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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.

Prediction of Compressive Strength for Recycled Rubber Aggregate Concrete Using Hybrid Machine-Learning Algorithms

2026International Journal of Concrete Structures and MaterialsJournalOpen access

10.1186/s40069-026-00887-4 Full text1 citations

Authors

9 authors across 4 institutions in 3 countries.

Md. Alhaz UddinFirst author
Md. Habibur Rahman SobuzCorresponding
Md. Abu Safayet
Md. Kawsarul Islam Kabbo
Md. Kanan Chowdhury Tilak
Mohammed Jameel
Bandar Alwushayh
Fayez Alanazi
Sani Aliyu AbubakarSenior authorCorresponding
- Kampala International University (UG)

Fields

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

Innovative concrete reinforcement materialslevel 3 · 0.93
Recycled Aggregate Concrete Performancelevel 3 · 0.05
Innovations in Concrete and Construction Materialslevel 3 · 0.00

Sources

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

openalexseen September 8, 2026
2026 · International Journal of Concrete Structures and Materials · 1 citations
https://openalex.org/W7129773280

Prediction of Compressive Strength for Recycled Rubber Aggregate Concrete Using Hybrid Machine-Learning Algorithms · Sankore