Department of Mathematical Sciences

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Now showing 1 - 20 of 207
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    A Lotka-Volterra Non-linear Differential Equation Model for Evaluating Tick Parasitism in Canine Populations
    (Mathematical Modelling of Engineering Problems, 2023-08-30) Adesina, Olumide Sunday
    This research employs a modified version of the Lotka-Volterra non-linear first-order ordinary differential equations to model and analyze the parasitic impact of ticks on dogs. The analysis reveals that fluctuations in pesticide effects significantly influence tick populations and the size of the canine host. The study also uncovers that alterations in the size of the interacting species can lead to both stable and unstable states. Interestingly, in a pesticide-free environment, a decline in the inter-competition coefficient catalyzes an increase in the sizes of both interacting species. This increase, although marginal for the tick population, contributes to overall system stability. The findings underscore the utility of the Lotka-Volterra non-linear first-order ordinary differential equations in modeling the parasitic effect of ticks on dogs. To protect pets, particularly dogs, from the harmful effects of tick infestation, this study recommends the appropriate and regular application of disinfectants.
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    A modified generalized class of exponential ratio type estimators in ranked set sampling
    (Scientific African, 2023-03-22) Adesina, Olumide Sunday
    Background: Researchers consider ranked set sampling (RSS) as an alternative to simple random sampling (SRS) for data collection because studies have shown that it is more efficient and less biased. Also, introducing population parameters to estimators increases the efficiency of such estimators. Aim: This study derived a modified generalized class of exponential ratio estimator in RSS by introducing available population parameters and compared the results with an existing version in SRS. Methodology: The biases and mean square errors (MSE) of the proposed estimators were derived up to the terms of first-order approximation using Taylor’s series expansion. Efficiency was used as the mode of comparison between the proposed and existing estimators. Results: Life data sets and simulated data supported the numerical illustration to corroborate the theoretical results. Conclusion: The MSEs of the modified generalized class of estimators under RSS were found to be smaller than those of the existing generalized class of estimators under SRS; hence they are more efficient estimators.
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    A modified generalized class of exponential ratio type estimators in ranked set sampling
    (scientific African, 2022-11-22) Ayobami Fadilat Akintola
    Background: Researchers consider ranked set sampling (RSS) as an alternative to simple random sampling (SRS) for data collection because studies have shown that it is more efficient and less biased. Also, introducing population parameters to estimators increases the efficiency of such estimators. Aim: This study derived a modified generalized class of exponential ratio estimator in RSS by introducing available population parameters and compared the results with an existing version in SRS. Methodology: The biases and mean square errors (MSE) of the proposed estimators were derived up to the terms of first-order approximation using Taylor’s series expansion. Effi- ciency was used as the mode of comparison between the proposed and existing estimators. Results: Life data sets and simulated data supported the numerical illustration to corrobo- rate the theoretical results. Conclusion: The MSEs of the modified generalized class of estimators under RSS were found to be smaller than those of the existing generalized class of estimators under SRS; hence they are more efficient estimators.
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    A MODIFIED SPECTRAL CONJUGATE GRADIENT METHOD FOR SOLVING UNCONSTRAINED MINIMIZATION PROBLEMS
    (Nigerian Mathematical Society, 2020) Onanaye, Adeniyi Samson
    The development a modified spectral conjugate gradient method for solving unconstrained minimization prob lems is considered in this paper. A new Conjugate (update) parameter isobtained by the idea of Dai-Kou’s technique for gen erating conjugate parameters. A new spectral parameter is also presented based on quasi-Newton direction and quasi-Newton condition. Under the strong Wolfe line search, the proposed method (DOO) is proved to be globally convergent. Numerical results showed that the algorithm takes lesser number of itera tions to obtain the minimum of a given function.
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    A non-parametric analysis of the effect of Covid-19 pandemic on Nigerians’ well-being based on geopolitical zones
    (JP Journal of Biostatistics, 2024-02-12) Adesina, Olumide Sunday
    The COVID-19 pandemic has crippled the economic activities of so many nations across the globe since its outbreak in 2019. This study is focused on the consequential effect of the COVID-19 pandemic in terms of standard of living, and perception of economic and security situation of Nigerians. A non-parametric approach was adopted on a primary data obtained through the administration of questionnaires online by NoiPolls during the COVID-19 period. The result obtained from this study depicts that there is a significant relationship between the security situation and perception of the country’s economic situation. Kruskal-Wallis test was used to check if there is a significant difference in economic perception, security situation and standard of living where it was observed that there exists a significant difference based on the geopolitical zone. We, therefore, recommend that efforts should be made by the government towards improving the economic state of affairs especially in the southern part of the country as this will in the long run lead to sustainable cities and communities across the geopolitical zones which is one of the goals of SDGs. Moreover, efforts should also be made by the government towards improving the security situation in the north and southeast as improvement in the country’s economic situation has a direct influence on the security position of the country.
