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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Artificial Neural Network for Predicting the Maximum Load at Failure of Sawdust-Ash-Cement Blends Reinforced Concrete Beams

2025FUOYE Journal of Engineering and TechnologyJournalOpen access

10.4314/fuoyejet.v10i3.26 Full text0 citations

Authors

3 authors across 2 institutions in 1 country.

Oluwatoyin E. OsanyinlokunFirst author
- Afe Babalola University (NG)
- Federal University Oye Ekiti (NG)
O.M. Olaniyan
- Federal University Oye Ekiti (NG)
as printed: Olatayo M. Olaniyan
Christopher A. FapohundaSenior author

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Innovative concrete reinforcement materialslevel 3 · 0.40
Concrete and Cement Materials Researchlevel 3 · 0.34
Concrete Properties and Behaviorlevel 3 · 0.08

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2025 · FUOYE Journal of Engineering and Technology · 0 citations
https://openalex.org/W7124252279

Artificial Neural Network for Predicting the Maximum Load at Failure of Sawdust-Ash-Cement Blends Reinforced Concrete Beams · Sankore