Communities in DSpace

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Recent Submissions

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Efficiency of Simpson’s Rule; A Case Study of Unilorin Land Area
(Nigerian Journal of Mathematics and Applications, 2026) Ayinla Ally Yeketi; Isola Olatomiwa Oluwadamilare
Simpson’s rule, a numerical integration technique, provides an efficient method for estimating the area of an irregularly shaped large landmasses when analytical solutions are impractical. This study applies Simpson’s 1/3, 3/8 and hybrid rules to determine the area of the University of Ilorin landmass. The hybrid method, combining the 1/3 and 3/8 rules, proves to be more efficient due to its flexibility with subintervals, improved accuracy and the efficient use of data points. Using the university’s map with a scale of 1.2 : 100, 000, the area was calculated as approximately 15, 200 hectares across all methods. The hybrid rule yielded the smallest absolute error compared to the estimated value of 15, 000 hectares. This work demonstrates that Simpson’s rule, particularly the hybrid approach, provides a practical and accurate method for land area calculations, suitable for complex geographical settings.
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Impact of Climate Change on Africa and the Challenges of the dispute resolution Regime under the kyoto Protocol
(Faculty of Law, University of Ibadan, 2012) Akanbi MM; Imam-Tamim MK; Abdulkadri AO
The paper examines the trade mechanism of the Kyoto Protocol and likely disputes under the Protocol
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CONTROL, OWNERSHIP AND DEVELOPMENT OF MINERAL RESOUCES IN INTERNATIONAL LAW: THE UNITED NATIONS APPROACH
(Faculty of Law, University of Maiduguri, 2010) Ismail Adua Mustapha,; M. K. Imam-Tamim,; Razaq O. Kadir
The paper examines the ownership, control and development of mineral resources before the United Nations intervention and the approach of United Nations to the ownership control and development of mineral resources.
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QUALITATIVE COMPARISON OF WI-FI TO FEMTOCELL (HNB) FOR INDOOR WIRELESS DATA ACCESS
(Zaria Journal of Electrical Engineering Technology, Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria., 2020-03-01) Ahmed O. M, Adebowale Q.R. , Imam-Fulani Y.O, Balogun M.O, Ajani A.A
The increasing pressure on spectrum resources of cellular networks has prompted service providers to identify the use of femtocells and Wi-Fi as options for increasing network quality and capacity for indoor data access. This work seeks to make a qualitative comparison of Wi-Fi and femtocell for indoor data access in a Long-Term Evolution (LTE) heterogeneous network, identifying which network access technology serves better for indoor data delivery, using video streaming and Voice over Internet Protocol (VoIP) as services of interest. The performance evaluation was carried out experimentally by using a live Wi-Fi and a Femtocell access point connected via same backhaul. A user equipment with Quality of Service (QoS) parameters measurement capabilities was used to measure parameters of interests from both devices under same measurement conditions for in different indoor scenarios multiple times. We observed differences in the QoS experiences in different scenarios for the access technologies observed, Wi-Fi showed better performance in all of the categories of measurements.
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ANN-based model for multiband path loss prediction in built-up environments
(Elsevier, 2022-08-10) Nasir Faruk a , b , ∗, Quadri Ramon Adebowale c , Imam-Fulani Yusuf Olayinka c , Kayode S. Adewole d , Abubakar Abdulkarim e , Abdulkarim A. Oloyede c , Haruna Chiroma f , Olugbenga A. Sowande c , Lukman A. Olawoyin c , Salisu Garba g , Aliyu D. Usman h , Yinusa A. Adediran i , Lawan S. Taura a , b
Path loss propagation models are critically needed for optimum planning and deployment of wireless communication networks. However, the complexity exhibited by the propa- gated signals makes the prediction of the received losses difficult in built-up environments. There is however a new paradigm shift towards the application of computational method- ologies, such as the Artificial Neural Networks (ANN), for multi-band path loss prediction. In this paper, we have developed a new ANN-based model for path loss prediction. The model was developed using large scale path loss data collected across 485 base stations in 6 urban cities of Nigeria, West Africa. The data collection, which spanned a period of 9 years, were taken over open areas, sub urban and urban environments, and the bands considered were 89.3 MHz, 103.5 MHz, 203.25MHz, 429.25 MHz, 529.25MHz, 615.25MHz, 629.25MHz, 900MHz, 1800 MHz and 2100MHz. The developed model was validated using independent path loss data across different frequencies, environments; and, distances and the results were compared with the popular empirical models such as Hata, COST 231 and Egli models, and to previously published ANN-based multi-frequency models. The global performance of 4.81 dB was obtained in terms of RMSE value with an R-value of 0.96, thus outperforming the existing ANN-based path loss models that were developed for multiple frequencies. Based on these findings, the proposed model can be deployed across all cate- gories since the average RMSE values are all within the acceptable thresholds. Furthermore, the model is multi-frequency, thus will be suitable for multiple and complex environments, and usable for both short- and long-range wireless communication networks.