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Two Albanian Mosques: the acoustics discovery inside prayer rooms

2021· article· en· W3217482787 on OpenAlexaff
Silvana Sukaj, Umberto Berardi, Giuseppe Ciaburro, Gino Iannace, Amelia Trematerra, Antonella Bevilacqua

Bibliographic record

Venue2021 Immersive and 3D Audio: from Architecture to Automotive (I3DA) · 2021
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPrayerActive listeningComputer scienceTheologyPhilosophyPsychologyCommunication

Abstract

fetched live from OpenAlex

The first mosque was built by Prophet Mohammad in 7thcentury. In Muslim society, mosques are important buildings erected with regular plants. The walls are plastered or finished with mosaics, the floor is carpeted; often, they are provided with a dome and side niches. The main activities are praying and listening to speech and, for these reasons, speech understanding is of paramount importance. This paper deals with the acoustic characteristics of two mosques in Albania. These buildings have a squared plan layout surmounted by a dome at the center of the space. Acoustic measurements were undertaken in line with the methodology explained by ISO 3382-1 standard. The monaural parameters T30, EDT, $C_{80}, D_{50}$, and STI were analyzed accordingly. One of the mosques is located in Tirana and was built in 1550; it has a volume of 1000 m3. This mosque showed a T30of 2.0 s and an STI of 0.5. The other mosque is located in Shkoder; it was built in 1750 and has a volume of 1300 m3. This latest mosque showed a T30of 2.3 s and a STI of 0.5. After comparing the acoustics of these two mosques, some solutions to improve their acoustics are suggested.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.234
Teacher spread0.226 · 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 designObservational
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

Citations9
Published2021
Admission routes1
Has abstractyes

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