Browsing by Author "Jimoh, Abdulazeez Kayode"

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    Constructive approach and randomization of a two-parameter chaos system for securing data
    (FLAYOO Publishing House Limited, 2024-05-21) Wahab, Olalekan Taofeek; Musa, Salaudeen Alaro; Jimoh, Abdulazeez Kayode; Dauda, Kazeem Adesina
    Secure communication techniques are important due to the increase in the number of technology users across the world. Likewise, a more random encryption algorithm suitable to secure data from unauthorised users is highly expected. This paper proposes a two-parameter nonlinear chaos map that is sensitive to the trio seed (s0, \alpha, \lambda) and has better information encryption. We introduce the parameter \alpha to linearise the conventional chaos system, which in turn brings a delay in the cryptosystems. The delay is a phenomenon that changes the chaotic features of a system. A small delay in the system leads to more aperiodicity and the unpredictability of the chaotic attractions. We normalise the new chaos map and use the Lipschitz and pseudo-contractive operators to obtain its irregularity region in Hilbert spaces. We also analyse the chaos map in terms of trajectory, Lyapunov exponent, complexity, and information entropy. Results obtained show that the new chaos map has a wide chaotic range and better statistical properties. It also maintains low complexity due to its linearity and produces more key spaces than most existing chaotic maps.
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    The New Extended Exponential-Gamma (NEEG) Distribution: Properties and Applications to Infectious Disease Modelling
    (African Journal Online, 2025-08-06) Aderoju, Samuel Adewale; Salau, Ganiyat Monishola; Sanni, Bello Ishola; Adeshola, Adediran Dauda; Jimoh, Abdulazeez Kayode; Wahab, Olalekan Taofeek; Kalu, Uchechukwu
    This study introduces the New Extended Exponential-Gamma (NEEG) distribution, a flexible lifetime model developed to address the limitations of classical and generalized distributions in capturing real-world data complexity. The statistical properties of the proposed distribution are thoroughly explored, including its probability density function, cumulative distribution function, and parameter estimation via the maximum likelihood method. The practical effectiveness of the NEEG model is demonstrated using two real-life COVID- 19 datasets from Italy and Nigeria, where it is benchmarked against several existing models such as the Gamma, Exponential, UYEG, and two variants of the Generalized Lindley distribution. Model comparison was conducted using a combination of information criteria (AIC, AICc, BIC, HQIC) and graphical tools such as density plots overlaid on empirical histograms. The results consistently show that the NEEG distribution provides the best fit across both datasets, outperforming all competing models in terms of flexibility, goodness-of-fit, and alignment with the empirical data. The model’s adaptability to skewed and peaked data structures is particularly evident in pandemic-related scenarios, where traditional models often fail. These findings position the NEEG distribution as a powerful and versatile tool for statistical modelling in public health, reliability analysis, and other domains requiring robust handling of nonnormal, skewed, or heavy-tailed data. Future research may extend the model into regression frameworks or multivariate contexts to enhance its applicability further. INTRODUCTION One notable development in lifetime data modelling