Selecting the optimal gridded climate dataset for Nigeria using advanced time series similarity algorithms.

Autor: Tanimu B; Department of Water Resources and Environmental Engineering, Ahmadu Bello University Zaria, Kaduna, Nigeria.; Department of Water and Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudia, Johor, Malaysia., Hamed MM; Construction and Building Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), B 2401 Smart Village, Giza, 12577, Egypt., Bello AD; Department of Water Resources and Environmental Engineering, Ahmadu Bello University Zaria, Kaduna, Nigeria., Abdullahi SA; Department of Water Resources and Environmental Engineering, Ahmadu Bello University Zaria, Kaduna, Nigeria., Ajibike MA; Department of Water Resources and Environmental Engineering, Ahmadu Bello University Zaria, Kaduna, Nigeria., Shahid S; Department of Water and Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudia, Johor, Malaysia. sshahid@utm.my.; Environmental and Atmospheric Sciences Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, Nasiriyah, 64001, Iraq. sshahid@utm.my.

Publikováno v: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2024 Feb; Vol. 31 (10), pp. 15986-16010. Date of Electronic Publication: 2024 Feb 03.

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Yield and Yield Componemts of Extra Early Maize (Zea Mays L.) as Influenced by Intra-Row Spacing, Nitrogen and Poultry Manure Rates

Autor: Sharifai, AI, Mahmud, M, Tanimu, B, Abubakar, IU

Publikováno v: Bayero Journal of Pure and Applied Sciences; Vol 5, No 1 (2012); 113-122

Field trials were conducted during the rainy seasons of 2006, 2007 and 2008 at the Institute for Agricultural Research (I.A.R.) Farm, Samaru to determine the performance of extra early maize (Zea mays L.) as affected by intra-row spacing, nitrogen an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=78975075580c::2fb5a482212a3ce3201d2ffb23a6a7ff
https://www.ajol.info/index.php/bajopas/article/view/80948

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Developing Machine Learning Models for Catalysts in Oxidative Dehydrogenation of n‐butane.

Autor: Tanimu, Gazali¹ (AUTHOR) gazali.tanimu@kfupm.edu.sa, Olawale Ajadi, Jimoh^1,2 (AUTHOR), Yahaya, Yussif² (AUTHOR), Alasiri, Hassan^1,3 (AUTHOR), Adegoke, Nurudeen A.⁴ (AUTHOR)

Publikováno v: ChemCatChem. 9/8/2023, Vol. 15 Issue 17, p1-9. 9p.