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    A Practical Guide to Data Analysis Using SPSS.
    (GODAD Publishers Nigeria Limited, Ketu, Lagos., 2018-02-17) Alayande SA
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    A TOPIC-SPECIFIC EVALUATION OF STUDENTS’ ATTITUDES TOWARDS STATISTICS
    (International Association of Statistics Education, 2022) Okewole, Dorcas Modupe
    This study involves an evaluation of students’ attitudes towards various topics in statistics. The purpose of the study is to determine how students’ attitudes towards statistics vary across different topics and to determine possible changes in students’ attitudes from the beginning to the end of a course. The target population is that of students taking a statistics course for non-majors at a university in Nigeria. The study involved a pre-test (within the first week of the course) and a post-test (applied at the end of the course) focused on specific topics in the statistics course. Results indicated that students’ attitudes were moderately positive at the onset and remained the same at the end of the course for most topics. Implications for teaching statistics are discussed.
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    A TOPIC-SPECIFIC EVALUATION OF STUDENTS’ ATTITUDES TOWARDS STATISTICS
    (ICOTS, 2022-12) Ayobami Fadilat Akintola
    This study involves an evaluation of students’ attitudes towards various topics in statistics. The purpose of the study is to determine how students’ attitudes towards statistics vary across different topics and to determine possible changes in students’ attitudes from the beginning to the end of a course. The target population is that of students taking a statistics course for non-majors at a university in Nigeria. The study involved a pre-test (within the first week of the course) and a post-test (applied at the end of the course) focused on specific topics in the statistics course. Results indicated that students’ attitudes were moderately positive at the onset and remained the same at the end of the course for most topics. Implications for teaching statistics are discussed.
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    Adaptive Models for Tails of Distributions
    (International Journal of Statistics and Economics, 2019) Adesina, Olumide Sunday
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    Adaptive Regression Model for Highly Skewed Count Data.
    (IAEME, 2019-01-11) Adesina, Olumide Sunday
    A big task often faced by practitioners is in deciding the appropriate model to adopt in fitting count datasets. This paper is aimed at investigating a suitable model for fitting highly skewed count datasets. Among other models, COM-Poisson regression model was proposed in this paper for fitting count data due to its varying normalizing constant. Some statistical models were investigated along with the proposed model; these include Poisson, Negative Binomial, Zero-Inflated, Zero-inflated Poisson and Quasi- Poisson models. A real life dataset relating to visits to Doctor within a given period was equally used to test the behavior of the underlying models. From the findings, it is recommended that COM-Poisson regression model should be adopted in fitting highly skewed count datasets irrespective of the type of dispersion.
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    Advanced Principal Component Analysis of Various Risk Factors of Hepatitis B Prevalence in Nigeria
    (Tanzania Journal of Science, 2024-09-30) Adesina, Olumide Sunday
    Hepatitis B virus (HBV) is an infectious disease globally estimated to have caused between 500,000 to 1.2 million deaths annually. HBV prevalence is still high in Nigeria. Thus, this research aimed to identify factors germane to the widespread of HBV infection in an apparent clinical survey. The methods of analysis used were frequency, percentage and Principal component analysis (PCA). This was achieved through hospital record extracts of consultant hepatologists and the dimensionality reduction of the acquired data while retaining essential factors that are germane to the prevalence of HBV infection. The findings revealed that out of seventeen components evaluated in the study, the PCA retained 15 components of which Eigen-values are greater than 1.00. The symptoms retained in every component were fever, muscle pain, fatigue, loss of appetite, blood in vomit, jaundice, pale stool, nausea, blood in faeces, weight loss, malaise, abdominal pain, joint ache, swollen of lower extremities, confusion and yellow eye. The symptoms were listed in accordance with their level of relevance for diagnosing HBV in patients, and all the variables retained accounted for 94.278% variation in the prevalence of HBV infection, with the majority of the infected populace found among the adults (18 -64 years).
