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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.

Machine learning models for predicting the compressive strength of agro-waste stabilized bricks for sustainable buildings

2024Discover Civil EngineeringJournalOpen access

10.1007/s44290-024-00052-4 Full text12 citations

Authors

6 authors across 4 institutions in 2 countries.

Ifeyinwa Ijeoma ObianyoFirst authorCorresponding
- Nile University of Nigeria (NG)
Jonathan Timothy Auta
- African Institute of Science and Technology (NG)
David Sciacca
Assia Aboubakar Mahamat
- Nile University of Nigeria (NG)
S. E. Kelechi
as printed: Sylvia Echezona Kelechi
Azikiwe Peter OnwualuSenior author
- African Institute of Science and Technology (NG)

Fields

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

Innovations in Concrete and Construction Materialslevel 3 · 0.99
Hygrothermal properties of building materialslevel 3 · 0.99
Recycled Aggregate Concrete Performancelevel 3 · 0.98

Sources

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

openalexseen September 9, 2026
2024 · Discover Civil Engineering · 12 citations
https://openalex.org/W4401550322

Machine learning models for predicting the compressive strength of agro-waste stabilized bricks for sustainable buildings · Sankore