| 1 |
Author(s):
Anthony Effiong Usoro, Akaninyene Ekong.
Page No : 1-12
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Profile Analysis of Non-Teaching Staff in Akwa Ibom State University, Nigeria.
Abstract
There is no gainsaying the fact that every academic institution conducts annual appraisal of teaching and non-teaching staff either for the purpose of promotion or annual salary increment. Like other tertiary institutions, Akwa Ibom State University Appointment and Promotion Committee evaluates senior and junior staff based on certain performance criteria, which include qualifications, work experience, attitude, initiative, community service, rewards/sanctions for the junior staff, and work output, communication, human relations, character traits, work habits, leadership attainment, reward/sanctions for the senior staff. The aim of this work was to subject the overall assessment to statistical analysis as a mathematical approach of evaluating staff performances in the university. Staff that were promoted based on the overall assessment were grouped into two categories, namely senior and junior staff with their respective appraisal scores for 2024/2025 appraisal year. Method of analysis adopted was multiple regression analysis with appraisal score as response variable, while the selected performance criteria for each category constituted predictor variables in the regression model. The justification for the multiple regression analysis was to fit a model as an alternative approach to the staff performance evaluation with a view to compare between the non-mathematical and mathematical approaches to staff appraisal. The analysis produced two different multiple regression models for junior and senior staff in the university. Estimates from the two models were compared with the appraisal scores awarded to staff by their respective reporting officers, and were found to be as good as the overall assessment scores awarded to staff in their appraisal forms. The advantage of the statistical modelling of the appraisal scores over the existing non-statistical method is the ability to identify the non-performing variables characterized by attributes of some staff. The model identified insignificant effect of work experience and initiative among the junior staff, while work-habits was identified as the weakness of the senior staff as shown in the parameter estimates of each model. The outcome of the research is a working instrument to strengthen quality assurance and plan manpower development for higher productivity in the university.
| 2 |
Author(s):
Henry Samambgwa, Simbarashe Chinyere, Thomas Musora.
Page No : 13-26
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Time Series Modeling and Forecasting of Petrol Sales at a Fuel Station in Zimbabwe.
Abstract
Petrol is an important commodity in the Zimbabwean economy. Its availability, shortage and pricing have a significant impact on key economic indicators and the livelihoods of the general population in the country. This study focuses on petrol sales volumes at a fuel station in Zimbabwe. There are costs and negative implications that emanate from overstocking or understocking of petrol at the fuel station. This makes it necessary to forecast future demand, so as to plan and maintain adequate volumes of petrol. This study sought to fit a SARIMA model using monthly sales data from January 2015 to December 2024. Minimal information criteria were used to compare and select from candidate models. Parameter p-values were then used to identify and eliminate likely insignificant parameters. This was because insignificant parameters contribute to model overfitting. The best fitting model was then used to forecast petrol sales volumes for the months from January to December 2025.
| 3 |
Author(s):
Samuel Shikaa, Hussaini Mamman, Nicholas Ejobu.
Page No : 27-38
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Ensembling Caputo, Caputo–Fabrizio and Atangana–Baleanu Fractional-Order Models to Study HIV Dynamics in Nigeria.
Abstract
This study investigates HIV dynamics in Nigeria using fractional-order epidemic models formulated with Caputo, Caputo–Fabrizio, and Atangana–Baleanu fractional derivatives, together with an ensemble framework integrating their predictions. A five-compartment SEIDT model representing susceptible, exposed, infected, diagnosed, and treated populations is developed to incorporate memory effects inherent in HIV transmission and treatment. Numerical simulations covering 1990–2030 are conducted using parameter values from the literature and Nigerian demographic data. Results show that the Caputo–Fabrizio model produces rapid early responses, the Atangana–Baleanu model exhibits improved long-term stability, and the ensemble model provides conservative and robust forecasts. Sensitivity analysis confirms the stabilizing advantage of the ensemble approach. These findings highlight the relevance of fractional-order models for realistic HIV forecasting and public health planning in Nigeria.
| 4 |
Author(s):
Nwankwo Chike H., Akujobi Princess Ijeoma.
Page No : 39-54
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Polytrigonometric and the Third Order Polynomial Regression Models: A Statistical Evaluation.
Abstract
This study explores the efficiency of polytrigonometric Regression models as viable alternatives to third-order polynomial regression models in curve fitting and predictive modeling. While polynomial regression is widely utilized for capturing nonlinear trends with characteristic turning points, polytrigonometric models integrate polynomial and trigonometric components, offering enhanced flexibility for diverse datasets, particularly when the underlying data structure is uncertain or may contain oscillatory characteristics. Simulated datasets of n = 10, 20, 50, 100, 200, and 500 were generated using third-order polynomial equations and fitted with both models. Model performance was evaluated using R², MSE, and p-values across the varying sample sizes. The Polytrigonometric models presented a reasonable proxy for the third order polynomial models for the various sample sizes, improving as sample sizes increases. The model's R² advanced from 0.723 at n=10 to perfect fit (R² = 1.000) at n ≥ 100, achieving high statistical significance (p < 0.0001) at larger sample sizes and strong performance (R² ≥ 0.978) at moderate sample sizes (n ≥ 50). A real-world agricultural dataset on tomato plant growth rates versus NPK fertilizer concentration of sample size n=300 was analyzed to validate the models under practical conditions. Findings reveal that the polytrigonometric model also demonstrated remarkable adaptability and progressive improvement with increasing sample size. The real-world dataset validated the model's practical utility, with R² = 0.649 (p < 0.001) explaining about 65% (64.9%) of the variance; a moderate-to-strong level representing substantial predictive capability for agricultural applications. While the polynomial model achieved superior performance on polynomial-structured data (R² = 0.885 for the real data). As theoretically expected, the polytrigonometric model's ability to attain strong performance using a fundamentally different mathematical framework demonstrates its versatility. Overall, this study confirms that the polytrigonometric model serves as a viable and practical alternative to polynomial regression, offering researchers a flexible tool that maintains strong predictive performance across diverse applications.
| 5 |
Author(s):
Olayiwola Babarinsa.
Page No : 55-71
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Strategic Security Zoning Via Chromatic Graph Theory: An Optimized Patrol Allocation for Nigeria’s Geopolitical Regions.
Abstract
Geographically distributed security risks throughout Nigeria tend to spread from one state to another via shared borders and movement routes, ensuring the requirement for an optimized and conflict-free security deployment strategy. In this work, a framework for allocating and deploying available security resources in a manner that avoids inter-unit conflicts in a Nigerian setting is proposed by formulating a graph-coloring model that represents the six geopolitical zones in a two-dimensional coordinate plane as map graphs and allocating states as vertices and borders between them as edges. For each zone, a backtracking algorithm based on an adjacency matrix approach is applied with a view to determining the chromatic numbers χ(G) that represent the optimal minimum needed non-conflicting security patrol units and schedules needed to avoid interference and overlap on inter-state levels for enhanced operational efficiency and effectiveness. From the results, it can be observed that while the North-East geopolitical zone has the highest connectivity and insurgent activities, security deployment needs χ(G) = 4 units, whereas for North-Central, North-West, South-East, South-South, and South-West zones, security deployment needs χ(G) = 3 units. This indicates the immediate applicability of security resource allocation into partitioned time schedules for nationwide security patrol network deployment and regional security force coordination. By appropriating map graphs on a plane into a real-time applicability tool, the research highlights the applicability of computational graph theory concepts for optimizing security resource planning from conventional-based approaches toward efficient strategies involving minimum resource spending with the highest operational ranges to achieve the UN Sustainable Development Goal.
