netra mempunyai spesifikasi dalam mendeteksi jarak 30 cm di kiri sabuk, 150 cm di depan sabuk, 30 cm di kanan sabuk dan 120 cm – 125 cm di bawah sabuk.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0040.002
Open science0.0090.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.004

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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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