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    AHP Algorithm in Data Diffusion Across a Social Networking Platform
    (Corpus Intellectual, 2023) Onanaye, Adeniyi Samson
    The Social Networking platforms (SNPs) have become major media of communication, information dissemination and sharing. SNP ignores the constraint of distance, time and type of information during communication among users. It is obviously seeming the best platform when it comes to marketing, advertisement and information transmission. In this paper, content ranking model was used to advance on how contents on a social networking platform can be shared among users faster and hereby improving the rate of information transmission over the network. Analytic Hierarchy Process (AHP) algorithm was deployed to find the level of importance in the constructed metadata.
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    Air Quality Trends and Pollution Analysis in Nigerian Cities Using Time Series Methods
    (International Journal of Advanced Statistics and Probability, 2024) Ayobami Fadilat Akintola
    Air pollution is a significant environmental and public health issue in rapidly urbanizing cities, particularly in developing countries like Nigeria. This study analyzes air quality trends in five major Nigerian cities Abuja, Lagos, Kano, Port Harcourt, and Enugu using satellitebased remote sensing data from January 2021 to December 2023. Key pollutants, including PM2.5, PM10, CO, NO2, SO2, and O3, were analyzed using time series models (ARIMA, SARIMA), seasonal decomposition (STL), and correlation analysis. The results reveal that Lagos and Kano experience the highest pollution levels, particularly during the Harmattan season, when Saharan dust exacerbates particulate matter. Abuja also sees significant pollution spikes, while Port Harcourt and Enugu show moderate pollution driven by industrial emissions and traffic. The study underscores the need for better air quality monitoring, seasonal interventions, and policies to reduce pollution, particularly during Harmattan
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    An Efficient Poisson-Distributed Adaptive Cluster Sampling Model Using Randomized Response Strategy
    (IIETA, 2024-08) Adesina, Olumide Sunday
    The key innovation lies in the incorporation of an adaptive cluster sampling strategy and a randomized response model based on the Poisson distribution. This integration aims to overcome shortcomings inherent in conventional models, providing a more robust framework for research area. In this paper, an adaptive cluster sampling randomized response model with Poisson distribution using a randomized response strategy was proposed. The proposed cluster randomized response model has improved efficiency and a large gain in precision. Conditions were obtained under which the proposed model is more efficient than the existing models. To validate the effectiveness of our approach, numerical computations were conducted, offering concrete illustrations of the model's performance. The results underscore the significant gains in efficiency and precision achieved by the proposed adaptive cluster sampling randomized response model.
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    An integro-collocation method for determining initial values for ordinary differential equations
    (corpus intellectual, 2023) Onanaye, Adeniyi Samson
    The collocation method used to formulate an integrated Lanczos Tau method for solving ordinary differential equations with starting values is the subject of this research. In order to uniquely determine the coefficients of the approximant of the solution, an algebraic system of linear equations is created by collocating the perturbed integrated equation at certain equally spaced intervals within the range of integration of the differential equation. The method is used to solve problems involving first- and second order ordinary differential equations, and data collected from numerical analysis supports its correctness and efficacy.
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    An Investigation of Cocoa Black Pod Disease Transmission through Mathematical Modelling
    (2023-05) Onanaye, Adeniyi Samson
    Cocoa black pod disease is a severe danger to global cocoa output. Mathematical models are commonly utilized to investigate disease transmission patterns and develop efficient control techniques. In this study, we investigated the dynamics of cocoa black pod disease spread using a mathematical model. The model's foundation is a system of ordinary differential equations that describes the interactions between susceptible (cherelles, young and mature pod, ripe pod), latent, infected, and recovered cocoa pods, as well as the population dynamics of the disease-carrying pathogen. The developed model was validated using data from the literature and ecological observation from cocoa plantations in Nigeria, West Africa. Our results suggested the importance of early detection and rapid response in controlling the spread of cocoa black pod disease. We also found that control measures, such as removal of infected pods and fungicide application can be effective in reducing the propagation of the disease. Our study highlights the importance of mathematical modeling in understanding the transmission dynamics of cocoa black pod disease and in guiding the development of effective control strategies.
