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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.

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char: A statistical neural network approach

2024Journal of Road EngineeringJournalOpen access

10.1016/j.jreng.2024.04.006 Full text12 citations

Authors

7 authors across 5 institutions in 5 countries.

Nura Shehu Aliyu YaroFirst authorCorresponding
- Ahmadu Bello University (NG)
Muslich Hartadi Sutanto
Noor Zainab Habib
A Usman
- Ahmadu Bello University (NG)
as printed: Aliyu Usman
Abiola Adebanjo
Surajo Abubakar Wada
- Ahmadu Bello University (NG)
Ahmad Hussaini JagabaSenior author

Fields

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

Asphalt Pavement Performance Evaluationlevel 3 · 1.00
Infrastructure Maintenance and Monitoringlevel 3 · 1.00
Innovative concrete reinforcement materialslevel 3 · 0.99

Sources

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

openalexseen September 9, 2026
2024 · Journal of Road Engineering · 12 citations
https://openalex.org/W4401438500

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char: A statistical neural network approach · Sankore