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Record W3094444119 · doi:10.37277/stch.v26i2.510

Pengendalian Jalur Voice Dari VHF-ER Repeater Sibiru-Biru Menggunakan Mobile Communication

2020· article· id· W3094444119 on OpenAlexaff
Syamsul El Yumin, Waginto Waginto, Masbah R. T. Siregar

Bibliographic record

VenueSainstech Jurnal Penelitian dan Pengkajian Sains dan Teknologi · 2020
Typearticle
Languageid
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Desk control sebagai perangkat utama ATC Bandara Polonia Medan dilengkapi dengan transmitter kendali wilayah penerbangan yang ditempatkan di Sibiru Biru, sejauh 24 km, yang terhubung dengan transmisi utama melalui satelit V-sat dan back up menggunakan radio link. Operasi V-sat dilakukan oleh Vendor belum tentu bisa menjamin sesuai dengan keinginan bandara dan respons waktu operasi normal cukup lama, 15 sampai 40 menit. Respons waktu itu sangat mengganggu pelayanan bandara, dimana sifat pelayanan dengan waktu on time. Dengan mengembangkan suatu perancangan kendali switch otomatis pada kedua jalur tersebut sesuai SOP serta dilengkapi pelayanan manajemen komunikasi Handphone (HP) yang dapat digunakan oleh pembuat keputusan kendali jalur jarak jauh secara otomatis, hal ini dapat dikendalikan dimana saja tanpa harus berada di lokasi. Dengan basis Dual Tone MultiFrequency (DTMF), suatu komponen yang dapat meng-konversi tombol angka HP menjadi datadigital 4 bit, dan seterusnya dapat digunakan sebagai sumber infromasi kendali jalur VHF-ER jarak jauh. Respons waktu switch jauh lebih kecil dibandingkan dengan operasi normal, kurang dari 3 s. Akan tetapi kendali melalui HP akan lebih lama dari waktu ini karena dipengaruhi oleh waktu tunda pada system komunikasi seluler yang ada, yang sulit diprediksi.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.011

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 head0.045
GPT teacher head0.295
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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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