This collection is made up of electronic theses and dissertations produced by post graduate students from Faculty of Sciences https://repository.biust.ac.bw/handle/123456789/34 2026-04-17T12:23:19Z 2026-04-17T12:23:19Z Oluyede, Broderick Mdlongwa, Precious Makubate, Boikanyo Huang, Shujiao https://repository.biust.ac.bw/handle/123456789/734 2026-03-16T10:19:20Z 2019-01-01T00:00:00Z

The Burr-Weibull Power Series Class of Distributions Oluyede, Broderick; Mdlongwa, Precious; Makubate, Boikanyo; Huang, Shujiao A new generalized class of distributions called the Burr-Weibull Power Series (BWPS) class of distributions is developed and explored. This class of distributions generalizes the Burr power series and Weibull power series classes of distributions, respectively. A special model of the BWPS class of distributions, the new Burr-Weibull Poisson (BWP) distri- bution is considered and some of its mathematical properties are obtained. The BWP distribution contains several new and well known sub-models, including Burr-Weibull, Burr- exponential Poisson, Burr-exponential, Burr-Rayleigh Poisson, Burr-Rayleigh, Burr-Poisson, Burr, Lomax-exponential Poisson, Lomax-Weibull, Lomax-exponential, Lomax-Rayleigh, Lomax-Poisson, Lomax, Weibull, Rayleigh and exponential distributions. Maximum likeli- hood estimation technique is used to estimate the model parameters followed by a Monte Carlo simulation study. Finally an application of the BWP model to a real data set is presented to illustrate the usefulness of the proposed class of distributions

2019-01-01T00:00:00Z Oluyede, Broderick Yang, Tiantian Makubate, Boikanyo https://repository.biust.ac.bw/handle/123456789/733 2026-03-16T10:17:19Z 2016-01-01T00:00:00Z

A New Class of Generalized Power Lindley Distribution with Applications to Lifetime DataApplications to Lifetime Data Oluyede, Broderick; Yang, Tiantian; Makubate, Boikanyo In this paper, a new class of generalized distribution called the Kumaraswamy Power Lindley (KPL) distribution is proposed and studied. This class of distributions con- tains the Kumaraswamy Lindley (KL), exponentiated power Lindley (EPL), power Lindley (PL), generalized or exponentiated Lindley (GL), and Lindley (L) distributions as special cases. Series expansion of the density is obtained. Statistical properties of this class of distributions, including hazard function, reverse hazard function, monotonicity property, shapes, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived. Method of maximum likelihood is used to estimate the parameters of this new class of distributions. Finally, a real data example is discussed to illustrate the applicability of this class of distribution.

2016-01-01T00:00:00Z Habtamu Bayissa, Yadeta https://repository.biust.ac.bw/handle/123456789/731 2026-03-16T09:43:32Z 2025-06-01T00:00:00Z

Magnetic drug targeting phenomena during non- Newtonian flow in the microvessel with time- Fractional derivative Habtamu Bayissa, Yadeta Cancer and cardiovascular disease are the leading causes of death worldwide incurring substantial medical costs and care and become a potential barrier to average life expectancy. Several treatment options available have considerable side effects and often are not sufficient for curative treatment. Most challenges include targeting non-specifically, poor pharmacokinetic characteristics drugs arising from poor solubility, stability, and toxicity, inefficacy and limited bio-distribution. Recently, with the advancement of nanotechnology, treatment options such as magnetic drug targeting (MDT) through the application of magnetic nanoparticles (MNPs) treatment have significantly changed the paradigm of cancer treatment due to minimum side effects and high efficacy. This research aims at theoretical analysis to examine the efficacy of the accumulation of drug carrier magnetic nanoparticles influenced by biophysical parameters near the diseased region during magnetic drug targeting. In this study, the time fractional derivatives of blood flow and factors governing the transport of drug carrier nanoparticles such as particle – particle interaction, Saffman uplift force, size and shape of carrier particles, permeability of the vessel, magnetic and viscous forces are considered. The conclusion drawn from the study shows that spherical shaped drugs carrying magnetic nanoparticles are more prominent to be targeted to the tumor region than other non-spherical shaped drugs carrying magnetic nanoparticles. Capture efficiency of the drug-carrier particles is improved with increase in the magnetization, and radius of carrier particles as both increase the magnetic force among the magnet and Drug-carrier particles. A decrease in Darcy number, Reynolds number, and tumor magnet distance decreases the total volume fraction of nanoparticles. Total volume fraction of magnetic nanoparticles decreases with increase in pulsatile frequency, Casson parameter and Hematocrit parameter. The velocity of blood and velocity of magnetic nanoparticles are boosted with enhancement in the Darcy number and Jeffrey fluid parameter, which shows an important application to the therapy of atherosclerosis. The flow resistance increases with an increase in stenosis height and Hartman number. The present study will help biomedical engineers and nanomedicine researchers develop magnetic devices and the next generation of drug carrier particles to treat cancerous tumors. Dissertation (PhD in Mathematics)---Botswana International University of Science and Technology, 2025

2025-06-01T00:00:00Z Oluyede, Broderick Pu, Shusen Makubate, Boikanyo Qiu, Yuqi https://repository.biust.ac.bw/handle/123456789/729 2026-03-16T09:36:33Z 2018-02-01T00:00:00Z

The Gamma-Weibull-G Family of Distributions with Applications Oluyede, Broderick; Pu, Shusen; Makubate, Boikanyo; Qiu, Yuqi Weibull distribution and its extended families has been widely studied in lifetime ap- plications. Based on the Weibull-G family of distributions and the exponentiated Weibull distribution, we study in detail this new class of distributions, namely, Gamma-Weibull- G (GWG) family of distributions. Some special models in the new class are discussed. Statistical properties of the family of distributions, such as expansion of density function, hazard and reverse hazard functions, quantile function, moments, incomplete moments, generating functions, mean deviations, Bonferroni and Lorenz curves and order statistics are presented. We also present R´enyi entropy, estimation of parameters by using method of maximum likelihood, asymptotic confidence intervals and applications using real data sets.

2018-02-01T00:00:00Z