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    Analyses of Spatial Variations of Kenaf in Experimental Field
    (2010) Adekeye, Kayode
    Preliminary investigations of experimental field usually involve collection of soil samples at widely spaced locations which are patchily or globally at variant spatially. This study was carried out to evaluate spatial variations in experimental fields using a split plot experiment distributed in a completely randomized design at Ikenne and Ilora between June and September 2006 (test crop was kenaf). The preliminary descriptive statistics suggested the dependency of the stem girth and height on the spatial positions. The variance - covariance analyses matrices of the plots showed that stem girth and plant height were independently distributed and exhibited a non stationarity principle. The results also revealed that spatial autocorrelation exists in patches in the experimental fields while the entire plots showed random distributions because the autocorrelatons were neither dominated by negative nor positive correlation and more than 50% of these values fall within the range of ± 2√n. From this study, a regionalized spatial variation is imminent in 625 m2 experimental plot despite the difference in the treatments. Spatial variations study was found necessary in any plot not more than an acre (250 m2) of land otherwise such variations should be treated as block or environmental effect(s).
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    Application of Response Surface Analysis of Three Factors of Fertilizer Treatment Combination to Determine the Optimum Plant Height of Maize
    (International Journal of Innovative Science and Research Technology, 2023-04-27) Oladipupo Olayinka Olusegun
    This study evaluated how three different fertilizer treatment combinations affected plant height. For specific variables or characteristics that can be taken into account, the optimal plant height is calculated using the first and second-order models of the Responsive Surface Methodology. According to the study's p-value of 0.087 for lack of fit, the Ho cannot be entirely discounted. Thus, there is no proof that the response surface lacks curvature or is poorly fitted. The interaction between 100 kg/ha of poultry manure (P/M10), 50 kg/ha of organic minerals (O/M5), and 50kg/ha of poultry manure (P/M5) is shown by the main effect plot, contour plot, and surface plot to be significant at the level of 0.05. Moreover, poultry manure at 50 kg/ha (P/M5), which spreads the longest, has the highest impact at 100 kg/ha (P/M10) and organic mineral at 50 kg/ha (O/M5). With the use of a Pareto chart, that serves as the reference line. The ideal values for the response variable for a specific location with the accompanying expected response plant height are 101.31cm and a composite desirability of 0.996269 to achieve the ideal plant height. The findings of this study demonstrate the potential of response surface analysis as a tool for optimizing fertilizer treatment combinations for the growth of maize. By identifying the optimal combination of fertilizer treatments, farmers can maximize the yield and quality of their maize crops, while minimizing the cost and environmental impact of their fertilizer use.
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    Approximation techniques for maximizing likelihood function of generalized linear mixed models for binary response data
    (sciencepubco, 2018-12-30) Adesina, Olumide Sunday
    Evaluating Maximum likelihood estimates in Generalized Linear Mixed Models (GLMMs) has been a serious challenge due to some integral complexities encountered in maximizing its likelihood functions. It is computationally difficult to establish analytical solutions for the integrals. In view of this, approximation techniques would be needed. In this paper, various approximation techniques were exam-ined including Laplace approximation (LA), Penalized Quasi likelihood (PQL) and Adaptive Gauss-Hermite Quadrature (AGQ) tech-niques. The performances of these methods were evaluated through both simulated and real-life data in medicine. The simulation results showed that the Adaptive Gauss-Hermit Quadrature approach produced better estimates when compared with PQL and LA estimation techniques based on some model selection criteria.
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    Assessing the Impact of ATM and POS Transactions on Currency Circulation in Nigeria: a comparison of artificial neural network and linear regression models
    (Revue d'Intelligence Artificielle, 2024-02) Adesina, Olumide Sunday
    This work is aimed at assessing the impact of ATM and POS transactions on currency in circulation in Nigeria via the comparison of the Artificial Neural Network and Linear Regression models. The Pearson product moment correlation coefficient was used to assess the degree of relationship between currency in circulation and ATM transactions, currency in circulation and POS transactions, ATM transactions and POS transactions. In addition to this, a multiple linear regression model was also fitted on the data to in order to assess the impact of currency in circulation on ATM transactions and POS transactions. From the results obtained, it was observed that POS transactions have a significant impact on the amount of currency in circulation compared to ATM transactions because the value of POS transactions has a P-value of 1.5542E-13 which is significant at 0.05. This was further studied using the Artificial Neural Network (ANN). The Multilayer preceptor of ANN was adopted, with 70 percent of the data initially subjected to training and 30 percent for validity. Thereafter, the amount of training data was increased to 61.4% and testing data was increased to 38.6% and it was observed that there was corresponding increase in the R-square from 0.809 to 0.839. This shows that the R-square of the ANN can be improved by increasing the amount of training data and testing data.